Handbook of Research on Human Cognition and Assistive Technology: Design, Accessibility and Transdisciplinary Perspectives (Handbook of Research On...)

Handbook of Research on Human Cognition and Assistive Technology: Design, Accessibility and Transdisciplinary Perspectives

Soonhwa Seok Center for Research on Learning - eLearning Design Lab, University of Kansas, USA Edward L. Meyen Kansas University, USA Boaventura DaCosta Solers Research Group, USA

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Published in the United States of America by Medical Information Science Reference (an imprint of IGI Global) 701 E. Chocolate Avenue Hershey PA 17033 Tel: 717-533-8845 Fax: 717-533-8661 E-mail: [email protected] Web site: http://www.igi-global.com/reference Copyright © 2010 by IGI Global. All rights reserved. No part of this publication may be reproduced, stored or distributed in any form or by any means, electronic or mechanical, including photocopying, without written permission from the publisher. Product or company names used in this set are for identification purposes only. Inclusion of the names of the products or companies does not indicate a claim of ownership by IGI Global of the trademark or registered trademark. Library of Congress Cataloging-in-Publication Data Handbook of research on human cognition and assistive technology : design, accessibility and transdisciplinary perspectives / Soonhwa Seok, Edward L. Meyen and Boaventura DaCosta, editors. p. cm. Includes bibliographical references and index. Summary: "The intent of this book is to assist researchers, practitioners, and the users of assistive technology to augment the accessibility of assistive technology by implementing human cognition into its design and practice"--Provided by publisher. ISBN 978-1-61520-817-3 (hbk.) -- ISBN 978-1-61520-818-0 (ebook) 1. Self-help devices for people with disabilities. 2. Cognitive science. 3. Human engineering. I. Seok, Soonhwa, 1970- II. Meyen, Edward L. III. DaCosta, Boaventura. HV1569.5.H364 2010 681'.761--dc22 2009054320 British Cataloguing in Publication Data A Cataloguing in Publication record for this book is available from the British Library. All work contributed to this book is new, previously-unpublished material. The views expressed in this book are those of the authors, but not necessarily of the publisher.

List of Reviewers Brian Bryant, University of Texas, USA Diana Bryant, University of Texas, USA Muhammet Demirbilek, Suleyman Demirel University, Turkey Joan B. Hodapp, Area Education Agency 267, USA Neha Khetrapal, University of Bielefeld, Germany Carolyn Kinsell, Solers Research Group, USA Angelique Nasah, Solers Research Group, USA Brian Newberry, California State University San Bernardino, USA

List of Contributors

Banerjee, Rashida / University of Northern Colorado, USA ............................................................ 339 Belfi, Marcie M. / University of Texas, USA ...................................................................................... 325 Brown, Monica R. / New Mexico State University, USA................................................................... 374 Bryant, Brian / University of Texas, USA.......................................................................................... 264 Bryant, Diana / University of Texas, USA ......................................................................................... 264 DaCosta, Boaventura / Solers Research Group, USA .............................................................. 1, 21, 43 Delisi, Jennifer / Lifeworks Services, USA ........................................................................................ 121 Demirbilek, Muhammet / Suleyman Demirel University, Turkey .................................................... 109 Dotterer, Gary / Oklahoma State University, USA .................................................................... 299, 306 Dunn, Michael W. / Washington State University Vancouver, USA .................................................. 313 Estrada-Hernández, Noel / University of Iowa, USA ............................................................... 239, 286 Fitzpatrick, Michael / New Mexico State University, USA ....................................................... 179, 374 Hodapp, Joan B. / Area Education Agency 267, USA ............................................................... 199, 220 Horn, Eva / University of Kansas, USA ............................................................................................. 339 Johnson, Vivian / Hamline University, USA...................................................................................... 192 Jones, Kristen E. / University of Texas, USA .................................................................................... 325 Khetrapal, Neha / University of Bielefeld, Germany .......................................................................... 96 Kinsell, Carolyn / Solers Research Group, USA ................................................................................. 61 Kouba, Barbara J. / California State University, San Bernardino, USA .......................................... 360 Laffey, James / University of Missouri, USA....................................................................................... 76 Lowe, Mary Ann / Nova Southeastern University, USA ................................................................... 251 Nankee, Cindy / UTLL (Universal Technology for Learning & Living), USA .................................. 157 Newberry, Brian / California State University, San Bernardino, USA ............................................. 360 Okrigwe, Blessing Nma / Rivers State College of Education, Nigeria ............................................. 388 Pascoe, Jeffrey / Laureate Learning Systems, Inc., USA ................................................................... 132 Plunkett, Diane / University of Kansas, USA .................................................................................... 339 Price, Carol / Hamline University, USA ............................................................................................ 192 Rachow, Cinda / Area Education Agency 13, USA ................................................................... 199, 220 Schmidt, Matthew / University of Missouri, USA............................................................................... 76 Seok, Soonhwa / Center for Research on Learning - eLearning Design Lab, University of Kansas, USA............................................................................................. 1, 21, 43, 264 Slotznick, Benjamin / Point-and-Read, Inc., USA ............................................................................ 169

Stachowiak, James R. / University of Iowa, USA ..................................................................... 239, 286 Stichter, Janine / University of Missouri, USA.................................................................................... 76 Theoharis, Raschelle / Gallaudet University, USA ........................................................................... 179 Wagner, Cynthia L. / Lifeworks Services, USA ................................................................................ 121 Wilson, Mary Sweig / Laureate Learning Systems, Inc., USA .......................................................... 132

Table of Contents

Foreword ............................................................................................................................................. xx Preface ................................................................................................................................................ xxi Acknowledgment ..............................................................................................................................xxiii Section 1 Human Cognition and Assistive Technology Design Chapter 1 Human Cognition in the Design of Assistive Technology for Those with Learning Disabilities ........... 1 Boaventura DaCosta, Solers Research Group, USA Soonhwa Seok, Center for Research on Learning - eLearning Design Lab, University of Kansas, USA Chapter 2 Managing Cognitive Load in the Design of Assistive Technology for Those with Learning Disabilities ..................................................................................................................... 21 Boaventura DaCosta, Solers Research Group, USA Soonhwa Seok, Center for Research on Learning - eLearning Design Lab, University of Kansas, USA Chapter 3 Multimedia Design of Assistive Technology for Those with Learning Disabilities ............................. 43 Boaventura DaCosta, Solers Research Group, USA Soonhwa Seok, Center for Research on Learning - eLearning Design Lab, University of Kansas, USA Chapter 4 Investigating Assistive Technologies using Computers to Simulate Basic Curriculum for Individuals with Cognitive Impairments ......................................................................................... 61 Carolyn Kinsell, Solers Research Group, USA

Section 2 The Internet, Media, and Cognitive Loads Chapter 5 Social Orthotics for Youth with ASD to Learn in a Collaborative 3D VLE ......................................... 76 James Laffey, University of Missouri, USA Janine Stichter, University of Missouri, USA Matthew Schmidt, University of Missouri, USA Chapter 6 Cognition Meets Assistive Technology: Insights from Load Theory of Selective Attention ............... 96 Neha Khetrapal, University of Bielefeld, Germany Chapter 7 Cognitive Load and Disorientation Issues in Hypermedia as Assistive Technology .......................... 109 Muhammet Demirbilek, Suleyman Demirel University, Turkey Section 3 Software and Devices Chapter 8 Multi-Sensory Environments and Augmentative Communication Tools ........................................... 121 Cynthia L. Wagner, Lifeworks Services, USA Jennifer Delisi, Lifeworks Services, USA Chapter 9 Using Software to Deliver Language Intervention in Inclusionary Settings ...................................... 132 Mary Sweig Wilson, Laureate Learning Systems, Inc., USA Jeffrey Pascoe, Laureate Learning Systems, Inc., USA Chapter 10 Switch Technologies ........................................................................................................................... 157 Cindy Nankee, UTLL (Universal Technology for Learning & Living), USA Chapter 11 Point-and-Chat®: Instant Messaging for AAC Users ......................................................................... 169 Benjamin Slotznick, Point-and-Read, Inc., USA Chapter 12 Assistive Technology for Deaf and Hard of Hearing Students ........................................................... 179 Michael Fitzpatrick, New Mexico State University, USA Raschelle Theoharis, Gallaudet University, USA

Chapter 13 A Longitudinal Case Study on the Use of Assistive Technology to Support Cognitive Processes across Formal and Informal Educational Settings .............................................................. 192 Vivian Johnson, Hamline University, USA Carol Price, Hamline University, USA Section 4 Evaluation and Assessment Chapter 14 Impact of Text-to-Speech Software on Access to Print: A Longitudinal Study .................................. 199 Joan B. Hodapp, Area Education Agency 267, USA Cinda Rachow, Area Education Agency 13, USA Chapter 15 Measure It, Monitor It: Tools for Monitoring Implementation of Text-to-Speech Software.............. 220 Joan B. Hodapp, Area Education Agency 267, USA Cinda Rachow, Area Education Agency 13, USA Chapter 16 Evaluating Systemic Assistive Technology Needs ............................................................................. 239 Noel Estrada-Hernández, University of Iowa, USA James R. Stachowiak, University of Iowa, USA Chapter 17 Developing Electronic Portfolios........................................................................................................ 251 Mary Ann Lowe, Nova Southeastern University, USA Chapter 18 Assistive Technology Solutions for Individuals with Learning Problems: Conducting Assessments Using the Functional Evaluation for Assistive Technology (FEAT) ............................. 264 Brian Bryant, University of Texas, USA Soonhwa Seok, Center for Research on Learning - eLearning Design Lab, University of Kansas, USA Diana Bryant, University of Texas, USA Section 5 Teacher Education Chapter 19 Improving Assistive Technology Training in Teacher Education Programs: The Iowa Model .......... 286 James R. Stachowiak, University of Iowa, USA Noel Estrada-Hernández, University of Iowa, USA

Chapter 20 Effects of Assistive Technologies Combined with Desktop Virtual Reality in Instructional Procedures (1) ..................................................................................................................................... 299 Gary Dotterer, Oklahoma State University, USA Chapter 21 Effects of Assistive Technologies Combined with Desktop Virtual Reality in Instructional Procedures (2) ..................................................................................................................................... 306 Gary Dotterer, Oklahoma State University, USA Chapter 22 Response to Intervention: Assistive Technologies which can Help Teachers with Intervention Programming and Assessment ............................................................................................................ 313 Michael W. Dunn, Washington State University Vancouver, USA Chapter 23 Assistive Technology for Teacher Education: From Research to Curriculum .................................... 325 Marcie M. Belfi, University of Texas, USA Kristen E. Jones, University of Texas, USA Chapter 24 Supporting Early Childhood Outcomes through Assistive Technology ............................................. 339 Diane Plunkett, University of Kansas, USA Rashida Banerjee, University of Northern Colorado, USA Eva Horn, University of Kansas, USA Section 6 Past, Present, and Future Chapter 25 Assistive Technology’s Past, Present and Future ................................................................................ 360 Barbara J. Kouba, California State University, San Bernardino, USA Brian Newberry, California State University, San Bernardino, USA Chapter 26 Digital Inequity: Understanding the Divide as it Relates to Culture and Disability........................... 374 Monica R. Brown, New Mexico State University, USA Michael Fitzpatrick, New Mexico State University, USA

Chapter 27 Cognition and Learning ...................................................................................................................... 388 Blessing Nma Okrigwe, Rivers State College of Education, Nigeria Compilation of References ............................................................................................................... 401 About the Contributors .................................................................................................................... 443 Index ................................................................................................................................................... 451

Detailed Table of Contents

Foreword ............................................................................................................................................. xx Preface ................................................................................................................................................ xxi Acknowledgment ..............................................................................................................................xxiii Section 1 Human Cognition and Assistive Technology Design Chapter 1 Human Cognition in the Design of Assistive Technology for Those with Learning Disabilities ........... 1 Boaventura DaCosta, Solers Research Group, USA Soonhwa Seok, Center for Research on Learning - eLearning Design Lab, University of Kansas, USA This chapter is the first of three serving as the introduction to this handbook which addresses the relationship between human cognition and assistive technologies and its design for individuals with cognitive disabilities. In this chapter the authors introduce the human information processing system, discuss the modal model of memory, and describe ways in which to increase learning. Altogether, the authors present the approach that assistive technologies for individuals with learning disabilities should be created with an understanding of design principles empirically grounded in the study of how the human mind works. Chapter 2 Managing Cognitive Load in the Design of Assistive Technology for Those with Learning Disabilities ..................................................................................................................... 21 Boaventura DaCosta, Solers Research Group, USA Soonhwa Seok, Center for Research on Learning - eLearning Design Lab, University of Kansas, USA This chapter is the second of three serving as the introduction to this handbook which addresses the relationship between human cognition and assistive technologies and its design for individuals with learning disabilities. In this chapter the authors present strategies to manage cognitive load in the design of

instructional materials for those with learning disabilities by introducing cognitive load theory. Altogether, the authors affirm the approach discussed in the last chapter—assistive technologies for individuals with learning disabilities should be created with an understanding of design principles empirically grounded in the study of how the human mind works. Chapter 3 Multimedia Design of Assistive Technology for Those with Learning Disabilities ............................. 43 Boaventura DaCosta, Solers Research Group, USA Soonhwa Seok, Center for Research on Learning - eLearning Design Lab, University of Kansas, USA This chapter is the last of three serving as the introduction to this handbook which addresses the relationship between human cognition and assistive technologies and its design for individuals with learning disabilities. In this chapter the authors build upon the last two chapters and focus specifically on research investigating the visual and auditory components of working memory by presenting the cognitive theory of multimedia learning (CTML). Altogether, the authors stress the common thread found throughout this three chapter introduction—assistive technologies for individuals with learning disabilities should be created with an understanding of design principles empirically grounded in the study of how the human mind works. They argue that the principles emerging from the CTML may have potential benefits in the design of assistive technologies for those with learning disabilities. Chapter 4 Investigating Assistive Technologies using Computers to Simulate Basic Curriculum for Individuals with Cognitive Impairments ......................................................................................... 61 Carolyn Kinsell, Solers Research Group, USA For middle and high school students, learning is often conducted in traditional classroom settings. Peer pressure is generally high and any lack of classroom participation or subject knowledge is quickly apparent to other classmates. The cognitively impaired student who is behind is not always properly identified nor is the learning solution readily available. It is the hope that assistive technologies can become more common-place for cognitively impaired students left hanging in the balance in traditional classrooms. This chapter addresses the use of computer-based simulations as an assistive technology solution for the cognitively impaired student who is having difficulties. Section 2 The Internet, Media, and Cognitive Loads Chapter 5 Social Orthotics for Youth with ASD to Learn in a Collaborative 3D VLE ......................................... 76 James Laffey, University of Missouri, USA Janine Stichter, University of Missouri, USA Matthew Schmidt, University of Missouri, USA

This chapter describes the conceptualization as well as design and development work underway to advance the use and study of social orthotics as an assistive technology in 3-Dimensional Virtual Learning Environment for youth with autism spectrum disorders (ASD). The work to understand and develop social orthotics is part of a larger effort to build iSocial, an online learning systems being developed to implement a curriculum for developing social competence for youth with ASD. The chapter describes the development of two forms of social orthotics, iTalk and iGroup. In their current forms, iTalk supports conversational turn taking by constraining interruptions, and iGroup supports conversational turn taking by supporting appropriate adjacency, distance and orientation behavior. This chapter describes results from early tests of prototypes of the social orthotics and suggests directions for future research. Chapter 6 Cognition Meets Assistive Technology: Insights from Load Theory of Selective Attention ............... 96 Neha Khetrapal, University of Bielefeld, Germany This chapter aspires to lay emphasis on transdignostic process as a means for diagnosis and for cognitive intervention by modern technological tools. In this pursuit, it highlights the intimate links shared by cognitive and emotional processes and brings in several examples for developing better understanding. The attempt on encouraging cooperative ties among disciplines and various contemporary concepts from cognition is also discussed. Chapter 7 Cognitive Load and Disorientation Issues in Hypermedia as Assistive Technology .......................... 109 Muhammet Demirbilek, Suleyman Demirel University, Turkey Hypermedia as an assistive technology has the potential to teach and train individuals with disabilities. However, like every technology, hypermedia itself is not free from problems. Disorientation and cognitive load are two of the most challenging problems related to hypermedia learning environments. The purpose of this chapter is to highlight disorientation and cognitive load problems in hypermedia learning environments where learners are usually faced a serious problem while navigating hypermedia systems. This chapter includes a brief introduction of assistive technologies, hypermedia as a learning environment, human memory and hypermedia, usability issues, disorientation, and cognitive load in hypermedia and hypermedia in inclusive education. Section 3 Software and Devices Chapter 8 Multi-Sensory Environments and Augmentative Communication Tools ........................................... 121 Cynthia L. Wagner, Lifeworks Services, USA Jennifer Delisi, Lifeworks Services, USA This chapter puts forward the idea that use of a multi-sensory environment to decrease defensiveness in the body can promote integration of the senses, and lead a person to be in a better position to communicate

their wants and needs. It has also been noted that adults with developmental disabilities or autism can sometimes be overlooked as emerging communicators. Shifting this view will increase their access to new tools and techniques for enhancing communication skills. People with severe disabilities can live, work, play, communicate, and form relationships with a wide variety of people in their communities, schools, and workplaces, and they deserve to be provided with opportunities to do so. Chapter 9 Using Software to Deliver Language Intervention in Inclusionary Settings ...................................... 132 Mary Sweig Wilson, Laureate Learning Systems, Inc., USA Jeffrey Pascoe, Laureate Learning Systems, Inc., USA Using Software to Deliver Language Intervention in Inclusionary Settings Receptive language intervention with an emphasis on syntax is essential when serving the educational needs of children with language delays and disorders. Syntax mastery is necessary for sentence understanding and use as well as for reading comprehension and writing. Yet there are challenges to providing individualized syntax intervention on a daily basis in inclusionary settings. This chapter reviews the linguistic foundations and instructional approaches used in language intervention software designed for preschool and elementary school children. Also described are the results of classroom field-testing where regular use of the software was found to be associated with accelerated language development. Chapter 10 Switch Technologies ........................................................................................................................... 157 Cindy Nankee, UTLL (Universal Technology for Learning & Living), USA This chapter provides information on best practices in the area of switch technologies including: (a) a background of the what, why, when and where of switch accessibility; (b) a summary of five popular assessment tools; and (c) an overview of types of switches and training strategies for the successful sustained use of switches. Information included in this chapter will benefit assistive technology professionals, case managers, educators, physical therapists, occupational therapists, speech and language pathologists, rehabilitation counselors as well as students of these professions and consumers. The information will apply to all age groups including birth to six, all levels of primary and secondary education, adulthood and senior services. The goal of this chapter is to compile information in a concise step-by-step fashion including information from assessment to implementation, additional resources, readings, and references for further study. Chapter 11 Point-and-Chat®: Instant Messaging for AAC Users ......................................................................... 169 Benjamin Slotznick, Point-and-Read, Inc., USA This chapter details the design choices and user interfaces employed by Point-and-Chat® software to make it easier to use by reducing cognitive load. Point-and-Chat® is software for Instant Messaging (IM) which is especially designed to be used in conjunction with Augmentative/Alternative Communication (AAC) devices. The software includes a built-in screen reader and special picture-based control and navigation for people who have difficulty reading or have cognitive limitations. This chapter also

discusses the challenges and opportunities to AAC users presented by the growing importance of IM, as well as recent research which points out a need to develop special IM vocabulary interfaces to overcome those challenges. Chapter 12 Assistive Technology for Deaf and Hard of Hearing Students ........................................................... 179 Michael Fitzpatrick, New Mexico State University, USA Raschelle Theoharis, Gallaudet University, USA This chapter discusses the reality that the majority of deaf and hard of hearing (d/hh) students are educated in the public school setting. Unfortunately educators are often ill prepared to address the unique technological needs of d/hh students. This chapter focuses on providing educators and other service providers with an overview of various educational technologies that they can employ to increase the academic and social outcomes for d/hh students. Chapter 13 A Longitudinal Case Study on the Use of Assistive Technology to Support Cognitive Processes across Formal and Informal Educational Settings .............................................................. 192 Vivian Johnson, Hamline University, USA Carol Price, Hamline University, USA This qualitative case study describes the challenges faced by one child with documented learning challenges and her parents in their ten-year struggle to include the use of assistive and repurposed technology in the learning environment. Understanding the context of this challenge juxtaposed with the impact of federal legislation can inform and encourage policy reform. Section 4 Evaluation and Assessment Chapter 14 Impact of Text-to-Speech Software on Access to Print: A Longitudinal Study .................................. 199 Joan B. Hodapp, Area Education Agency 267, USA Cinda Rachow, Area Education Agency 13, USA This chapter examines the outcome of extended use text-to-speech software as an accommodation to improve student access to core content. Using the Time Series Concurrent and Differential Approach, this study examines the impact on student fluency and comprehension. In addition, multiple measures of perceptual and objective data measures were collected from 20 middle school special education students and nine teachers during the 27-week study. Chapter 15 Measure It, Monitor It: Tools for Monitoring Implementation of Text-to-Speech Software.............. 220 Joan B. Hodapp, Area Education Agency 267, USA Cinda Rachow, Area Education Agency 13, USA

This chapter examines a variety of innovative tools for monitoring successful implementation of assistive technology that were field tested in the Iowa Text Reader Project. Explanations of each tool and its use are provided. Strategies include measures to collect data from students, teachers, administrators, and assistive technology team members. Chapter 16 Evaluating Systemic Assistive Technology Needs ............................................................................. 239 Noel Estrada-Hernández, University of Iowa, USA James R. Stachowiak, University of Iowa, USA The purpose of this chapter is to introduce the concept and application of needs assessment, as well as the benefits of conducting this type of research to improve the quality of assistive technology (AT) services. This chapter begins with a discussion of what is AT and the role it plays in the life of a person with a disability. This will include a discussion of the idea that the earlier AT is introduced to the individual, the more likely it will continue to be used and the larger effect it will have on the individual’s future education, employment, and independent living needs. Also, this chapter highlights the impact this type of research has on teacher preparation. Chapter 17 Developing Electronic Portfolios........................................................................................................ 251 Mary Ann Lowe, Nova Southeastern University, USA This chapter explores the use of electronic portfolios as a way of documenting the use of Assistive Technology / Augmentative and Alternative Communication (AT/AAC) for individuals with severe physical needs and communication impairments. Documenting individual student characteristics, the strategies used for successful implementation of AT/AAC tools, and the progress of these individuals using technology via electronic portfolios can be a useful tool for service providers. Chapter 18 Assistive Technology Solutions for Individuals with Learning Problems: Conducting Assessments Using the Functional Evaluation for Assistive Technology (FEAT) ............................. 264 Brian Bryant, University of Texas, USA Soonhwa Seok, Center for Research on Learning - eLearning Design Lab, University of Kansas, USA Diana Bryant, University of Texas, USA This chapter provides information about how such an assistive technology (AT) assessment can be conducted using the Functional Evaluation for Assistive Technology (FEAT). Readers are provided with an overview of the importance of person-centered assessments, and then are given a description of each of the FEAT components. A case study is also provided, wherein the process of an effective and efficient AT assessment is described.

Section 5 Teacher Education Chapter 19 Improving Assistive Technology Training in Teacher Education Programs: The Iowa Model .......... 286 James R. Stachowiak, University of Iowa, USA Noel Estrada-Hernández, University of Iowa, USA This chapter discusses the model that the College of Education at the University of Iowa is using to provide assistive technology training to their preservice teacher education students. The College’s Iowa Center for Assistive Technology Education and Research has developed an innovative hands-on project that revolves around their Mobile AT Lab. This chapter will focus on how the project was developed, is being carried out, and an evaluation of its success. Chapter 20 Effects of Assistive Technologies Combined with Desktop Virtual Reality in Instructional Procedures (1) ..................................................................................................................................... 299 Gary Dotterer, Oklahoma State University, USA With the advancements in technology and the ability to use different training techniques in industry, business, and educational environments, those who may need alternate methods of delivery of training materials should also be considered. Individuals with impairment who rely on assistive technologies could benefit from these alternative methods. Desktop virtual reality combined with assistive technologies could provide a safe, reliable, and productive opportunity while addressing the specific needs from the safety of their own personal computer. This chapter introduces the merging of these technologies and the opportunities that may be possible by providing viable training procedures and processes in the workforce. Chapter 21 Effects of Assistive Technologies Combined with Desktop Virtual Reality in Instructional Procedures (2) ..................................................................................................................................... 306 Gary Dotterer, Oklahoma State University, USA This chapter frames the structure of the study introduced in the previous chapter. The framework of the chapter sets up the methodology (subjects, testing instruments, and procedures) and includes screenshots of the three web-based instruments. The results and findings section contains detailed information with illustrated tables containing the data generated from the statistical analysis program SPSS. The chapter concludes with the discussion, further research directions, and conclusions based on the outcomes of the findings.

Chapter 22 Response to Intervention: Assistive Technologies which can Help Teachers with Intervention Programming and Assessment ............................................................................................................ 313 Michael W. Dunn, Washington State University Vancouver, USA How to assess and provide intervention programming for students with characteristics of having a learning disability has been a long-standing challenge in education. Traditionally, students with a possible learning disability completed assessments of IQ (i.e., intellectual potential) and academic achievement (i.e., demonstrated ability) around the end of third grade; a discrepancy of 15 points or more would typically provide for a student to be classified with a learning disability and receive special education services. Due to systemic bias in standardized assessments, such as IQ tests as well as a desire to address the needs of low-functioning students in the early/initial grades of school, educators have developed a new intervention and assessment process called response to intervention. If students do not make good progress with intervention programming, this curriculum-based data can be used to justify learningdisability classification. Assistive technologies such as intervention software can help teachers manage the provision of intervention programming and data collection. Chapter 23 Assistive Technology for Teacher Education: From Research to Curriculum .................................... 325 Marcie M. Belfi, University of Texas, USA Kristen E. Jones, University of Texas, USA This chapter provides teacher educators with research on assistive technology in K-12 schools from two different strands, and concludes with a model of teacher training to meet those needs. The first section describes assistive technology needs for culturally and linguistically diverse families of children with special needs. The second section highlights instructional and assistive technology for students with learning disabilities in the area of writing. Finally, the chapter concludes with a curriculum model for training preservice teachers to use assistive technology across the lifespan of students within all populations. Chapter 24 Supporting Early Childhood Outcomes through Assistive Technology ............................................. 339 Diane Plunkett, University of Kansas, USA Rashida Banerjee, University of Northern Colorado, USA Eva Horn, University of Kansas, USA This chapter focuses on the application of assistive technology to meet the Office of Special Education Programs early childhood outcomes with attention given to evidence-based strategies and practices in the use of assistive technology. By offering case vignettes, early childhood professionals may reflect upon their experience, and recognize the benefit that assistive technology has in meeting child developmental outcomes. In presenting a firm understanding for assistive technology consideration, the early childhood professional can assist children with disabilities and their families in meeting early childhood outcomes.

Section 6 Past, Present, and Future Chapter 25 Assistive Technology’s Past, Present and Future ................................................................................ 360 Barbara J. Kouba, California State University, San Bernardino, USA Brian Newberry, California State University, San Bernardino, USA The term assistive technology is relatively new, however the use of technology to assist humans to perform better is certainly not. Throughout history we have been creating devices to assist us by augmenting our senses, retaining information, accessing information, communicating and finding our way in the world. Many technologies that were originally assistive have become mainstream. New technologies that are being developed as assistive will no doubt also become mainstream in the future. Chapter 26 Digital Inequity: Understanding the Divide as it Relates to Culture and Disability........................... 374 Monica R. Brown, New Mexico State University, USA Michael Fitzpatrick, New Mexico State University, USA This chapter presents literature and research related to the digital divide for students from culturally and linguistically diverse (CLD) backgrounds. This chapter discusses issues of access for CLD students with disabilities, factors that have led to inequitable access to technology for those groups, and provides solutions for increasing access to technology for students with disabilities and students from CLD backgrounds. Chapter 27 Cognition and Learning ...................................................................................................................... 388 Blessing Nma Okrigwe, Rivers State College of Education, Nigeria Cognitivist theories have identified the cognitive skills—perception, conception, memory, language, reasoning and creativity—as underlying all academic learning, and absence of these skills will result in the child’s academic failure. Learners learning in different ways, which has an implication to personalized learning with the teacher playing the role of a facilitator, can help the student construct knowledge rather than the production of facts. This has thus led to a shift in paradigm from the traditional behavioral approach, where learners are passive, to a paradigm where learners are active and empowered. Personalized learning is made possible through digital technology such as the Internet; hence, innovation in teaching and learning has been dominated by the computer. Despite the numerous advantages of digital technology, which can provide opportunities for individuals with disabilities to meet their full learning potential, this has yet to be seen by most countries in the developing world. Compilation of References ............................................................................................................... 401 About the Contributors .................................................................................................................... 443 Index ................................................................................................................................................... 451

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Foreword

This handbook is the realization of a year long unified learning endeavor of collaborative writing and thinking from educators and professionals from around the world dedicated to the field of assistive technology. The contributors of this handbook have been leaders and positive influences in the everchanging, transdisciplinary assistive technology landscape. We are grateful to have been able to harvest such a wonderful collection of works into a single source. This handbook is a collaboration of 27 empirically-supported chapters addressing the current issues of human cognition and assistive technology design, the Internet, media, cognitive load, software and devices, evaluation and assessment, teacher education, and the practices of assistive technology in the past, present, and future. This handbook was written specifically for families, practitioners, and others involved in aiding those with disabilities. It is our hope that this handbook is a step forward in bettering the practice of assistive technology, the lives of those with disabilities, and a positive influence towards the mission behind the Individuals with Disabilities Education Act (IDEA). Gary M. Clark University of Kansas, USA

Gary M. Clark’s research focus is assessment for transition planning; consultation and training on using and interpreting the Transition Planning Inventory. Teaching assignments over the 38 years at the University of Kansas have included courses at the undergraduate and graduate levels. Most consistently, the courses assigned have been the introductory courses (UG and G) to the field of special education and two core courses in transition education and services. One other course taught periodically has been a course on counseling individuals with disabilities. Visiting professorship teaching assignments have focused on secondary special education and transition from school to adult living.

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Preface

The Handbook of Research on Human Cognition and Assistive Technology: Design, Accessibility and Transdisciplinary Perspectives marks a critical milestone in the history of implementation and practice of assistive technology in this country. We have come a long way since the term universal design was coined in the 1970s and linear perspectives and technology were at the forefront of assisting those with disabilities. Over the years, numerous studies have been conducted on assistive technology from a special education perspective. With the unprecedented advancements in computing power coupled with the societal movement towards inclusive settings, there is no better time than today to strive for assistive technology equity in terms of universal implementation within a transdisciplinary perspective. This edited book is borne from this opportunity and attempts to consolidate the relationships among human cognition and assistive technology. The intent of this book is to assist researchers, practitioners, and the users of assistive technology to augment the accessibility of assistive technology by implementing human cognition into its design and practice. Consequently, this book presents assistive technology as an intervention for people with disabilities from a transdisciplinary perspective. This book is composed of 27 chapters prepared into six sections. Section 1 serves as the scaffolding for the remainder of the book, by laying the theoretical foundation of human cognition and its direct applicability to the design of assistive technology. The chapters in this part are intended to align assistive technology with the study of how the human mind works, discussing the importance of cognitive load and knowing when to avoid it, how to managing it, and in some cases, promote it. The chapters also delve into the understanding of empirically supported instructional principles that can be leveraged to assist those with special needs. The use of simulation-based instruction is also introduced as a precursor to Section 2 of this book, presenting the significant contributions simulation technology has towards assisting those with learning disabilities. Section 2 focuses specifically on the Internet, media, and continues the line of thinking behind the management of cognitive load. The benefits of simulation-based instruction are expounded upon and the utilization of 3D virtual environments is presented. There has been a surge of popularity with such environments given the potentially limitless possibilities beyond that of entertainment. The chapters in this part discuss how such environments may hold significant opportunities to assist those who are challenged by traditional classroom instruction and interaction. Section 3 looks at software and devices as tools to benefit interventions for individuals with disabilities. The chapters in this part discuss the role of assistive technology practice in the field as it aligns with research. That is, practice triggers motivation to conduct formative and experimental design research to enhance the quality life of individuals with disabilities. Section 4 emphasizes the changing culture of evaluation and assessment in the area of assistive technology. In particular, the use of ecological evaluations and multi-model assessments reflect the

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trend toward transdisciplinary perspectives. The chapters in this part present evidence-based systematic research in the field. Section 5 stresses the practice of assistive technology as a strategy for teaching and learning. The chapters in this Section 1nitiate the development of formative instructional strategies using assistive technology to achieve effective learning outcomes. Finally, Section 6 summaries and describes what assistive technology looked like in the past, how it looks now, and how it might look in the future. This includes a review of the history of assistive technology-related legislation, research, and practice from traditional to modernist theories, from Helen Keller to Steven Hawking. It also addresses the “digital divide” and equity as major issues in the history of assistive technology. There are many books providing insights into assistive technology. What sets this book apart from other edited books is that this book has been forged from a transdisciplinary perspective. The editors and contributing authors come from a number of disciples to include computer science, instructional design, curriculum and special education, and psychology, to name only a few. This book is a collaboration between researchers and practitioners alike and we hope that you enjoy reading it as much as we enjoyed the delightful journey it was in getting it published. Soonhwa Seok University of Wisconsin-Whitewater, USA Edward L. Meyen Kansas University, USA Boaventura DaCosta Soler Research Group, USA

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Acknowledgment

First, special thanks go to the authors of the 27 chapters comprising this edited book. We especially thank them for their support and encouragement through the writing and publishing process and their interest in this effort. They were an inspiration to us as we carried out our research. This work is a reflection of their vision in guiding our collaboration. Sincere gratitude is extended to Julia Mosemann for her editorial efforts, her style, but most importantly, her unwavering sense of humor. Special appreciation goes to Brian Bryant, for his support, encouragement, and inspiration. He taught us how to turn water into wine. Finally, we are grateful to our all of our research collaborators who donated their time and expertise in this publication. “Thank You.” Soonhwa Seok University of Wisconsin-Whitewater, USA Edward L. Meyen Kansas University, USA Boaventura DaCosta Soler Research Group, USA

Section 1

Human Cognition and Assistive Technology Design To say that learning through the use of technology has had an intertwined past of failing to deliver on expectations is an understatement. History can provide a myriad of examples related to motion picture, radio, television, and computer-assistive instruction that serve as a reminder to what many of us already know—using technology for the sake of technology does not work. In fact, it can be detrimental to learning. Instead, the driving force behind technology should be the learner; namely, the manner in which technologies can be used to promote human cognition. Instructional designers, educators, practitioners, and others involved in the design of learning technologies know that the latest advancements in cutting-edge technology are simply not enough, but rather, such knowledge must be coupled with an understanding of the human information processing system. Such an argument could not be any more applicable to the design of assistive technologies for those with learning disabilities. Firmly grounded in the field of cognitive psychology, the human information processing system provides a useful frame in which to understand the mental processes involved in higher-order thinking and consequently, learning. Why is this important? Some theories in cognitive psychology suggest that working memory, a system that temporarily stores and manages information for performing complex cognitive tasks, is limited in capacity. When coupled with the deficits of those with learning disabilities, such as difficulty with attention, memory, and problem-solving, all of which are vital factors in learning, the human information processing system can prove invaluable to designers in understanding best practices in which to present information. In the first part of this handbook, we present the relationship between human cognition and assistive technologies and its design for individuals with learning disabilities. In the first chapter, we introduce the human information processing system, discuss the modal model of memory, and describe ways in which to increase learning. In the second chapter, we present strategies to manage cognitive load in the design of instructional materials for those with learning disabilities by introducing cognitive load theory—a learning theory that proposes a set of instructional principles grounded in human information processing research that can be leveraged in the creation of efficient and effective learning environments. In the third chapter, we focus specifically on research investigating the visual and auditory components of working memory by presenting the cognitive theory of multimedia learning—a learning theory proposing a set of instructional principles grounded in human information processing research that provide best practices in designing efficient multimedia learning environments. While finally, in the fourth chapter, we present the use of computer-based simulation as an assistive technology solution. Altogether, we present the approach that assistive technologies for individuals with learning disabilities should be created with an understanding of design principles empirically grounded in the study of how the human mind works.

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Chapter 1

Human Cognition in the Design of Assistive Technology for Those with Learning Disabilities Boaventura DaCosta Solers Research Group, USA Soonhwa Seok Center for Research on Learning - eLearning Design Lab, University of Kansas, USA

AbstrAct This is the first of three chapters serving as the introduction to this handbook which addresses the relationship between human cognition and assistive technologies and its design for individuals with cognitive disabilities. In this chapter the authors introduce the human information processing system. They discuss the modal model of memory, a basic framework offering the most popular explanations behind the active processes used in the construction of new knowledge. In doing so, the authors examine the three memory stores comprising the modal model which are responsible for the acquisition, storage, and retrieval of information. The authors then discuss ways in which to increase learning. Altogether, they present the approach that technology for learning should be created with an understanding of design principles empirically grounded in the study of how the human mind works, particularly when it comes to the design of assistive technologies for individuals with learning disabilities.

IntroductIon the case for Human cognition in the design of Assistive technology for those with Learning disabilities First published in the Technology-Related Assistance for Individuals with Disabilities Act of 1988 DOI: 10.4018/978-1-61520-817-3.ch001

and since amended and replaced with the Assistive Technology Act of 1998, assistive technology (AT) has been formally defined as “any item, piece of equipment, or product system, whether acquired commercially, modified, or customized, that is used to increase, maintain, or improve functional capabilities of individuals with disabilities” (United States Congress, 1998, Definitions and Rule section, para. 3). Although we typically think of technologies such as wheelchairs and prosthetics to help those with

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Human Cognition in the Design of Assistive Technology for Those with Learning Disabilities

physical impairments, ATs can also have a significant impact on the lives of those with cognitive disabilities. If created with the abilities and deficits of those with cognitive disabilities in mind, ATs can remove obstacles and offer individuals greater independence which they might not otherwise be able to experience. Likewise, the opposite is also true. Assistive technologies created without an understanding of the cognitive disabilities of individuals can become a hindrance. Unlike that of AT, the mere act of defining the term “cognitive disability” has proved troublesome.

the broad nature of cognitive disabilities and our Focus on Learning disabilities Definitions for the term “cognitive disability” vary by source. Generally speaking, a cognitive disability is any disorder which affects mental processing. There are different severities of cognitive disabilities. Individuals with severe disorders may need uninterrupted assistance and supervision by caregivers in almost every aspect of daily life, whereas individuals with minor cognitive disabilities may require very little if any assistance. In fact, some cognitive disabilities may be so minor that they are never diagnosed (Rogers, 1979).

Our Focus on Learning Disabilities In this three chapter introduction we focus on cognitive disabilities which impair learning. Specifically, children, adolescents, and adults diagnosed with learning disabilities (LDs). We refer to children, adolescents, and adults because LDs are considered to be lifelong disorders. Children with LDs will someday grow up to become adults with LDs. Their brains are not defective or damaged. Instead, they see, hear, and understand things differently. Learning disabilities are thought to be neurological in nature and are related to central

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nervous system dysfunction (National Joint Committee on Learning Disabilities, 1991). This brings up an important point. Learning disabilities should not be used as a measure in which to gauge intelligence. Individuals with LDs have average or above average intelligence, but have difficulty with rudimentary skills that those without LDs take for granted. Learning disabilities are typically considered to be less severe cognitive disorders which can manifest themselves in many different forms. Reading disabilities (dyslexia), writing disabilities (dysgraphia), and math disabilities (dyscalculia), are probably the most recognizable LDs owing their mainstream familiarity to the media and other public channels.

bAckground What are Learning disabilities? There have been a myriad of efforts to define LDs. The need for a definition has stemmed from the fact that without one, LDs cannot be clearly recognized and measured for the purpose of diagnosis and remediation (Wong, Graham, Hoskyn, & Berman, 1996). As you might imagine, obtaining consensus among professionals and policy makers within the LDs community has been difficult. In fact, some efforts have ignited fierce debates, such as the 2004 reauthorization of the U.S. Individuals with Disabilities Act (Fletcher, Lyon, Fuchs, & Barnes, 2006). Although varying definitions continue to exist among professional organizations and government agencies (see Wong et al., 1996, for an in-depth review), a definition that appears to have captured the essence of LDs and received the broadest endorsement in the LDs community (Hammill, 1993, as cited in Wong et al., 1996) is the one by the National Joint Committee on Learning Disabilities (NJCLD) (1991), which reads:

Human Cognition in the Design of Assistive Technology for Those with Learning Disabilities

Learning disabilities is a generic term that refers to a heterogeneous group of disorders manifested by significant difficulties in the acquisition and use of listening, speaking, reading, writing, reasoning, or mathematical abilities. These disorders are intrinsic to the individual and presumed to be due to central nervous system dysfunction. Even though a learning disability may occur concomitantly with other handicapping conditions (e.g., sensory impairment, mental retardation, social and emotional disturbance), or environmental influences (e.g., cultural differences, insufficient/ inappropriate instruction, psychogenic factors), it is not the direct result of those conditions or influences (p. 3). As seen in the definition, the NJCLD supports the idea that LDs are not the direct result of other disabilities, but instead may occur alongside other disorders. This is important in the context of this and the next two chapters because although we focus on children, adolescents, and adults diagnosed with LDs, we do not exclude more severe cognitive disabilities such as autism, Down syndrome, the most common form of dementia, Alzheimer’s disease, and disorders resulting from traumatic brain injury.

Viewing Learning Disabilities from a Functional Perspective Given the broad nature of LDs and the potential degree of severity that can exist with these disorders, it goes without saying that individuals with LDs interact with technology in different ways. So, in addition to viewing LDs from a clinical standpoint, as we just have, when developing ATs, it might be more advantageous to view such disabilities from a functional standpoint. This perspective focuses strictly on the abilities and deficits facing individuals with LDs. As defined by the NJCLD (1991), deficits typically include difficulty with listening speaking, reading, writing, reasoning, or mathematical abilities. Taking

a step back and examining these deficits further reveal that individuals diagnosed with LDs have difficulty with attention, memory, and problemsolving, all of which are vital factors in learning. We once again stress that the utmost care must be taken by designers involved in the creation of ATs. Designers must not only have a deep understanding of the technologies currently available, but an even deeper functional understanding of the abilities and deficits facing the individuals for whom they are designing. As commonsensical as this may sound, as we will discuss next, history has shown us quit the opposite.

the troubled Past of technology and Learning The potential for the improvement of learning through the use of technology within education has not translated very well into everyday practice. For the most part, technology and learning have had an intertwined past of failing to deliver on expectations. In fact, a mere cursory examination of the prospect of new technology for learning in the 20th century would produce a myriad of examples relating to motion picture, radio, television, and computer-assisted instruction (see Cuban, 1986, for an in-depth review). The example commonly cited as evidence for this long-lasting, tempestuous relationship is the quote by Thomas Edition, who in 1922 prophesized “…the motion picture is destined to revolutionize our educational system and that in a few years it will supplant largely, if not entirely, the use of textbooks” (cited in Cuban, 1986, p. 9). This quote serves as a reminder to what many of us all ready know—using technology for the sake of technology does not work. In fact, there is a consequence when the technology-centered approach is adopted over that of the learner-centered one (Mayer, 2005b). Namely, the technologycentered approach does not generally lead to longterm advancements in education (Cuban, 1986, as cited in Mayer, 2005b). Hindsight has taught us

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Human Cognition in the Design of Assistive Technology for Those with Learning Disabilities

this lesson with the prediction made by Thomas Edison and the many other failed attempts at using technology for learning that have followed. Needless to say, the driving force behind technology design should not be the technology itself, but rather the learner. When the learner-centered approach is taken, focus is placed on the manner in which technologies can be used in the promotion of human cognition (Mayer, 2005b). This should come as no surprise to instructional designers, educators, practitioners, and others involved in the design of technology for the improvement of learning. Understanding the latest advancements in cutting-edge technology is simply not enough. Rather, such knowledge must be coupled with an understanding of the human information processing system. According to Mayer (2005b), “…designs that are consistent with the way the human mind works are more effective in fostering learning than those that are not” (p. 9). If the full potential of technology for learning is to be realized, there must be a clear understanding between design principles and the means by which humans acquire, store, and retrieve information.

Assistive technology, Learning disability, and Human Information Processing We argue that this approach could not be any more applicable to the design of ATs for those with LDs. Arising from work in cognitive psychology, the human information processing system and associated models provide a useful framework in which to understand the mental processes involved in higher-order thinking and consequently, learning. This is important because some theories in cognitive psychology suggest that working memory, a system that temporarily stores and manages information for performing complex cognitive tasks, is limited in capacity (Baddeley, 1986, 1998, 2002). When coupled with the functional perspective of LDs, the human information processing system can prove invalu-

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able to designers in understanding best practices in which to present information. This is the first of three chapters serving as the introduction to this handbook which addresses the relationship between human cognition and ATs and its design for individuals with LDs. In this chapter, we introduce the human information processing system. We describe the most popular explanations behind the acquisition, storage, and retrieval of information. We then discuss ways in which to increase learning. This chapter serves as scaffolding for the subsequent two chapters of which are both grounded in learning theory. In the second chapter, we focus specifically on the cognitive limitations of working memory. In doing so, we introduce cognitive load theory and its applicability in the design of ATs. Finally, in the third and final chapter in this introduction, we discuss the importance of visual and auditory modality in the design of ATs. We go about this by offering an in-depth discussion of the cognitive theory of multimedia learning. In both chapters, we focus predominately on those individuals who have been diagnosed with LDs, but as we have discussed, may also include individuals diagnosed with more severe cognitive disabilities. We begin this chapter with a brief history of the field of cognitive psychology. To better understand the most accepted theories behind human cognition, we feel it is prudent to first understand how the field came to be.

A brIeF HIstory oF cognItIve PsycHoLogy As you might imagine, the study of the human mind is centuries old. In fact, the study of human cognition can be traced back as early as the ancient Greeks, with Aristotelian notions of the beginnings of empiricism, the belief that knowledge originates from experience (John Robert Anderson, 2004). However, early study of the human mind was philosophical in nature, purely grounded in con-

Human Cognition in the Design of Assistive Technology for Those with Learning Disabilities

jecture. According to Anderson (2004), “only in the last 125 years has it been realized that human cognition could be the subject of scientific study rather than philosophical speculation” (p. 6). It was not conceived until the Nineteenth century, actually, that the study of the human mind could be grounded in scientific analysis (John Robert Anderson, 2004). This does not imply that cognitive psychology emerged right away as a major field of study in the 20th century. Instead, it would be half a century before the beginnings of such a movement would be seen. According to Brunning, Schraw, Norby, and Ronning (2004), from 1920-1970, associationism, the proposition that all consciousness can be explained by the association of sensory stimulus with responses, was the dominant, theoretical, psychological perspective in America. So it should come as no surprise that by the 1960s (Brunning et al., 2004), behaviorism, the theory that all behaviors are a result of conditioning, began to flourish. As a matter of fact, during the behaviorism movement, psychologists such as B. F. Skinner, who were involved in one branch of stimulusresponse psychology called radical behaviorism, were successfully applying behavioral principles to a variety of settings, which included education (Brunning et al., 2004). It was right about this time that American psychologists, wanting to provide plausible explanations of human memory, where becoming increasingly disenchanted and bothered with the strict stimuli-response framework governing behaviorism (Brunning et al., 2004). The focus of behaviorism was external behavior. It was not concerned with the internal workings of human memory that cause this behavior. Behaviorism, for that reason, was ill-equipped to provide the necessary scaffolding needed to adequately describe human cognition. It is difficult to say exactly when the cognitive revolution overthrew behaviorism. We know that the cognitive psychology movement took form between 1950 and 1970, with significant mark-

ers, such as the journal, Cognitive Psychology, first appearing in 1970 (John Robert Anderson, 2004). Another commonly cited milestone is that of the publication of Ulrich Neisser’s Cognitive Psychology in 1967, which helped both legitimize the field and define it (John Robert Anderson, 2004; Brunning et al., 2004). Although cognitive psychology is still relatively young in American psychology, it has seen widespread growth. The field has far reaching implications, touching many other disciplines such as computer science and the study of artificial intelligence. The exception is education, as Brunning et al. point out (2004), which only until recently has become the target of exploration (e.g., Brandt, 2000; Bransford, Brown, & Cocking, 2000; Jonassen & Land, 2000; Kirschner, 2002; Marshall, 1996). Unlike earlier portrayals, cognitive psychology views humans as information processors. The field of cognitive psychology is dedicated to the understanding of how information is represented in the human mind. Thus, cognitive psychologists have developed numerous models aimed at adequately depicting the active nature of cognition. From this, cognitive learning models have been conceived, which attempt to explain the processes of learning (Brunning et al., 2004). In the next section, we begin our discussion of these models and their most common features.

tHe HumAn InFormAtIon ProcessIng modeLs Human memory has been traditionally depicted as models composed of acquisition, storage, and retrieval stages, otherwise collectively referred to as information processing models (e.g., Atkinson & Shiffrin, 1968; Waugh & Norman, 1965). Although variations of these models have been abundant (e.g., Atkinson & Shiffrin, 1968; Norman, 1968; Shiffrin & Atkinson, 1969; Waugh & Norman, 1965), their common features have influenced a basic framework made popular over

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Human Cognition in the Design of Assistive Technology for Those with Learning Disabilities

Figure 1. The modal model of memory (Adapted from Brunning et al., 2004, pg. 16; Clark, 2003, pg. 54-55; and Mayer, 2005b, pg. 37)

the past five decades called the modal model of memory (Healy & McNamara, 1996). The modal model offers a helpful way in which to describe the active processes that humans use to construct new knowledge. The model postulates that information is processed by means of sensory memory, short-term memory (STM) (or what is more commonly referred to as working memory), and long-term memory (LTM), all of which are discrete memory systems each serving a specific function (Healy & McNamara, 1996). The model is typically compared metaphorically with that of the operations of a computer (Atkinson & Shiffrin, 1968; Shiffrin & Atkinson, 1969). Although variations exist as to how learning takes place with regard to the modal model, it is generally agreed upon that information is transferred between these memory stores using a variety of encoding and retrieval processes (see Brunning et al., 2004, for an in-depth discussion of these processes). A representation of the modal model of memory is depicted in Figure 1. As the figure illustrates, for learning to take place, new information must first be brought into sensory memory. This is accomplished through what is seen and/or heard. While other senses obviously play a role, sensory memory is typically described in terms of visual and auditory modality, as these are the senses that have been studied the most with regard to cognition and

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learning, for obvious reasons. Information found in sensory memory is then brought into STM or working memory. Here, the information is further processed and potentially associated with relevant, prior knowledge, until it is permanently encoding into LTM. As you may already have guessed, there is much more to the modal model than our rushed explanation. In fact, Figure 1 could be very well argued as a gross oversimplification as to the actually mechanics behind human information processing. In the subsequent sections we introduce each of the memory stores comprising the modal model.

An Introduction to sensory memory We turn our attention to the first store of the modal model, sensory memory. We begin with a general discussion, describing sensory memory in terms of visual and auditory modality. We then present the significant role that perception and attention have in our ability to process information.

Visual and Auditory Modalities Information first enters sensory memory by means of the senses. Sensory memory is considered to be a short-term buffer limited in both capacity and duration. Stimuli entering sensory memory are

Human Cognition in the Design of Assistive Technology for Those with Learning Disabilities

stored in what is referred to as sensory registers (Brunning et al., 2004). It is in these registers where information is held until it can be processed. Sensory memory is typically described in two modalities: iconic memory, which handles visual stimuli (see Sperling, 1960) and echoic memory, which handles auditory stimuli (see Darwin, Turkey, & Crowder, 1972). Overall, evidence in support of echoic memory is much less impressive than that of iconic memory (Pashler, 1998). Furthermore, echoic information is considered to be more persistent in sensory memory, lasting approximately one to two seconds (Pashler, 1998), than that of iconic information, which is believed to last approximately one to two tenths of a second (Ware, 2004). Practically speaking, however, this difference is negligible, and both are viewed as short-term buffers.

Perception and Attention Perception is considered vital in the successful processing of incoming stimuli. Perceptual analysis occurs by means of attention and the recognition of patterns (Brunning et al., 2004). That is, we focus our attention on information that we consider meaningful. For example, we are constantly inundated with visual and auditory information. We are incapable of processing all information that enters through our senses, so instead we only focus on information that we perceive as significant and useful (Brunning et al., 2004; Clark, 2003). Attention can, therefore, be defined as the cognitive process involved in selectively focusing on relevant information, while at the same time, ignoring information that is not relevant. We attend to only certain information that, one way or another stimulates us. Our level of attention can, therefore, vary depending on our state of arousal which can be inadvertently affected by ailments such as fatigue and anxiety (Clark, 2003). What we already know or what we are currently processing in STM can also play a significant role on what sensory information we focus our atten-

tion. Prior knowledge found in LTM has a direct influence on perception and pattern recognition (Adams, 1990), helping us make sense of what we see and/or hear. The significance of prior knowledge on sensory memory brings up and important point. Although the modal model is depicted as a system composed of discrete memory structures, each serving a specific function, these stores do not operate in isolation. Instead, it is believed that there is a substantial amount of interactivity that occurs between the memory stores. What’s more, attention is considered a key contributor in the interactivity between these stores; helping us focus only on what is relevant, mitigating the extent to which STM becomes overwhelmed. (The importance of attention will become clearer as we progress through this chapter.) Unfortunately, research focused on attention has been controversial at best. In fact, research on the subject has yielded contradictory findings. Brunning et al. (2004) explains that conflicting findings frequently result from the extremely susceptible nature of attention allocation to the type of task being carried out. So a commonly accepted explanation as to the mechanics behind attention has yet to be adopted (Clark, 2003). What is agreed upon, however, is that we are severely limited as to the quantity of information that can be attended to at any given time (e.g., Friedman, Polson, & Dafoe, 1988; Spear & Riccio, 1994). Many of us have experienced this in our professional lives when trying to juggle multiple tasks all at the same time. In the end, we may realize that we were only successful at carrying out everything poorly. (The exception to this is the ability to automatically process tasks, which we discuss next in this chapter.) Instead, we think most effectively and maximize our ability for learning when we are selective in our attention, only forwarding pertinent information into STM. Doing so, as we will soon discuss, does not guarantee learning, however. Short-term memory has its own share of limitations.

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Human Cognition in the Design of Assistive Technology for Those with Learning Disabilities

An Introduction to shortterm memory In this section, we turn our attention to the second store of the modal model, short-term memory. We begin with a discussion of the capacity and duration limitations of the memory store. In doing so, we present chunking and automaticity, means by which we can increase the efficiency of STM. We then discuss working memory, a theoretical model explaining the information processing mechanics behind STM.

Capacity and Duration Limitations Short-term memory has long been viewed as the store limited in both capacity and duration where information is processed for meaning. The earliest quantification of the capacity limitations of STM is the landmark article by Miller (1956) who proposed that an “informational bottleneck” (Summary section, ¶ 2) exists with regard to STM. Miller had proposed that STM is limited to seven (plus or minus two) chunks at any one time. Think of a chunk as a meaningful grouping of information. This means that we can only handle 5 to 9 units of information in memory. Fortunately, the capacity limit of STM can be stretched by increasing chunk size, thus providing an outlet in which to dramatically improve information processing (Miller, 1956). This is important, because although STM is limited in the number of chunks that can be held, these chunks are not restricted in their size. The example of chunking most commonly offered is probably that of telephone numbers. When initially learning a new local phone number, such as 5-6-8-0-8-5-4, each individual digit must be chunked because the number has not yet been committed to memory (i.e., encoded into LTM). Based on the format of telephone numbers, we know that we can chunk these digits into groups of three and four numbers. Using our example, we could consequently chunk the number as

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568-0854. Furthermore, since it is a local number, we more than likely have already chunked the area code. By grouping the individual units of information into large blocks (as we did in our example from seven chunks to that of two) we are capable of managing larger amounts of information in STM. There is yet another way in which to deal with the seven (plus or minus two) limitation. Automaticity is the belief that if a task is repeated enough times, it can be performed automatically, to the extent that it bypasses and no longer needs STM (Brunning et al., 2004; Clark, 2003). Performing such tasks with little or no conscious attention or thought alleviates the burden placed on STM. These available resources can then be used towards the processing of new information. An example is the decoding you are doing right now while reading this chapter. Another example commonly cited (e.g., Brunning et al., 2004) is that of driving. You might have, at some point in your life, witness a driver making a turn, which may have consisted of the driver: shifting gears, speaking to their passenger(s) or on their cell phone, activating their turning signal, making the actual turn, and watching out for other drivers and pedestrians, all while obeying local traffic laws! Without the ability to perform tasks automatically, the capacity limitation of STM would severely cripple our ability to function. Much like attention, automaticity is considered essential to learning. Research quantifying the duration limit of STM can also be found dating as far back as half a century. Early studies found that information is incredibly volatile in STM. For example, Peterson and Peterson (1959) had demonstrated in two experiments that information in STM is quickly forgotten within about 20 seconds if not rehearsed. (Take a moment to recall, if you can, the telephone number used in our chunking example. Do you remember it?) Early psychologists believed this decay of information was due to time (Waugh & Norman, 1965). Subsequent studies (e.g., Waugh & Norman, 1965), however, have suggested in-

Human Cognition in the Design of Assistive Technology for Those with Learning Disabilities

terference caused by later information (i.e., items in a series) is more than likely the culprit of this information decay (Greene, 1992; Solso, 2001). In other words, information is easily forgotten if it is immediately followed by other information.

Working Memory As an assortment of operations were being attributed to STM, little was being offered as to how these operations occurred, and by the later half of the 20th century, researchers were becoming dissatisfied with the idea of STM (Brunning et al., 2004). The complexities of STM eventually led cognitive theorists and psychologists towards proposing theoretical models explaining the information processing mechanics behind STM, or what would be called working memory. Although the distinction between STM and working memory varies, in the broadest sense, STM can be viewed as an abstract and theory neutral premise explaining the temporary storage of information within behavioral psychology (e.g., Miller, 1956); whereas, working memory is much more theoretical in nature, explaining the processing of information within cognitive psychology (e.g., Baddeley, 1986, 1998). Working memory is seen as the store responsible for active processing, unlike STM, which has been seen as a much more passive store, responsible for the maintenance of information. Although various models have been created (e.g., MacDonald & Christiansen, 2002; Niaz & Logie, 1993), one of the most prominent contributors to the theory of working memory is Baddeley (1986, 1998, 2002), who proposed the model of working memory. A three system model composed of an executive control system, a phonological loop, and a visuospatial sketchpad. The executive control system manages the two subsystems along with deciding what information to allow into working memory and what course of action to take to process information once in working memory. The

two subsystems, the visuospatial sketchpad and the phonological loop, hold and process information. Spatial information is handled by the visualspatial sketchpad, whereas acoustic and verbal information are handled by the phonological loop. According to Baddeley (1986, 1998, 2002), these three systems work collaboratively to process all information in working memory. Much like STM, working memory is believed to suffer from the same capacity and duration limitations. Cognitive psychologists see working memory as a limited capacity information processing system which temporarily stores and processes information for encoding into LTM. It is limited to seven (plus or minus two) chunks of information at any one time. It is believed that as storage demands increase, available processing resources decrease (Niaz & Logie, 1993). This poses a significant challenge, as these limitations can seriously hamper learning. Although Baddeley’s model is seen as one of the most influential contributions to cognitive psychology, many feel that working memory is not a distinct store composed of separated components. But instead, tightly integrated with and strongly influenced by LTM. As we discuss next, LTM plays a vital role in the processing of information within working memory.

An Introduction to Longterm memory Thus far we have discussed the first two stores of the modal model: sensory memory and STM. (We will use the term “working memory” from this point forward.) In this section, we turn our attention to the third and final component of the model, long-term memory. We begin by presenting the different types of knowledge found in LTM. We then describe how this knowledge is stored and organized. We finish this section with a brief discussion of the connections between LTM and working memory.

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Human Cognition in the Design of Assistive Technology for Those with Learning Disabilities

Classifications of Knowledge Long-term memory is the persistent store of all the information we have amassed over the course of a lifetime. We call it a persistent store because LTM is not susceptible to the capacity and duration limitations which plaque sensory memory and working memory. Long-term memory is composed of three different types of knowledge: declarative, procedural (John R. Anderson, 1983; Squire, 2008), and conditional (see Brunning et al., 2004). Declarative and procedural knowledge are the most commonly discussed in cognitive psychology, whereas conditional knowledge has not been as widely talked about (Brunning et al., 2004), but as we will soon see, is just as important if not more. Declarative knowledge is best described as “what” we know about things (Brunning et al., 2004). It is factual knowledge that can be easily recalled and explicitly articulated. Declarative knowledge has been further categorized into semantic memory and episodic memory (Squire, 2008; Tulving, 2002). Semantic memory refers to the generalization of knowledge. It is composed of factual information and general knowledge that is unrelated to personal events in our lives. Examples include geographic knowledge we have about places we have visited (and not visited for that matter). Episodic memory, on the other hand, is knowledge that is associated with personal events from our past. Episodic knowledge is autobiographical in nature (Tulving, 1983) and may date as far back as childhood or as recently as today. Retrieving episodic knowledge can help activate the reconstruction of personal events. The opposite is also true. The recollection of personal events can help in the retrieval of specific knowledge which might otherwise be inaccessible. Whereas declarative knowledge deals with factual information, procedural knowledge is the knowledge we have about “how” to do things (Brunning et al., 2004). Procedural knowledge is the implicit knowledge we have about the skills

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we posses. Because it is implicit, procedural knowledge cannot be easily communicated. For example, if someone were to ask you to clearly explain how to ride a bicycle, could you do it? Could you provide an unambiguous explanation on how to play a musical instrument, such as the clarinet? When performing a task that requires procedural knowledge, we are not consciously aware of the individual steps which comprise it, and consequently, have difficulty putting into words how we go about performing such a task. Finally, conditional knowledge is best described as knowing “when” and “why” to use and not use declarative and procedural knowledge (Brunning et al., 2004). Conditional knowledge is knowledge about why we should use certain strategies, under what conditions to use them, and why we should use them over other strategies we have. Conditional knowledge can be easily argued as the most important of the three for obvious reasons. It goes beyond facts and skills. Unfortunately, as you might suspect, it is also the one that individuals struggle with the most. Meaning, unlike the learning of factual information or a skill, learning to make decisions is incredibly difficult. Think about how you decide to use one strategy over that of another? How did you learn to do this?

Organization of Knowledge There have been a number of theories proposed which attempt to explain how knowledge is represented in LTM. These theories are best suited towards the different classifications of knowledge we have discussed thus far. As Brunning et al. (2004) explain, the theories—concepts, propositions, and schemata—best describe ways of representing declarative knowledge, most notably semantic memory; whereas the theories— productions and scripts—best describe ways of representing procedural knowledge. While all of these theories have made significant contributions to the understanding of human memory and

Human Cognition in the Design of Assistive Technology for Those with Learning Disabilities

cognition, we focus solely on schemata (sing., schema), which are mental frameworks explaining the means by which knowledge is organized in LTM. Schemata are cognitive structures we use to organize our knowledge so that we can understand the world around us. Schemata are representations of our prior knowledge and experience and are responsible for the encoding, storage, and retrieval of information (Brunning et al., 2004). Needless to say, schemata are viewed as essential to information processing. It is through schemata that our current knowledge influences new information we are trying to learn. Schemata are viewed as having relationships between variables called slots (Brunning et al., 2004). Think of these slots as “placeholders” that house information associated with the schemata. As you might expect, schemata can be composed of an array of slots. The information stored in these slots control what knowledge we encode, store, retrieve, and even attend to. For example, if you were to bring the schema of “human face” to mind, the schema’s slots would be instantiated with information that you’ve associated with the human face. More than likely your array of slots might have the values “eyes”, “ears”, “nose”, “mouth”, and “hair”; you would also have slots for “eye color”, “hair color”, and so on. While this example is a gross oversimplification, it helps illustrate this concept. By bringing the schema of the human face into the foreground, you retrieve all the knowledge that you’ve associated with it. This also brings up an important point; schemata vary in complexity (Jonassen, Louise, & Grabowski, 1993). They can represent relatively simply concepts or very complex ones to the extent of comprising an infinite array of values and relationships. The complexity of a schema relies heavily on the personal experiences of the individual. The more an individual knows about something, the more complex their schema will be. It is also believed that the more sophisticated the schema, the better the learning (Clark, 2003).

For example, a medical professional, such as a dermatologist might have a much more sophisticated schema about the human face than most adults, but at the same time, the average adult might have a much more complex schema of the human face than most young children.

Working Memory and LongTerm Memory Interactions The complexity of schemata also has an impact on working memory, since LTM and working memory interact with one another. Recall our discussion on the chunking of information? (Were you able to remember that telephone number? If so, can you recall it again?) In that although working memory is limited in the number of chunks that can be held, chunks are not restricted in their size. This has direct applicability to schemata. The more sophisticated our schemata, the more we can chunk and temporarily store in working memory. Everything you know about the human face could be retrieved into working memory as a single chunk of information, making best use of working memory’s limited resources. Automaticity also plays a significant role in the interactions between LTM and working memory. We discussed that if a task is repeated enough times, it can be performed automatically, requiring very little from working memory’s already limited resources. This is applicable to schemata as well; alleviating resources than can be used in the processing of new information. All in all, schemata theory is one of the more compelling explanations to have emerged. This popularity stems from the fact that the theory views the encoding of information as a constructive process (Brunning et al., 2004). Information is stored in LTM as representations of knowledge. For information to be retrieved, it must be re-created based on the schemata instantiated at the time (Brunning et al., 2004). In attempting to understand how knowledge is organized in LTM as well as how LTM and working memory interact

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Human Cognition in the Design of Assistive Technology for Those with Learning Disabilities

with one another, we can come closer to understanding the complex nature of learning. In the next section, we briefly introduce metacognition, a concept just as important as attention to human information processing and learning.

An Introduction to metacognition Spawning a wealth of research since it was first proposed nearly four decades ago, metacognition refers to an individual’s awareness of his or her own cognitive processes and strategies (e.g., Flavell, 1979). Simply put, metacognition is “thinking about thinking” (Brunning et al., 2004; Clark, 2003; Reid & Lienemann, 2006). It is the means by which we know what we know, but more importantly, what we don’t know. Metacognition makes us aware of our own cognitive processes and suggests strategies to help us with learning. Metacognition is typically best explained with an example. Imagine a college student studying for a final exam. During the final class lecture, she asks the professor if the final exam will be cumulative, composed of all the material taught in the course to-date. She has done well during the semester, and in the days prior to the exam, chooses to only study the material that she has struggled with. Another example is the rate at which you are reading this chapter. Depending on your familiarity with the material, you may be reading each section carefully, highlighting and/ or taking notes, or you may be quickly reading through each section, skipping passages you are comfortable with. Both of our examples show how metacognition is important in determining what we know and don’t know. It allows us to maximize our time and only focus on what we believe is important for our own learning. Metacognition has been traditionally described as encompassing both knowledge and regulation (e.g., Flavell, 1979). Metacognitive knowledge is what we know about cognition (Brown, 1987). It is more than knowing factual information. It is knowledge about our own cognitive processes that

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can be used to help us in learning. Metacognitive knowledge is knowledge about what we need to do to accomplish our goal of learning and what strategies we need to employ to meet that goal. It is knowledge and beliefs about us. Not surprisingly, metacognitive knowledge is described as three components: declarative, procedural, and conditional knowledge (Brown, 1987; Jacobs & Paris, 1987). In the case of our college student, she might decide to study at the local library because she knows that she will be better able to focus on the material and consequently learn more in a shorter period of time than if she were to go home and be tempted by the many distractions she has become accustomed to. Metacognitive regulation, on the other hand, is the means by which we control cognition (Brown, 1987). These are strategies that we use to manage our cognitive activities. Metacognitive regulation allows us to plan appropriate strategies and allocate resources, monitor our cognitive activities, and reflect on the outcomes of those activities, making changes if necessary. Our college student might use a number of strategies to help her learn the material while at the library. These strategies will help her gauge whether or not she has learned the material well enough to get a satisfactory score on the final exam. She may decide to self-test after reading each section, by mentally asking herself questions about what she has just read. If she answers the questions to her own satisfaction, she may decide to continue to the next section, otherwise, she may instead decide to read the material a second time. Without metacognition, our ability to function, let alone learn, becomes stippled. We know from research on the subject that individuals of equal intellect can experience varying levels of success in learning based on their metacognitive skills (Clark, 2003). As a result, individuals who have problems with metacognition, such as those with LDs, cannot actively engage in the task of learning (Reid & Lienemann, 2006), placing these individuals at a severe disadvantage. Further

Human Cognition in the Design of Assistive Technology for Those with Learning Disabilities

compounding matters, research has told us that metacognition develops later in life (Alexander, Carr, & Schwanenflugel, 1995). We are simply not born with a repertoire of metacognitive skills, but instead these skills develop as we mature and gain experience. There is a great deal more to metacognition than we have been able to present in this chapter. However, we trust that our discussion has painted a picture of the undeniable importance metacognition serves in human information processing and learning. This section also completes our discussion of the modal model of memory. Next, we end this chapter with a discussion of the ways in which we can increase learning based on what we have presented thus far.

concLusIon Ways to Increase Learning As we have learned, human information processing is rather constrained. According to Brunning et al. (2004), there are three ways in which learning is hindered. First, working memory is seen as a contradiction in terms. Its limitations cause it to be a bottleneck (Miller, 1956); yet, it is also the conduit for learning. This is a problem because the acquisition of new knowledge relies so heavily on the processing and storage capabilities of working memory (Low & Sweller, 2005; Sweller & Chandler, 1994). New information may potentially overload working memory capacity and subsequently encumber learning (Kalyuga, Chandler, & Sweller, 1999; Sweller, van Merrienboer, & Paas, 1998). Second, the organization of knowledge in LTM may also be problematic depending on the construction of schemata. Prior knowledge retrieved into working memory which is not efficiently chunked can cause severe limitations in our ability to learn. Finally, a lack of metacognitive ability can prevent us from using

our memory as efficiently as possible, also seriously hampering learning. Despite these cognitive roadblocks, humans are obviously fully capable of learning. There are three ways in which to improve learning according to Brunning et al. (2004). These are: increase the amount of attention, decrease the amount of attention being consumed by each task, and limit attention to only important and relevant information to be learned. It should come as no surprise that attention is the means by which we can increase our learning potential. Attention allows us to focus only on relevant information in our environment. It also helps us in the retrieval of relevant prior knowledge found in LTM. Although attention can and has been viewed in a number of ways, from a learning standpoint, attention is typically described in two forms: selective and divided. Selective attention is the process of selecting from among many potentially available stimuli while at the same time screening out other stimuli (Pashler, 1998). The most common example given for selective attention is that of a dinner party in which focus is placed on a single voice, or a single conversation, among many voices or conversations being held at the same time. Divided attention, on the other hand, is just the opposite. As the name implies, is the selection of many stimuli all at once (Pashler, 1998). Needless to say, we can maximize our chances of learning by avoiding divided attention and using selective attention as much as possible. This is easier said than done, however. As Clark (2003) points out, when focused on new material, learners must be able to handle both selective and divided attention. She further explains that success at managing divided attention is dependent on a number of factors. First, the difficulty of the task plays a significant role in managing divided attention. We can handle more tasks at once if they are simple. The opposite is true as well. The more complex the tasks, the less likelihood we can perform more than one at

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Human Cognition in the Design of Assistive Technology for Those with Learning Disabilities

a time. The exception to this is automaticity. We know that tasks which have been automated require very little resources from working memory. Automaticity can be acquired through extensive repetition and practice. However, if the tasks have not been automated, complex tasks should be broken down into smaller chunks whenever possible. A complex task separated into smaller simpler tasks can be more easily learned (Brunning et al., 2004). Second, experience level plays a critical role. Individuals with significant prior knowledge use much less attentional resources than those who have little knowledge about the instructional material. The same can be said about novice learners when the material is complex in nature. Fortunately, sound instructional practices can help. Clark (2003) notes that strategies (cues) such as the use of topic headers, learning objectives, and support questions that can be used to steer attention towards important instructional material, lessening divided attention and maximizing selective attention. (This is called the signaling principle and we discuss it in the third chapter in this introduction.) Finally, the means by which the instructional material is presented is very important. There are known benefits to presenting instructional material both visually and auditorially. Presenting information in dual modality can best help utilize the limited resources of working memory (Mayer & Moreno, 2003) and thus mitigate cognitive overload. Learning theories have emerged from the study of working memory. These theories offer best practices in the design of instructional material. In the next two chapters we will expound upon this in significant detail.

summAry This chapter is the first of three serving as the introduction to this handbook addressing the relationships among human cognition and ATs

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and its design for individuals with LDs. In this chapter we introduced the most popular information processing model, the modal model of memory, a helpful way in which to explain the active processes involved in the construction of new knowledge. The modal model is composed of three memory stores: sensory memory, STM or working memory, and LTM, each of which serve a specific function, but as we have learned, are far from being distinct from one another. For learning to take place, we know that new information must first be brought into sensory memory. Information, presented as words and pictures, enters sensory memory through the eyes and ears. These visual and auditory stimuli are held for a brief period of time in the sensory registers. Depending on where attention is focused, a subset of this information in the registers is selected and retrieved into working memory. Once again, we cannot over emphasis the importance of attention. By focusing attention on what is significant, only relevant information is moved into working memory. This not only helps increase the chances of learning new information, but at the same time, helps mitigate cognitive load on the already taxed resources of working memory. Once in working memory, the information is temporarily stored for further processing. To help facilitate learning, prior knowledge in LTM that is relevant to new information currently stored in working memory is stimulated. By stimulated we mean that schema relevant to new information is activated. This activated prior knowledge is temporarily retrieved into working memory where it is integrated with new information. Depending on how well the schema has been chunked will determine the degree to which prior knowledge impacts the limited resources of working memory. The more efficiently prior knowledge is organized, the more resources are left on hand in working memory for use in learning new information. While in working memory, new information must be rehearsed if it has any chance of being encoding in LTM. Rehearsal helps in the integra-

Human Cognition in the Design of Assistive Technology for Those with Learning Disabilities

tion of new information with prior knowledge. The more new information in working memory is rehearsed the more likely it will be encoded within LTM. However, information which makes its way into LTM must still be retrieved if it is to be of any use and can still overburden working memory. Automaticity can aid in mitigating this dilemma, which we have already discussed, is believed to use very little of working memory’s limited resources. However, extensive practice is needed before a task becomes automatic. Meanwhile, amongst all this activity, metacognition is at play, helping in differentiating between what is known and not known all the while monitoring cognitive activities. While this explanation is much more detailed that our original rushed account presentation with Figure 1, we have only begun to scratch the surface of research on information processing models, specifically the modal model of memory. For example, this chapter did not include a discussion on motivational factors in learning, nor did it include a discussion on encoding and retrieval processes. Instead, our focus has been to strengthen our stance which was hopefully made clear earlier in this chapter—understanding the latest advancements in cutting-edge technology is simply not enough. Rather, such knowledge must be coupled with an understanding of the human information processing system. There must be a clear understanding between design principles and the means by which humans acquire, store, and retrieve information, if the full potential of technology for learning is to be realized; particularly when it comes to the design of ATs for individuals with LDs.

Alexander, J. M., Carr, M., & Schwanenflugel, P. J. (1995). Development of metacognition in gifted children: Directions for future research. Developmental Review, 15(1), 1–37. doi:10.1006/ drev.1995.1001

reFerences

Brown, A. L. (1987). Metacognition, executive control, self-regulation, and other more mysterious mechanisms. In Weinert, F. E., & Kluwe, R. H. (Eds.), Metacognition, motivation, and understanding (pp. 65–116). Hillsdale, NJ: Lawrence Erlbaum Associates.

Adams, M. J. (1990). Beginning to read: Thinking and learning about print. Cambridge, MA: The MIT Press.

Anderson, J. R. (1983). The architecture of cognition. Cambridge, MA: Harvard University Press. Anderson, J. R. (2004). Cognitive psychology and its implications (6th ed.). New York: Worth Publishers. Atkinson, R. C., & Shiffrin, R. M. (1968). Human memory: A proposed system and its control processes. In Spence, K. W., & Spence, J. T. (Eds.), The Psychology of learning and motivation: Advances in research and theory (Vol. 2, pp. 89–195). Oxford, UK: Academic Press. doi:10.1016/S0079-7421(08)60422-3 Baddeley, A. D. (1986). Working memory. New York: Oxford University Press. Baddeley, A. D. (1998). Human memory: Theory and practice. Boston, MA: Allyn and Bacon. Baddeley, A. D. (2002). Is working memory still working? European Psychologist, 7(2), 85–97. doi:10.1027//1016-9040.7.2.85 Brandt, R. S. (Ed.). (2000). Education in a new era. Alexandria, VA: Association for Supervision & Curriculum Development. Bransford, J. D., Brown, A. L., & Cocking, R. R. (Eds.). (2000). How people learn: Brain, mind, experience, and school: Expanded edition. Washington, DC: National Academies Press.

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Brunning, R. H., & Schraw, G. J., Norby, M. M., & Ronning, R. R. (2004). Cognitive psychology and instruction. Upper Saddle River, NJ: Pearson/ Merrill/Prentice Hall. Clark, R. (2003). Building Expertise: Cognitive Methods for Training and Performance Improvement (2nd ed.). Washington, DC: International Society for Performance Improvement. Cuban, L. (1986). Teachers and machines: The classroom use of technology since 1920. New York: Teachers College Press. Darwin, C. J., Turkey, M. T., & Crowder, R. G. (1972). An auditory analogue of the Sperling Partial Report Procedure: Evidence for brief auditory storage. Cognitive Psychology, 3, 255–267. doi:10.1016/0010-0285(72)90007-2 Flavell, J. H. (1979). Metacognition and cognitive monitoring: A new area of cognitive-developmental inquiry. The American Psychologist, 34, 906–911. doi:10.1037/0003-066X.34.10.906 Fletcher, J. M., Lyon, G. R., Fuchs, L. S., & Barnes, M. A. (2006). Learning disabilities: From identification to intervention. New York: The Guilford Press. Friedman, A., Polson, M. C., & Dafoe, C. G. (1988). Dividing attention between the hands and the head: Performance trade-offs between rapid finger tapping and verbal memory. Journal of Experimental Psychology. Human Perception and Performance, 14, 60–68. doi:10.1037/00961523.14.1.60 Greene, R. L. (1992). Human memory: Paradigms and paradoxes. Hillsdale, NJ: Lawrence Erlbaum. Healy, A., F., & McNamara, D., S. (1996). Verbal learning and memory: Does the modal model still work? Annual Review of Psychology, 47, 143–172. doi:10.1146/annurev.psych.47.1.143

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Jacobs, J. E., & Paris, S. G. (1987). Children’s metacognition about reading: Issues in definition, measurement, and instruction. Educational Psychologist, 22(3), 255–278. doi:10.1207/ s15326985ep2203&4_4 Jonassen, D. H., & Land, S. (Eds.). (2000). Theoretical foundations of learning environments. Mahwah, NJ: Lawrence Erlbaum. Jonassen, D. H., Louise, B., & Grabowski, H. (1993). Handbook of individual differences, learning, and instruction. Mahwah, NJ: Lawrence Erlbaum. Kalyuga, S., Chandler, P., & Sweller, J. (1999). Managing split-attention and redundancy in multimedia instruction. Applied Cognitive Psychology, 13, 351–371. doi:10.1002/ (SICI)1099-0720(199908)13:4<351::AIDACP589>3.0.CO;2-6 Kirschner, P. A. (2002). Cognitive load theory: Implications of cognitive load theory on the design of learning. Learning and Instruction, 12(1), 1–10. doi:10.1016/S0959-4752(01)00014-7 Low, R., & Sweller, J. (2005). The modality principle in multimedia learning. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning (pp. 147–158). New York: Cambridge University Press. MacDonald, M. C., & Christiansen, M. H. (2002). Reassessing working memory: Comment on Just and Carpenter (1992) and Waters and Caplan (1996). Psychological Review, 109(1), 35–54. doi:10.1037/0033-295X.109.1.35 Marshall, H. H. (1996). Recent and emerging theoretical frameworks for research on classroom learning: Contributions and limitations (Vol. 31). Mahwah, NJ: Educational Psychologist. Mayer, R. E. (2005a). Principles of multimedia learning based on social cues: Personalization, voice, and image principles. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning (pp. 201–212). New York: Cambridge University Press.

Human Cognition in the Design of Assistive Technology for Those with Learning Disabilities

Mayer, R. E. (Ed.). (2005b). The Cambridge handbook of multimedia learning. New York: Cambridge University Press.

Sperling, G. (1960). The information available in brief visual presentations. Psychological Monographs: General and Applied, 74(11), 1–29.

Mayer, R. E., & Moreno, R. (2003). Nine ways to reduce cognitive load in multimedia learning. Educational Psychologist, 38(1), 43–52. doi:10.1207/S15326985EP3801_6

Squire, L. R. (2008). Memory and brain. New York: Oxford University Press.

Miller, G., A. (1956). The magical number seven, plus or minus two: Some limits on our capacity for processing information. Psychological Review, 63, 81–97. doi:10.1037/h0043158 National Joint Committee on Learning Disabilities. (1991). Learning disabilities: Issues on definition [Electronic Version]. Asha, 33, 18–20. Retrieved April 29, 2009, from www.ldonline.org/?module =uploads&func=download&fileId=514 Niaz, M., & Logie, R. H. (1993). Working memory, mental capacity and science education: Towards an understanding of the ‘working memory overload hypothesis’. Oxford Review of Education, 19(4), 511–525. doi:10.1080/0305498930190407 Pashler, H. E. (1998). The psychology of attention. Cambridge, MA: The MIT Press. Peterson, L., & Peterson, M. J. (1959). Shortterm retention of individual verbal items. Journal of Experimental Psychology, 58(3), 193–198. doi:10.1037/h0049234 Reid, R., & Lienemann, T. O. (2006). Strategy instruction for students with learning disabilities. New York: The Guilford Press. Rogers, F. K. (1979). Parenting the difficult child. Radnor, PA: Chilton Book Co.

Sweller, J., & Chandler, P. (1994). Why some material is difficult to learn. Cognition and Instruction, 12(3), 185–233. doi:10.1207/ s1532690xci1203_1 Sweller, J., van Merrienboer, J. J. G., & Paas, F. G. W. C. (1998). Cognitive architecture and instructional design. Educational Psychology Review, 10(3), 251–296. doi:10.1023/A:1022193728205 Tulving, E. (1983). Elements of episodic memory. Oxford, UK: Oxford University Press. Tulving, E. (2002). Episodic memory: From mind to brain. Annual Review of Psychology, 53, 1–25. doi:10.1146/annurev.psych.53.100901.135114 United States Congress. (1998). Assistive Technology Act of 1998. Retrieved from http://section508. gov/docs/AT1998.html Ware, C. (2004). Information visualization: Perception for design (2nd ed.). San Francisco, CA: Morgan Kaufmann Publishers. Waugh, N. C., & Norman, D., A. (1965). Primary memory. Psychological Review, 72(2), 89–102. doi:10.1037/h0021797 Wong, B. Y. L., Graham, L., Hoskyn, M., & Berman, J. (1996). The ABCs of learning disabilities (2nd ed.). New York: Elsevier/Academic Press.

Solso, R. L. (2001). Cognitive psychology (Vol. 6). Needham Heights, MA: Allyn & Bacon.

AddItIonAL reAdIng

Spear, N. E., & Riccio, D. C. (1994). Memory: Phenomena and principles. Boston, MA: Allyn & Bacon.

Anderson, J. R. (2004). Cognitive psychology and its implications (6th ed.). New York: Worth Publishers.

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Baddeley, A. D. (1998). Human memory: Theory and practice. Boston, MA: Allyn and Bacon. Brunning, R. H., & Schraw, G. J., Norby, M. M., & Ronning, R. R. (2004). Cognitive psychology and instruction. Upper Saddle River, NJ: Pearson/ Merrill/Prentice Hall. Clark, R. (2003). Building Expertise: Cognitive Methods for Training and Performance Improvement (2nd ed.). Washington, DC: International Society for Performance Improvement. Greene, R. L. (1992). Human memory: Paradigms and paradoxes. Hillsdale, NJ: Lawrence Erlbaum. Mayer, R. E. (Ed.). (2005). The Cambridge handbook of multimedia learning. New York: Cambridge University Press. Pashler, H. E. (1998). The psychology of attention. Cambridge, MA: The MIT Press. Reid, R., & Lienemann, T. O. (2006). Strategy instruction for students with learning disabilities. New York: The Guilford Press. Sweller, J. (1994). Cognitive load theory, learning difficulty, and instructional design. Learning and Instruction, 4(4), 295–312. doi:10.1016/09594752(94)90003-5

key terms And deFInItIons Associationism: The theory that all consciousness can be explained by the association of sensory stimulus with responses. Assistive Technology: Any form of technology which can be used to aid individuals with disabilities. Attention: The cognitive process involved in selectively focusing on relevant information, while at the same time, ignoring other irrelevant information.

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Automaticity: The automatic execution of cognitive skills requiring little conscious attention; lessens the need for resources from working memory. Behaviorism: The theory that all objectively, observable behaviors are a result of conditioning; the theory discredits mental activities. Cognitive Disability: Any disorder which affects mental processing. Cognitive Psychology: A branch of psychology dedicated to the study of the human mind focused on the acquisition, processing, and storage of information. Cognitive Load Theory: A theory proposed by John Sweller and his colleagues focused on the limitations of working memory during instruction. Cognitive Theory of Multimedia Learning: A theory credited to Richard E. Mayer and his colleagues focused on best practices in the use of visual and auditory information in multimediabased instruction. Conditional Knowledge: A classification of knowledge found in long-term memory; can be best described as knowing “when” and “why” to use declarative and procedural knowledge and when not to use those (Brunning et al., 2004). Chunk: A meaningful grouping of information; originally proposed in the 1956 paper “The Magical Number Seven, Plus or Minus Two: Some Limits on Our Capacity for Processing Information” by cognitive psychologist George A. Miller as the means to quantify the capacity limitations of working memory. Declarative Knowledge: A classification of knowledge found in long-term memory (John R. Anderson, 1983; Squire, 2008); deals specifically with factual information and can be best described as knowing “what” (Brunning et al., 2004). Divided Attention: The selection of many stimuli all at once (Pashler, 1998). Echoic Memory: The temporary storage of auditory stimuli in sensory memory.

Human Cognition in the Design of Assistive Technology for Those with Learning Disabilities

Empiricism: The belief that knowledge originates from experience (John Robert Anderson, 2004). Episodic Memory: A categorization of declarative knowledge; knowledge associated with personal, autobiographical events (Tulving, 1983). Executive Control System: One of three components comprising the model of working memory; manages the visuospatial sketchpad and the phonological loop in addition to controlling information flow in working memory (Baddeley, 1986, 1998, 2002). Iconic Memory: The temporary storage of visual stimuli in sensory memory. Information Processing Models: Models of human memory portraying the acquisition, storage, and retrieval of information (e.g., Atkinson & Shiffrin, 1968; Waugh & Norman, 1965). Learner-Centered: An instructional approach which places focus on the manner in which technologies can be used in the promotion of human cognition (Mayer, 2005b). Learning Disability: A heterogeneous group of disorders manifested by significant difficulties in the acquisition and use of listening, speaking, reading, writing, reasoning, or mathematical abilities (National Joint Committee on Learning Disabilities, 1991). Long-Term Memory (LTM): A memory store responsible for the persistent storage of the personal experiences, general and factual knowledge, and skills accumulated over the course of a lifetime. Metacognition: Refers to an individual’s awareness of his or her own cognitive processes and strategies (e.g., Flavell, 1979); commonly referred to as “thinking about thinking” (Brunning et al., 2004; Clark, 2003; Reid & Lienemann, 2006). Metacognitive Knowledge: A dimension of metacognition; refers to what we know about our own cognitive processes (Brown, 1987).

Metacognitive Regulation: A dimension of metacognition; the means by which we regulate our cognition (Brown, 1987). Modal Model of Memory: A widely accepted representation of the information processing model typically referred to as the classic Atkinson & Shiffrin (1968) model; depicted as three distinct memory stores: sensory memory, STM or working memory, and long-term memory. Perception: The process to recognize, store, and get meaning from sensory information. Phonological Loop: One of three components comprising the model of working memory; responsible for the management of acoustic and verbal information (Baddeley, 1986, 1998, 2002). Prior Knowledge: Information already learned and held in long-term memory. Procedural Knowledge: A classification of knowledge found in long-term memory (John R. Anderson, 1983; Squire, 2008); deals specifically with skills and can be best described as knowing “how” (Brunning et al., 2004). Radical Behaviorism: A branch of stimulusresponse psychology credited to American psychologist, B. F. Skinner which postulated that all measurable behavior can be predicted, and consequently controlled. Selective Attention: The process of selecting from among many potentially available stimuli while at the same time screening out other stimuli (Pashler, 1998). Semantic Memory: A categorization of declarative knowledge; refers to factual and general knowledge unrelated to personal, autobiographical events. Sensory Memory: A temporary memory store responsible for the handling of visual and auditory sensory information. Sensory Register: A temporary buffer responsible for the storage of sensory stimuli (Brunning et al., 2004). Schemata (sing., Schema): A popular explanation as to the organization of knowledge found in long-term memory.

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Human Cognition in the Design of Assistive Technology for Those with Learning Disabilities

Short-Term Memory (STM): A memory store responsible for the temporary, passive storage of information; cognitive psychologists have since adopted a much more active view–working memory. Signaling Principle: An instructional principle proposing that learners learn more when cues are added to highlight the organization of the essential material (Mayer, 2005a). Slot: The core component of schemata; considered “placeholders” containing specific information about the concept represented by the schema (Brunning et al., 2004).

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Technology-Centered: An approach which places focus on the capabilities of the technology and not necessarily on the capabilities of the learner (Mayer, 2005b). Visuospatial Sketchpad: One of three components comprising the model of working memory; responsible for the handling spatial information (Baddeley, 1986, 1998, 2002). Working Memory: A temporary memory store responsible for the active processing of information; the most widely accepted model is that by cognitive psychologist Alan D. Baddeley who proposed the model of working memory.

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Chapter 2

Managing Cognitive Load in the Design of Assistive Technology for Those with Learning Disabilities Boaventura DaCosta Solers Research Group, USA Soonhwa Seok Center for Research on Learning - eLearning Design Lab, University of Kansas, USA

AbstrAct This is the second of three chapters serving as the introduction to this handbook which addresses the relationship between human cognition and assistive technologies and its design for individuals with cognitive disabilities. In this chapter the authors present strategies to manage cognitive load in the design of instructional materials for those with learning disabilities. The authors introduce cognitive load theory, which proposes a set of instructional principles grounded in human information processing research that can be leveraged in the creation of efficient and effective learning environments. They attempt to separate conjecture and speculation from empirically-based study and consolidate more than twentyfive years of research to highlight the best ways in which to increase learning. Altogether, the authors affirm the approach discussed in the last chapter—that technology for learning should be created with an understanding of design principles empirically supported by how the human mind works, particularly when it comes to the design of assistive technologies for individuals with learning disabilities. DOI: 10.4018/978-1-61520-817-3.ch002

Copyright © 2010, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

Managing Cognitive Load in the Design of Assistive Technology for Those with Learning Disabilities

IntroductIon cognitive Load, Assistive technology, and those with Learning disabilities In the last chapter, we learned that human information processing is constrained in both capacity and duration. We explained how working memory, a system that temporarily stores and manages information for performing complex cognitive tasks, is a contradiction in terms. Its limitations cause it to be a bottleneck, restricted to seven (plus or minus two) chunks of information at any given time (Miller, 1956); yet, it is also the conduit for learning. This is a problem because the acquisition of new knowledge relies so heavily on the processing and storage capabilities of working memory (Low & Sweller, 2005; Sweller & Chandler, 1994). New information may potentially overload working memory capacity and subsequently encumber learning (Kalyuga, Chandler, & Sweller, 1999; Sweller, van Merrienboer, & Paas, 1998). While we are all confronted by these information processing roadblocks, individuals with cognitive disabilities are at particular risk. There has been considerable research focused on working memory and children with learning disabilities (LDs). Generally speaking, research on the matter suggests that children with LDs have difficulty with working memory in areas such as reading and mathematics (e.g., Bull, Johnston, & Roy, 1999; de Jong, 1998; Hitch & McLean, 1991; Keeler & Swanson, 2001; McLean & Hitch, 1999; Passolunghi & Siegel, 2004). For example, those with reading disabilities are not poor readers, but have less working memory capacity than more skilled readers (Swanson & Siegel, 2001). Fortunately, there has been considerable research in the study of cognitive load with regard to working memory. Even though some researchers

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have examined cognitive load under the premise of the working memory overload hypothesis (e.g., Niaz & Logie, 1993), the most predominant work on cognitive load can be attributed to cognitive load theory (CLT) (e.g., Chandler & Sweller, 1991; Kalyuga, Chandler, Tuovinen, & Sweller, 2001; Mousavi, Low, & Sweller, 1995; Sweller, 1999; Sweller et al., 1998)—a learning theory focused on the limitations of working memory during instruction. This is the second of three chapters serving as the introduction to this handbook which addresses the relationship between human cognition and assistive technologies (ATs) and its design for individuals with cognitive disabilities. In this chapter we present strategies to manage cognitive load in the design of instructional materials for those with LDs. We introduce CLT, which proposes a set of instructional principles grounded in human information processing research that can be leveraged in the creation of efficient and effective instructional material. We attempt to separate conjecture and speculation from empirically-based study and consolidate more than twenty-five years of research to highlight the best ways in which to increase learning. This chapter also serves as scaffolding for the next chapter where we present the cognitive theory of multimedia learning (CTML), a learning theory which focuses on best practices in the use of visual and auditory information in multimedia-based instruction. Altogether, we affirm the approach discussed in the last chapter—that technology for learning should be created with an understanding of design principles empirically supported by how the human mind works, particularly when it comes to the design of ATs for individuals with LDs. Before we present these instructional principles, we begin this chapter with an in-depth discussion of CLT and its history.

Managing Cognitive Load in the Design of Assistive Technology for Those with Learning Disabilities

bAckground What is cognitive Load theory? Originating in the 1980s by John Sweller and undergoing substantial growth in later decades by researcher from around the globe (F. Paas, Renkl, & Sweller, 2003) (see Clark, Nguyen, & Sweller, 2006, for an in-depth historical account), CLT is grounded in aspects of human cognitive architecture and information structure to provide instructional principles best facilitating learning given the limitations of working memory (Pollock, Chandler, & Sweller, 2002). Put simply, CLT is a learning theory. It is grounded in the belief that instructional design needs to be driven by an understanding of human cognition because improperly presented instructional material may impose too great a burden on working memory, subsequently leading to higher information processing load on the already limited cognitive resources of working memory (Sweller et al., 1998). Without knowledge of the relevant aspects of human cognitive structures and their organization into a coherent cognitive architecture, it is thought that the efficiency of instructional material is likely to suffer. Consequently, information should be structured to reduce preventable load on working memory (Kalyuga, Chandler, & Sweller, 1998; Sweller, 1999; Sweller et al., 1998) by designing instructional material in such a way that it is processed more easily in working memory (Chandler & Sweller, 1991). Cognitive load theory has thereby been used to bridge the gap between instructional principles and knowledge of human cognition (Sweller, 2005a). This is what sets CLT apart from other theories. While it may be easy to find information on instructional design, such information may be solely based on conjecture and speculation. Cognitive load theory, on the other hand, is empirically grounded in research found in the field of cognitive psychology. Research, we might add, that can be found in dozens of articles, most

of which have been published in peer-reviewed journals that have been available for scrutiny by researchers, educators, and practitioners for the last 25 years. Since the theory is firmly grounded in the study of human cognition, it is based on a number of assumptions: cognitive tasks are carried out in working memory (Shiffrin & Atkinson, 1969); working memory is limited in capacity (Baddeley, 1986, 1998) and is only capable of processing a finite amount of information (recall our discussing of chunking in the last chapter) at any one time (Miller, 1956); working memory is composed of both visual and auditory information processing channels (Paivio, 1990); efficiency and unlimited capacity of long-term memory (LTM) to hold knowledge can be leveraged to overcome working memory capacity limitations (Pollock et al., 2002); schemas held in LTM, which allow multiple elements of information to be categorized as a single element (Sweller, 2005a), require less working memory capacity (Pollock et al., 2002); and cognitive load can be reduced through automation, which allows schemas to be processed automatically rather than consciously (Kotovsky, Hayes, & Simon, 1985; Schneider & Shiffrin, 1977; Richard M. Shiffrin & Schneider, 1977). While the goal of CLT is the reduction of preventable load on working memory through the structuring of information (Kalyuga, Chandler, & Sweller, 1998; Sweller, 1999; Sweller et al., 1998), not all types of cognitive load are bad. As we will discuss next, some cognitive load can be beneficial (Clark et al., 2006).

tHe tHree tyPes oF cognItIve LoAd Cognitive load theory distinguishes between three types of load: (a) extraneous, (b) intrinsic (Pollock et al., 2002; Sweller, 2005a; Sweller & Chandler, 1994; Sweller et al., 1998), and (c) germane (Sweller, 2005a; Sweller et al., 1998).

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Managing Cognitive Load in the Design of Assistive Technology for Those with Learning Disabilities

Each of these must be accounted for in the design of instructional material if the instruction is to be efficient and effective.

extraneous Load Extraneous load (also called irrelevant load) is caused in situations where instructional material is created using instructional design that ignores the limitations of working memory and consequently fails to focus working memory resources on schema construction and automation (Sweller, 2005a). As the name implies, extraneous load is irrelevant to the learning goals at hand (Clark et al., 2006). In fact, extraneous load is detrimental to learning. It can result in longer learning times, unsatisfactory learning outcomes, or both (Clark et al., 2006). Extraneous load is the worst of the three types of cognitive load because it wastefully consumes the already limited resources of working memory. Fortunately, extraneous load is considered to be under the control of the instructional designer (Pollock et al., 2002) and is therefore avoidable if proper steps are taken. There has been extensive research on extraneous load (van Merrienboer & Ayres, 2005). From this research, a number of effects have emerged to include worked examples (e.g., Cooper & Sweller, 1987; Kalyuga et al., 2001; Stark, Mandl, Gruber, & Renkl, 2002; Van Gerven, Paas, Van Merrienboer, & Schmidt, 2002), split-attention (e.g., Sweller, Chandler, Tierney, & Cooper, 1990), modality (e.g., Tindall-Ford, Chandler, & Sweller, 1997), and redundancy (e.g., Chandler & Sweller, 1991). These effects can yield better schema construction and a decrease in extraneous load (van Merrienboer & Ayres, 2005) when applied correctly as instructional principles. For example, the worked examples principle replaces conventional practice problems with worked-out examples, reducing extraneous load by focusing the learner’s attention on problem states and useful solution steps. The split-attention principle replaces multiple sources of information

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with a single source, thus reducing extraneous load because learners do not need to mentally integrate multiple sources of information. The modality principle reduces extraneous load through using both the visual and auditory processors of working memory. While finally, the redundancy principle replaces multimodal sources of information that are self-contained (i.e., can be understood in isolation) with a single source of information, reducing extraneous load typically caused by the unnecessary processing of superfluous information (van Merrienboer & Ayres, 2005).

Intrinsic Load Unlike extraneous load, intrinsic load is caused by the natural complexity of the information that must be processed. Intrinsic load is not under the control of the instructional designer, but instead is determined by levels of element interactivity (Sweller, 2005a). Think of an element as a single unit of information to be processed in working memory. To an extent this is similar to the chunking concept that we discussed in the last chapter. These elements may interact with one another at different levels of complexity. For instance, some information can be learned individually, element by element (Pollock et al., 2002). Sweller (2005a) has provided the example of learning nouns of a foreign language to demonstrate this idea. Each noun translation can be learned independent of other translations. For example, the noun “cat” can be learned independently of the noun “dog.” Element interactivity in this case is low because only a limited number of elements need to be processed in working memory at any given time to learn the information. As a result, cognitive load on working memory is also low (Pollock et al., 2002; Sweller, 2005a). Some information, however, cannot be learned in isolation, but instead must be learned in the context of other material. In other words, meaningfully learning of an element cannot occur without simultaneously learning other ele-

Managing Cognitive Load in the Design of Assistive Technology for Those with Learning Disabilities

ments (Sweller, 2005a). Take the construction of sentences, an example provided by Clark et al. (2006). The composition of sentences requires more than the mere understanding of words. There are grammar and syntax rules that must be taken into consideration as well. Unlike the learning of words that may be done in isolation of one another, the composition of sentences is a much more complex task, requiring the juggling of multiple elements simultaneously. Pollock et al. (2002) provide the example of understanding an electric circuit to further demonstrate this idea. Components of a circuit may be learned in isolation of one another; however, an understanding of the entire electrical circuit cannot be achieved without simultaneously considering several components and their relations. Element interactivity in this case is high because many elements must be processed in working memory simultaneously. As a result, cognitive load on working memory is also high (Pollock et al., 2002; Sweller, 2005a). This is why complex instructional material is difficult to comprehend, because of the high element interactivity and the resulting heavy cognitive load it imposes on working memory (Chandler & Sweller, 1996; Marcus, Cooper, & Sweller, 1996; Sweller & Chandler, 1994). Intrinsic load cannot be avoided or changed (Clark et al., 2006); however, it can be managed. There is research which has investigated various instructional methods on intrinsic load, although not to the extent that can be found with extraneous load. From this research, the pre-training and segmenting effects have emerged. These effects can be used to manage intrinsic load on the limited resources of working memory when applied correctly as instructional principles. For example, the pre-training principle can help manage intrinsic load when complex information is decomposed into smaller, simpler, and more manageable named concepts. These concepts and their behaviors can then be taught

first in the lesson. This allows instructional designers to establish prerequisites, sequence content, and scaffold complex information (Clark et al., 2006). The segmenting principle, on the other hand, affords the learner greater control during the learning process by allowing the learner to decide potentially what instructional material to receive and when.

germane Load Germane load (also called effective load) is caused by instructional design implementations that aid in meaningful learning. Clark et al. (2006) describe germane load “as relevant load imposed by instructional methods that lead to better learning outcome” (p. 11). Germane load is meaningful learning resulting from schema construction and automation (F. Paas et al., 2003; Sweller, 2005a). Like extraneous load and unlike intrinsic load, germane load is considered to be under the control of the instructional designer. Whereas extraneous load interferes with learning, germane load enhances learning. Extraneous load can tax the limited resources of working memory; whereas in germane load, those resources are devoted to schema acquisition and automation (F. Paas et al., 2003). If used properly, germane load can prove advantageous to learners in applying what they have learned to new tasks. Ironically, germane load is the least studied to date with regard to instructional methods. However, as we will soon learn, the effect that has shown promise thus far is worked examples. This effect can be used to promote germane load on the limited resources of working memory when applied correctly as an instructional principle. Overall, when implemented properly into instructional material, germane load allows learners to build a repertoire of skills and knowledge which they can apply to different situations (Clark et al., 2006).

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Managing Cognitive Load in the Design of Assistive Technology for Those with Learning Disabilities

AvoIdIng extrAneous, mAnAgIng IntrInsIc, And PromotIng germAne LoAd When handling extraneous, intrinsic, and germane load it is important to understand that these types of cognitive load are additive (Clark et al., 2006; Paas et al., 2003). We learned earlier in this chapter that intrinsic load is not under the control of the instructional designer, but is instead caused by the natural complexity of the information that must be processed. Although there are instructional principles that can be used to help with intrinsic load, such as the pre-training and segmenting principles, in general, if the information to be learned is complex and intrinsic load is high, actions must be taken to lower extraneous load (van Merrienboer & Ayres, 2005). If extraneous load is not lowered, the total intrinsic and extraneous load may leave little, if any, cognitive resources available within working memory for the incorporation of germane load. For the best learning outcome possible, and to avoid cognitive overload, it is vital to managing intrinsic load by incorporating instructional principles that help avoid extraneous load and that help in promoting germane load whenever possible (Clark et al., 2006; F. Paas et al., 2003; van Merrienboer & Ayres, 2005). This is easier said than done. The problematic nature of extraneous load on the learner is dependent on the level of intrinsic load or the complexity of the information to be learned (van Merrienboer & Ayres, 2005); and herein lies the rub, in that the complexity of a task is relative to the expertise level or prior knowledge of the learner. In the last chapter we discussed the concept of schemata, which are mental frameworks explaining the means by which knowledge is organized in LTM. Depending on our experience level or prior knowledge, our schemata about a subject may be elementary or sophisticated. While some information may be relatively complex to a novice, the same information may be rudimentary for an expert. The level of expertise must be taken

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into consideration in the design of instructional material, because this helps in determining the level of intrinsic load (van Merrienboer & Ayres, 2005). It also aids in determining to what effort extraneous load should be avoided. What’s more, research has shown that instructional principles used to avoid extraneous load only improve the learning of complex tasks (Clark et al., 2006). To compound matters further, extraneous load should only be avoided when it helps in mitigating the complexity of the instructional material if the learners are considered novices. Employing instructional principles to avoid extraneous load when learners are experts in the subject matter may actually impede learning (Clark et al., 2006; Paas et al., 2003; van Merrienboer & Ayres, 2005). This is because experts have more sophisticated schemata as a result of their prior knowledge, requiring far less cognitive resources than those of novices (Clark et al., 2006). As it can be seen from our discussion, though, the application of CLT is in no way “cookie-cutter”, but instead must be tailored to the situation at hand (Clark et al., 2006). Avoiding extraneous, managing intrinsic, and promoting germane load are dependent on the learners expertise level or prior knowledge, the complexity of the information to be learned, and the instructional environment (Clark et al., 2006). We dedicate the rest of this chapter to discussing each of these types of cognitive load in detail, outlining the instructional principles most applicable to these types of load in the design of instructional materials.

AvoIdIng extrAneous LoAd Extraneous load is the most detrimental of the three cognitive loads because it wastefully consumes limited resources in working memory. It is completely under the control of the instructional designer and consequently can be avoided with initial forethought in the design of instructional material. Research into extraneous load has re-

Managing Cognitive Load in the Design of Assistive Technology for Those with Learning Disabilities

sulted in the discovery of a number of effects that if implemented as instructional principles can be used to help alleviate cognitive load. We mentioned these principles briefly earlier in this chapter. These principles are: worked examples, split-attention, modality, and redundancy. We discuss each of these principles next in greater detail.

the Worked examples Principle The worked examples principle (also referred to as the worked-out-examples principle) proposes that learners learn more deeply when studying worked examples than studying practice problems (Sweller, 2005a). A worked example is a “step-by-step demonstration of how to perform a task or solve a problem” (Clark et al., 2006, p. 190). Firmly grounded in CLT, it is believed that individuals gain a better understanding when exposed to worked examples in initial cognitive skill acquisition (Renkl, 2005). This is because novice learners have the most to learn. They typically have little experience with or prior knowledge of the information to be learned. So, as you might expect, as experience and prior knowledge increases, the benefits of worked examples decrease. This should not be surprising. We learned earlier in the chapter that employing instructional principles to avoid extraneous load may actually impede learning when learners are experts in a subject matter (Clark et al., 2006; Paas et al., 2003; van Merrienboer & Ayres, 2005). Renkl (2005) explains that worked examples are normally composed of a problem formation, solutions steps, and a final solution. Typically applied in the mathematics and physics domains, worked examples are generally applied in the following way: first, the principle, rule, or theorem is first introduced to the learner; a worked example is offered; and then one or more to-be-solved problems are given. Worked examples are most efficient when offered in a series or paired with

problems (Renkl, 2005). These are called worked example-problem pairs and are implemented by altering a worked example with a similar practice problem (Clark et al., 2006). One of the drawbacks with worked examples is that they must be studied in-depth to be of any value. This becomes a problem if learners do not make the effort to first study the presented worked example(s). This dilemma can be addressed with the use of completion examples. Clark et al. (2006) describe completion examples as a hybrid between worked examples and practice problems. The idea behind the completion example is simple—some steps are provided as worked example, whereas others are presented as practice problems. Together, worked and completion examples can be used to help deal with the problem of the learner gaining experience and prior knowledge. Although this is the goal of instruction, as we have already discussed, worked examples can have negative effects on learning when learners have transitioned from novices to experts. Sweller and his colleagues call out the approach of backwards fading, to help handle this situation. Backwards fading is a strategy in which worked examples become gradually replaced with practice problems in a lesson as the learner gains expertise in the subject matter (Clark et al., 2006). Clark et al. (2006) demonstrates this concept with an example lesson composed of four problems. The first problem may be a full worked example. The next two problems may be completion examples, in which the second of the two examples includes more practice than completion steps. Finally, the fourth step is a full practice problem. Care should be taken when applying worked examples. Worked examples which are improperly formatted may cause more harm that good (Clark et al., 2006). To help aid the formatting of worked examples, other instructional principles can be applied, such as the two principles we will discuss next, the split-attention and modality principles.

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Managing Cognitive Load in the Design of Assistive Technology for Those with Learning Disabilities

Empirical Support for the Worked Examples Principle

practice problems depended on prior knowledge and experience level.

There is wealth of researching investigating the effects of worked examples on learning dating back 25 years. We discuss three here, but you can find an in-depth discussion of these studies and others in Sweller (2005b) and Clark et al. (2006). The earliest quantification was that of Sweller and Cooper (1985) who used algebra to show that worked examples could be used more constructively than practice-based problems. In the study, one group was assigned eight practice-based problems, whereas the other group was assigned four worked example-problem pairs. Findings showed that those who received the worked examples completed a test of six new problems in significantly less time than those who had not. In a study conducted by Paas (1992), practice problems, worked examples and practice pairs, and completion example and practice pairs were compared for their learning effectiveness in the study of statistical concepts. The completion of the practice problem took significantly more time than completion of the worked examples or completion examples. In fact, more was learned from the worked and completion examples than the practice problems. Finally, Kalyuga et al. (2001) studied instances where practice problems were superior over that of worked examples. The researchers studied worked examples to practice problems over a period of time. Apprentices of mechanical trade were presented with one of two lessons, composed of a series of worked examples or practice problems. Test findings showed that learners initially benefited most from the worked examples, showing lower cognitive load than those who solved the practice problems. However, as time passed and experience grew, worked examples proved less beneficial and the problem-solving became superior. All in all, Kalyuga et al. (2001) concluded that the benefits of worked examples and

the split-Attention Principle

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Examined in a number CLT related studies, the split-attention principle is derived from the worked example principle (Sweller et al., 1998). Splitattention occurs when multiple sources of information must be mentally integrated in a simultaneous manner before meaningful learning can take place. Because multiple sources of information must be mentally integrated, extraneous cognitive load is increased, negatively impacting learning (Ayres & Sweller, 2005). Clark et al. (2006) uses the example of having to look at an illustration on one page, while reading the accompanying text on another. This causes split-attention because both the illustration and text cannot be learned in isolation, but are dependent on one another, causing additional load on working memory as a result of having to integrate the disjointed sources of information. These multiple sources of information are frequently represented as pictures and accompanying text (Ayres & Sweller, 2005; van Merrienboer & Ayres, 2005), but can also be represented as text with text, or different forms of multimedia. Since there are always at least two sources of information involved in multimedia, it is very susceptible to split-attention (Sweller, 2005a). Split-attention can be avoided, however. If the instructional material is presented as a figure and text, split-attention can be circumvented by integrating the figure and text together (Sweller & Chandler, 1994). This is the premise behind the split-attention principle. It is important to understand that split-attention is only applicable when the sources of information are unintelligible from one another. If a figure and text can be learned in isolation of one another, meaning they are both self-explanatory, split-attention will not occur (Clark et al., 2006). In addition, split-attention is only applicable with

Managing Cognitive Load in the Design of Assistive Technology for Those with Learning Disabilities

complex information. This should come as no surprise. We learned earlier in this chapter that extraneous load should only be avoided when it helps in mitigating the complexity of instructional material when the learners are considered novices. The example commonly provided by Sweller and his colleagues (see Ayres & Sweller, 2005; Sweller & Chandler, 1994; Sweller et al., 1998) has been that of geometry instruction. The study of geometry typically requires the learner to examine a figure and associated text. Neither the figure nor text are intelligible in isolation, but instead need to be mentally integrated for meaningful learning to occur. This involves finding relationships between elements of the figure and text. If these relationships are not formed, meaningful learning does not occur. Geometry instruction is considered inherently complex by nature and, therefore, an amount of intrinsic cognitive load is unavoidable. However, in separating the figure and text, extraneous cognitive load is also imposed. If the split-attention principle is followed and the figure and text are incorporated together, it is believed that extraneous cognitive load can be greatly reduced if not eliminated (Sweller & Chandler, 1994).

Empirical Support for the Split-Attention Principle The earliest research on split-attention was conducted by Tarmizi and Sweller (1988) who examined the effectiveness of worked examples on learning geometry. Their findings showed that learners who studied worked examples did not have an advantage over those who did not. A finding that contradicted earlier investigations of the benefits of worked examples. Tarmizi and Sweller (1988) concluded that their findings were a result of participants having to integrate two sources of information, diagrams and text, which resulted in a split-attention.

The study by Sweller et al. (1990) would soon follow, which reproduced the study by Tarmizi and Sweller (1988), but used coordinated geometry examples instead. They found that worked examples depicted in the traditional way did not provide learners with an advantage. Instead, what proved beneficial was an integrated worked example format, in which text was placed on the diagrams, reducing unnecessary searching, consequently reducing cognitive load and helping learners master the information. The findings of the Sweller et al. (1990) study showed that learners who received the integrated worked examples performed significantly better than those who received those traditionally formatted. More studies would follow, such as that by Ward and Sweller (1990), who showed similar findings to that of Sweller et al. (1990). Other studies include the CTML related studies by Richard E. Mayer and his colleagues, most notably that by Mayer and Moreno (1998), which pioneered the way for the modality principle.

the modality Principle The modality principle proposes that presenting information in dual modalities (i.e., partly visual and partly auditory) spreads total induced load across the visual and auditory channels of working memory thereby reducing cognitive load (Low & Sweller, 2005; Sweller & Chandler, 1994; Sweller et al., 1998). In other words, a modality effect occurs when material, such as text, is presented in an auditory rather than written mode when integrated with other non-verbal material (Sweller et al., 1998; Tindall-Ford et al., 1997), such as illustrations, photos, animations, or video. This is important as learning novel material can be impeded due to the capacity limitations of working memory (Low & Sweller, 2005; Sweller & Chandler, 1994). Much like split-attention, the modality principle is only applicable when both sources of information are essential to learning. Both visual and auditory

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Managing Cognitive Load in the Design of Assistive Technology for Those with Learning Disabilities

sources must be unintelligible when in isolation requiring mental integration for meaningful learning to occur. If both sources are intelligible, other principles, such as the redundancy principle should be leveraged instead (Low & Sweller, 2005). Furthermore, as you probably have already guessed, the use of audio is only beneficial for novice learners, or those with little prior knowledge (Clark et al., 2006). The modality principle has been thoroughly examined in numerous studies in past decades. Some of the earliest research focused specifically on the notion of distinct, yet interrelated information processing channels in working memory for visual and auditory information (see Penney, 1989, for an in-depth review). Much of the early research demonstrated that a dual mode of presenting information can result in increased performance, suggesting that there are modality specific processing resources in working memory (Low & Sweller, 2005). This is consistent with Baddeley’s (1986, 1998, 2002) model of working memory. (We will learn in the next chapter that the modality principle is also consistent with Paivio’s (J. M. Clark & Paivio, 1991; Paivio, 1971, 1990) dual coding theory, the idea that cognition is composed of verbal and non-verbal subsystems.) Cognitive load theory leveraged this early work, which established the premise that performance can be increased by presenting information in dual rather than single modalities, to suggest that a modality effect can be obtained under occurrences of split-attention (Low & Sweller, 2005). In fact, according to Clark et al. (2006), the most compelling finding of CLT research is the modality effect.

Empirical Support for the Modality Principle Perhaps the most well-known study addressing split-attention and modality (using CLT as the theoretical foundation) is the research conducted by

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Mousavi et al. (1995), who has examined presentation sequence and modality and split-attention effects using geometry instruction. Their findings have shown instructional material presented in visual and auditory modes is significantly better than the same instructional material presented in a visual manner only. Their research has also enforced the idea that the benefits of multimodal material occurred irrespective of either sequential or simultaneous presented information. Similar studies would follow, examining the modality effect in the context of CLT (e.g., Jeung & Chandler, 1997; Leahy, Chandler, & Sweller, 2003; Tindall-Ford et al., 1997). It should come as no surprise that the modality principle is extremely relevant in the context of learning through multimedia (Low & Sweller, 2005). Consequently the modality principle is grounded in a wealth of research, thoroughly studied in number of experiments (Jeung & Chandler, 1997, see experiments 1, 2, and 3; Kalyuga et al., 1999, see experiment 1; Mayer, Dow, & Mayer, 2003, see experiment 1; Mayer & Moreno, 1998, see experiments 1 and 2; Moreno & Mayer, 1999, see experiments 1 and 2; 2002, see experiments 1a, 1b, 1c, 2a, and 2b; Moreno, Mayer, Spires, & Lester, 2001, see experiments 4a, 4b, 5a, and 5b). These experiments have studied a wide variety of instructional topics to include math problems, the formation of lightning, a car brake system, electrical engineering, an aircraft simulation, an environmental science game, and the mechanics behind an electric motor (see Mayer (2005b) for a discussion of the these experiments and Mayer (2005c) for an in-depth discussion of the modality principle). While we do not provide a discussion of each of the studies, we can tell you that across all experiments, learners who received animation with concurrent narration multimedia presentations performed better on transfer tests than did learners who received the text-based presentations (Mayer, 2003).

Managing Cognitive Load in the Design of Assistive Technology for Those with Learning Disabilities

the redundancy Principle The redundancy principle proposes that learners learn more deeply when identical information is not presented in more than one format (Mayer, 2005a). The redundancy principle is based on the premise that less is more. When it comes to instructional material, however, this practice can be sometimes difficult to accept, primarily because those who develop instruction sometimes want to include as much information as possible. According to Sweller (2005b), this is typically done as a way to enrich or elaborate upon information. However, research on the matter suggests that the use of redundant information in instructional material can interfere with learning (Sweller, 2005b). We have learned that working memory is limited in both capacity and duration. Redundant information places unnecessarily load on working memory. Therefore, the redundancy principle should be applied in the design of instructional materials. The redundancy principle advocates the replacement of multiple sources of information that are self-contained with a single source of information; reducing extraneous load typically caused by the unnecessary processing of redundant information (van Merrienboer & Ayres, 2005). In other words, only present the minimum information that is required to meet the instructional goals at hand, distinguishing between “need-to-have” information and information that is “nice-to-have” (Clark et al., 2006). Adding any more than is essential to the understanding of the information to be learned and you risk unnecessary load on the already taxes resources of working memory. Instructional material should be concise, clear, and to the point. This is particularly important to those with LDs in mathematics, for example, who may have problems in the ability to inhibit extraneous information due to a general working memory deficit (Passolunghi & Siegel, 2004).

Empirical Support for the Redundancy Principle Although signs of a redundancy effect can be seen in a number of studies spanning the last two decades, the redundancy principle did not formally emerge until recently. Sweller (2005b) blames this on a lack of a theoretical explanation. The principle was thought as a new discovery each and every time it appeared, but each subsequent discovery was not linked to the last. Sweller (2005b) points to a number of studies to substantiate this claim, among them the study by Chandler and Sweller (1991). Although the study focused on the effect of split-attention, Chandler and Sweller (1991) noted that with some types of instructional material (i.e., the flow of blood in the heart, lungs, and body), there was no difference between integrated material and material that imposed a split-attention. The cause for this was the redundancy effect. According to Sweller (2005b), since the Chandler and Sweller (1991) study, the redundancy effect has been shown in a variety of context to include the experiments by Sweller and Chandler (1994), Chandler and Sweller (1996), and Kalyuga et al. (1999). There have also been a number of studies by Mayer and his colleagues examining the redundancy effect with regard to multimedia. These studies have been conducted by Mayer, Heiser, and Lonn (2001) and Moreno and Mayer (2000a, 2000b). For an in-depth discussion of these studies and others in the context of the redundancy principle, see Sweller (2005b) and Clark et al. (2006).

mAnAgIng IntrInsIc LoAd Recall from our earlier discussion that intrinsic load is not in the control of the instructional designer because it is based on the complexity of the information to be learned. Further recall that

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the pre-training and segmenting principles are two instructional principles that have emerged from the research that can be leveraged to help in managing the amount of intrinsic load on working memory. One promotes deeper learning when named concepts are presented first, whereas the other promotes deeper learning when learners are allowed to pace themselves through instruction. We describe each of these principles next in greater detail.

the Pre-training Principle The pre-training principle is a load reducing method typically described as an instructional principle in the context of CTML. The principle proposes that learners learn more deeply when they are aware of names and behaviors of main concepts (Mayer, 2005a; Mayer & Moreno, 2003). According to Mayer (2005b), the theoretical foundation for the pre-training principle is that it allows learners to build schemata or prior knowledge about essential concepts or components that can be applied later in the learning process, thus decreasing the amount of cognitive load. This strategy may be particularly useful to individuals who have difficulty processing information as continuous units of information, such as those with LDs. Clark et al. (2006) describe this concept as segmenting. Furthermore, they indicate that it should be implemented differently depending on whether you are dealing with process or procedure knowledge. They define process knowledge as “a flow of events that summarize the operations of business, scientific, or mechanical systems” (p. 163) and procedure knowledge as “knowledge underpinning performance of a task that is completed more or less the same way each time” (p. 168). Examples of process knowledge are how a car break system and bicycle tire pump work, while examples of procedure knowledge are the steps you take to start your car, computer,

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or perhaps even how you go about doing your grocery shopping.

Handling Process and Procedure Knowledge To avoid cognitive overload when dealing with process knowledge, the individual components comprising a system should be first introduced before the rest of the system. Clark et al. (2006) point to the study by Mayer, Mathias, and Wetzell (2002) as empirical support for this strategy, who recommend “providing pre-training aimed at clarifying the behavior of the components of the system” (p. 154). To accomplish this, they propose that three steps be followed: decompose the system into components, visually segregate and name the components, and represent the state change in each of the components (Mayer, Mathias et al., 2002). To avoid cognitive overload when dealing with procedure knowledge, Clark et al. (2006) present two alternative strategies based on the findings of Pollock et al. (2002, see experiments 2 and 3). In the first strategy, each step should be first taught, the learner should be allowed to practice each step, and then each step should be taught again, but this time accompanied by supporting information. In the second strategy, the support information is first taught and then each step (Clark, 1999, as cited in Clark et al., 2006). These strategies have their advantages and disadvantages. Both divide the complex information to be learned into two major segments, that of steps and supporting information (Clark et al., 2006). However, in implementing the first strategy, the learner may not fully grasp the steps because they are taught out of context of the supporting information. On the other hand, in implementing the second strategy, hands-on experience is postponed because the steps are not taught until after the supporting information is presented (Clark et al., 2006). So, which strategy should be used? It is

Managing Cognitive Load in the Design of Assistive Technology for Those with Learning Disabilities

really up to you to decide. As Clark et al. (2006) indicate, there is insufficient research suggesting one strategy is better than the other.

Empirical Support for the Pre-Training Principle The empirical basis for the pre-training principle lies in the studies conducted by Mayer, Mathias et al., (2002, see experiments 1, 2, and 3), Mayer, Mauntone, and Prothero (2002, see experiments 2 and 3) and Pollock et al. (2002, see experiments 2 and 3). We have already discussed the Mayer, Mathias et al., (2002) study to some extent. In the study, learning outcomes were compared between two groups who viewed a multimedia presentation on a car break system or a bicycle pump system. In the car break system experiment, those in the pre-training group were exposed to the names and states of the components comprising the break system before viewing the presentation. In the bicycle pump system experiment, those in the pre-training group were exposed to a model of a bicycle pump and allowed to operate it before viewing the presentation. In both experiments, the pre-training groups outperformed the other two groups in problem-solving tests. In the Mayer, Mauntone, et al. (2002) study, learning outcomes were compared between two groups who played a simulation game to learn about geology. Both groups were asked to identify a geological feature found on the earth’s surface. One group was afforded pre-training in the form of illustrations depicting geological features, while the other was not. The group who received the pre-training outperformed the group who did not on a problem-solving test. Finally, in the Pollock et al. (2002) study, learning outcomes were compared between two groups who viewed a two-phase multimedia lesson on how to conduct safety tests for electrical appliances. The first group received the lesson in which the first phase focused on how each individual component worked and the second

phase focused on how the individual components worked together within the entire system. The second group received the same lesson, however, both phases focused on how the individual components worked together within the entire system. The group who received the pre-training lesson outperformed those who did not receive the pre-training lesson on a problem-solving test. Although the findings presented in these seven experiments are promising, further research is needed in studying the conditions in which the pre-training principle is most effective.

the segmenting Principle The segmenting principle is also a load reducing method typically described as an instructional principle in the context of the CTML. The principle proposes that deeper learning can occur when a lesson is presented in learner-controlled segments rather than continuous units (Mayer, 2005a; Mayer & Moreno, 2003). This strategy allows learners to pace themselves as they move through instruction. The premise behind the principle is to slow the pace of instruction so that learners have more time to process the information to be learned. This is especially useful in situations where the instructional material is presented at too fast a rate for the learner. The principle places learners in control of the learning process. Learners can decide when (i.e., at what speed) the instructional material is presented, but could also be given the capability to decide what instructional material should be presented. This makes the segmenting principle an attractive and commonsense concept, particularly for those with LDs, who may have difficulty keeping pace with instruction, and consequently, are unable to engage in the processing needed to learn new information. There is a potential pitfall with the principle, however. Clark et al. (2006) share the concern that for a novice, deciding the order in which instructional units will be taught may impose too much of a cognitive load, because these novice

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Managing Cognitive Load in the Design of Assistive Technology for Those with Learning Disabilities

learners may not understand the subject matter well enough to be able to make such decisions. However, they do agree with research on the matter—in that allowing a novice to decide at what speed to proceed through instructional material may be advantages to learning. Probably the most common way to implement self-pacing in instruction, at least from a computer-based standpoint, is with “Continue” or “Next” buttons. All of us have probably experienced this implementation at some point in our lives.

Empirical Support for the Segmenting Principle The empirical basis for the segmenting principle are the studies conducted by Mayer and Chandler (2001, see experiment 2) and Mayer, Dow, and Mayer (2003, see experiments 2a and 2b). In the Mayer and Chandler (2001) study, learning outcomes were compared between a group who viewed a 140-second narrated animation on lightning formation as a continuous presentation and a group who received the same presentation divided into 16 segments, each lasting approximately 10-seconds and sequenced by clicking a “Continue” button. The group who received the segmented presentation performed better on a problem-solving test than the group who viewed the continuous presentation. In the Mayer, Dow, and Mayer (2003) study, learning outcomes were compared between groups who learned about electronic motors while interacting with an avatar within a simulation game. One group was offered a continuous version of the simulation game in which the avatar showed how the electronic motor worked when clicked. The other group was offered a segmented version of the same game which displayed questions that corresponded to the segments of the narrated animation. Students in the segmented group could control what segments to view based on the question clicked. Like the findings of the Mayer and Chandler (2001) study, those in the segmented

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group outperformed those in the continuous group across all experiments. Although these findings are promising, Mayer (2005b) is quick to point out that evidence for the segmenting principle is still preliminary and further research is warranted.

the modality Principle We end our discussion of instructional principles that help manage intrinsic load with the modality principle. We have already discussed this principle in the context of avoiding extraneous load and so we do not repeat the effort here. We know that the modality principle, under certain conditions, can effectively mitigate certain loads leaving more resources for other processing in working memory. Through presenting material in dual modalities, the total induced load is spread across the visual and auditory components of working memory, thereby reducing cognitive load. The modality principle, can therefore, prove advantages in managing intrinsic load.

PromotIng germAne LoAd We end our discussion of CLT with the most beneficial of three cognitive loads, germane load. As we have discussed, if used properly, germane load can prove advantageous to learners in applying what they have learned to new tasks, or what is called the transfer of learning. This is essentially the ability to apply what has been learned to new settings or situations. This may include the transfer of skills, knowledge, and/or attitudes. Transfer of learning can be decomposed into two types of transfer, near and far. Near transfer of skills and knowledge is typically applied the same way each and every time the skills and knowledge are used. Near transfer is procedure-based, and consequently, order is significant. Far transfer, on the other hand, is applied under conditions of change. Learners must be able to apply the skills and knowledge that they have learned to new

Managing Cognitive Load in the Design of Assistive Technology for Those with Learning Disabilities

situations. As you might expect, far transfer is the harder of the two to teach, but the most advantages. To foster transfer of learning, specifically far transfer, Clark et al. (2006) propose the use of diverse worked examples.

diverse Worked examples Far transfer requires the forming of new schemata. We learned in the last chapter that the formation of new schemata imposes additional cognitive load on working memory. Although we typically want to avoid any kind of unnecessary impact on working memory, the load in question is that of germane and is both helpful and necessary for learning. Diverse worked examples can be used to help minimize extraneous load and in the process offset the additional load imposed in the formatting of new schemata resulting from germane load (Clark et al., 2006). As the name implies, diverse worked examples are varied worked examples and practice problems that help in the application of skills and knowledge to varied scenarios. Because diverse worked examples are so diverse, they impose much more of a cognitive load. However, these diverse examples can lead to greater transfer of learning than examples which are all similar in nature (Clark et al., 2006). All in all, when learners are expected to transfer the skills and knowledge they have learned to new situations, a series of diverse worked examples and practice problems should be used to promote germane load and at the same time help mitigate extraneous load (Clark et al., 2006).

Additional Empirical Support for the Worked Examples Principle Unfortunately, germane load is the least empirically supported of the three loads (Clark et al., 2006). The reason for this is quite simple; although more and more CLT related studies are now investigating the effects of instructional methods on

intrinsic and germane load, CLT was once used to predominately study instructional methods intended to decrease extraneous load (van Merrienboer & Ayres, 2005). Consequently, we revisit the study conducted by Paas (1992), who showed that practice problems took significantly more time to complete than that of worked examples or completion examples, and that participants learned more from the worked and completion examples than the practice problems. Paas (1992) also investigated near and far transfer with regard to worked and completion examples. Test findings showed that scores for problems dealing with near transfer did not vary. However, scores did vary significantly for problems which dealt with far transfer for those participants who were exposed to the worked and completion examples. The rationale behind this finding was that the examples required fewer resources from working memory, leaving more resources for learning the information.

concLusIon Applying What We Have Learned In this chapter, we learned that CLT can be used to bridge the gap between instructional principles and knowledge of human cognition (Sweller, 2005a). We discussed a number of instructional principles coming out of the research on CLT. Instructional principles that if used properly can help manage intrinsic, avoid extraneous, and promote germane load. Although considerations for cognitive load should be part of the design of all instructional material, we argue that such principles hold even more weight in the design of instruction to assist those with learning disabilities. For example, a possible explanation for the inability of some children to meet mathematical literacy standards is that cognitive load on mathematics curriculum may be too high and these children may not be able to keep up with instructional

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Managing Cognitive Load in the Design of Assistive Technology for Those with Learning Disabilities

activities that are otherwise optional to learning (Woodward, 2006; Woodward & Montague, 2002, as cited in Wong, Graham, Hoskyn, & Berman, 1996). In such a case, it is important to ensure that the redundancy principle is followed. Only include instruction that is essential to the understanding of the information to be learned. Additionally, worked examples should be leveraged in the delivery of the instruction. Initially, only worked examples should be used, and as the learner grows in their skills and knowledge of the subject, these worked examples can be slowly replaced with traditional practice problems—essentially implementing the approach of backwards fading. Moreover, the split-attention and modality principles should be considered in the design of the worked examples to ensure that, for example, a split-attention effect is not inadvertently created. The pre-training and sequencing principles can also be evaluated to their potential benefits. For instance, it may be prudent to allow the learner to control the rate in which the instruction is presented. While our example is simple, we understand that the design of instructional materials to assist those with LDs is far from such, but is instead a taunting, complex, and challenging task. However, we believe that it is important that technology for learning be created with an understanding of design principles empirically supported by how the human mind works. Thus, we invite those involved in the creation of instruction for those with learning disabilities to learn more about the principles presented in this chapter and add them to their repertoire of instructional design knowledge. Furthermore, we add that there are many more instructional principles stemming from the research on CLT that could be leverage to assist those with LDs. In the next and final chapter of this introduction, we present a number of these additional instructional principles developed from the body of research focused specifically on multimedia learning.

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reFerences Ayres, P., & Sweller, J. (2005). The split-attention principle in multimedia learning. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning (pp. 135–146). New York: Cambridge University Press. Baddeley, A. D. (1986). Working memory. New York, NY: Oxford University Press. Baddeley, A. D. (1998). Human memory: Theory and practice. Boston, MA: Allyn and Bacon. Baddeley, A. D. (2002). Is working memory still working? European Psychologist, 7(2), 85–97. doi:10.1027//1016-9040.7.2.85 Bull, R., Johnston, R. S., & Roy, J. A. (1999). Exploring the roles of the visual-spatial sketch pad and central executive in children’s arithmetical skills: Views from cognition and developmental neuropsychology. Developmental Neuropsychology, 15, 421–442. doi:10.1080/87565649909540759 Chandler, P., & Sweller, J. (1991). Cognitive load theory and the format of instruction. Cognition and Instruction, 8(4), 293–332. doi:10.1207/ s1532690xci0804_2 Chandler, P., & Sweller, J. (1996). Cognitive load while learning to use a computer program. Applied Cognitive Psychology, 10, 151–170. doi:10.1002/ (SICI)1099-0720(199604)10:2<151::AIDACP380>3.0.CO;2-U Clark, J. M., & Paivio,A. (1991). Dual coding theory and education. Educational Psychology Review, 3(3), 149–210. doi:10.1007/BF01320076 Clark, R., Nguyen, F., & Sweller, J. (2006). Efficiency in learning: Evidence-based guidelines to manage cognitive load. San Francisco, CA: Pfeiffer. de Jong, P. F. (1998). Working memory deficits of reading disabled children. Journal of Experimental Child Psychology, 70(2), 75–96. doi:10.1006/ jecp.1998.2451

Managing Cognitive Load in the Design of Assistive Technology for Those with Learning Disabilities

Hitch, G. J., & McLean, J. F. (1991). Working memory in children with specific arithmetical learning difficulties. The British Journal of Psychology, 82, 375–386.

Marcus, N., Cooper, M., & Sweller, J. (1996). Understanding instructions. Journal of Educational Psychology, 88(1), 49–63. doi:10.1037/00220663.88.1.49

Jeung, H. J., & Chandler, P. (1997). The role of visual indicators in dual sensory mode instruction. Educational Psychology, 17(3), 329. doi:10.1080/0144341970170307

Mayer, R. E. (2003). Elements of science in E-learning. Journal of Educational Computing Research, 29(3), 297–313. doi:10.2190/YJLG09F9-XKAX-753D

Kalyuga, S., Chandler, P., & Sweller, J. (1998). Levels of expertise and instructional design. Human Factors, 40(1), 1–17. doi:10.1518/001872098779480587

Mayer, R. E. (2005a). Introduction to multimedia learning. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning (pp. 1–16). New York: Cambridge University Press.

Kalyuga, S., Chandler, P., & Sweller, J. (1999). Managing split-attention and redundancy in multimedia instruction. Applied Cognitive Psychology, 13, 351–371. doi:10.1002/ (SICI)1099-0720(199908)13:4<351::AIDACP589>3.0.CO;2-6

Mayer, R. E. (2005b). Principles for managing essential processing in multimedia learning: Segmenting, pretraining, and modality principles. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning (pp. 169–182). New York: Cambridge University Press.

Kalyuga, S., Chandler, P., Tuovinen, J., & Sweller, J. (2001). When problem solving is superior to studying worked examples. Journal of Educational Psychology, 93(3), 579–588. doi:10.1037/00220663.93.3.579

Mayer, R. E. (Ed.). (2005c). The Cambridge handbook of multimedia learning. New York: Cambridge University Press.

Keeler, M. L., & Swanson, H. L. (2001). Does strategy knowledge influence working memory in children with mathematical disabilities? Journal of Learning Disabilities, 34(5), 418–434. doi:10.1177/002221940103400504 Leahy, W., Chandler, P., & Sweller, J. (2003). When auditory presentations should and should not be a component of multimedia instruction. Applied Cognitive Psychology, 17, 401–418. doi:10.1002/acp.877 Low, R., & Sweller, J. (2005). The modality principle in multimedia learning. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning (pp. 147–158). New York: Cambridge University Press.

Mayer, R. E., & Chandler, P. (2001). When learning is just a click away: Does simple user interaction foster deeper understanding of multimedia messages? Journal of Educational Psychology, 93(2), 390–397. doi:10.1037/0022-0663.93.2.390 Mayer, R. E., Dow, G. T., & Mayer, S. (2003). Multimedia learning in an interactive self-explaining environment: What works in the design of agent-based microworlds? Journal of Educational Psychology, 95(4), 806–812. doi:10.1037/00220663.95.4.806 Mayer, R. E., Heiser, J., & Lonn, S. (2001). Cognitive constraints on multimedia learning: When presenting more material results in less understanding. Journal of Educational Psychology, 93(1), 187–198. doi:10.1037/0022-0663.93.1.187

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Mayer, R. E., Mathias, A., & Wetzell, K. (2002). Fostering understanding of multimedia messages through pre-training: Evidence for a two-stage theory of mental model construction. Journal of Experimental Psychology. Applied, 8(3), 147–154. doi:10.1037/1076-898X.8.3.147 Mayer, R. E., Mautone, P., & Prothero, W. (2002). Pictorial aids for learning by doing in a multimedia geology simulation game. Journal of Educational Psychology, 94(1), 171–185. doi:10.1037/00220663.94.1.171 Mayer, R. E., & Moreno, R. (1998). A splitattention effect in multimedia learning: Evidence for dual processing systems in working memory. Journal of Educational Psychology, 90(2), 312– 320. doi:10.1037/0022-0663.90.2.312 Mayer, R. E., & Moreno, R. (2003). Nine ways to reduce cognitive load in multimedia learning. Educational Psychologist, 38(1), 43–52. doi:10.1207/S15326985EP3801_6 McLean, J. F., & Hitch, G. J. (1999). Working memory impairments in children with specific arithmetic learning difficulties. Journal of Experimental Child Psychology, 74(3), 240–260. doi:10.1006/jecp.1999.2516 Miller, G., A. (1956). The magical number seven, plus or minus two: Some limits on our capacity for processing information. Psychological Review, 63, 81–97. doi:10.1037/h0043158 Moreno, R., & Mayer, R. E. (1999). Cognitive principles of multimedia learning: The role of modality and contiguity. Journal of Educational Psychology, 91(2), 358–368. doi:10.1037/00220663.91.2.358 Moreno, R., & Mayer, R. E. (2000a). A coherence effect in multimedia learning: The case for minimizing irrelevant sounds in the design of multimedia instructional messages. Journal of Educational Psychology, 92(1), 117–125. doi:10.1037/0022-0663.92.1.117

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Moreno, R., & Mayer, R. E. (2000b). Engaging students in active learning: The case for personalized multimedia messages. Journal of Educational Psychology, 92(4), 724–733. doi:10.1037/00220663.92.4.724 Moreno, R., & Mayer, R. E. (2002). Learning science in virtual reality multimedia environments: Role of methods and media. Journal of Educational Psychology, 94(3), 598–610. doi:10.1037/0022-0663.94.3.598 Moreno, R., Mayer, R. E., Spires, H. A., & Lester, J. C. (2001). The case for social agency in computer-based teaching: Do students learn more deeply when they interact with animated pedagogical agents? Cognition and Instruction, 19(2), 177–213. doi:10.1207/S1532690XCI1902_02 Mousavi, S. Y., Low, R., & Sweller, J. (1995). Reducing cognitive load by mixing auditory and visual presentation modes. Journal of Educational Psychology, 87(2), 319–334. doi:10.1037/00220663.87.2.319 Niaz, M., & Logie, R. H. (1993). Working memory, mental capacity and science education: Towards an understanding of the ‘working memory overload hypothesis’. Oxford Review of Education, 19(4), 511–525. doi:10.1080/0305498930190407 Paas, F., Renkl, A., & Sweller, J. (2003). Cognitive load theory and instructional design: Recent developments. Educational Psychologist, 38(1), 1–4. doi:10.1207/S15326985EP3801_1 Paas, F. G. W. C. (1992). Training strategies for attaining transfer of problem-solving skill in statistics: A cognitive-load approach. Journal of Educational Psychology, 84(4), 429–434. doi:10.1037/0022-0663.84.4.429 Paivio, A. (1971). Imagery and verbal processes. New York: Holt, Rinehart and Winston.

Managing Cognitive Load in the Design of Assistive Technology for Those with Learning Disabilities

Paivio, A. (1990). Mental representations: A dual coding approach. New York: Oxford University Press. Passolunghi, M. C., & Siegel, L. S. (2004). Working memory and access to numerical information in children with disability in mathematics. Journal of Experimental Child Psychology, 88(4), 348–367. doi:10.1016/j.jecp.2004.04.002 Penney, C. G. (1989). Modality effects and the structure of short-term verbal memory. Memory & Cognition, 17, 398–422. Pollock, E., Chandler, P., & Sweller, J. (2002). Assimilating complex information. Learning and Instruction, 12, 61–86. doi:10.1016/S09594752(01)00016-0 Renkl, A. (2005). The worked-out examples principle in multimedia learning. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning (pp. 229–245). New York: Cambridge University Press. Shiffrin, R. M., & Atkinson, R. C. (1969). Storage and retrieval processes in long-term memory. Psychological Review, 76(2), 179–193. doi:10.1037/ h0027277 Swanson, H. L., & Siegel, L. (2001). Learning disabilities as a working memory deficit. Issues in Education: Contributions of Educational Psychology, 7(1), 1–48. Sweller, J. (1999). Instructional design in technical areas. Australia: ACER Press. Sweller, J. (2005a). Implications of cognitive load theory for multimedia learning. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning (pp. 19–30). New York: Cambridge University Press. Sweller, J. (2005b). The redundancy principle in multimedia learning. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning (pp. 159–167). New York: Cambridge University Press.

Sweller, J., & Chandler, P. (1994). Why some material is difficult to learn. Cognition and Instruction, 12(3), 185–233. doi:10.1207/ s1532690xci1203_1 Sweller, J., Chandler, P., Tierney, P., & Cooper, M. (1990). Cognitive load as a factor in the structuring of technical material. Journal of Experimental Psychology. General, 119(2), 176–192. doi:10.1037/0096-3445.119.2.176 Sweller, J., & Cooper, G. A. (1985). The use of worked examples as a substitute for problem solving in learning algebra. Cognition and Instruction, 2(1), 59–89. doi:10.1207/s1532690xci0201_3 Sweller, J., van Merrienboer, J. J. G., & Paas, F. G. W. C. (1998). Cognitive architecture and instructional design. Educational Psychology Review, 10(3), 251–296. doi:10.1023/A:1022193728205 Tarmizi, R. A., & Sweller, J. (1988). Guidance during mathematical problem solving. Journal of Educational Psychology, 80(4), 424–436. doi:10.1037/0022-0663.80.4.424 Tindall-Ford, S., Chandler, P., & Sweller, J. (1997). When two sensory modes are better than one. Journal of Experimental Psychology. Applied, 3(4), 257–287. doi:10.1037/1076-898X.3.4.257 van Merrienboer, J. J. G., & Ayres, P. (2005). Research on cognitive load theory and its design implications for e-learning. Educational Technology Research and Development, 53(3), 5–13. doi:10.1007/BF02504793 Ward, M., & Sweller, J. (1990). Structuring effective worked examples. Cognition and Instruction, 7(1), 1–39. doi:10.1207/s1532690xci0701_1 Wong, B. Y. L., Graham, L., Hoskyn, M., & Berman, J. (1996). The ABCs of learning disabilities (2nd ed.). New York: Elsevier/Academic Press.

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AddItIonAL reAdIng Ayres, P., & Sweller, J. (2005). The split-attention principle in multimedia learning. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning (pp. 135–146). New York: Cambridge University Press. Clark, R., Nguyen, F., & Sweller, J. (2006). Efficiency in learning: Evidence-based guidelines to manage cognitive load. San Francisco, CA: Pfeiffer. Low, R., & Sweller, J. (2005). The modality principle in multimedia learning. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning (pp. 147–158). New York: Cambridge University Press. Mayer, R. E. (2005a). Introduction to multimedia learning. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning (pp. 1–16). New York: Cambridge University Press. Mayer, R. E. (2005b). Principles for managing essential processing in multimedia learning: Segmenting, pretraining, and modality principles. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning (pp. 169–182). New York: Cambridge University Press. Mayer, R. E. (Ed.). (2005c). The Cambridge handbook of multimedia learning. New York: Cambridge University Press. Mayer, R. E., & Moreno, R. (2003). Nine ways to reduce cognitive load in multimedia learning. Educational Psychologist, 38(1), 43–52. doi:10.1207/S15326985EP3801_6 Paas, F., Renkl, A., & Sweller, J. (2003). Cognitive load theory and instructional design: Recent developments. Educational Psychologist, 38(1), 1–4. doi:10.1207/S15326985EP3801_1

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Renkl, A. (2005). The worked-out examples principle in multimedia learning. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning (pp. 229–245). New York: Cambridge University Press. Sweller, J. (2005a). Implications of cognitive load theory for multimedia learning. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning (pp. 19–30). New York: Cambridge University Press. Sweller, J. (2005b). The redundancy principle in multimedia learning. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning (pp. 159–167). New York: Cambridge University Press. Sweller, J., van Merrienboer, J. J. G., & Paas, F. G. W. C. (1998). Cognitive architecture and instructional design. Educational Psychology Review, 10(3), 251–296. doi:10.1023/A:1022193728205

key terms And deFInItIons Backwards Fading: A strategy in which worked examples become gradually replaced with practice problems in a lesson as the learner gains expertise in the subject matter (Clark et al., 2006). Cognitive Load: Refers to the amount of cognitive resources imposed on working memory. Cognitive Load Theory (CLT): A theory proposed by John Sweller and his colleagues focused on the limitations of working memory during instruction. Cognitive Theory of Multimedia Learning: A theory credited to Richard E. Mayer and his colleagues focused on best practices in the use of visual and auditory information in multimediabased instruction. Completion Examples: A hybrid approach between worked examples and practice problems

Managing Cognitive Load in the Design of Assistive Technology for Those with Learning Disabilities

where some steps are provided as worked example and others are presented as practice problems. Diverse Worked Examples: Varied worked examples and practice problems that help in the application of skills and knowledge to varied scenarios. Dual-Coding Theory: The theory proposed by Allan Paivio that cognition is composed of verbal and non-verbal subsystems. Element Interactivity: Used to measure intrinsic load; think of an element as a single unit of information to be processed in working memory. Extraneous (Irrelevant Load) Load: One of three types of cognitive load that is caused in situations where instructional material is created using instructional design that ignores the limitations of working memory and consequently fails to focus working memory resources on schema construction and automation (Sweller, 2005a); this load is irrelevant to the learning goals at hand (Clark et al., 2006) and is considered to be under the control of the instructional designer (Pollock et al., 2002) and, consequently, is avoidable if proper instructional methods are applied. Far Transfer: Transfer of skills and knowledge that is applied under conditions of change; learners must be able to apply the skills and knowledge that they have learned to new situations. Germane (Effective) Load: One of three types of cognitive load that can prove advantageous to learners in applying what they have learned to new tasks; it is caused by instructional design implementations that aid in meaningful learning and is under the control of the instructional designer. Intrinsic Load: One of three types of cognitive load that is caused by the natural complexity of the information that must be processed or the amount of element interactivity involved; this load is not under the control of the instructional designer. Modality Principle: An instructional principle proposing that presenting information in dual modalities spreads total induced load across the

visual and auditory channels of working memory thereby reducing cognitive load (Low & Sweller, 2005; Sweller & Chandler, 1994; Sweller et al., 1998). Near Transfer: The transfer of skills and knowledge that are typically applied the same way each and every time the skills and knowledge are used. Pre-training Principle: An instructional principle proposing that learners learn more deeply when they are aware of names and behaviors of main concepts (Mayer, 2005a; Mayer & Moreno, 2003). Procedure Knowledge: “[K]nowledge underpinning performance of a task that is completed more or less the same way each time” (Clark et al., 2006, p. 168). Process Knowledge: “[A] flow of events that summarize the operations of business, scientific, or mechanical systems” (Clark et al., 2006, p. 163). Redundancy Principle: An instructional principle proposing that learners learn more deeply when identical information is not presented in more than one format (Mayer, 2005a). Segmenting Principle: An instructional principle proposing that deeper learning can occur when a lesson is presented in learner-controlled segments rather than continuous units (Mayer, 2005a; Mayer & Moreno, 2003). Split-Attention Principle: An instructional principle proposing that if the instructional material is presented as a figure and text, split-attention can be circumvented by integrating the figure and text together (Sweller & Chandler, 1994). Transfer of Learning: The ability to apply what has been learned to new settings or situations. Worked (Worked-out) Examples: A stepby-step example that demonstrates how a task is performed or how to solve a problem (Clark et al., 2006); the principle proposes learners learn more deeply when studying worked examples than studying practice problems (Sweller, 2005a).

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Managing Cognitive Load in the Design of Assistive Technology for Those with Learning Disabilities

Worked Example-Problem Pairs: The strategy of altering of worked example with similar practice problems (Clark et al., 2006).

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Chapter 3

Multimedia Design of Assistive Technology for Those with Learning Disabilities Boaventura DaCosta Solers Research Group, USA Soonhwa Seok Center for Research on Learning - eLearning Design Lab, University of Kansas, USA

AbstrAct This is the final of three chapters serving as the introduction to this handbook which addresses the relationship between human cognition and assistive technologies and its design for individuals with cognitive disabilities. In this chapter the authors build upon the last two chapters and focus specifically on research investigating the visual and auditory components of working memory. The authors present the cognitive theory of multimedia learning, a learning theory proposing a set of instructional principles grounded in human information processing research that provide best practices in designing efficient multimedia learning environments. Much like the last chapter, the instructional principles presented are grounded in empirically-based study and consolidate nearly twenty years of research to highlight the best ways in which to increase learning. Altogether, the authors stress the common thread found throughout this three chapter introduction—that technology for learning should be created with an understanding of design principles empirically supported by how the human mind works. They argue that the principles emerging from the cognitive theory of multimedia learning may have potential benefits in the design of assistive technologies for those with learning disabilities. DOI: 10.4018/978-1-61520-817-3.ch003

Copyright © 2010, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

Multimedia Design of Assistive Technology for Those with Learning Disabilities

IntroductIon multimedia, Assistive technology, and those with Learning disabilities Unlike early theories which viewed short-term memory as a single store capable of performing numerous operations (Sweller, 2005a), working memory is assumed to be composed of multiple stores (Baddeley, 1986, 1998, 2002; Paivio, 1990; Penney, 1989; Sweller, 2005). Baddeley’s model of working memory portrays numerous operations by handling visual and acoustic information individually with the visuospatial sketchpad and phonological loop subsystems. Making use of partial autonomy for processing visual and auditory information is believed to be a way in which to address the limitations of working memory. For example, Frick (1984) had investigated the idea of separate visual and auditory memory stores, showing how digit-span recall could be increased; Penney (1989), in a review, had provided evidence that appropriate use of the visual and auditory stores can maximize working memory capacity. Although researchers seem to disagree on a common nomenclature, using terms such as stores, channels, bisensory, dual-coding, and dual-processing (e.g., Allport, Antonis, & Reynolds, 1972; Baddeley, 1986, 1998; Jones, Macken, & Nicholls, 2004; Mayer & Anderson, 1991; Paivio, 1971; Penney, 1989) to represent the components of working memory, they do seem to agree with the premise that dual-processing is vital towards overcoming the limitations of working memory. This dual-processing assertion is best represented in Paivio’s dual-coding theory (Clark & Paivio, 1991; Paivio, 1971, 1990), which proposes that cognition is composed of verbal and nonverbal subsystems. These two subsystems are considered distinct, but interrelated. The verbal subsystem favors organized, linguistically-based information, stressing verbal associations. Examples include words, sentences, and stories. The

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non-verbal subsystem, organizes information in nested sets, processed either synchronously or in parallel. Examples include pictures and sounds (Paivio, 1971, 1990; Paivio, Clark, & Lambert, 1988). Multimodal instructional material, which can be coded in both subsystems, rather than just one, is more easily recalled. By leveraging both the verbal and non-verbal subsystems, more information can be processed. Studies examining dual-coding have shown greater performance can be achieved when learners are presented with instructional material that takes advantage of both the verbal and non-verbal subsystems (e.g., Frick, 1984; Gellevij, Van Der Meij, De Jong, & Pieters, 2002; Leahy, Chandler, & Sweller, 2003; Mayer & Moreno, 1998; Moreno & Mayer, 1999). These findings are promising, as they suggest the limited capacity of working memory can be addressed by presenting instruction in a verbal and non-verbal manner (Mayer, 2001, 2005e; Sweller, van Merrienboer, & Paas, 1998). More importantly, the converse has also been shown. The verbal and non-verbal subsystems are believed to pool from the same processing resources. As such, multimodal information that is not interrelated can negatively impact working memory performance (Morey & Cowan, 2004). Thus, the non-verbal presentation of information should be relational to the verbal (textual), for it has a significant impact on working memory and learning. This is the final of three chapters serving as the introduction to this handbook which addresses the relationship between human cognition and assistive technologies (ATs) and its design for individuals with cognitive disabilities. In this chapter we build upon the last two chapters and focus specifically on research investigating the visual and auditory components of working memory. We present the cognitive theory of multimedia learning (CTML), a learning theory proposing a set of instructional principles grounded in human information processing research that provide best practices in designing efficient multimedia learn-

Multimedia Design of Assistive Technology for Those with Learning Disabilities

ing environments. Much like the last chapter, the instructional principles presented are grounded in empirically-based study and consolidate nearly twenty years of research to highlight the best ways in which to increase learning. Altogether, we stress the common thread found throughout this three chapter introduction—that technology for learning should be created with an understanding of design principles empirically supported by how the human mind works. We argue that the principles emerging from the CTML may have potential benefits in the design of ATs for those with learning disabilities (LDs). Before we delve into the principles composing the CTML, we begin by first defining multimedia learning itself. We then provide a brief explanation of the theory and discuss its theoretical foundation.

bAckground

then integrated with relevant existing knowledge (Marshall, 1996; Mayer, 2001; Mayer & Moreno, 2003; Wittrock, 1990). Meaningful learning is distinguished by good retention and transfer performance. Retention is reflected in the ability to remember pertinent presented material. Transfer is reflected in the ability to understand what was learned and apply it to new situations (Mayer, 2002, 2005b). Transfer includes being able to solve new problems with knowledge that is not explicitly presented in the material (Mayer, 2005b). Multimedia learning can therefore be described as the building of mental representations from the amalgamation of words and pictures, which induces the promotion of meaningful learning (Mayer, 2001, 2005b). As we will see later in this chapter, many CTML studies measure multimedia learning in terms of retention and transfer through post-tests.

What is multimedia Learning?

WHAt Is tHe cognItIve tHeory oF muLtImedIA LeArnIng?

In the broadest sense, multimedia can be defined as the presentation of both words and pictures to a learner in a variety of ways. Words can be presented in verbal form and can be written or spoken. Either their phonological or semantic aspects can be emphasized. Pictures are presented in pictorial form and can consist of static or dynamic objects to include illustrations, photos, animations, or video. The pairing of presentation mode and sensory modality allow for many conceivable permutations (Mayer, 2005b; Reed, 2006). Meaningful learning involves remembering and understanding instructional material. Whereas remembering is the ability to recognize or reproduce instructional material, understanding is the ability to construct sound mental representations from the material (Mayer, 2005b). Meaningful learning occurs when important aspects of the material are cognitively recognized, when the material is organized into a coherent structure, and

The CTML has shown steady growth since its earliest studies in the 1990s exploring the plausibility of multimedia learning. The premise that learners learn more deeply from words and pictures than from words only was one of the first predictions made by Richard E. Mayer and his colleagues based at the time on his generative theory. This would later become known as the multimedia principle, serving as the founding principle behind the CTML. Mayer and his colleagues continued to explore numerous effects while developing recommendations and guidelines throughout the remainder of the twentieth century. These effects would later be described as principles and encompass over 80 individual experiments (Veronikas & Shaughnessy, 2005). In recent years, research in the CTML has significantly grown. Although a substantial amount of research can be found exploring advanced effects and posturing new principles for how to

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Multimedia Design of Assistive Technology for Those with Learning Disabilities

design multimedia learning, an emerging trend points to the study of existing principles in various content areas. One such example is the study of multimedia learning in the context of advanced computer-based environments (Mayer, 2005b). For example, Mayer and his colleagues have of late been examining the use of animated pedagogical agents (Moreno, 2005). Mayer hypothesizes that the basic principles can be applied in the use of these agents (Veronikas & Shaughnessy, 2005). Other such examples include the examination of multimedia learning in the context of virtual reality (Cobb & Fraser, 2005) and games, simulations, and microworlds (Rieber, 2005). These contexts have already fueled a number of studies (e.g., Atkinson, Mayer, & Merrill, 2005, Experiments 1 and 2; Dunsworth & Atkinson, 2007; Mayer, Dow, & Mayer, 2003, Experiments 1, 2a and 2b, 3, and 4; Merrill, 2003; Moreno & Flowerday, 2006; Moreno & Mayer, 2004; 2005, Experiments 1, 2, and 3; Moreno, Mayer, Spires, & Lester, 2001, Experiments 1, 2, 3, 4, and 5).

dual-channels, Limited capacity, and Active Processing Assumptions Three cognitive learning principles provide the theoretical underpinnings for the CTML. The first of these assumptions, dual-channels, posits that the human information processing system is composed of a separate processing channel for visual and auditory represented material. Mayer (Mayer, 2001, 2005f) has conceptualized these dual-channels as a presentation mode and a sensory modality. The presentation mode addresses verbal (e.g., spoken or written words) and pictorial (e.g., illustrations, photos, animations, or video) representations of presented material. This notion best resembles Paivio’s dual-coding theory (Clark & Paivio, 1991; Paivio, 1971, 1990) and borrows from the distinctions between the verbal and nonverbal subsystems (Mayer, 2001, 2005a). Sensory modality, on the other hand, deals with the sense through which the presented material is processed.

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For example, learners initially process presented material through their eyes or ears. One channel processes verbal represented material, whereas the other channel processes auditory represented material. This notion is consistent with Baddeley’s (1986, 1998, 2002) model of working memory and borrows from the distinctions between the visuospatial sketchpad and the phonological loop (Baddeley, 2002; Mayer, 2001, 2005a). The second assumption, limited capacity, has already been discussed to some degree in the last two chapters. The assumption posits that working memory is limited in how much information can be processed within each channel. Unprocessed information that cannot be handled immediately decays over time. This notion is most consistent with Baddeley’s model of working memory as well as cognitive load theory (CLT) (Mayer, 2001, 2005a). The last assumption, active processing, posits that humans must actively engage in cognitive processing for learning to occur. Mayer has identified three processes required for this to take place. First, relevant incoming information must be cognitively recognized and selected. In other words, the learner must be actively paying attention for the relevant information to be brought into working memory. Second, the incoming information must be organized into a coherent structure. This involves constructing a logical mental representation (i.e., model) of the elements composing the selected information within working memory. Finally, the organized information must be integrated with relevant existing knowledge found in long-term memory (LTM) (Mayer, 1996, 2001; Mayer & Moreno, 2003; Wittrock, 1990). These three assumptions can be found in Mayer’s cognitive model of multimedia learning (see Mayer, 2001). Mayer (2001) provides a rather straightforward example of his cognitive model. Multimedia (presented in words and pictures) enters sensory memory through the eyes and ears. This permits the information to be held as visual and auditory

Multimedia Design of Assistive Technology for Those with Learning Disabilities

images for a brief period until such time that the relevant incoming information is selected and brought into working memory. Once in working memory, the incoming information is stored as raw material based on the visual and auditory sensory modalities. This information is then organized into coherent mental representations as verbal and pictorial models. Finally, the organized verbal and pictorial information is integrated with each other and relevant existing knowledge from LTM. This newly integrated knowledge is persistently stored in LTM resulting in multimedia learning. As you may have already realized, this process is very similar to that discussed in the first chapter in this introduction in which we presented the modal model of memory. We turn our attention next in this chapter to the instructional principles.

bAsIc And AdvAnced PrIncIPLes Mayer (2005b) has logically divided the effects emerging from the research into two groups of principles, basic and advanced. The basic principles make up the cornerstone of the CTML. In fact, some of the basic principles serve as the theoretical foundation for other principles. For example, the multimedia principle is the basis for all the CTML principles. It is embodied in 11 experiments across six studies (e.g., Mayer, 1989, Experiments 1 and 2; Mayer & Anderson, 1991, Experiments 2a and 2b; 1992, Experiments 1 and 2; Mayer & Gallini, 1990, Experiments 1, 2, and 3; Moreno & Mayer, 1999, Experiment 1; 2002, Experiment 1). It is one of the well-documented principles in the CTML along with the modality and the contiguity (spatial and temporal) principles. Other basic principles include the coherence principle, pre-training principle, personalization, voice, and image principles, redundancy principle, segmentation principle, and the signaling principle (see Mayer, 2005b; Mayer & Moreno, 2003, for an in-depth review). The modality, pre-training, and segmenting principles can be used effectively to

manage the extraneous processing of multimedia instructional material (we presented these in the last chapter in our discussion of cognitive load theory), whereas the coherence, contiguity, redundancy, and signaling principles can be effectively used in reducing it (Mayer, 2005f). The advanced principles, conversely, mark some of the most current research being conducted in multimedia learning. These principles, as expected, are the weakest in terms of empirically-based research. These principles include the animation and interactivity principles, collaboration principle, guideddiscovery principle, navigation principles, prior knowledge principle, self-explanation principle, site map principle, worked-out example principle, and the cognitive aging principle (see Mayer, 2005b, for an in-depth review). In the following sections, we briefly discuss each of the principles. We present the basic principles in terms of managing and reducing extraneous processing of multimedia-based instructional material. We pay particularly attention to the coherence, contiguity, and signaling principles as these have not yet been discussed in this three part chapter introduction, whereas the modality, pretraining, redundancy, and segmenting principles have. Finally, we end by briefly introducing each of the advanced principles.

reducing the extraneous Processing of multimedia According to Mayer (2005d), there are five ways in which situations that cause extraneous load on working memory can be handled. First, irrelevant, extraneous instructional materials should be eliminated whenever possible. This can be accomplished by applying the coherence principle. Second, signals and cues can be inserted into the instructional material to emphasis the importance of certain instruction. This can be accomplished by applying the signaling principle. Third, related instructional content can be placed next to one another. In the case of multimedia, text would

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Multimedia Design of Assistive Technology for Those with Learning Disabilities

be placed next to graphics or as part of animations. This can be accomplished by applying the spatial contiguity principle. Finally, the temporal contiguity principle, when applied appropriately, can be leveraged to avoid the holding of crucial information in working memory for long periods of time. Overall, these principles point out that in the design of multimedia, less is more (Mayer, 2005d). We describe each of these principles next in greater detail.

Coherence Principle The coherence principle is a basic instructional principle proposing that learners learn more deeply when extraneous information is excluded (Mayer, 2005d). If used properly the coherence principle can reduce extraneous cognitive load on working memory. The principle is similar to that of the redundancy effect, in which learning may be hindered if identical information is not presented in more than one format (Mayer, 2005b). In the case of the coherence principle, learning may be hindered if irrelevant information is included in the instructional material. This may include words and pictures, but may also include animation and audio as well. A common example is the presentation of video prior to instruction. Mayer (2005d) cites the example of showing a video of lightning storms during an instructional animation that depicts the formation of lightning. Such extraneous information can serve as a distraction, hindering learning, and should be removed. There have been a number of CTML studies focused on the coherence principle (e.g., Harp & Mayer, 1997, experiment 1; 1998, experiments 1, 2, 3, and 4; Mayer, Bove, Bryman, Mars, & Tapangco, 1996, experiments 1, 2, and 3; Mayer, Heiser, & Lonn, 2001, experiment 3; Moreno & Mayer, 2000, experiments 1 and 2). In the studies conducted by Harp and Mayer (1997, 1998), two groups of students were asked to read a paper-based

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lesson on lightning formation. Whereas one lesson was concise, void of extraneous information, the other was embellished. Both groups were given a transfer test upon reading the lesson. The group who was given the concise lesson outperformed the group who was given the embellished one. A similar study was conducted a year earlier by Mayer et al. (1996) resulting in the same finding. The group who read the concise, paper-based lesson outperformed the group who had been given the embellished one. In the study by Moreno and Mayer (2000), two groups were exposed to multimedia presentations depicting lightning formation and a car’s brake system. Each presentation was delivered as animation and narration. One presentation included background music and environmental sounds, whereas the other did not. The group who received the presentation without the extraneous sound outperformed the group who had. Finally, a similar study was conducted by Mayer et al. (2001), who used extraneous video clips of lightning formation. The group who was exposed to the extraneous information performed poorer on a transfer test than the group who had not.

Redundancy Principle The redundancy principle was discussed in the last chapter and so we do not duplicate the effort here. This instructional principle proposes that learners learn more deeply when identical information is not presented in more than one format (Mayer, 2005b). While this is sometimes a difficult concept to accept, because those who develop instruction sometimes want to include as much information as possible, research on the matter suggests that the use of redundant information in instructional material can interfere with learning (Sweller, 2005b). In a nutshell, redundant information places unnecessary load on working memory and should be eliminated whenever possible.

Multimedia Design of Assistive Technology for Those with Learning Disabilities

Signaling Principle The signaling principle proposes that learners learn more deeply when cues are added to highlight the organization of essential instructional material (Mayer, 2005d). The recommendations behind the signaling principle can help learners focus attention on instruction important in meeting the objectives of the lesson. Examples of signals that can be incorporated into instructional material include the use of highlighted, bolded, underlined, or italicized text, circles or arrows pointing to specific text, and the use of paragraph headings (Clark, Nguyen, & Sweller, 2006). By inserting cues into the instructional material, learner attention can be directly away from content that may be extraneous. There have been a number of CTML studies focused on the signaling principle (e.g., Harp & Mayer, 1998, experiment 3a; Mautone & Mayer, 2001, experiments 3a and 3b). In the study by Harp and Mayer (1998), two groups were offered paper-based lessons on the formation of lighting. One of the lessons used an organizational sentence listing the main steps of lightning formation, whereas the other did not. The group who was offered the paper-based lesson that included the signaling strategy performed better on a transfer test than the group who had not. A similar finding was found by Mautone and Mayer (2001), who incorporated signaling techniques into multimedia presentations delivered as animation and narration. The signaling group outperformed the non-signaling group.

Spatial Contiguity Principle The spatial contiguity principle proposes that learners learn more deeply when related words and pictures are presented near one another than far apart (Mayer, 2005d). The goal in the spatial contiguity principle is to create instructional material where all pertinent information is integrated.

We learned in the last chapter that a split-attention effect is created when the learner must expel cognitive resources accessing instructional content that is physically placed in different locations. This case is no different. Learners must spend cognitive resources to search for words connected to pictures or visa versa. To avoid extraneous load when presenting words and pictures, ensure they are integrated with one another. Like the name implies, the spatial contiguity principle is concerned with space. There have been a number of CTML studies focused on the spatial contiguity principle (e.g., Chandler & Sweller, 1991, experiment 1; Mayer, 1989, experiment 2; Mayer, Steinhoff, Bower, & Mars, 1995, experiments 1, 2, and 3; Moreno & Mayer, 1999, experiment 1; Sweller, Chandler, Tierney, & Cooper, 1990, experiment 1; TindallFord, Chandler, & Sweller, 1997, experiment 1). In the studies conducted by Chandler and Sweller (1991), Mayer (1989), Mayer et al. (1995), Sweller et al. (1990), and Tindall-Ford et al. (1997), students were exposed to paper-based lessons across three different content areas. In the Chandler and Sweller (1991) and Tindall-Ford et al. (1997) studies, students were exposed to a lesson on topics from electrical engineering; in the Mayer (1989) study, students were exposed to a lesson on a car’s break system; in the Mayer et al. (1995) study, students were exposed to a lesson on the formation of lightning; whereas in the Sweller et al. (1990) study, students were exposed to worked examples showing how to solve geometry problems. Across all five studies, students were divided into two groups—those who received paper-based lessons in which the text was placed next to the corresponding graphic, and those in which text was placed outside of the graphic. For example, in the case of the Chandler and Sweller (1991) study, the text was placed after the geometric diagram. Across all the experiments, those who received the integrated lessons outperformed those who had received the separated lessons. Similar findings

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Multimedia Design of Assistive Technology for Those with Learning Disabilities

were also found by Moreno and Mayer (1999), who examined the contiguity principle with a multimedia presentation delivered as animation and on-screen text. The group who received the animation with integrated text performed better on a transfer test than the group who had not.

Temporal Contiguity Principle The temporal contiguity principle is an instructional principle proposing that learners learn more deeply when related animation and narration are presented concurrently rather than consecutively (2005d). According to the CTML, simultaneous presentation of words and pictures increases the odds that the information will be stored in the visual and auditory components of working memory, unlike the successive presentation of information, in which the learner must hold the information presented as auditory in working memory until the animation is presented. Visual and auditory information presented at the same time allows learners to build mental connections between the materials, whereas the same information presented successively makes the formation of mental connections much more difficult. While the spatial contiguity principle is focused on the proximity of words and pictures, the temporal contiguity principle is focused on time. There have been a number of CTML studies focused on the temporal contiguity principle (e.g., Mayer & Anderson, 1991, experiments 1 and 2; 1992, experiments 1 and 2; Mayer, Moreno, Boire, & Vagge, 1999, experiments 1 and 2; Mayer & Sims, 1994). The Mayer and Anderson (1991, 1992), Mayer et al. (1999) and Mayer and Sims (1994) studies all had similar findings. Those exposed to the animation with synchronized narrations outperformed those on transfer tests who received the animations with narrations that were presented in sequence.

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managing the extraneous Processing of multimedia The modality, pre-training, and segmenting principles can be used effectively to manage the extraneous processing of multimedia instructional material (Mayer, 2005f). These principles were presented in detail in the last chapter in the discussion on the avoidance of extraneous, management of intrinsic, and promotion of germane load, and so we only briefly define them here. Furthermore, to complete our discussion of the basic principles, we also briefly define the multimedia and personalization, voice, and image principles.

Modality Principle The modality principle is one of the most important instructional principles to have emerged from the CTML. It proposes that presenting information in dual modalities spreads total induced load across the visual and auditory channels of working memory thereby reducing cognitive load (Low & Sweller, 2005; Sweller & Chandler, 1994; Sweller, van Merrienboer, & Paas, 1998). For an in-depth discussion of the modality principle, please see Low and Sweller (2005), Clark, Nguyen, and Sweller (2006), and Mayer (2005c).

Pre-Training Principle The pre-training principle proposes that learners learn more deeply when made aware of names and behaviors of main concepts prior to presenting the main lesson (Mayer, 2005b; Mayer & Moreno, 2003). For an in-depth review of the principle, please see Mayer (2005c).

Segmentation Principle The segmentation principle proposes that deeper learning occurs when a lesson is presented in

Multimedia Design of Assistive Technology for Those with Learning Disabilities

learner-controlled segments rather than continuous units (Mayer, 2005c; Mayer & Moreno, 2003). For an in-depth review of the principle, please see Mayer (2005c).

Multimedia Principle The multimedia principle is the cornerstone principle in which the CTML is founded. The principle proposes that learners learn more deeply from words and pictures than from words only. For an in-depth review of the principle, please see Fletcher and Tobias (2005).

Personalization, Voice, and Image Principles The personalization, voice, and image principles provide recommendations based on social cues. According to Mayer (2005e), the personalization principle proposes that learners learn more deeply when words are presented in a conversational style as opposed to formally; the voice principle proposes that learners learn more deeply when words are spoken in a human voice void of accent, opposed to an accented voice or a machine voice; while the image principle proposes that learners learn more deeply when a speaker’s image can be seen by the learner on screen. For an in-depth review of the principles, please see Mayer (2005e).

Advanced Principles The advanced principles, as we mentioned earlier, mark some of the most current research being conducted in multimedia learning. These principles, as expected, are the weakest in terms of empirically-based research. We briefly define them here.

Animation and Interactivity Principles The animation and interactivity principles provide guidance on the design of multimedia that incorporate sophisticated animated graphics. The principles focus on the complexities of learner interactivity during learning. For an in-depth discussion of the principles, please see Betrancourt (2005).

Cognitive Aging Principle The cognitive aging principle is focused on helping older learners by effectively managing working memory resources (Mayer, 2005b). Subscribing to the idea that working memory capability declines with age (Paas, Van Gerven, & Tabbers, 2005; Van Gerven, Paas, Van Merrienboer, & Schmidt, 2006), the principle suggests that some instructional materials presented in multiple modalities may be more efficient than instructional material presented in a single modality for older learners. For an in-depth review of the principle, please see Paas et al. (2005) and DaCosta (2009).

Collaboration Principle In recent years, online collaboration has taken root. The collaboration principle proposes a variety of recommendations that support online multimedia-based collaborative learning environments (Jonassen, Lee, Yang, & Laffey, 2005). For an in-depth review of the principle, please see Jonassen, Lee, Yang, and Laffey (2005).

Guided-Discovery Principle The guided-discovery principle proposes that learners learn more deeply when using the strategy of directing the learner toward discovery (Jong, 2005). For an in-depth review of the principle, please see Jong (2005).

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Multimedia Design of Assistive Technology for Those with Learning Disabilities

Navigation Principles

Worked-out Example Principle

The navigation principles provide recommendations on the use of navigational aids. These aids include a broad category of visual and auditory devices ranging from local cues (e.g., headings and subheadings) to global content (e.g., tables and outlines) (Rouet & Potelle, 2005). For an indepth review of the principle, please see Rouet and Potelle (2005).

We discussed the worked-out example principle in the last chapter. A worked-out example is a stepby-step example that demonstrates how a task is performed or how to solve a problem (Clark et al., 2006). The principle proposes learners learn more deeply when studying worked examples than studying traditional practice problems (Sweller, 2005a). For an in-depth review of the principle, please see Renkle (2005) and Clark et al. (2006).

Prior Knowledge Principle The prior knowledge principle is focused on the effects of learner prior knowledge on the CTML principles (Kalyuga, 2005). The principle has emerged from consistent research findings suggesting that instructional principles may not benefit or adversely impact learners with high prior knowledge of the content to be learned. For an in-depth review of the principle, please see Kalyuga (2005).

Self-Explanation Principle The self-explanation principle proposes that learners learn more deeply when engaged in selfexplanation, a strategy which aids in attention and promotes meaningful learning though knowledge construction and integration activities (Roy & Chi, 2005). For an in-depth review of the principle, please see Roy and Chi (2005).

Site Map Principle The site map principle proposes that learners learn more deeply when appropriately structured site maps are used. It is suggested that these maps aid in learning because they provide learners with overarching view of the information to be learned (Shapiro, 2005). For an in-depth review of the principle, please see Shapiro (2005).

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cHALLenges In APPLyIng tHe PrIncIPLes Although these principles and recommendations are grounded in a number of experiments spanning many studies over two decades, care should be exercised when applying these principles. As with all empirically-based research, methodological limitations exist. Although limitations could easily be described in the context in which they are studied (e.g., multimedia learning as it applies to reading or mathematics), we discuss limitations commonly cited. We do this independent of their application. This amounts to four major categories: (a) setting and content, (b) sampling, (c) time, and (d) individual differences. Laboratory versus real-world settings has long been a methodological concern. Early experiments were performed in controlled laboratory-like environments suggesting that principles need further examination in real-world settings, such as the classroom. Content has also been an issue, as early treatments typically dealt with cause-and-effect subject matter. This has brought about the need to test the principles in the context of authentic learning environments using real-world content. The need for real-world testing and the exploration of advanced content have been explicitly noted in a number of studies (e.g., Mautone & Mayer, 2001; Mayer & Chandler, 2001; Mayer, Heiser,

Multimedia Design of Assistive Technology for Those with Learning Disabilities

& Lonn, 2001; Mayer & Moreno, 1998; Mayer & Sims, 1994; Moreno et al., 2001). Sampling has also been a voiced methodological concern (e.g., Dunsworth & Atkinson, 2007; Mayer et al., 2001; Mayer & Moreno, 1998). Early experiments typically used college students from the psychology subject pool at the University of California, Santa Barbara. Consequently, the principles have been predominately tested with younger learners 18 and 19 years of age (e.g., Mautone & Mayer, 2001; Mayer & Chandler, 2001; Mayer, Fennell, Farmer, & Campbell, 2004; Mayer, Hegarty, Mayer, & Campbell, 2005; Mayer & Jackson, 2005; Mayer, Johnson, Shaw, & Sandhu, 2006; Mayer & Massa, 2003; Mayer, Sobko, & Mautone, 2003; Moreno & Mayer, 2004, 2005). Furthermore, other concerns have stemmed from sample size. These limitations have established the need to test the principles with larger samplings across different demographics, to include age, gender, and language. The implication of time on multimedia learning has also been noted in studies (e.g., Craig, Gholson, & Driscoll, 2002; Mayer & Chandler, 2001; Mayer & Sims, 1994). Early experiments typically administered measures of multimedia learning immediately after exposure to multimedia presentations. In other cases, presentations themselves were relatively short in length. As a result, the depth of learning measured in these studies has been a concern, suggesting the need to test the principles in consideration to time. For example, would the principles produce the same depth of learning if delayed testing were used or if exposed to multimedia learning presentations for longer periods? Finally, the matter of individual differences has been commonly identified as a limitation (e.g., Craig et al., 2002; Mayer & Anderson, 1992; Mayer et al., 2001; Mayer & Sims, 1994; Moreno et al., 2001). Many experiments have procedures to identify and preclude learners who can demonstrate a predetermined level of prior knowledge. This exclusion is based on the study by Mayer

and Gallini (1990) (and subsequently Mayer and Sims (1994)), which concluded that learners with low prior knowledge had shown improved performance over those with high prior knowledge. This is in line with our discussions in the last chapter. Many studies, however, still argue the point that the CTML principles need to be examined with high prior knowledge learners.

concLusIon Final thoughts In this three chapters introduction we have presented a number of theories, with each chapter building on the last. In the first chapter, we offered the most popular beliefs about human information processing, presenting the modal model of memory. Along the way we learned that working memory is both a blessing and a curse, in that its limitations cause it to be a bottleneck, but it is also the means for learning. This is a serious problem because the acquisition of new knowledge relies so heavily on the processing and storage capabilities of working memory (Low & Sweller, 2005; Sweller & Chandler, 1994). In the second chapter, we presented cognitive load theory, a learning theory proposing a set of instructional principles rooted in human information processing research that can be used to create sound instructional materials that take into considerations the limitations of working memory. We presented a number of recommendations that can help in avoiding extraneous, managing intrinsic, and promoting germane load—three types of cognitive load that learners must deal with during the learning process. While finally, in this chapter, we presented the CTML, another learning theory focused specifically on the design of multimodal instructional materials that take into account human information processing theories and focuses specifically on taking advantage of the visual and auditory components of working memory.

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Our goal has been to separate conjecture and speculation from empirically-based study and consolidate more than twenty-five years of research to highlight the best ways in which to increase learning. Altogether we have stressed that technology for learning should be created with an understanding of design principles empirically supported by how the human mind works. Although considerable research is needed in the study of the instructional principles emerging from both CLT and the CTML with regard to ATs, we argue that the principles presented in this three chapter introduction show promise in helping those with LDs because of the focus these principles have in how the human mind works, specifically, cognitive load. We invite instructional designers, educators, practitioners, and others involved in the design of AT to learn more about CLT and the CTML and how the instructional principles they offer can be used as learning strategies for those with learning and potentially other cognitive disabilities.

DaCosta, B. (2009). The effect of cognitive aging on multimedia learning: An investigation of the cognitive aging principle. Germany: VDM Verlag Dr. Muller. Flecher, J. D., & Tobias, S. (2005). The multimedia principle. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning (pp. 117–133). New York: Cambridge University Press. Frick, R. W. (1984). Using both an auditory and a visual short-term store to increase digit span. Memory & Cognition, 12(5), 507–514. Harp, S. F., & Mayer, R. E. (1997). The role of interest in learning from scientific text and illustrations: On the distinction between emotional interest and cognitive interest. Journal of Educational Psychology, 89(1), 92–102. doi:10.1037/00220663.89.1.92

reFerences

Harp, S. F., & Mayer, R. E. (1998). How seductive details do their damage: A theory of cognitive interest in science learning. Journal of Educational Psychology, 90(3), 414–434. doi:10.1037/00220663.90.3.414

Betrancourt, M. (2005). The animation and interactivity principles of multimedia learning. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning (pp. 287–296). New York: Cambridge University Press.

Jonassen, D. H., Lee, C. B., Yang, C.-C., & Laffey, J. (2005). The collaboration principle in multimedia learning. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning (pp. 247–270). New York: Cambridge University Press.

Chandler, P., & Sweller, J. (1991). Cognitive load theory and the format of instruction. Cognition and Instruction, 8(4), 293–332. doi:10.1207/ s1532690xci0804_2

Jong, T. d. (2005). The guided discovery principle in multimedia learning. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning (pp. 215–228). New York: Cambridge University Press.

Clark, R., Nguyen, F., & Sweller, J. (2006). Efficiency in learning: Evidence-based guidelines to manage cognitive load. San Francisco, CA: Pfeiffer. Cobb, S., & Fraser, D. S. (2005). Multimedia learning in virtual reality. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning. New York: Cambridge University Press.

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Kalyuga, S. (2005). Prior knowledge principle in multimedia learning. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning (pp. 325–338). New York: Cambridge University Press.

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Low, R., & Sweller, J. (2005). The modality principle in multimedia learning. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning (pp. 147–158). New York: Cambridge University Press. Mautone, P. D., & Mayer, R. E. (2001). Signaling as a cognitive guide in multimedia learning. Journal of Educational Psychology, 93(2), 377–389. doi:10.1037/0022-0663.93.2.377 Mayer, R. E. (1989). Systematic thinking fostered by illustrations in scientific text. Journal of Educational Psychology, 81(2), 240–246. doi:10.1037/0022-0663.81.2.240 Mayer, R. E. (2001). Multimedia learning. New York: Cambridge University Press. Mayer, R. E. (2002). Rote versus meaningful learning. Theory into Practice, 41(4), 226–232. doi:10.1207/s15430421tip4104_4 Mayer, R. E. (2005a). Cognitive theory of multimedia learning. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning (pp. 31–48). New York: Cambridge University Press. Mayer, R. E. (2005b). Introduction to multimedia learning. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning (pp. 1–16). New York: Cambridge University Press. Mayer, R. E. (2005c). Principles for managing essential processing in multimedia learning: Segmenting, pretraining, and modality principles. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning (pp. 169–182). New York: Cambridge University Press. Mayer, R. E. (2005d). Principles for reducing extraneous processing in multimedia learning: Coherence, signaling, redundancy, spatial contiguity, and temporal contiguity principles. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning (pp. 183–200). New York: Cambridge University Press.

Mayer, R. E. (2005e). Principles of multimedia learning based on social cues: Personalization, voice, and image principles. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning (pp. 201–212). New York: Cambridge University Press. Mayer, R. E. (Ed.). (2005f). The Cambridge handbook of multimedia learning. New York: Cambridge University Press. Mayer, R. E., & Anderson, R. B. (1991). Animations need narrations: An experimental test of a dual-coding hypothesis. Journal of Educational Psychology, 83(4), 484–490. doi:10.1037/00220663.83.4.484 Mayer, R. E., & Anderson, R. B. (1992). The instructive animation: Helping students build connections between words and pictures in multimedia learning. Journal of Educational Psychology, 84(4), 444–452. doi:10.1037/00220663.84.4.444 Mayer, R. E., Bove, W., Bryman, A., Mars, R., & Tapangco, L. (1996). When less is more: Meaningful learning from visual and verbal summaries of science textbook lessons. Journal of Educational Psychology, 88(1), 64–73. doi:10.1037/00220663.88.1.64 Mayer, R. E., & Gallini, J. K. (1990). When is an illustration worth ten thousand words? Journal of Educational Psychology, 82(4), 715–726. doi:10.1037/0022-0663.82.4.715 Mayer, R. E., Heiser, J., & Lonn, S. (2001). Cognitive constraints on multimedia learning: When presenting more material results in less understanding. Journal of Educational Psychology, 93(1), 187–198. doi:10.1037/0022-0663.93.1.187 Mayer, R. E., & Moreno, R. (2003). Nine ways to reduce cognitive load in multimedia learning. Educational Psychologist, 38(1), 43–52. doi:10.1207/S15326985EP3801_6

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Mayer, R. E., Moreno, R., Boire, M., & Vagge, S. (1999). Maximizing constructivist learning from multimedia communications by minimizing cognitive load. Journal of Educational Psychology, 91(4), 638–643. doi:10.1037/00220663.91.4.638 Mayer, R. E., & Sims, V. K. (1994). For whom is a picture worth a thousand words? Extensions of a dual-coding theory of multimedia learning. Journal of Educational Psychology, 86(3), 389–401. doi:10.1037/0022-0663.86.3.389 Mayer, R. E., Steinhoff, K., Bower, G., & Mars, R. (1995). A generative theory of textbook design: Using annotated illustrations to foster meaningful learning of science text. Educational Technology Research and Development, 43(1), 31–43. doi:10.1007/BF02300480 Moreno, R. (2005). Multimedia learning with animated pedagogical agents. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning (pp. 507–523). New York: Cambridge University Press. Moreno, R., & Mayer, R. E. (1999). Cognitive principles of multimedia learning: The role of modality and contiguity. Journal of Educational Psychology, 91(2), 358–368. doi:10.1037/00220663.91.2.358 Moreno, R., & Mayer, R. E. (2000). A coherence effect in multimedia learning: The case for minimizing irrelevant sounds in the design of multimedia instructional messages. Journal of Educational Psychology, 92(1), 117–125. doi:10.1037/0022-0663.92.1.117 Morey, C. C., & Cowan, N. (2004). When visual and verbal memories compete: Evidence of crossdomain limits in working memory. Psychonomic Bulletin & Review, 11(2), 296–301.

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Paas, F., Van Gerven, P. W. M., & Tabbers, H. K. (2005). The cognitive aging principle in multimedia learning. In R. E. Mayer (Ed.), The Cambridge handbook of multimedia learning (pp. 339-354). New York: Cambridge University Press. Penney, C. G. (1989). Modality effects and the structure of short-term verbal memory. Memory & Cognition, 17, 398–422. Reed, S. K. (2006). Cognitive architectures for multimedia learning. Educational Psychologist, 41(2), 87–98. doi:10.1207/s15326985ep4102_2 Renkl, A. (2005). The worked-out examples principle in multimedia learning. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning (pp. 229–245). New York: Cambridge University Press. Rieber, L. P. (2005). Multimedia learning in games, simulations, and microworlds. In R. E. Mayer (Ed.), The Cambridge handbook of multimedia learning (pp. 549-567). New York: Cambridge University Press. Rouet, J.-F., & Potelle, H. (2005). Navigational Principles in Multimedia Learning. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning (pp. 297–312). New York: Cambridge University Press. Roy, M., & Chi, M. T. H. (2005). The self-explanation principle in multimedia learning. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning (pp. 271–286). New York: Cambridge University Press. Shapiro, A. M. (2005). The site map principle in multimedia learning. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning (pp. 313–324). New York: Cambridge University Press. Sweller, J. (2005a). Implications of cognitive load theory for multimedia learning. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning (pp. 19–30). New York: Cambridge University Press.

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Sweller, J. (2005b). The redundancy principle in multimedia learning. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning (pp. 159–167). New York: Cambridge University Press.

Jong, T. d. (2005). The guided discovery principle in multimedia learning. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning (pp. 215–228). New York: Cambridge University Press.

Sweller, J., & Chandler, P. (1994). Why some material is difficult to learn. Cognition and Instruction, 12(3), 185–233. doi:10.1207/s1532690xci1203_1

Kalyuga, S. (2005). Prior knowledge principle in multimedia learning. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning (pp. 325–338). New York: Cambridge University Press.

Sweller, J., Chandler, P., Tierney, P., & Cooper, M. (1990). Cognitive load as a factor in the structuring of technical material. Journal of Experimental Psychology. General, 119(2), 176–192. doi:10.1037/0096-3445.119.2.176 Tindall-Ford, S., Chandler, P., & Sweller, J. (1997). When two sensory modes are better than one. Journal of Experimental Psychology. Applied, 3(4), 257–287. doi:10.1037/1076-898X.3.4.257 Van Gerven, P. W. M., Paas, F., Van Merrienboer, J. J. G., & Schmidt, H. G. (2006). Modality and variability as factors in training the elderly. Applied Cognitive Psychology, 20, 311–320. doi:10.1002/ acp.1247 Veronikas, S., & Shaughnessy, M. F. (2005). An interview with Richard Mayer. Educational Psychology Review, 17(2), 179–189. doi:10.1007/ s10648-005-3952-z

AddItIonAL reAdIng Betrancourt, M. (2005). The animation and interactivity principles of multimedia learning. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning (pp. 287–296). New York: Cambridge University Press. Jonassen, D. H., Lee, C. B., Yang, C.-C., & Laffey, J. (2005). The collaboration principle in multimedia learning. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning (pp. 247–270). New York: Cambridge University Press.

Mayer, R. E. (2001). Multimedia learning. New York: Cambridge University Press. Mayer, R. E. (2005a). Cognitive theory of multimedia learning. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning (pp. 31–48). New York: Cambridge University Press. Mayer, R. E. (2005b). Introduction to multimedia learning. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning (pp. 1–16). New York: Cambridge University Press. Mayer, R. E. (2005c). Principles for reducing extraneous processing in multimedia learning: Coherence, signaling, redundancy, spatial contiguity, and temporal contiguity principles. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning (pp. 183–200). New York: Cambridge University Press. Mayer, R. E. (2005d). Principles of multimedia learning based on social cues: Personalization, voice, and image principles. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning (pp. 201–212). New York: Cambridge University Press. Mayer, R. E. (Ed.). (2005e). The Cambridge handbook of multimedia learning. New York: Cambridge University Press. Moreno, R. (2005). Multimedia learning with animated pedagogical agents. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning (pp. 507–523). New York: Cambridge University Press.

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Paas, F., Van Gerven, P. W. M., & Tabbers, H. K. (2005). The cognitive aging principle in multimedia learning. In R. E. Mayer (Ed.), The Cambridge handbook of multimedia learning (pp. 339-354). New York: Cambridge University Press. Rieber, L. P. (2005). Multimedia learning in games, simulations, and microworlds. In R. E. Mayer (Ed.), The Cambridge handbook of multimedia learning (pp. 549-567). New York: Cambridge University Press. Rouet, J.-F., & Potelle, H. (2005). Navigational Principles in Multimedia Learning. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning (pp. 297–312). New York: Cambridge University Press. Roy, M., & Chi, M. T. H. (2005). The selfexplaination principle in multimedia learning. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning (pp. 271–286). New York: Cambridge University Press. Shapiro, A. M. (2005). The site map principle in multimedia learning. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning (pp. 313–324). New York: Cambridge University Press.

key terms And deFInItIons Active Processing Assumption: One of the three theoretical assumptions underpinning the cognitive theory of multimedia learning; proposes that humans must actively engage in cognitive processing for learning to occur. Animation and Interactivity Principles: A set instructional principles providing guidance on the design of multimedia that incorporate sophisticated animated graphics while at the same time taking into account learner interactivity (Betrancourt, 2005).

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Cognitive Aging Principle: An instructional principle focused on helping older learners by effectively managing working memory resources (Mayer, 2005b). Subscribing to the idea that working memory capability declines with age (Paas et al., 2005; Van Gerven et al., 2006), the principle suggests that some instructional material presented in multiple modalities may be more efficient than instructional material presented in a single modality. Cognitive Load Theory: A theory proposed by John Sweller and his colleagues focused on the limitations of working memory during instruction. Cognitive Theory of Multimedia Learning (CTML): A theory credited to Richard E. Mayer and his colleagues focused on best practices in the use of visual and auditory information in multimedia-based instruction. Coherence Principle: An instructional principle proposing that learners learn more deeply when extraneous information is excluded (Mayer, 2005d). Collaboration Principle: An instructional principle proposing a variety of recommendations that support collaborative learning (Jonassen et al., 2005). Dual-channels Assumption: One of the three theoretical assumptions underpinning the cognitive theory of multimedia learning; proposes that the human information processing system is composed of a separate processing channel for visual and auditory represented material. Dual-coding Theory: A theory proposed by Allan Paivio, which proposes that cognition is composed of verbal and non-verbal subsystems. Guided-discovery Principle: An instructional principle proposing that learners learn more deeply when using the strategy of directing the learner toward discovery (Jong, 2005). Limited Capacity Assumption: One of the three theoretical assumptions underpinning the cognitive theory of multimedia learning; proposes that working memory is limited in how

Multimedia Design of Assistive Technology for Those with Learning Disabilities

much information can be processed within each channel. Meaningful Learning: The remembering and deep understanding of instructional material; occurs when important aspects of the material are cognitively recognized, when the material is organized into a coherent structure, and then integrated with relevant existing knowledge (Marshall, 1996; Mayer, 2001; Mayer & Moreno, 2003; Wittrock, 1990). Modality Principle: An instructional principle proposing that presenting information in dual modalities spreads total induced load across the visual and auditory channels of working memory thereby reducing cognitive load (Low & Sweller, 2005; Sweller & Chandler, 1994; Sweller et al., 1998). Multimedia: Broadly speaking, it is the presentation of both words and pictures to a learner in a variety of ways. Multimedia Learning: The building of mental representations from the amalgamation of words and pictures, which induces the promotion of meaningful learning (Mayer, 2001, 2005b). Multimedia Principle: An instructional principle proposing that learners learn more deeply from words and pictures than from words only. Navigation Principles: A variety of instructional principles providing recommendations on the use of navigational aids which include a broad category of visual and auditory devices ranging from local cues (e.g., headings and subheadings) to global content (e.g., tables and outlines) (Rouet & Potelle, 2005). Personalization, Voice, and Image Principles: Three instructional principles providing recommendations based on social cues. According to Mayer (2005e), the personalization principle proposes that learners learn more deeply when words are presented in a conversational style as opposed to formally; the voice principle proposes that learners learn more deeply when words are spoken in a human voice void of accent, opposed to an accented voice or a machine voice; and the

image principle proposes that learners learn more deeply when a speaker’s image can be seen on screen by the learner. Pre-Training Principle: An instructional principle proposing that learners learn more deeply when they are made aware of the names and behaviors of main concepts in the lesson before they are presented with the main lesson itself (Mayer, 2005a; Mayer & Moreno, 2003). Prior Knowledge Principle: An instructional principle focused on the effects of learners’ prior knowledge on the cognitive theory of multimedia learning principles (Kalyuga, 2005). The principle stems from consistent research findings that suggest instructional principles may not benefit or adversely impact learners with high prior knowledge of the content to be learned. Redundancy Principle: An instructional principle proposing that learners learn more deeply when identical information is not presented in more than one format (Mayer, 2005a). Segmentation Principle: An instructional principle proposing that learners learn more deeply when a lesson is presented in learner-controlled segments rather than continuous units (Mayer, 2005a; Mayer & Moreno, 2003). Self-Explanation Principle: An instructional principle proposing that learners learn more deeply when engaged in self-explanation, a strategy which aids in attention and promotes meaningful learning though knowledge construction and integration activities (Roy & Chi, 2005). Signaling Principle: An instructional principle proposing that learners learn more deeply when cues are added to highlight the organization of the essential material (Mayer, 2005d). Site Map Principle: An instructional principle proposing that learners learn more deeply when appropriately structured site maps are used because these maps provide learners with overarching view of the information to be learned (Shapiro, 2005). Spatial Contiguity Principle: An instructional principle proposing that learners learn more deeply

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when related words and pictures are presented near one another than far apart (Mayer, 2005d). Temporal Contiguity Principle: An instructional principle proposing that learners learn more deeply when related animation and narration are presented concurrently rather than consecutively (Mayer, 2005d).

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Worked-out Example Principle: A stepby-step example that demonstrates how a task is performed or how to solve a problem (R. Clark et al., 2006); the principle proposes learners learn more deeply when studying worked examples than studying practice problems (Sweller, 2005a).

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Chapter 4

Investigating Assistive Technologies using Computers to Simulate Basic Curriculum for Individuals with Cognitive Impairments Carolyn Kinsell Solers Research Group, USA

AbstrAct Providing assistive technologies to cognitively impaired students, in the form of computer-based simulations, may improve the transfer of learning at a greater rate than other training media. The underlying premise for using computer-based simulations is that the cognitively impaired student is no longer the passive learner normally found in traditional classrooms. Instead, the cognitively impaired student becomes an active participant with the simulation and learning. In addition, this type of assistive technology provides the student with an opportunity for repeated exposure and practice at a speed in which the student feels comfortable. This chapter discusses the benefits of using computer-based simulations, defines the theoretical foundations that support the transfer of learning, and presents the processes that facilitate individual acquisition and refinement of knowledge and skills. It concludes with a review of the cognitive elements in the creation of mental models and schema.

IntroductIon Let me set the stage for this chapter—Thomas is a middle-school student who has been labeled as a slow learner, not only by his teachers, but by his classmates. Thomas is not slow at all of his school subjects, but reading is the hardest for him DOI: 10.4018/978-1-61520-817-3.ch004

to comprehend. He gets picked on in class and is tired of it! Thomas has been heard saying, “I just can’t keep up”! Unfortunately, Thomas is not alone. Based upon my readings, many individuals are not aware they have a learning disability and many are never diagnosed. In 1997, the Individuals with Disabilities Education Act (IDEA) helped to broaden the definition of the use of assistive technologies (AT) in the educational system to include special

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Investigating Assistive Technologies using Computers to Simulate Basic Curriculum

education “services” (Rapp, 2005). According to Families and Advocates Partner (FAPE, 2001), AT includes “any service that directly assists a child with a disability in the selection, acquisition, or use of an assistive technology device.” This act helped to open many doors for students who are considered cognitively impaired. As noted in most AT literature, AT devices are widely used in the educational system but have mainly been provided for those who are physically challenged, such as computer screen readers for the visually impaired. However, there is an entire student body with learning disabilities at the cognitive level, such as those with attention deficit disorders (Harty, Miller, Newcorn, & Halperin, 2008), that are not being targeted as candidates for AT devices (Bausch & Hasselbring, 2004). Addressing the concern of Thomas for “just not getting it” can be supported by the longitudinal study conducted by Juel (1988) which indicated that over eighty-eight percent of first graders who were noted to be poor readers were still considered poor readers as fourth graders. To further complicate the situation, you have the cycle of a student who is unlikely to fit in with their peers (especially if there are feelings of low self-esteem, like Thomas) as they continue to lag behind. Stanovick (1986) supports Juel’s (1988) findings by calling this continual lag as the “Matthew Effect”—those who excel at reading continue to do so, while those who lag behind continue to do just that. It was noted in a report generated by the National Institute of Child Health (2005) that although assistive devices for those with mental retardation and development disabilities exists, it is not always easy for the Mental Retardation and Development Disabilities (MRDD) individual or for those involved in their health care or as care-givers to gain access or to know these devices exist. Hasselbring and Bausch (2005) also indicated that it is not the lack of availability of AT services and devices that have caused this gap but the lack of knowledge by teachers about AT

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and how and when to implement. Many teachers, it appears, rely on specialists in the area of AT to implement the program, thus eliminating the immediate connection the teacher may have in the classroom to identify AT services and devices for their students. However, this gap is another topic of discussion. This chapter addresses a narrow part of AT devices, classified as computer-based simulations, that can provide the cognitively impaired a method for learning in their own context—a style of learning that could benefit a student like Thomas. Context is referring to a preferred method of learning on subjects in which the cognitively impaired individual is weak; subjects such as math, science, and reading. These contexts can use a single piece of media or hybrid approach to include animation, graphics, audio and text as a way to impart information that is in alignment with the person’s cognitive impairment. As clarification, and for the purposes of this chapter, computer-based simulations or systems, although there are many, only refer to desktop or personal computers. This topic does not address console systems, large immersive systems, or systems using haptics or head-mounted displays. In addition, the focus of the cognitively impaired examples will be on the task of reading in which the student should be able to grasp principles and derive meaning from text. The proposed chapter addresses: (a) a brief background on simulation history, its limitations, and benefits, (b) the theoretical framework fundamentals in the process of learning, (c) the mechanics of the transfer of learning that promotes knowledge/skill acquisition, and (d) a cognitive perspective.

bAckground Why computer-based simulation Simulation devices provide a means to replicate some form of reality so that an individual, or individuals, can increase their ability by applying

Investigating Assistive Technologies using Computers to Simulate Basic Curriculum

accurate actions through repeated exposure in a safe environment. Simulations have been used to facilitate learning as far back as the 17th century, such as those demonstrated by sand tables used for “war games” in the 1600s, up to the complex hybrid systems of today that involve a live, virtual, and constructive (DoD Modeling and Simulation (M&S) Glossary, 1998)) integration into a single exercise. As noted by Ausburn and Ausburn (2004) simulations are often a choice for tasks involving complex equipment or areas that are not easily accessible, or simply too dangerous to practice in real life, such as emergency room procedures, war tactic practice with improvised explosive devices, to name a few. The problem with simulations that support these types of tasks is that they are usually expensive to build, and as noted by Cloud and Rainer (1998), require built-in dynamic interactions that are limited by the model, behavior, and capabilities of the computer-based system. However, simulations that are effective as training modalities are designed with a specific objective supporting a finite set of conceivable options with a finite set of reactions (Cloud & Rainer, 1998), which is in alignment with educational purposes for those with cognitive impairments. And, with the advancement of computer processing technology of the personal computer, simulations can now be rendered, displayed, and engaged using desktop computers—which are commonly found in school classrooms. Simulations should only be considered if this type of medium will assist in the transfer of learning at a greater rate than other training media. As noted by Kritzenberger, Winkler, & Herczeg (2002) and Herczeg (2004), if training can involve the “real environment” or simulation of a real environment, learning expectations are higher. There are several conditions under which simulations are viable, which include training complex or unexpected events (not in scope with this chapter), to using simulations as a method for practice in a safe environment. For the purposes of AT, simulation should be considered for aiding

those with cognitive impairments who otherwise would not be capable of obtaining the right experience for learning in a traditional classroom environment. The benefits of using simulations often allow a person to practice and improve on their knowledge and skills in an environment that is safe (in this case without the pressure of peers) yet duplicates a specific performance context (reading). For this chapter, simulation is defined as interactive computer-based product that helps to engage the student in an active, not passive, learning mode— thereby increasing the potential for transferring knowledge and skills to the student above other types of passive media (such as lecture or book reading). The design of AT tools that target the cognitively impaired needs to consider, for example, reading level as well as reading skill as defined by the International Patient Aid Standards (IPAS) Collaboration. Although IPAS is a regulatory body for medical education, these standards should be implemented into training materials created for the use of AT—in other words, consider the target audience and their specific needs. One consideration by Herczeg (2004) defines the strategy for design of interactive user friendly computer programs for those who are challenged either cognitively or are new to computers and the technology to include special design in the areas of audio for voiceover narration matching text and illustrations; limited text at a level designed for the target audience; enhancements to support text through the use of graphics/illustrations to include animations, two-dimensional and threedimensional images, video/photographic stills; and a graphical user interface that incorporates simple navigation, easy to read icons, and an uncluttered interface. The simpler design reduces cognitive load and thus allows the student to process training content (Jibaja-Weiss, & Volk, 2007) without regard to computer issues. Without the target audience being considered in the design parameters, the cognitively impaired student,

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such as Thomas, can quickly become lost and unmotivated, thus hindering learning. There is also a learning progression student’s advance through to gain knowledge and skills that is covered under the theoretical foundation in this chapter. This is followed by the transfer of learning process concluding with how information is cognitively linked.

Theoretical Foundation The basis of this section will focus on determining how computer-based simulations can help in the actual transfer of knowledge and skills for those who are cognitively impaired. Based upon a review of learning theories, there are several that support the transfer of learning. Prior to reviewing those theories, we must note that in regards to issues on transfer of learning, Carraher and Schliemann (2002) indicate that transfer is a theory and cannot provide a solid foundation for explaining how prior knowledge and experience accounts for learning. As noted, for many years, transfer was not validated in research environments (Carraher & Schliemann, 2002). However, Simons (1999) believes that optimized transfer will occur once it is determined how to work through problems that are encountered. With that caveat, we will set out under the guise that the transfer of learning is being achieved as one progresses through the stages of the theories listed. One theory, by Rasmussen (1986), has proclaimed that learning can be divided into three cognitive categories: knowledge-based, rulebased and skill-based. Knowledge can be classified in types, yet there is no one defined set of types in use (Jorna, 2001). Examples of varying types of knowledge include, but are not limited to terms such as logical, semantic, systematic, empirical (Pecorino, 2000); explicit and tacit (Edvinsson & Malone, 1997); theoretical (Jorna, 2001); to the general to specific (Gagne, 1962), and declarative, procedural, and conditional. These types are in some way connected in the

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process in which knowledge is gained. Knowledge is integrated at all three cognitive levels of Rasmussen’s (1986) categories as one is exposed to new information. Rule-based learning combines new information-based upon responses, such as the feedback or outcomes provided. For rule-based learning to work there must be a foundation of previously acquired rules that are then built upon, in what may be referenced as logical thinking (Hong, 1998). Skill-based learning looks at the rules and procedures (specified order for accurate performance). In the case of reading, it would be the student’s ability to identify and comprehend a word, pronounce a word, and fluently read. It is these types of phonological processing inefficiencies (as noted by (O’shaughnessy & Swanson, 2007) that contribute to reading disabilities. To support Rasmussen’s (1986) theory, it is stated by Ackerman (1992) and Anderson, (1980) that individuals record environmental stimuli in order to advance among the three categories proposed by Rasmussen. If knowledge is not gained, then new information cannot be combined with a response, especially a correct response in order to formulate heuristics. Finally, correct skills cannot be built if rules and procedures cannot be followed and completed. In theory, as one is exposed to more practice, they become more proficient at a task—a task that is usually measured by a skillbased behavior. This behavior becomes automated in response to environmental stimuli that one has now become familiar. Using Thomas as our example, to improve his reading skills, he must first build upon his reading foundation with exposure and practice to reading concepts and rules. To achieve this, if Thomas was provided a computer-based simulation that contained audio and speech recognition capabilities, he could listen to the pronunciation of a word, practice pronouncing the word using speech recognition tools, and receive immediate auditory feedback. One would think that the likelihood of transfer would be greater if exposed to the

Investigating Assistive Technologies using Computers to Simulate Basic Curriculum

Figure 1. Theoretical framework and study measures

AT tool than remaining in a traditional classroom. In theory, Ackerman (1992) states there are three levels to the transfer of learning for skill acquisition: cognitive, associative and autonomous. As one understands instruction, goals and formalizes strategies (cognitive phase) they can then move on to actual practice for skill acquisition (associative phase). As they become more proficient (autonomous) at the task, it will require very little attention to perform—a task that is usually measured by a skill-based behavior. This skill-based behavior becomes automated in response to stimuli. But, as Hockey, Healey, Crawshaw, Wastell and Sauer (2003) indicate, when uncertainty in a situation increases, cognitive demand increases and the individual will fall back on knowledge-based processes (if they exist and are correct) and not

rule-based behavior. Hence, simulated devices used as AT can aid in repeated exposure to build and move forward in learning. Collectively, Ackerman’s (1992) three levels define a cognitive process that distinguishes a novice from an expert. The phases of the process build upon one another to the point that skillbased behavior eventually becomes automated in response to environmental stimuli. Figure 1, provides a graphic representation of this theoretical framework including the relationship of the three phase cognitive process, specifically focused on verbal and mechanical cognitive applications. As shown, the initial cognitive phase, typical of novice behavior, is focused on formulating concepts and developing procedural skill, such as attention to semantics for verbal information

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related to the text-based description lecture or written instruction. During the associative phase basic skill and knowledge become engrained. There is less deliberate cognitive focus and more of an emphasis on increasing speed and accuracy through practice or exposure to the learning material. With continued practice, the novice moves toward mastery, or the autonomous phase exemplified by expert behavior. In this phase actions are automatic and there is no attentional effort. Overall, the use of a computer-based simulation would afford Thomas this exposure. Based upon the example shown in Figure 1, the advancement through the cognitive phase is depicted in two areas: (a) the verbal context where information is introduced, in our example, either through lecture or written instruction, and, (b) in the mechanical phase where a student can interact with a computer-based training program. When a cognitively impaired student experiences anxiety in a classroom, there will be a high cognitive demand once in that setting, especially if that information is not being comprehended at the speed in which the rest of the students experience. With practice, transition to the associative phase of increased knowledge and skill may well begin at the point where the student grasps the concepts and increases performance, which, in the case of content knowledge (comprehension), could be shown through testing. It is anticipated that some students will not experience or may take longer to transition to the associative phase due to the limited amount of time in which they are exposed to the material or due to their more advanced cognitive challenges. Therefore, if, after testing, there is no improvement in a student’s score from the first measure to the second measure, then the student is considered to still be in the cognitive phase. To aid in a person’s ability to gain proficiency with a particular curriculum component (such as reading), computer-based simulations are being used to increase an individual’s knowledge and skill through repeated exposure and practice to a set of conditions for learning, such as using

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specific content for a particular reading ability. One key, to successful transferal, as defined in the study conducted by Sumrall and Curry (2006), is that transferal should be defined by how the knowledge and skills gained through classroom training can be synthesized and transferred into the real-world. For instance, a student who is using AT to gain knowledge and skills required of a particular subject should be able to eventually blend in with the regular classroom and be a part of the teacher-student classroom learning process. As early as the 1900’s, Thorndike studied similarities between facts and skills for transfer attainment and also researched the theory of Between-Subjects Variability, measuring if subjects converge or diverge in performance over time with training. Although there were no conclusive findings from Thorndike’s research, Ackerman (1986, 1987, 1988) found that interindividual variability of performance did decrease with practice if the task was within the abilities of the individual. Additionally, novel tasks, combined with complex tasks, required greater attention, which led to an increase in errors and a decrease in speed with which the task was accomplished. What should also be considered, is that when implementing a computer-based simulation, as an AT training device, cognitive demand will increase if the student is not familiar with using computers. This will also be a contributor to the student’s slower performance. However, as the student is able to practice, their abilities should improve based upon exposure to not only content, but to the technology. Ability determinants of performance, also known as Simplex theory, was further studied by Humphreys (as cited in Ackerman, 1988). Simplex theory suggests that as one gains practice, ability determinants of performance are changing but not in a linear fashion. Another theory, Ability-Performance Correlations (Fleishman, 1972; Fleishman, & Quaintance, 1984), ties in a cognitive assessment, such as identifying broad intellectual abilities during initial learning of a

Investigating Assistive Technologies using Computers to Simulate Basic Curriculum

simple, consistent task. Ackerman (1986) determined that there is an alignment between ability, performance, and information-processing, especially for those tasks that are inconsistent (not route processes). As a final theory, a theory that could be applied to the research of computer-based simulated training and transfer to real situations is the expectancy-value theory, as first coined by Fishbein (1967). As an individual continues to learn, they also acquire and build upon expectations resulting from actions and the consequences of those actions—which becomes the foundation for behavioral choices in the future. As for Thomas, without being identified as a student with a cognitive impairment that requires alternative learning methods, he not only remains behind in reading but becomes slower over time than those considered typical readers.

Transfer of Learning Transfer of learning is the process of applying what has been learned (carried over) to a new or similar situation, problem, or setting. It is this transfer, or carry-over, from an instructional situation to the real-world setting that is the goal of training. In essence the transfer process occurs when an individual builds requisite associations, or mental schema, that enhances storage and retrieval from memory. In effect this mental framework helps individuals learn related subject matter more rapidly (Bransford, Brown, & Cocking, 2000; Hume & Shepard, 2001; Leberman, McDonald, & Doyle, 2006; McKeachie, 2001). Transfer of learning is a key ingredient in a training environment intended to facilitate individual acquisition and refinement of knowledge and skills. As noted by Leberman, McDonald, and Doyle (2006), “transfer is the link between learning and the performance.. .” (p. 31). Although transfer has been studied for decades, it is still a process that is not completely understood (McKeachie, 2001; Salomon & Perkins, 1989).

There are key elements to transfer that are highlighted that may help to explain ‘why’ transfer would or would not take place. This discussion begins with an exploration of the three dimensions of transfer; (a) positive and negative transfer, (b) simple to complex transfer, and (c) near and far transfer.

Positive and negative transfer Positive transfer occurs when stimuli and responses are similar (Leberman et al., 2006; McKeachie, 2001; Royer, 1986). Ansburg and Shields (2003) examined the transfer of principles between different reasoning tasks. In their experiment they studied the transfer abilities of 84 subjects (students in an introduction psychology course) trying to solve six permission problems under four training conditions (combination of problem comparison with and without feedback). Those who received training on the problem comparison solved 15% more of the target problems (solutions) than those who did not receive the training, indicating positive transfer. Reinforced skills can produce a measure of success in the transference between learning and performance. In the case of the cognitively impaired student with a reading disability, such as dyslexia or a short term memory problem, may require the use of an AT tool to aid the student in learning in a different way other than a traditional classroom setting. Assistive technologies may offer a method by which the word on the screen is highlighted and through audio, is heard. If this type of interactive technology is supported, the student can speak the word aloud into a microphone for capture and computer analysis for immediate feedback. When using a computer-based simulation as an AT tool, the cognitively impaired student can practice over time to become positively qualified (tested) for their grade level; hence, allowing, Thomas to fit into the classroom with his classmates. When these reinforced reading skills, that are gained in

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the simulation and are applied to the real-world, a positive transfer is then fully realized. While positive transfer facilitates learning or performance in another situation, negative transfer means that a learned response actually hinders appropriate performance. For example, people who learn a second language typically apply patterns of speech production characteristic of their native tongue, thus giving them a foreign accent, Ormrod (as cited in Schmidt, Young, Cormier, & Hagman, 1987). The cognitively impaired student, for example, who can read but not comprehend spatial concepts, may have a difficult time with the statement, “She knew that she had to succeed at this task!” How does the cognitively impaired student comprehend “succeed”? Finally, if stimuli and responses are significantly different, neither positive nor negative transfer occurs, causing a transfer gap.

simple to complex transfer Leberman et al. (2006) define simple transfer as occurring when previous knowledge can be used in a new situation with little to no effort. This is in alignment with Salomon and Perkin’s (1989) “low road transfer” concept when tasks are performed effortlessly. The effortless transfer to related situations may be termed automatization, as noted by Salomon and Perkin’s (1989), as the “automatic triggering of well learned behavior in a new context” (p. 113). This is similar to the definition of expert behavior as noted by Ackerman (1988). Leberman et. al, (2006) define complex transfer as using the previously acquired knowledge in a new situation while seeking extended applications in which that knowledge can be used. This process of complex transfer is defined by Salomon and Perkin’s (1989) as “high road transfer”, which requires greater cognitive processing and may be detected in situations in which individuals are learning rules and principles.

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Simple transfer, for the purpose of this chapter, is illustrated when a student’s fundamental knowledge of reading comprehension in the simulated environment is easily duplicated in different real-world environments, such as being able to participate in reading in a classroom setting and then being able to transfer that reading to the real-world, such as a grocery store. This would be inclusive of Thomas as he continued to improve upon his reading knowledge and skills. Conversely, complex transfer may be illustrated when students, who can read, comprehend, and test positively on a computer-based program and can transfer their acquired knowledge to the realworld without transition to the regular classroom. Further cognitive extension would include the student’s ability to comprehend (construct meaning) and decode (recognize) more difficult words, such as “succeed” described earlier. As students seek extended applications of their reading ability to the real-world, a “complex” integration of knowledge is formed.

near and Far transfer Near transfer is posited to take place when previous knowledge is being applied to situations that are similar to what is being newly experienced and takes minimal cognitive effort (Leberman et al., 2006; McKeachie, 2001; Royer, 1986). For example, near procedural transfer, is indicated by the student that is already proficient in reading at a particular grade level (previous knowledge and skills) and then is required to read similar material at a high grade level. Far transfer is essentially the process of applying existing knowledge to a novel learning situation which takes a high cognitive effort (Leberman et al., 2006; McKeachie, 2001). This concept is suggested to occur when knowledge gained from previous experiences is put into a dissimilar situation, and the individual is expected to successfully apply this acquired knowledge.

Investigating Assistive Technologies using Computers to Simulate Basic Curriculum

Far transfer, which requires a high cognitive effort, is posited to occur if a cognitively impaired student, who is not given the simulated reading assistance but remains in the regular classroom under difficult odds, is able to acquire classroom knowledge and transfer that information to the realworld. Now that the three dimensions of transfer have been explored, the cognitive elements that aid in transfer will be examined: cognition, situativity, and automaticity. As noted in Figure 1 of Ackerman’s (1992) theory, the transfer of learning and the cognitive elements that aid in that transfer are required to becoming an expert.

experts vs novices Bransford et al. (2000), report in great detail the characteristics that distinguish experts from novices. There is strong evidence to suggest that experts interpret information differently, as well as organize, represent, and create mental models of a situation differently than that of novices (Hinds, Patterson, & Pfeffer, 2001; Novick, 1988; Schoenfeld, 1987). Experts tend to create schema from similarities that are perceived, whereas, novices are too concerned with seeing the smaller pieces, such as facts (Schoenfeld, 1987). However, as noted by Bransford et al., experts become expert through the use of cognitive thinking, starting with basic learning, moving on to the association of stimuli with responses, and finally, practicing to the point that performing a task becomes automated. Experts generally demonstrate reduced stimuli interference and reduced errors (Correll et al., 2007); just like experts, novices, can become expert through the same process. But, we cannot forget, underlying this process is the science of transfer. If transfer is not taking place, one cannot move from one cognitive element to the next, which is also supported in Ackerman’s (1988) theory and in Ackerman’s (1992) description of cognitive phases. According to Ackerman, transfer occurs in skill acquisition in the three phases, from (a) cognitive, to (b) associative, and finally

to (c) autonomous. These phases are parallel to the elements described below: (a) cognition, (b) situativity (also considered the associative phase), and (c) automaticity. The following paragraphs describe the mental process involved as to how these cognitive elements are linked with the transfer of learning.

Cognitive Elements From a cognitive perspective, and related to Ackerman’s (1992) definition of the cognitive phase, as individuals are learning, they create mental models and structures (schema) to make connections with various pieces of information. Schema originated from elements of semantic memory which contains the “knowledge of concepts, rules, principles, generalizations, skills, and metacognitive skills” (p. 7) that are based on the extraction of experience (Andre & Phye, 1986). Schema is often triggered by stimulation in our environment, which, when drawn upon can result in three types of cognitive mechanics: assimilation, accommodation, or equilibration. Lunzer (1986) provided explanations of the mechanics in the following manner: (a) assimilation takes existing schema and creates new schema that is extended to the existing situation; (b) accommodation adapts existing schema to fit a novel situation through trial-and-error or systemic inquiry or through logical inferences and creates a new schema; (c) equilibration is the balancing act of separating two conflicting schemas, known as cognitive dissonance, that have been triggered by the same stimulation and creating yet another schema. Exposure to stimulation, both new and existing, evokes these cognitive mechanics that lead to higher order thinking. In a situated learning condition, the focus is then on the development of higher order thinking (Leberman et al., 2006) in which real-world conditions are presented and aligned with existing prior knowledge. Under this type of optimized learning environment, schema building, as noted

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by Clark (2003), allow one to interpret their environment and to make sense of what is being experienced-based upon their prior knowledge. Eventually, schema or sequences are stored in long-term memory and, through practice, become over-learned and turn into automated processes (Phye, 1986). As adult learners, Clark (2003) and Huitt (2003) indicate there are three primary stages to process information: encoding, storage, and retrieval; as a learner receives new information, it is the integration with prior knowledge that results in encoding, and the creation of a new schema into long-term memory. When information is needed from recall, it is retrieved from long-term memory and aids in higher order thinking. Engaging in higher order thinking forms connections between an environment and experience, and is known as critical thinking (Desse, 2001), problem-solving, (Price & Driscoll, 1997) and reasoning (McKeachie, 2001). It has also been noted that higher levels of cognitive processes require higher demands on cognitive skills, and therefore, a novice may be ill-equipped, lacking these skills (Kuhn, Black, Keselman, & Kaplan, 2000). As with cognitively impaired students, they are not afforded the opportunity to grasp concepts or knowledge within a regular classroom. In these circumstances this is when simulations can allow practice, and at length, thereby helping to form connections regarding the concept at hand. However, at the onset, when a cognitively impaired student begins using AT (such as simulations), they may experience a higher demand on their cognitive resources by the mere fact of being exposed to the AT tool itself. This in turn could produce higher adrenaline that may interfere with their initial learning. These students may require time to become familiar with the tool, the computer, and the navigation within the simulation. Once these factors are overcome, the progression through learning of the content can begin. Situativity, which is related to Ackerman’s (1992) definition of the associative phase, is part

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of the higher level cognitive perspective when one participates in regular patterns of activities, which is characterized as communities of practice (Greeno, 1998). In addition, with cognitively impaired students, there may be little to no existing schema to draw from to aid in a successful outcome. However, over time, if enough practice could be afforded, it would be expected to see some form of improvement. Finally, the higher order thinking involved with situativity eventually encompasses automaticity, characteristics of an expert (Leberman et al., 2006). Automoticity, which is related to Ackerman’s (1992) definition of the autonomous phase, is an unconscious process that experts tend to use based on a highly organized structure of chunked information, stored as schemas, that was developed over years of experience, (Bransford et al., 2000; Salomon & Perkins, 1989). Automaticity involves less routine cognitive processing (Ferguson, 2000) and is individual to each person. Automaticity is created either through (a) intentional goal-directed processes that require an act, or (b) preconscious processing that only requires the environment as a trigger (Bargh & Chartrand, 1999). However, tasks that are not consistent in nature and that have many possibilities with various responses are not as easy to learn (Halff, Hollan, & Hutchins, 1986; Tubau, Hommel, & Lapez-Moliner, 2007). To increase the likelihood of automaticity, repeatable actions and higher-order thinking need to be infused into the learning situation. The more we learn about AT, transfer of learning, simulated environments, and real-world problems and outcomes, the more adept the training industry will become at designing training systems that get to the heart of what is now missing; a learning continuum for students of all learning capabilities. As for our hypothetical example, Thomas’s advancement in reading could be dependent upon two things, (a) the identification of his cognitive condition, and (b) the implementation of AT services and devices.

Investigating Assistive Technologies using Computers to Simulate Basic Curriculum

concLusIon The AT services and devices program has been proven to benefit the physically challenged student. However, there is still work to be done in the school systems in identifying students who have a cognitive impairment that inhibits learning. Based upon the theories, the transfer of learning concepts, and the cognitive elements presented in this chapter, there is still the potential for learning improvement for those cognitively impaired students who receive an AT device designed for their level of learning. Additional studies should be conducted to determine if a computer-based simulation designed as an AT device for the cognitively impaired student results in improved transfer of learning not only to the classroom but to the real-world.

reFerences Ackerman, P. L. (1986). Individual differences in information processing: An investigation of intellectual abilities and task performance during practice. Intelligence, 10(2), 101–139. doi:10.1016/0160-2896(86)90010-3 Ackerman, P. L. (1987). Individual differences in skill learning: An integration of psychometric and information processing perspectives. Psychological Bulletin, 101(1), 3–27. doi:10.1037/00332909.102.1.3 Ackerman, P. L. (1988). Determinants of individual differences during skill acquisition: Cognitive abilities and information processing. Journal of Experimental Psychology. General, 117(3), 288–318. doi:10.1037/0096-3445.117.3.288 Ackerman, P. L. (1992). Predicting individual differences in complex skill acquisition: Dynamics of ability determinants. The Journal of Applied Psychology, 77(5), 598–614. doi:10.1037/00219010.77.5.598

Anderson, J. R. (1980). Cognitive psychology and its implications. San Francisco: Freeman. Andre, T., & Phye, G. D. (1986). Cognition, learning, and education. In Phye, G. D., & Andre, T. (Eds.), Cogntivie classroom learning: Understanding, thinking, and problem solving. Orlando, FL: Academic Press. Ansburg, P. I., & Shields, L. (2003). Training overcomes reasoning schema effects and promotes transfer. The Psychological Record, 53(2), 231–242. Ausburn, L. J., & Ausburn, F. B. (2004). Desktop virtual reality: A powerful new technology for teaching and research in industrial teacher education. Journal of Industrial Teacher Education, 41(4), 33–58. Bargh, J. A., & Chartrand, T. L. (1999). The unbearable automaticity of being. The American Psychologist, 54(7), 462–479. doi:10.1037/0003066X.54.7.462 Bausch, M. E., & Hasselbring, T. S. (2004). Assistive technology: Are the necessary skills and knowledge being developed at the preservice and inservice levels? Teacher Education and Special Education: The Journal of the Teacher Education Division of the Council for Exceptional Children, 27(2), 97–104. doi:10.1177/088840640402700202 Bransford, J. D., Brown, A. L., & Cocking, R. R. (2000). How People Learn: Brain, Mind, Experience, and School. Expanded Ed.: NationalAcademy of Sciences - National Research Council, Washington D. C. Commission on Behavioral and Social Sciences and Education. Carraher, D., & Schliemann, A. (2002). The transfer dilemma. Journal of the Learning Sciences, 11, 1–24. doi:10.1207/S15327809JLS1101_1 Clark, R. (2003). Building Expertise: Cognitive Methods for Training and Performance Improvement. Silver Springs, MD: International Society for Performance Improvement.

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Cloud, D. J., & Rainer, L. B. (1998). Applied modeling and simulation: An integrated approach to development and operation. New York: McGraw Hill. Correll, J., Park, B., Judd, C. M., Wittenbrink, B., Sadler, M. S., & Keesee, T. (2007). Across the thin blue line: Police officers and racial bias in the decision to shoot. Journal of Personality and Social Psychology, 92(6), 1006–1023. doi:10.1037/00223514.92.6.1006 Desse, J. (2001). The state of education and the double transfer of learning paradox. In Haskell, R. E. (Ed.), Transfer of learning: Cognition, instruction, and reasoning (pp. 3–21). San Diego: Academic Press. DoD Modeling and Simulation (M&S) Glossary. (1998). Under Secretary of Defense for Acquisition Technology. Edvinsson, L., & Malone, M. S. (1997). Intellecutal Captial: Realizing your Company’s True Value by Finding its Hdden Brainpower. New York: Harper Business. FAPE. (2001). 1997 Individuals with disabilities education act amendments increase access to technology for students. Families and Advocates Partnership for Education (FAPE) Retrieved August 1, 2009, from http://www.fape.org/pubs/ FAPE-13.pdf Ferguson, C. J. (2000). Free will: An automatic response. The American Psychologist, 55(7), 762–763. doi:10.1037/0003-066X.55.7.762 Fishbein, M. (Ed.). (1967). Attitude and the Prediction of Behaviour. New York: Wiley. Fleishman, E. A. (1972). On the relation between abilities, learning and human performance. The American Psychologist, 27(11), 1017–1032. doi:10.1037/h0033881 Fleishman, E. A., & Quaintance, M. K. (1984). Taxonomies of human performance. Orlando, FL: Academic Press.

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Gagne, R. (1962). The acquisition of knowledge. Psychological Review, 69(4), 355–365. doi:10.1037/h0042650 Greeno, J. G. (1998). The situativity of knowing, learning, and research. The American Psychologist, 53(1), 5–26. doi:10.1037/0003-066X.53.1.5 Halff, H. M., Hollan, J. D., & Hutchins, E. L. (1986). Cognitive science and military training. The American Psychologist, 41(10), 1131–1139. doi:10.1037/0003-066X.41.10.1131 Harty, S. C., Miller, C. J., Newcorn, J. H., & Halperin, J. M. (2008). Adolescents with childhood ADHD and disruptive behavior disorders: Aggression, anger, and hostility. Child Psychiatry and Human Development, (40): 85–97. Hasselbring, T. S., & Bausch, M. E. (2005). Assistive technologies for reading. Educational Leadership, 63(4), 72–75. Herczeg, M. (2004). Experience design for computer-based learning systems: Learning with engagement and emotions. Paper presented at the ED-MEDIA 2004 World Conference on Educational Multimedia, Hypermedia and Telecommunications. Hinds, P. J., Patterson, M., & Pfeffer, J. (2001). Bothered by abstraction: The effect of expertise on knowledge transfer and subsequent novice performance. The Journal of Applied Psychology, 86(6), 1232–1243. doi:10.1037/0021-9010.86.6.1232 Hockey, G. R., Healey, A., Crawshaw, M., Wastell, D. G., & Sauer, J. (2003). Cognitive demands of collision avoidance in simulated ship control. Human Factors, 45(2), 252–265. doi:10.1518/ hfes.45.2.252.27240 Hong, F. T. (1998). Picture-Based vs. Rule-Based Learning. Department of Physiology, Wayne State University. Huitt, W. (2003). The information processing approach to cognition. Valdosta State University. Retrieved July 14, 2007, from http://chiron.valdosta. edu/whuitt/col/cogsys/infoproc.html

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Hume, D., & Shepard, R. N. (2001). Introduction. In Haskell, R. E. (Ed.), Transfer of learning: Cognition, instruction, and reasoning (pp. xiii–xx). San Diego: Academic Press. Jibaja-Weiss, M. L., & Volk, R. J. (2007). Utilizing computerized entertainment education in the development of decision aids for lower literate and naïve computer users. Journal of Health Communication, 12(7), 681–697. doi:10.1080/10810730701624356 Jorna, R. (2001). Knowledge types and organizational forms in knowledge managment. ISMICK. Juel, C. (1988). Learning to Read and Write: A Longitudinal Study of 54 Children from First through Fourth Grades. Journal of Educational Psychology, 80(4), 437–447. doi:10.1037/00220663.80.4.437 Kritzenberger, H., Winkler, T., & Herczeg, M. (2002). Mixed reality environments as collaborative and constructive learning spaces for elementary school children. Paper presented at the ED-Media 2002 World Conference on Educational Multimedia, Hypermedia and Telecommunications, Denver, Colorado. Kuhn, D., Black, J., Keselman, A., & Kaplan, D. (2000). The development of cognitive skills to support inquiry learning. Cognition and Instruction, 18(4), 495–523. doi:10.1207/S1532690XCI1804_3 Leberman, S., McDonald, L., & Doyle, S. (2006). The transfer of learning: Participants’ perspectives of adult education and training. Burlington, VT: Gower. Lunzer, E. (1986). Cognitive development: Learning and the mechanisms of change. In Phye, G. D., & Andre, T. (Eds.), Cogntivie classroom learning: Understanding, thinking, and problem solving. Orlando, FL: Academic Press.

McKeachie, W. (2001). Transfer of learning: What it is and why it’s important. In Haskell, R. E. (Ed.), Transfer of learning: Cognition, instruction, and reasoning (pp. 23–39). San Diego: Academic Press. National Institute of Child Development. (2005). Mental retardation and developmental disabilities (MRDD) branch. NICHD Report to the NACHHD Council: National Institute of Child Health and Human Development. NICHD. Novick, L. R. (1988). Analogical transfer, problem similarity, and expertise. Journal of Experimental Psychology. Learning, Memory, and Cognition, 14(3), 510–520. doi:10.1037/02787393.14.3.510 O’shaughnessy, T. E., & Swanson, H. L. (2007). A comparison of two reading interventions for children with reading disabilities. Journal of Learning Disabilities, 33(3), 257–277. doi:10.1177/002221940003300304 Pecorino, P. A. (2000). Chapter 5: Epistemology. Types of knowledge. In. Phye, G. D. (1986). Practice and skilled classroom performance. In Phye, G. D., & Andre, T. (Eds.), Cognitive classroom learning: Understanding, thinking, and problem solving (pp. 141–168). Orlando, FL: Academic Press. Price, E. A., & Driscoll, M. P. (1997). An inquiry into the spontaneous transfer of problem-solving skill. Contemporary Educational Psychology, 22(4), 472–494. doi:10.1006/ceps.1997.0948 Rapp, W. H. (2005). Using assistive technology with students with exceptional learning needs: When does an aid become a crutch? Reading & Writing Quarterly, 21(2), 193–196. doi:10.1080/10573560590915996 Rasmussen, J. (1986). Information processing and human-machine interaction: An approach to cognitive engineering. New York: Elsevier.

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Royer, J. M. (1986). Designing instruction to produce understanding: An approach based on cognitive theory. In Phye, G. D., & Andre, T. (Eds.), Cognitive classroom learning: Understanding, thinking, and problem solving. Orlando, FL: Academic Press. Salomon, G., & Perkins, D. N. (1989). Rocky roads to transfer: Rethinking mechanisms of a neglected phenomenon. Educational Psychologist, 24(2), 113–142. doi:10.1207/s15326985ep2402_1 Schmidt, R. A., Young, D. E., Cormier, S. M., & Hagman, J. D. (1987). Transfer of movement control in motor skill learning. In Transfer of learning: Contemporary research and applications (pp. 47–79). San Diego, CA: Academic Press. Schoenfeld, A. H. (1987). Confessions of an accidental theorist. For the Learning of Mathematics--An International Journal of Mathematics Education, 7(1), 30. Simons, P. R. J. (1999). Transfer of learning: Paradoxes for learners. International Journal of Educational Research, 31, 577–589. doi:10.1016/ S0883-0355(99)00025-7 Smurall, W. J., & Curry, K. (2006). Teaching for transferal. Science Scope, 14(17). Stanovick, K. E. (1986). Matthew effects in reading: Some consequences of individual differences in the acquisition of literacy. Reading Research Quarterly, 21, 360–407. doi:10.1598/ RRQ.21.4.1

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Tubau, E., Hommel, B., & Lapez-Moliner, J. (2007). Modes of executive control in sequence learning: From stimulus-based to plan-based control. Journal of Experimental Psychology. General, 136(1), 43–63. doi:10.1037/00963445.136.1.43

key terms And deFInItIons Cognitive Impairment: Processing and generation of new information is hindered, but not at obvious or observable levels. Computer-Based Simulations: A multimedia, interactive method for learning using a desktop or personal computer that combines two-dimensional or three-dimensional images with animation, audio, voice recognition tools, and/or video. Theoretical Framework: A progression of learning from a cognitive, to associative, to an autonomous phase using knowledge- and skillsbased on exposure and practice to learning situations over time. Transfer of Learning: The ability to relate prior schema learned in the classroom to new situations outside the learning environment. Schema: Mental models which are developed over time due to exposure to various learning situations help to make connections between new knowledge and existing prior knowledge stored in long-term memory.

Section 2

The Internet, Media, and Cognitive Loads In the first part of this handbook, we emphasized a common quandary found in education—the technology-centered approach typically trumps that of a learner-centered one—which has left the better half of the 20th century littered with examples as to why this does not work. Implementing the latest advancements in cutting-edge technology are not enough, but instead, such knowledge must be coupled with an understanding of the human information processing system. In the first part of this handbook, we focused on theoretical scaffolding, presenting the importance of managing cognitive load and best practices in the design of multimedia-based instruction and its applicability in assisting those with learning disabilities. We also introduced the use of simulation-based instruction, and the significant contributions it has towards assisting those with learning disabilities. In the second part of this handbook, we continue this line of thinking and elaborate further on the use of 3D virtual environments. These environments have been made popular in recent years by advancements in software and computing power, and while typically seen as a form of entertainment and a means for social networking by many, these environments, such as SecondLife, have also lend themselves to businesses as well as educational institutions, because of the potential limitless possibilities such virtual environments may bring. These environments may very well hold significant opportunities to assist those who are challenged by traditional classroom instruction and interaction. Overall, we continue to merge cognitive architecture with assistive technologies and describe how this marriage can aid those with special needs. We accomplish this through the presentation of three chapters. In the fifth chapter, we present findings in the development of a 3D virtual learning environment to help develop and practice social competence (i.e., social interaction and social learning) for individuals with Autism Spectrum Disorders through the iSocial project. The goal of the project is for youth to transfer lessons learned in a virtual environment to the real world. In the sixth chapter, we present the nature of treating disorders through the aid of virtual reality in a rehabilitative focus. Highlighted are the clinical, social, and technological issues in the hope of gaining a better understanding of the coupling between cognitive architectures and rehabilitation. While finally, in the seventh chapter, we present advancements in information and communication technologies and their impact on inclusive education and how such technologies can assist those with special needs. Specifically, hypermedia learning environments as an assistive technology are discussed along with the disorientation and cognitive load problems faced by learners in navigating such environments.

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Chapter 5

Social Orthotics for Youth with ASD to Learn in a Collaborative 3D VLE James Laffey University of Missouri, USA Janine Stichter University of Missouri, USA Matthew Schmidt University of Missouri, USA

AbstrAct Online systems, especially 3D virtual environments, hold great potential to enrich and expand learning opportunities for those who are challenged by traditional modes of instruction and interaction. In the process of developing a 3D Virtual Learning Environment to support the development and practice of social competence for individuals with Autism Spectrum Disorders, the iSocial project explored and advanced ideas for social orthotics in virtual environments. By social orthotics the authors mean structures in the environment that overcome barriers to facilitate social interaction and social learning. The vision of social orthotics in a 3D world is to be both assistive and adaptive for appropriate social behavior when the student, peers and guide are represented by avatars in a 3D virtual world designed to support learning and development. This chapter describes the formulation of social orthotics for avatar orientation and conversational turn-taking and describes experiences and lessons from early tests of prototype orthotics.

IntroductIon A multi-disciplinary team including special educators and learning technologist at the University of Missouri are developing a 3-Dimensional Virtual DOI: 10.4018/978-1-61520-817-3.ch005

Learning Environment (3D-VLE) to assist youth with autism spectrum disorders (ASD) in their development of targeted social competencies. The project, iSocial (http://isocial.rnet.missouri.edu/), seeks to take a successful face-to-face program delivered over a 10-week period by a trained guide to groups of 4 to 5 youth and deliver the program online via a

Copyright © 2010, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

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3D Internet-based virtual world (Laffey, Schmidt, Stichter, Schmidt, Oprean, Herzog, & Babiuch, in press; Laffey, Schmidt, Stichter, Schmidt, & Goggins, 2009; Schmidt, Laffey, Stichter, Goggins, & Schmidt, 2008). A key goal of building an online program is to increase access to the program. To engage in iSocial the youth must work cooperatively in the online environment, including following directions from an online guide and collaborate on many online learning activities with other youth with ASD. While a key goal of iSocial is for the youth to transfer lessons and competencies learned in the online environment to their traditional face-toface settings with parents, teachers, friends and classmates, in planning for iSocial, the developers recognized a need for design features to help the youth interact and be social during the online learning processes. Youth who do not readily take turns, attend to social cues and expectations nor cooperate effectively in face-to-face settings are also likely to struggle with social practices in the online setting. The challenge, of course, is to assist youth with ASD, who have traditional social performance deficiencies, to be social while learning social performance competencies. This is a key feature of the face-to-face curriculum and an essential requirement in the translation to the online environment. We articulated a concept of social orthotics to represent types of structures that might be needed to facilitate social interaction and social learning in iSocial. The vision of social orthotics in a 3D VLE is to be both assistive and adaptive for appropriate social behavior when the student, peers and guide are represented by avatars in a 3D virtual world designed to support learning and development. This chapter describes how we are thinking about and developing early implementations of social orthotics. The chapter also shares what we are learning about these ideas and their potential to support appropriate online behavior. Additionally we discuss some key challenges for design and development of social orthotics.

bAckground Literature As a collaboration of researchers in the field of Special Education with researchers in the field of Learning Technologies we consider the role of technology in assisting social performance as an integration of both traditions. In special education, assistive technology refers to devices that increase, maintain, or improve capabilities of individuals with disabilities for those performances. Learning technologies are generally seen as a means for augmenting human capabilities. Donald Norman, a noted human interface guru, wrote a book about “Things that make us Smart” (Norman, 1994), articulating the view that the design quality of devices impacts human capability both for good and for worse. These two world views of technology assisting individuals to overcome disabilities and augmenting individuals to enhance their abilities combine to sensitize the design of iSocial to the general impact of all design decisions on human capability and the specific potential of a class of devices that may shape targeted social behavior. Researchers in the field of assistive technology for individuals with ASD pay particular attention to communication functions and have asserted the value of augmenting language input through visual devices (Hodgdon, 1995; Quill, 1997; Mirenda, 2001). Mirenda’s (2001) review of literature from prior to 1999 showed the potential of visual cues to support comprehension of speech, managing activity and choice making. Methods to stimulate language production with symbols and augment language by using voice generation devices also showed some evidence of support for communication. Two conclusions seem apparent from the review: (a) communication-related behaviors can be augmented and visual cues seem especially promising for individuals with ASD and (b) the benefits of any assistive technology is highly dependent on the fit between the form of the technology intervention and the individual’s needs

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and capabilities. The importance of the fit between technology and individual needs has been further supported by research in the promising domain of using robots to foster communication practice for youth with ASD. Examinations of robots as assistive technology (Robins, Dautenhahn, te Boekhorst & Billard, 2004) confirm the need to fit the technology to the individual characteristics of the child. More recently (Mirenda, 2009), the evidence for assistive technology for communication and social skills has increased and the forms of devices have become more sophisticated and integrated. Another review and effort to guide the application of assistive technology (Pierangelo & Giulani, 2008) emphasizes matching technologies (both low and high technology) with the needs of the child and attending to developmental progression in the use of forms of the technology. In addressing the use of assistive technologies for the development of social skills, Pierangelo and Giulani (2008) recommend low-tech strategies such as reading social stories, using comic strip conversations and having social scripts. Numerous software systems have been developed as high-tech ways to enhance these low-tech strategies. Some researchers in the field of assistive technology for youth with ASD have also examined the capability of youth with ASD to work and learn in a 3D VLE as a means for developing social skills and competencies. These studies have demonstrated that participants with ASD can use and interpret VLEs successfully and use VLEs to learn simple social skills (Cobb, S., Beardon, L., Eastgate, R., Glover, T., Kerr, S., Neale, H., Parsons, S., Benford, S., Hopkins, E., Mitchell, P., Reynard, G., & Wilson J., 2002; Mitchell, Parsons, & Leonard, 2007). However, this prior work has addressed the teaching of skills but not structures and mechanisms (orthotics) for actually being social in a 3D environment. For example Parsons, Leonard, and Mitchell (2006) use a café scene to teach skills of finding an appropriate seat, but the scene is a single-user context and

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only implements a set of rules for finding a seat, rather than possibly providing opportunities for greeting others, leaving others, or practicing how to act in a café with peers taking on other roles in the scene. The majority of 3D VLE prior work has viewed VLEs as an experience of a single-user sitting at a computer to take on a specific task with a physically-present adult assistant. iSocial, however, seeks to immerse the youth in a VLE for multiple and integrated experiences as well as support these youth as they learn collaboratively with and from other members within the VLE. Since Douglas Engelbart wrote the seminal work on augmenting human intellect with technology (Engelbart, 1962) the idea of technology assisting or augmenting human capabilities has been a core principle in the field of designing computer systems for learning and performance. In this sense, the notion of assistive technology is much broader and general than in the field of special education and is viewed as amplifying human capacity rather than as compensating for disabilities. However, in the practice of design, the blending of affordances and constraints to customize support for unique forms of human capability is common to both special education and more general design work. Two tracks of work in computer systems design for learning and performance seem appropriate to mention as foundations for our conceptualization of social orthotics— performance support and scaffolding. Performance support has been a design approach since the late 1980’s and early 1990’s in response to the growing presence of computers in the workplace and the need to improve productivity. We do not often speak of this approach now as a separate form of design because it has generally been incorporated into most approaches to the design of modern computer systems. Tax preparation software, such as TurboTax by Intuit, represents a canonical example of the application of performance support in that it is meant to act as a butler assisting with tasks that the user knows how to perform and acts as a coach for tasks un-

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familiar or challenging to the user (Laffey, 1995). Scaffolding is the other construct from learning technology that shapes our thinking about social orthotics. Collins, Brown, and Newman (1989) characterized instructional scaffolding as a process where an expert performs part of a complex task for which a learner is unprepared, thereby allowing the learner to engage in work that would normally be outside his/her grasp. Scaffolding can take the form of a suggestion or other discourse based assistance or specialized devices such as the short skis used in teaching downhill skiing (Burton, Brown, & Fischer, 1984). Explicit forms of instructional scaffolding—those delivered primarily through interaction with an advisor or expert—represent only one kind of scaffolding. Procedure and task facilitation, realized through physical and structural supports that are implicit to the design of an interface, are also forms of scaffolding. This extended notion of scaffolding (Quintana, C., Reiser, B. J., Davis, E. A., Krajcik, J., Fretz, E., Duncan, R. G., Kyza, E., Edelson, D., & Soloway, E., 2004; Hmelo-Silver, 2006; Lin, 2004), which includes both advisor-like expertise delivered via agents in the 3D VLE and structures designed to constrain and invite appropriate behavior, are a basis for conceptualizing and designing social orthotics.

early Field experience for isocial A unit on conversational turn-taking, from the five-unit SCI-CBI curriculum (Stichter, Herzog, Visovsky, Schmidt, Randolph, Schultz, & Gage, in review; Stichter, Randolph, Gage & Schmidt, 2007) was developed for delivery in the iSocial VLE prior to our implementation of explicit devices for social orthotics. Four youth in pairs of two (boys on the autism spectrum, ages 11-14) undertook the lesson facilitated by an online guide. For each pair, the unit consisted of two training sessions of one hour and then four one-hour lessons delivered in a two-week period. Our findings for system usage show iSocial to be easy to use and

enjoyable. However we also found many challenges for social interaction and specifically for executing appropriate turn-taking behavior and the coordination of activity. During the lessons there were numerous instances when youth would interrupt each other, fail to initiate conversation when needed and fail to respond appropriately. The online guide had difficulty facilitating these exchanges as she could only see avatar behavior and it took time to determine if the youth were participating appropriately, inappropriately, or were just not attending. The online guide also had trouble coordinating activity in the VLE, due to a lack of traditional control mechanisms, such as nonverbal cues. For example, in the classroom, the guide notices subtle cues from students as they are starting to drift from instruction, and she can use those cues to start processes to bring the student back to attention. However, when learners engaged in undesirable behavior in their physical environment, such as gazing out the window or excessively clicking mouse buttons or keyboard keys, the online guide often did not know these behaviors were occurring and could only try verbal prompts to keep the youth on track. In addition, the youth were both curious about the environment and uncertain about how to move effectively. As a result, learners often were missing in action, sometimes out exploring and sometimes trapped in walls or other dead ends in the iSocial environment. Such issues of navigation and inappropriate behavior were distracting, which typically slowed the rate of instruction and impeded the flow of the lessons. Consequentially, the online guide was unable to address the same amount of instruction in one-hour in the VLE as is typical in a face-to-face class, causing instruction to be sometimes rushed.

socIAL ortHotIcs In our early conceptualization of iSocial, we envisioned devices for mediating the learning

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Figure 1. A conversation console as an early prototype of social orthotics

activities in ways that provided scaffolding for the youth in the learning process. For example, Figure 1 shows an early prototype of how a conversation console could be used to both constrain and support turn-taking and facilitate empathy during various interactive exercises that made up the curriculum. This form of scaffolding was directly linked to the instructional objectives of the curriculum, such as to support appropriate turn-taking and trying to understand what others might be thinking or feeling. You might imagine the conversation console operating like an expert coach or advisor helping the youth make sense of the situation and suggesting attention to certain aspects of the situation. Following from our review of the literature, which showed the potential of visual representations and the need for tailored assistance, we envisioned varying the implementation and intensity of the visual representation so as to customize the mediation to the individual youth’s needs.

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Based on our early field tests of the turn-taking unit, the need for support for core aspects of social engagement and interaction became apparent. We still envision scaffolding for learning such as the conversation console, but we turned our immediate attention to devices that might help keep students together, focused, and provide errorless learning (something not available in natural contexts) to better scaffold instruction and hence avoid initial excessive and distracting behavioral errors such as interruptions. Our primary focus in developing social orthotics was to assist the youth in being social and to support the online guide, whose role it was to manage youth behavior and facilitate learning in the 3D VLE. Since the nature of a computing environment affords the potential to vary the implementation and intensity of the implementation, our view was to customize orthotics to the individual youth’s needs, present and future, and to provide the orthotic in the most

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Figure 2. Conceptual diagram of social orthotics for iSocial: Round 2

appropriate way for the youth, social competency development level and activity.

conceptual Framework for social orthotics in isocial Social orthotics are pieces of software tools and customizations to the virtual environment which are integrated into the interface and virtual world in such a way as to support social interaction and mediate acquisition of social competency from coaching, on-demand assistance and just-in-time feedback. A goal of these orthotics is to enable learners to engage in effective social practice for which they do not have full competence. Figure 2 provides schemata for how these tools pair pedagogical strategies for teaching social

competency with software mechanisms geared towards facilitating pro-social behavior. For our second round of prototyping and field testing to be undertaken in 2009 and early 2010, we are focused on two essential skills for basic social practice: (a) avoiding interruptions (iTalk) and (b) exhibiting proper adjacency, distance and orientation behavior (iGroup). All activity in a 3D VLE is mediated by designed spaces and devices. Since it is the intention of the design work to make all elements work toward the desired ends of competent social practice within the system and practice for social competency beyond the system, it is important to distinguish between three major design aspects related to assisting social practice. The three design elements related to the role of social orthotics are:

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Figure 3. An example of a “virtual” physical social orthotic

general environment, physical devices for targeted behavior and dynamic agents. We will illustrate these three design approaches by describing work completed from round one to round two of the design in addressing the problem of youth getting lost or wandering in the space, thus delaying the progress of lessons. As an approach to general environment design we went from an environment that had numerous rooms related to specific elements of the curriculum to a more open layout. In this new environment it was easier for the online guide to see where the students were, and it was less likely that students would get lost in rooms or stuck in walls. An example of physical devices for targeted behavior can be seen in Figure 3. Here the circle indicates a space for the youth to enter which in turn changes their perspective from a third-person view of themselves and others in the scene to a point of view perspective of the materials of the lesson. Entering the circle can also have other properties such as not allowing the user to leave until the guide permits it as well as managing

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orientation to other members in the circle and focus on aspects in the user view. An example of an agent, for being in the appropriate place and keeping an appropriate focus, will be described in the next sections, but it includes monitoring user behavior and providing feedback and guidance. While all three of these approaches are meant to be “assistive” for social practice, we consider the latter two to be social orthotics and for the purposes of this chapter, we will focus solely on agent-based forms of orthotics.

igroup Avatar Orientation, Adjacency and Distance A key problem observed during the field test was the difficulty of having the target youth learn in a group when he or she struggled with rudimentary behaviors and orientations necessary for group activity, such as facing another youth and not invading another’s space. In the case of our

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field test the group was limited to two youth and an online guide. We anticipate groups of 5 to 6 youth with a guide, so mechanisms are needed for helping users manage the non-verbal aspects of group interaction. iGroup is a software-based means to reinforce desired adjacency, distance and orientation behavior and constrain undesirable behavior. Orientation refers to the directionality of the user’s avatar towards a speaker. For instance, a user having his or her avatar’s back turned to a speaker is considered undesirable behavior as opposed to desirable behavior of looking at the speaker. Adjacency refers to how close users’ avatars are to one another. For example, a user having his or her avatar directly in front of the speaker’s avatar or touching the speaker’s avatar is considered undesirable behavior as opposed to having the avatar approximately within one virtual meter of the speaker (desirable behavior). Distance refers to the area between users’ avatars. For example, a user having his or her avatar across the room from the speaker’s avatar is considered undesirable behavior as opposed to having the avatar within three or four virtual meters of the speaker (desirable behavior). The iGroup tool provides users with mechanisms that constrain inappropriate adjacency, distance and orientation behavior and encourage users to follow the rules for appropriate adjacency, distance and orientation when holding a conversation. iGroup monitors users’ avatar adjacency, distance and orientation in respect to other users, notifies users when they are displaying inappropriate adjacency, distance and orientation behaviors and constrains their ability to continue these behaviors. In addition, iGroup provides coaching and assistance by sending notifications to users such as, “Someone is speaking, but my back is turned. I should turn around and face the speaker or else they may think that I am not interested or I am being rude.” Finally, iGroup can be fit to users’ differing abilities for managing their avatars’ orientation, adjacency and distance. As an example of fitting the functionality to the

individual needs of the youth, one child might be provided text messages reminding him of more appropriate behavior while another child with a record of inappropriate behavior might be “virtually” physically restrained from moving outside the circle or have a specific orientation imposed on his avatar in response to a series of undesirable behaviors. Given a conversation between users with the iGroup tool enabled, inappropriate adjacency, distance or orientation behaviors during a conversation will be identified and the user exhibiting these behaviors will be provided with a notification. From the user’s perspective, iGroup sends notifications to the user’s screen when undesirable adjacency, distance, or orientation behaviors are detected. From the guide’s or administrator’s perspective, iGroup is configured using a settings panel which can be selected from the iSocial client window’s menu.

Use Case In the case described here, the guide has sets the time before notification for orientation, adjacency. and distance to three seconds. If one user remained too close to another user for three seconds, that user received a notification. If a user began speaking and another user was far away and did move to within an appropriate distance of the speaker within three seconds, that user received a notification. If a user began speaking and another user’s avatar was not oriented towards the speaker and/or did not turn his or her avatar to face the speaker within three seconds, that user received a notification. In our example, Joe and Ryan were present in a virtual space, were approximately eight virtual meters apart and were facing away from one another. Joe began speaking to Ryan. Ryan listened to Joe, but did not turn to face him or move any closer to him. Joe continued speaking for more than three seconds. Ryan then received two notifications: One prompting him to orient

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Figure 4. Illustration of an iGroup notification prompting re-orientation

his avatar towards Joe (see Figure 4) and the other prompting him to move closer to Joe. After the notification Ryan then moved very close to Joe and properly oriented his avatar. Because Ryan was too close to Joe, he received a notification after three seconds elapsed. Because his avatar was correctly oriented to Joe, Ryan did not receive a second notification regarding orientation. Over time Ryan improved his orientation and adjacency behavior and received fewer and fewer notifications related to these behaviors. The iGroup software detected this change in behavior and decreased the frequency of notifications that Ryan received for these behaviors. However, Ryan continued to move away from the speaker and received notifications related to distance. The iGroup software detected this and increased the frequency of notifications that Ryan received regarding his distance behavior.

Settings Panel The guide or administrator is able to configure iGroup using a settings panel. This settings panel

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is used to set the orientation settings, adjacency settings and distance settings, as well as to set notification messages customized to the pedagogical levels of learning for the youth. Figure 5 shows the options for setting orientation controls. The orientation settings make it possible to set the amount of time that can elapse when a user exhibits undesirable orientation behavior before a notification is sent. Acquisition, maintenance and fluency are pedagogical levels which will be discussed in the section on pedagogical strategies, but the mock-up in Figure 4 shows that they have default duration settings which can be overridden manually. The notifications area toggles notifications on/off, sets the duration that the notification is displayed on the client’s screen and sets custom notification messages. In practice, the iGroup tool determines if others’ avatars are appropriately or inappropriately oriented to the speaker (see Figure 6). The software allows the pre-determined “Notification Duration” setting time to elapse prior to sending a notification to any users exhibiting inappropriate orientation behavior. This delay provides users the chance to appropriately orient

Social Orthotics for Youth with ASD to Learn in a Collaborative 3D VLE

Figure 5. Mock-up of the iGroup settings panel

Figure 6. Top-down view of avatars exhibiting inappropriate orientation behavior (left) and appropriate orientation behavior (right)

their avatar without receiving a reminder notification from the system. For example, if a user hears someone speaking and turns to face the speaker within the given time limit, that user would not receive a notification. However, if the user does not turn his or her avatar to the speaker within the given time allotted, that user would receive a notification. The delay also constrains the system

from sending a notification if, for example, the speaker is only making a brief statement and not beginning a continued discourse. The settings under the adjacency tab define a personal space for the avatars, such as a diameter of one virtual meter from the center of the avatar. A proximity trigger is activated in the iGroup tool if another avatar enters and stays in the space

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beyond the threshold time. The settings under the distance tab control the behavior or pop-up notifications related to users’ avatar distance from one another. The distance settings make it possible for an administrator or instructor to set the distance diameter and the amount of time that can elapse when a user exhibits undesirable distance behavior before a notification is sent. The distance diameter is defined as a space around an avatar that is speaking. When one user begins speaking, the iGroup tool determines if others’ avatars are appropriately or inappropriately distanced from the speaker based on the value provided in the settings panel for “Distance Diameter.”

italk Speaking/Listening Tool iTalk is a software-based means to reinforce desired speaking and listening behavior and constrain undesirable behavior. The first iteration of iTalk focuses specifically on eliminating audio interruptions. This tool will monitor conversation; will inform users when they are interrupting and, if needed, will constrain their ability to continue speaking out of turn. Moreover, iTalk will provide coaching and assistance by sending notifications to users such as, “I just interrupted my partner. Maybe I should wait for a pause in conversation before I speak.” In addition, iTalk will be able to dynamically adjust its settings to fit users’ differing conversational abilities. From the user’s perspective, iTalk displays the frequency of conversational interruptions to the screen and presents the user with a notification when a specified threshold of interruptions is met. From the instructor’s or administrator’s perspective, iTalk is configured using a settings panel which can be selected from the iSocial client window’s menu. The iTalk tool monitors audio by hooking in to the microphone channel on user’s clients. Assuming silence, when one user begins speaking, that user is assigned the speaking floor. If another user begins speaking but

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does not have the speaking floor, the utterance is detected on that user’s microphone channel and is counted as an interruption. Obviously, this is a gross oversimplification of conversation dynamics and turn-taking behavior and has the potential for falsely identifying interruptions if, for example, a user accidentally brushes his or her microphone, there is a loud noise in the background, or the user makes a common interjection such as “uh huh” or “yeah.” To control for this, the sensitivity can be adjusted within the tool. The tool can be configured to allow for a certain degree of conversational overlap. For instance, the tool can be configured to allow for one user to interject during a conversation for less than one second, In addition, using frequency thresholds, which allow the user to make a few interruptions before the system sends a notification helps to control for falsely identified interruptions.

Use Case The instructor set an interruption threshold of five interruptions in 30 seconds in the iTalk settings panel. If a user interrupted five times in 30 seconds, a notification displayed on his or her screen informing that the interruption threshold was met and provided coaching hints and tips for avoiding future interruptions. Joe and Ryan began speaking and a progress meter showed the amount of time left until the interruption threshold resets began to count down. Joe interrupted frequently during the conversation. Each interruption caused a separate progress meter showing the number of interruptions to increment by one. When Joe made five interruptions within 30 seconds, a notification pop-up displayed on his screen that states that the user interrupted too frequently and provided tips on avoiding interrupting. If Joe continued to receive notification pop-ups for three consecutive 30-second intervals, iTalk dynamically adjusted the interruption threshold to meet Joe’s level of ability. Ryan did not interrupt frequently. In this case, iTalk hypothesized that Ryan’s threshold was

Social Orthotics for Youth with ASD to Learn in a Collaborative 3D VLE

too easy for his level of ability. The exact way that iTalk will work is not completely specified, but in this case Ryan might have received a token as a reward for his performance and is dynamically moved to a more challenging threshold.

Settings Panel The iTalk settings panel shown in Figure 7 is used to set the interruption threshold, enable/disable progress meters, set a custom notification message and enable/disable user muting. The interruption threshold makes it possible for the instructor or administrator to set the number of interruptions that are allowed within a given time period before a notification is sent. The three pedagogical levels have default settings which can be overridden manually. The progress meters check box toggles the visibility on the

client’s display of interruption progress meters. Notifications can be toggled on/off, can be set for a display duration on the client’s screen and have custom notification messages. In addition to the interruption threshold, progress meters and notifications, the settings panel allows the instructor or administrator to mute a user for a given time duration when an interruption threshold is met. Figure 8 shows how the progress indicators and pop-up notifications are displayed on the user’s screen. When iTalk is enabled, the user sees two progress meters on the bottom-right portion of the iSocial client window. The meter on the right is a timer and represents the time interval set by the administrator or the instructor in the settings panel. The meter on the left indicates the number of times a user has interrupted in a given time interval. When the time interval reaches zero, both meters reset.

Figure 7. Mock-up of iTalk settings panel

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The meters indicating the interruption threshold is color coded (green, yellow and red) in order to convey how close a user is to receiving an interruption notification. The interruption indicators use an incremental model; that is, given an interruption threshold of five interruptions in 30 seconds for the first interruption, the progress meter will display in green. For the next two interruptions, the progress meter displays in yellow. For the fourth and fifth interruptions, the progress meter displays red. Green indicates a lower interruption frequency, yellow a moderate interruption frequency and red a severe interruption frequency.

Pedagogical strategy The social orthotics tools are designed with a three-phase model of capability. The phases are: (a) acquisition, (b) maintenance and (c) fluency.

The acquisition phase is for users who have not yet acquired the ability; hence, the times that elapse before a notification is sent are short and the goals for appropriate behavior may be lower or less refined. The maintenance phase is for users who have acquired rudimentary ability, so the times that elapse before a notification is sent are moderate. The fluency phase is for users who have become adept at the competency and long times can elapse before a notification is sent. By the fluency phase goals for appropriate behavior are quite refined and expectations are as close to those in typical environments as possible. The support, prompts and scaffolding provided by the orthotics fade across the phases of acquisition, being heavy yet tolerant during the acquisition phase, moderate during the maintenance phase and light during the fluency phase. An overview of how fading works across phases of acquisition is provided below:

Figure 8. Mock-up of iTalk progress meters and pop-up notifications as seen by the user

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Acquisition ◦ Shorter times before notifications are sent, ◦ More specifically and clearly worded notifications (e.g., “You are too close to the speaker.” and “You have interrupted.”) ◦ Additional hints and strategies for avoiding inappropriate behavior. ◦ Specific hints and strategies provided to avoid inappropriate behavior (“precorrects”). ◦ More tolerant expectations. • Maintenance ◦ Moderate times before notifications are sent. ◦ Less specific worded notifications (e.g., “If you stand so close to someone, you might make them uncomfortable or they might think you are being rude.”) ◦ Some hints and strategies (“pre-corrects”) for avoiding inappropriate adjacency, distance, orientation and interrupting behavior. • Fluency ◦ Longer times before notifications are sent. ◦ Few notifications. ◦ Occasional and generalized “precorrects.” ◦ Expectations most resemble those of typical environments. Unless there is some basis for choosing a different phase, at the beginning of the curriculum orthotics are set to the acquisition phase. Thereafter, the behavior of the orthotic is dynamically adjusted within a phase and when moving to another phase based on the youth’s performance. The orthotic tool is able to determine a user’s ability by the number of times a user receives a notification of inappropriate behavior. For instance, if a user is in the acquisition phase and receives five notifications of inappropriate adjacency •

behavior, iGroup will adjust in order to increase the frequency of notifications that user receives. If a user is in the acquisition phase and receives very few or no notifications, iGroup will adjust in order to decrease the frequency of notifications that user receives. The social orthotic tool also maintains a log of user’s behavior related to that orthotic and is able to create a report for the guide at the end of a lesson or for review before the next session. The online guide can use this report to determine changes over time for a given user’s social behavior. For instance, if a user is not making progress and exhibits little or no change in behavior over time, the guide can be made aware of this through the reporting functionality. The guide and researchers can also use the social orthotic reports to determine specific times or parts of lessons that cause difficulty for users and use this information to specifically focus on these issues.

usAbILIty testIng In the spring of 2009 a usability test was undertaken for the iTalk social orthotic. Two youths from the previous field test were invited to participate. The study included an online guide and both participants simultaneously and collaboratively worked through two usability protocols. The screens of the participants were recorded using ScreenFlow screen-recording software that allowed for keyboard and mouse tracking. ScreenFlow also enabled the computer’s web camera to record the physical behavior of the participant working at his computer. Each protocol lasted approximately one hour. During each usability test, the iTalk software tool was enabled for the full duration of the test. A default setting for receiving pop-up notifications from iTalk was used for the entirety of protocol one. Three different notification settings were used for protocol two—high notification frequency, medium notification frequency and low notification frequency. Participants received no training

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on iTalk for the first protocol, but did receive training for the second protocol. In the second usability protocol, participants first reviewed a short video of their experience in the first usability protocol and then received training on using iTalk. Following the training, participants engaged in a conversation intense, game-like, activity using the iTalk software set at a high notification frequency. The notification frequency was set to medium on the second iteration as the participants worked through the activity a second time. Participants were able to complete all of the tasks from both protocols in the iSocial environment, although not without help. Participant one needed more help than participant two. Both participants characterized their experience as easy and enjoyable and both said they would like to return to continue using iSocial. During protocol, one both subjects noticed the pop-up text notifications and the meters. They understood the text messages, but expressed confusion about the meaning and purpose of the meters. They both saw changes in the meters but did not readily understand how changes in the meter representation related to their own behavior. When asked about their opinions about the meters, participant two said that “they’re distracting, and they’re bright. I hate bright.” Participant one agreed with the negative sentiment saying “They get annoying too.” Participant two thought the social orthotic was too sensitive and gave too many notifications. He stated that the pop-up message appeared when he “didn’t mean to interrupt,” explaining that he was just “moving the microphone.” Indeed, participant two touched his microphone to get the pop-up message deliberately several times. Participant one seemed to take the orthotic more seriously. At one time, he tried to say something while the online guide was talking, but when he noticed a change in his meters, he gave up the attempt and kept quiet. Participant two, on the other hand, appeared to be enjoying getting the pop-up window by moving or touching his microphone. When asked about whether they tried to interrupt less,

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participant one first claimed that he did not try, but participant two claimed, “I tried. Didn’t work.” Participant one corrected himself by saying that “I tried too. But it didn’t work.” Prior to protocol two, the two participants watched a video of some of their activity in protocol one with the guide using the video to show how iTalk worked. After the guide illustrated the functionality of the two meters, Participant two acknowledged, “it makes sense.” And participant one was able to restate the functionality of the two meters correctly. He explained that “when you speak when other person spoken, then this timer [the yellow bar] goes down. The green one goes up.” Upon prompting from the physical facilitator, both participants understood that they were going to try to not interrupt during the session. After the first activity in protocol two, neither participant received any pop-up text notifications for verbal interruptions. They reported that they attended to changes in the meters and they tried not to interrupt. Participant two said, “That’s [the change of the meters] why I was silent for a few times.” Participant one also reported “when I noticed the yellow one went down, that means I was interrupting. So I shut up my mouth and just pay attention.” After the second activity of the protocol, both participants reported that the orthotics were less sensitive than before. Participant two described it as “the thing didn’t pop-up, but it still says that I’m talking”, and he also described it as “looks like if I did it multiple times, it just says ‘you have interrupted’ once”, which indicated that he understood the functionality of the meters. However, participant one thought the orthotics were shut down.

key Lessons for social orthotics The purpose of a usability test was to develop insights for improving the human-computer interaction of a system and not to draw conclusions about the value of the concepts and principles in play. Keeping this purpose in mind the findings from the

Social Orthotics for Youth with ASD to Learn in a Collaborative 3D VLE

usability test suggest several results about the use of iTalk. In protocol one, although the participants did not fully understand the mechanisms they did attend to them. However, there did not seem to be any substantial regulation of interruption behavior even from text that specifically told the participants they were interrupting. In protocol two the participants better understood the mechanisms and seemed to self-regulate their interruption behavior by attending to the physical cues from the meters. It is hard to tell if there was any impact from the text messages, but the meters seemed to establish a feedback loop that was attended to and used in regulating verbal behavior. Additionally in protocol one the participants complained that iTalk was annoying and too sensitive. However, in protocol two they no longer complained about iTalk being annoying and saw it as less sensitive or even turned off (although it was not). These assertions suggest that as the youth were able to understand and thus use the visual cues from the meters that iTalk started to become effective and accepted by the participants. Taken together, our lessons from the reviews of literature and from the usability results suggest several assertions about the design and development of social orthotics for youth with ASD in virtual environment for learning social competence. First, the visual nature of the representation seems to have some impact. This assertion is strongly suggested in the literature and seems to be borne out with the role of the meters in iTalk. The text messages from the pop-up notifications provided information to the participants and may have provided some regulatory influence on their behavior, but the regulatory influence of the meters in protocol two seemed much more profound. A second assertion is that when the participants understood the relationship between the visual meters and their behavior they created a feedback loop that was a dynamic mediator of their own behavior. In this sense they seemed to take ownership of the meters as their own tools. In Mind as Action, James Wertsch (1998) char-

acterizes “ownership” or “appropriation” as one of the most profound relationships that users can have with the tools they use to interact in their socio-cultural milieu. Having ownership of the tools gives the user a sense of power and authority to act. While we may not want to make too much of the small set of data we have collected in the usability test, it makes sense to use a “sense of ownership” as an attribute to be examined and strived for in the design, development and implementation of social orthotics. Is the orthotic appropriated as empowering by the user or seen as a constraining annoyance in the service of others? A third lesson suggests the relevance of customization and adaptability in orthotics. We see this lesson in three forms, the first being that the youths have different capabilities relevant to the social practices and that they experience the VLE in different ways, thus the participants need orthotics that fit their individual profiles. The computer environment affords the potential to match orthotics to profiles, but we still have much to learn about just what is relevant in the student profile of experience and capability and how best to match characteristics of the orthotic, such as duration and form of feedback, to meet individual needs. A second form of lesson three is that the orthotics should also match the task and environment. For example, orthotics for not interrupting during turn-taking in game playing may require different features than for not interrupting when the youth is talking with a teacher or counselor. A third form of this lesson is that in the iSocial context some of the capabilities that the orthotics is supporting are also the target of the curriculum. Thus one might expect an upward trajectory for these capabilities as the youth progress through the curriculum. What is the relationship between the curriculum and the orthotics? For example, if the youth gets to a later unit in the curriculum, but the orthotic still needs to apply methods from the “acquisition” phase, are new approaches needed from the curriculum, orthotics or both?

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Future reseArcH And desIgn It is quite obvious that there is much more “future” than “past” in research and design for social orthotics in support of social practice and learning in a 3D VLE by youth with ASD. Our designs for iTalk and iGroup, while quite exciting to us, are still fairly rudimentary. We will continue a process of research and design iteration as we seek to articulate our vision into software tools. A first step is to take the lessons learned from the usability test and re-implement iTalk and implement iGroup for a next field test. Fortunately, with support from AutismSpeaks and the Institute for Educational Sciences of the U.S. Department of Education, we have resources to both investigate best approaches to social orthotics and to develop a full implementation of iSocial. The social orthotics we have described and specified need to be fully and well implemented, but we also need to think beyond the current aspects to see if there are other important features to grouping beyond adjacency, distance or orientation and to talking beyond interruptions. Obviously there are, but can we find effective ways to monitor and provide feedback for them. Beyond extending the capabilities that orthotics can help regulate, we also need research on how best to implement the orthotics. For example, under our lessons learned we speculate that the meters had a special prominence in regulating interruptions because of their visual cues and the match that visual information has with the ways the individual’s with ASD process information. However, the influence on interruptions may also have come because the meters represented a scoring-like function that made the action game-like. In our results both mechanisms may have been at work. Can we isolate the impact of visual representation from game-like challenge? Can we find the best ways to harness both mechanisms for the power of orthotics? Is there something else going on that we have not considered? These questions are quite exciting and iSocial is a good laboratory

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for exploring these and other design principles. A final area for continued research and development stems from the lesson described above related to customization and adaptability. These concepts seemingly hold great promise, yet we are just at the beginning of imagining how to best support individual differences, contextual relevance and trajectories of development.

concLusIon The many special education researchers who have contributed to advances in assistive technology do so because they see the potential of design and engineering to overcome disabilities and provide more normal functioning to those otherwise limited or deprived. For individuals with ASD these designs and engineering efforts primarily attend to mechanisms for communication and social interaction. As computers have moved from devices that simply calculate and word process to environments that support communication and being social, attention to how software design best supports social behavior is warranted and is especially important for individuals who are non-typical in the way they interact and process information for social interchange. These new computer environments will increasingly be called upon as supplements to traditional forms of work and learning or in some cases entirely replace traditional forms of work and learning. For example, K-12 education is increasingly being delivered online and outside of traditional schools. The Sloan Consortium estimates that over one million K-12 students were engaged in online learning in the 2007-2008 school year (Picciano & Seaman, 2008). Further, Christensen, Horn, and Johnson (2008), predict that by 2013 10% of all K-12 school enrollments will be online and that by 2018 the number will be 50% of all enrollments. Our particular interest in social orthotics is to build a custom 3D VLE for youth with ASD to develop social competence in a way that over-

Social Orthotics for Youth with ASD to Learn in a Collaborative 3D VLE

comes limited access to these forms of educational support. However, as suggested by the statistics on the growing use of online education in K-12, social orthotics offers great potential to assist students with special needs to participate in new and more effective ways with others in many forms of online education. For example, can social orthotics help a student and his mathematics teacher achieve better teaching and learning outcomes by using online aids for lessons? However, while we are excited about what we are learning about how to do social orthotics in a 3D environment for youth with ASD, speculation must be tempered by how much we still need to learn about how youth will use these tools, what impact they may have on social interaction and learning, and the potential for unintended consequences. Clearly though, social orthotics in 3D VLE is an area for further research and development. Furthermore, our abilities to use visual cues appropriately, customize and fit the orthotics to the individual, the task and the environment, provide orthotics in a way that gives ownership to the youth, and see the use of orthotics in a virtual world as part of a developmental trajectory will be key to innovation and achievement.

Christensen, C. M., Horn, M. B., & Johnson, C. W. (2008). Disrupting class: How disruptive innovation will change the way the world learns. New York: McGraw-Hill. Cobb, S., Beardon, L., Eastgate, R., Glover, T., Kerr, S., & Neale, H. (2002). Applied virtual environments to support learning of social interaction skills in users with Asperger’s Syndrome. Digital Creativity, 13(1), 11–22. doi:10.1076/ digc.13.1.11.3208 Collins, A., Brown, J. S., & Newman, S. E. (1989). Cognitive apprenticeship: Teaching the crafts of reading, writing, and mathematics. In Resnick, L. B. (Ed.), Knowing, learning, and instruction: Essays in honor of Robert Glasser (pp. 453–494). Hillsdale, NJ: Lawrence Erlbaum & Associates, Inc. Engelbart, D. (1962). Augmenting Human Intellect: A conceptual framework, summary report. SRI International. On Contract AF, 49(638), 1024.

AcknoWLedgment

Hmelo-Silver, C. E. (2006). Design principles for scaffolding technology based inquiry. In O’Donnell, A. M., Hmelo-Silver, C. E., & Erkens, G. (Eds.), Collaborative reasoning, learning and technology (pp. 147–170). Mahwah, NJ: Erlbaum.

The authors wish to acknowledge the University of Missouri Research Board, the Thompson Center for Autism and Neurodevelopmental disorders and grant # 2915 (principal investigator, James Laffey) from Autism Speaks for support for the work described in this chapter.

Hodgedon, L. Q. (1995). Solving social-behavioral problems through the use of visually supported communication. In Quill, K. A. (Ed.), Teaching children with Autism: Strategies to enhance communication and socialization (pp. 265–286). New York: Delmar.

reFerences

Laffey, J. (1995). Dynamism in performance support systems. Performance Improvement Quarterly, 8(1), 31–46.

Burton, R., Brown, J. S., & Fischer, G. (1984). Skiing as a model of instruction. In Rogoff, B., & Lave, J. (Eds.), Everyday cognition: Its development in social context (pp. 139–150). Cambridge, MA: Harvard University Press.

Laffey, J., Schmidt, M., Stichter, J., Schmidt, C., & Goggins, S. (2009). iSocial: A 3D VLE for Youth with Autism. Proceedings of CSCL 2009, Rhodes, Greece.

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Laffey, J., Schmidt, M., Stichter, J., Schmidt, C., Oprean, D., Herzog, M., & Babiuch, R. (in press). Designing for social interaction and social competence in a 3D-VLE. In Russell, D. (Ed.), Cases on collaboration in virtual learning environments: Processes and interactions. Hershey, PA: Information Science Reference. Lin, F. (Ed.). (2004). Designing distributed learning environments with intelligent software agents. Hershey, PA: Information Science Publishing. Mirenda, P. (2001). Autism, augmentative communication, and assistive technology: What do we really know? Focus on Autism and Other Developmental Disabilities, 16(3), 141–151. doi:10.1177/108835760101600302 Mirenda, P. (2009). Introduction to AAC for individuals with Autism Spectrum Disorders. In Mirenda, P., & Iacono, T. (Eds.), AAC for individuals with Autism Spectrum Disorders (pp. 247–278). Baltimore, MD: Paul H. Brookes Publishing Co. Mitchell, P., Parsons, S., & Leonard, A. (2007). Using virtual environments for teaching social understanding to 6 adolescents with autistic spectrum disorders. Journal of Autism and Developmental Disorders, 37(3), 589–600. doi:10.1007/s10803006-0189-8 Norman, D. (1994). Things that make us smart. Reading, MA: Addison-Wesley Publishing Co. Parsons, S., Leonard, A., & Mitchell, P. (2006). Virtual environments for social skills training: Comments form two adolescents with autistic spectrum disorder. Computers & Education, 47, 186–206. doi:10.1016/j.compedu.2004.10.003 Picciano, A. G., & Seaman, J. (2008). K-12 online learning: A 2008 follow-up of the survey of U.S. school district administrators. The Sloan Consortium.

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Pierangelo, R., & Giuliani, G. (2008). The educator’s step-by-step guide to classroom management techniques for students with autism. Thousand Oaks, CA: Corwin Press. Quill, K. (1997). Instructional considerations for young children with autism: The rationale for visually cued instructions. Journal of Autism and Developmental Disorders, 27, 697–714. doi:10.1023/A:1025806900162 Quintana, C., Reiser, B. J., Davis, E. A., Krajcik, J., Fretz, E., & Duncan, R. G. (2004). A scaffolding design framework for software to support science inquiry. Journal of the Learning Sciences, 13, 337–386. doi:10.1207/s15327809jls1303_4 Robins, B., Dautenhahn, K., te Boekhorst, R., & Billard, A. (2004). Robots as assistive technology - Does appearance matter? Proceedings of the 2004 IEEE International Workshop on Robot and Human Interactive Communication Kurashiki, Okayama Japan. Schmidt, M., Laffey, J., Stichter, J., Goggins, S., & Schmidt, C. (2008). The design of iSocial: A three-dimensional, multiuser, virtual learning environment for individuals with autism spectrum disorder to learn social skills. The International Journal of Technology. Knowledge and Society, 2(4), 29–38. Stichter, J. P., Herzog, M.J., Visovsky, K., Schmidt, C., Randolph, J., Schultz, T., & Gage, N. (in review). Social competence intervention for youth with Asperger Syndrome and high-functioning autism: An initial investigation. Submitted to review in the Journal of Autism and Developmental Disorders. Stichter, J. P., Randolph, J., Gage, N., & Schmidt, C. (2007). A review of recommended practices in effective social competency programs for students with ASD.exceptionality, 15, 219-232. Wertsch, J. (1998). Mind as action. New York: Oxford University Press.

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key terms And deFInItIons 3-Dimensional Virtual Learning Environment (3D-VLE): A software system representing dimensionality for simulating physical movement and interaction with objects and other members designed to support teaching and learning activity. Avatar: A user’s representation on a computer. In a 3D VLE avatars are usually virtual representations of humans that can move throughout a virtual space. Dynamic Agents: Used here to represent social orthotics that monitor user behavior and intervene based on a set of variables that may change through the interaction and over time. iGroup: A form of software-based social orthotic to reinforce adjacency, distance and orientation behavior and constrain undesirable behavior such as looking away from the speaker.

iTalk: A form of software-based social orthotic to reinforce desired speaking and listening behavior and constrain undesirable behavior such as interrupting others. Pedagogical Strategy: A method for supporting learning outcomes. In iSocial we implement a method for differentially constraining and providing feedback for behavior based on a users learning phase of (a) acquisition, (b) maintenance or (c) fluency. Scaffolding: Types of structures that support advanced performance when the users may be novice or in a learning process. Social Orthotics: Types of structures that facilitate social interaction and social learning when there is an expectation that a natural and effective process is unlikely; used here to represent unique computational functionality to support talking and orientation to others in a 3D VLE.

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Chapter 6

Cognition Meets Assistive Technology: Insights from Load Theory of Selective Attention Neha Khetrapal University of Bielefeld, Germany

AbstrAct This chapter deals with the issue of treating disorders with the help of virtual reality (VR) technology. To this end, it highlights the concept of transdiagnostic processes (like cognitive biases and perceptual processes) that need to be targeted for intervention and are at the risk of becoming atypical across disorders. There have been previous theoretical attempts to explain such common processes, but such theoretical exercises have not been conducted with a rehabilitative focus. Therefore, this chapter urges greater cooperation between researchers and therapists and stresses the intimate links between cognitive and emotional functioning that should be targeted for intervention. This chapter concludes by providing future directions for helping VR to become a popular tool and highlights issues in three different areas: (a) clinical, (b) social and (c) technological. Coordinated research efforts orchestrated in these directions will be beneficial for an understanding of cognitive architecture and rehabilitation alike.

IntroductIon This chapter will begin with background on the concept of cognitive rehabilitation and will serve to illustrate a recently successful popular example of it. It will then describe cognitive models that explain cognitive and emotional functioning and

how these could give rise to disorders. A major focus of the chapter is to highlight the manner in which various disorders could be treated in a similar manner and how technology could aid this process—bringing in the concept of transdiagnostic approach—the basic tenet of which is to emphasize that the processes that serve to maintain disorders cut across these disorders and hence could be dealt

DOI: 10.4018/978-1-61520-817-3.ch006

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Cognition Meets Assistive Technology

with a single appropriately built technology. Though there has not been much research in this direction because therapists prefer to specialize in particular treatment approaches and disorders, this kind of work has picked up momentum (due to the recent scientific focus on an interdisciplinary framework). This chapter will make an initial attempt in this direction by describing how cognitive theories could be applied in understanding the transdiagnostic processes like attentional biases and perceptual processing. This chapter will also attempt to describe the merger of cognitive architecture, specially the transdiagnostic processes and recent rehabilitative tools. Since there remains much work to be done in this direction, this chapter will highlight the areas that require much needed research attention, and at the same time, will provide future directions for embarking upon this process. This chapter will provide an important resource for understanding the transdiagnostic process in terms of assistive technology to psychologists, cognitive scientists, teachers, parents, students of psychology, neuroscientists and rehabilitation professionals.

bAckground cognitive rehabilitation The aim of rehabilitation is to maintain an optimal level of functioning in domains like physical, social and psychological (McLellan, 1991). Therefore, a rehabilitation program is designed for a particular individual and is conducted over a period of time based on the nature of impairment. The basic goal is not to enhance performance on a set of standardized cognitive tasks, but instead to improve functioning in the day-to-day context (Wilson, 1997). Models of cognitive rehabilitation stress the need to address cognitive and emotional difficulties in an integrated manner and not as isolated domains (Prigatano, 1999). Therefore,

cognitive training could be of immense help in this endeavor. Cognitive tasks could thus be designed to deal with cognitive functions like memory, attention, language, and so on, and the level of difficulty could also be varied to suit individual specification (Clare & Woods, 2004).

techniques for cognitive rehabilitation An exciting new development in the field of cognitive rehabilitation is the use of virtual reality (VR). Virtual environments (VE) could be built by keeping in mind the needs of the individual. Examples include presenting a specific number of stimuli to an autistic child that can be gradually increased as the treatment progresses (Max & Burke, 1997) or virtual wheelchair training for people afflicted by physical disabilities (Stephenson, 1995). Schultheis and Rizzo (2001) define VR for behavioral sciences as, “an advanced form of human-computer interface that allows the user to interact with and become immersed in a computer-generated environment in a naturalistic fashion.” Virtual reality could also be viewed as an excellent example of assistive technology (AT) because it can be used to build upon the existing strengths of an individual who in turn helps in offsetting the disability or, in other words, provides an alternate way of completing a task which also helps in compensating for the disability (Lewis, 1998). Virtual reality technology has yielded promising results in terms of cognitive functioning (Rose, Attree, & Johnson, 1996), social benefits (Hirose, Taniguchi, Nakagaki, & Nihei, 1994), and has proved to be less expensive than the real-world simulators. The previous discussions show that VR as AT could be fruitfully employed to treat disabilities. But it is also important to take into account the functioning of human cognitive systems while designing the VR/VE or any other AT and rehabilitation program. So far in the scientific literature

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there have been discussions about both cognitive psychology and AT, but each one has remained isolated from the other. Due to the significant contributions from both fields, it becomes essential that both are discussed in relation to each other so that each of these fields could be utilized to maximize the benefits that the other can confer. To begin with, one needs to adopt a good working definition of deficient cognitive components that require rehabilitative attention and which also cut across various disabilities. An important concept in this regard is the concept of “transdiagnostic approach.” According to this approach, behavioral and cognitive processes that serve to maintain disorders are transdiagnostic in nature (Mansell, Harvey, Watkins, & Shafran, 2008). The transdiagnostic approach has many advantages to itself and these include a better understanding about comorbidity—generalization of knowledge derived from cognitive model(s) to explain a particular disorder. Therefore, when the processes are seen as cutting across the disorders, it becomes easier to generalize one explanation to other processes that are similar in nature. The next advantage is the development of treatment approaches. If the processes are assumed to be common, then it becomes easier and even cost-effective to treat various disorders. Studies in cognitive psychology indeed support the transdiagnostic approach. For instance, attention to external or internal concern related stimuli have been found to be common across various psychological disorders like social phobia, panic disorder, depression, eating disorder, psychotic disorder, posttraumatic stress disorder and so on. Other processes that are also transdiagnostic are memory, thought, reasoning and the like (Mansell et al., 2008). But how exactly are transdiagnostic processes implicated in disorders? How could such processes serve as targets for rehabilitation? The following discussion on cognitive models will make this clearer.

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cognItIve modeLs For emotIonAL ProcessIng Any program of cognitive rehabilitation is built upon a comprehensive understanding of the cognitive and behavioral processes/architecture. Cognitive models that explain cognitive functioning and behavior are good candidates on which rehabilitation endeavors could be built. Current scientific theorizing proposes a more intimate link between cognition and emotion than has been proposed before. Therefore, it may be useful as rehabilitation programs are planned to keep both cognitive and emotional processing in mind because of the intimate interaction. Describing all such theories is outside the scope of this paper; however, the following discussion will touch upon some of these theories.

A cognitive model for selective Processing in Anxiety Mathews and Machintosh (1998) proposed a cognitive model to explain selective processing in anxiety. Anxiety is usually the experience of unpleasant feelings of tension and worry in reaction to unacceptable wishes or impulses. A popular finding in anxiety research is attentional bias towards anxiety relevant concerns only under competitive conditions (where the competition is between neutral and anxiety relevant stimuli). The Mathews and Macintosh (1998) model provides a parsimonious explanation for this finding. The model essentially explains that stimuli attributes are processed in a parallel manner and compete for attention due to the involvement of two different routes. A threat evaluation system (TES) is in place that provides help in easing the competition between the two routes by interacting with the level of anxiety and consequently strengthens activations of anxiety relevant attributes. Within their model, a slower route is used when the threat value is appraised by the consciously controlled

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higher level, such as in a novel anxious situation. Repeated encounters with similar situations will store the relevant cues in the TES and, therefore, a later encounter will produce anxiety through the shorter route bypassing the slower one. As a result, attention will be captured automatically in a competing situation (where the competition is between neutral and anxiety relevant stimuli). Cues encountered in a novel situation that resemble attributes already stored in TES will also tend to elicit anxiety automatically and receive attentional priority. In the model, some danger related attributes are innate while the others are learned. At the same time, other neurobiological evidence suggests that the threat value of a stimulus is evaluated and determined in two distinct ways (LeDoux, 1995). One is a shorter and quicker route that directly runs from the thalamus to the amygdale and the other is a slower route, which is mediated by higher cortical level resources. The proposal of two routes within the model proposed by Mathews and Machintosh (1998), implies that a threatening cue that matches the current concern of anxiety disordered people will sufficiently attract attention under competing situations due to the involvement of the shorter route and will counteract the functioning of the higher level; but following treatment, these patients would no longer show the attentional effects mediated by the shorter route. This is because in the later case, the higher level counteracts the processing of the faster route. Their model also implies that when people encounter threatening cues (no neutral cue), the most threatening one will capture attention and the least threatening one will be inhibited. The model is also applicable in an evolutionary framework because it is certainly more adaptive to process the most potent source of danger and its consequence as a result of mutual inhibition within the TES. The model proposed by Mathews and Machintosh (1998) deals exclusively with selective processing in anxiety and even though it has implications for treatment, it does not give a detailed

account of the how treatment will counteract the effects of anxiety. Their model entails a link between cognitive and emotional processing, but a different model proposed by Power and Dalgleish (1997) serves to document a closer relationship between cognitive and emotional processing. The model proposed by Power and Dalgleish (1997) deals with explaining the processing of five basic emotions, such as sadness, happiness, anger, fear, disgust, as well as complex emotions. Since this model is more comprehensive in nature it will be detailed here rather than other models designed to explain processing in specific disorders.

the sPAArs Approach SPAARS (Schematic, Propositional, Analogical and Associative Representational Systems) is the integrated cognitive model of emotion proposed by Power and Dalgleish (1997). It is a multilevel model. The initial processing of stimuli occurs through specific sensory systems that are collectively termed the analogical processing system. This system can play a crucial role in emotional disorders, for instance, where certain sights, smells, noise, etc. become inherent parts of a traumatic event. The output from this system then feeds into three semantic representation systems. These systems operate in parallel. At the lowest level is the associative system which takes the form of a number of modularized connectionist networks. The intermediate level has the propositional system that has language like representation though it is not language specific. There is no direct route from intermediate level to emotions, but they feed either through appraisals at the schematic level or directly through the associative system. The highest level is called the Schematic Model level. It has the merit of storing information in a flexible manner along with the traditional schema approach. At this level, the generation of emotion occurs through the appraisal process. Appraisal refers to the evaluation of meaning of affective stimuli and is considered

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causal in the generation of an emotional response. Different types of appraisals exist for eliciting the five basic emotions of sadness, happiness, anger, fear and disgust. An appraisal for sadness would focus on the loss (actual or possible) of some valued goal to an individual and pathological instances, for sadness appraisal could be termed as depression. An individual will feel happy when he or she successfully moves towards the completion of some valued goal. When an appraisal of physical or social threat to self or some valued goal is done by the person, then he or she will experience fear and, when such an appraisal is done for a harmless object, it could result in instances of phobia or anxiety. The appraisal of blocking or frustration of a role or goal through an agent leads to feelings of anger. A person will feel disgust when he or she appraises elimination from a person, object or idea, repulsive to the self or some valued goal (Power & Dalgleish, 1997). These appraisals provide the starting point for complex emotions or a sequence of emotions. In this scheme, complex emotions as well as the disorders of emotions are derived from the basic emotions. A second important feature of emotional disorders is that these may be derived from a coupling of two or more basic emotions or appraisal cycles that further embroider on the existing appraisals through which basic emotions are generated or through the integration of appraisals which include the goals of others. Examples include the coupling of happiness and sadness, which can generate nostalgia. Indignation can result from the appraisal of anger combined with the further appraisal that the object of anger is an individual who is inferior in the social hierarchy. Empathy results from sadness when combined with the loss of another person’s goal. The model acknowledges the need for two routes for the generation of emotions and this need is based in part on the fact that basic emotions have an innate pre-wired component; additionally, certain emotions may come to be

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elicited automatically. These two routes are not completely separable. Thus genetics provides a starting psychological point, though the subsequent developmental pathways may be different for each individual. An additional way in which emotions might come to be generated through the direct route is from repeated pairings of certain event-emotion sequences that eventually leads to the automatization of the whole sequence. This repetition bypasses the need for any appraisal. An example of the involvement of the direct route in an emotional disorder, which is an instance of phobia or anxiety where the automatic processing of the objects is anxiety provoking even though it is non-threatening—but due to previous encounter with the object in an individual’s past always in an anxiety provoking situation—it comes to be associated with anxiety. The two routes, for example, can also sometimes generate conflicting emotions as in when the individual may appraise a situation in a happy way, while the direct route is generating a different emotion. The therapeutic technique for working with emotional disorders varies depending on which route the emotion is involved in the disorder. For instance, the person can be provided with a new schematic model for the appraisal of events. Once this model has been accepted the recovery is faster. This type of therapy will work in situations where the schematic level is involved in the disorder. This is an example of fast change processes occurring in therapy. But the patient may continue to experience the maladaptive emotions through the activation of the direct route that is slow to change and is an example of slow processes in recovery. In such cases, exposure-based techniques (as used in the case of phobias) can be helpful. There may also be cases in which a combination of the two techniques will be most effective. Therapies that try to focus on the propositional level of representation only may not be successful if the higher schematic models are flawed.

Cognition Meets Assistive Technology

The description of the SPAARS approach shows various similarities with the model proposed by Mathews and Machintosh (1998). Both the models posit two different routes for emotion generation. The models are parsimonious since they advance the same explanation for both normal and disordered cognition, though the SPAARS approach has a broader scope and also gives more detailed specification for treatment choices.

AssIstIve tecHnoLogy And HumAn cognItIon Current rehabilitative tools and assistive technologies could be significantly improved by considering the architecture of human cognition during the design. The principles derived from cognitive models described, if incorporated into AT tools will help the tools to serve effectively with the target population. Before embarking on the process of merging the nature of human cognition with assistive tools, I will discuss another popular theory of how selective attention operates—load theory of selective attention, which could be utilized to explain the nature of emotional and cognitive functioning in both order and disorder.

Load theory of selective Attention Goal-directed behavior requires focusing attention on goal relevant stimuli. The load theory of selective attention proposes two mechanisms for selective control of attention (Lavie, Hirst, Fockert, & Viding, 2004). The first is a perceptual selection mechanism, which is passive in nature and ensures the exclusion of distractors from perception under high perceptual load (Lavie, 1995). The distractors are not perceived under high perceptual load as the target absorbs all the available processing capacity. But under conditions of low perceptual load, spare processing capacity left over from processing task relevant stimuli “spills-over” to irrelevant stimuli that are processed accordingly

(Lavie & Tsal, 1994). Loading perception would require either adding more items to the task at hand or a more perceptually demanding task on the same number of items. The second mechanism of attentional control is more active in nature and is evoked for the purpose of rejecting distractors that have been perceived under low perceptual load. This type of control depends on higher cognitive functions, like working memory. Therefore, loading higher cognitive functions that maintain processing priorities result in increased distractor processing. The effect occurs because the reduced availability of control mechanisms in turn reduces the ability to control attention according to the processing priorities. Supporting the theory, Lavie and Cox (1997) have shown that an irrelevant distractor failed to capture attention under high perceptual load conditions as compared to low perceptual load. The load was manipulated by either increasing the number of stimuli among which the target had to be detected or by increasing the perceptual similarity between the target and distractors making the task increasingly perceptually demanding in nature. This result was cited as a support for passive distractor rejection in contrast to active inhibitory mechanisms that are employed for the purpose of rejecting distractors under low perceptual load conditions.

Load theory and disorders The two mechanisms of selective attention could be distributed in disorders and hence the load theory of selective attention could serve as an aid while describing the attentional deficits encountered in both cognitive and emotional disorders. A complete description of all the disorders and how these attentional deficits are present in each are out of the scope of this chapter, but for illustrative purpose, a few disorders will be chosen here to further illustrate the transdiagnostic processes.

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Consistent with the theories previously introduced, Bishop, Jenkins, and Lawrence (2007) showed that anxiety modulated the amygdalar response to fearful distractors that interfered with the task performance only under low perceptual load conditions. But this effect was observed for state anxiety (current anxious state) rather than trait anxiety (a permanent personality feature). Trait anxiety, on the other hand, correlated with reduced activity in brain regions responsible for controlled processing under low perceptual load. This result implies that trait anxiety is associated with poor attentional controls. Therefore, state and trait anxiety potentially produce interactive effects and disturb task performance because of the disturbed passive mechanisms and faulty attentional control which in turn does not prevent irrelevant emotional distractors from capturing attention under conditions of load. Deficient attentional control was also observed for aged participants by Lavie (2000; 2001). Maylor and Lavie (1998) investigated the role of perceptual load in aging. They showed that distractor processing was decreased for older participants at lower perceptual loads as compared to the younger ones. Similarly high level affective evaluation (appraisals that are necessary for emotion generation as described in the SPAARS approach) requires attention and working memory, and as a result, is disrupted under high cognitive load. Kalisch, Wiech, Critchley, and Dolan (2006) varied cognitive load, while at the same time, anxiety was induced with the help of anticipation of an impending pain. They observed no change in subjective and physiological indices of anxiety expectations under conditions of load. They did obtain reductions in the activity of brain areas responsible for controlled processing under conditions of high load indicating that high level appraisal was suppressed. Their results did not only show dissociation between brain areas responsible for higher and lower level appraisals, but also how these interact with the manipulations of load.

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merging technology and cognition Having described the intimate role between cognitive and emotional processing in both order and disorder and their interaction with perceptual and cognitive load, what should be the next step if we need to plan a rehabilitative program considering the aforementioned principles of human cognition? Therapy with VR, as previously described, has shown promising results. For instance, VR has been employed effectively for the treatment of phobias, that are usually described as intense and irrational fears of objects or events, like acrophobia (Emmelkamp, Krijn, Hulsbosch, de Vries, Schuemie, & van der Mast, 2002), fear of flying (Rothbaum, Hodges, Smith, Lee, & Price, 2000), spider phobia (Garcia-Palacios et al., 2002) and social phobia (Roy, Légeron, Klinger, Chemin, Lauer, & Nugues, 2003). Clinicians also consider phobias as part of anxiety disorders. VR as a potential tool for dealing with phobias has several advantages. Because the essential component in the treatment of phobias is exposure to the threat related object (like spiders in case of spider phobia) either in the form of imagery or in vivo (the latter involves graded exposure), VR as a treatment device could be employed effectively. When working with VR/VE, the therapist can control feared situation and graded exposure with a significant degree of safety. VR thus turns out to be more effective than the imagination techniques/sessions, where the patients are simply left to themselves to imagine the feared object. Under the imagination procedure the therapist not only lacks control on the imagination of the patient, but it also becomes hard for the therapist to determine whether the patient is actually following the imagination procedure leading to poor treatment generalization outside the treatment clinics. On the other hand, real exposure to the feared object could lead the patient to be traumatized, making him/her more fearful of it. Consequently VR could be employed fruitfully to overcome the difficulties of both the

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imagination techniques and real exposure. The other most important advantage that VR confers on the treatment process is the opportunity for interoceptive exposure (Vincelli, Choi, Molinari, Wiederhold, & Rive, 2000). This becomes important given the fact that bodily sensations are interpreted as signs of fear in the presence of feared object. Virtual reality also turns out to be effective when higher level distorted cognitions need to be challenged (Riva, Bacchetta, Baru, Rinaldi, & Molinari, 1999).

Future reseArcH dIrectIons Future research efforts on VR as a successful application for rehabilitation should concentrate on three major issues and associated problems: (a) clinical, (b) social and (c) technological issues.

clinical Issues The previous discussion clearly shows that VR as a rehabilitative tool has shown promising results and, therefore, has implications for further improvement. Virtual reality could be better suited to rehabilitate a range of disorders by meshing it with the functioning of human cognition. Much remains to be done in order to pinpoint the specific transdiagnostic processes that cuts across disorders and are also found to be deficient. A promising direction in this regard is the application of load theory of selective attention. Though the studies conducted by Bishop et al. (2007) and Kalisch et al. (2006) show that atypical cognitive bias interacts with behavior and neural responses under differing conditions of load, these kinds of results still await to be incorporated into a rehabilitative VR endeavor. As we have previously stated, VR has been used successfully for treating various phobias like acrophobia (Emmelkamp et al., 2002), fear of flying (Rothbaum et al., 2000), spider phobia (Garcia-Palacios et al., 2002) and social phobia

(Roy et al, 2003). What the literature lacks currently is an intimate link between cognitive architecture and the basis for VR successes. Cognitive psychologists, rehabilitative therapists, and VR professionals will stand to gain much if more studies are planned in this direction. For instance, VR is a good choice in exposure techniques for phobias, but since the SPAARS framework and the model proposed by Mathews and Machintosh (1998) show that there could be two routes to emotions—and exposure technique is useful when the faster route that runs from thalamus to amygdala is involved—it will be fruitful to plan future VR studies as was done by Bishop et al. (2007). If such studies show improved attentional control under different conditions of load and prevent anxiety from modulating amygdalar response to anxiety relevant distractors (that disrupt task performance under low perceptual load) with VR treatment, then this will strengthen the link between cognitive models and rehabilitation. The prior theorizing also shows that for successful treatment, practitioners need to provide the patient with a new schematic model for the appraisal of events other than exposure techniques. Once this model has been accepted, recovery is faster. This type of therapy will work in situations where the schematic level is involved in the disorder. This is an example of fast change processes occurring in therapy. For the future, VR could be used in conjunction with brain imaging techniques to study the brain responses along with behavioral responses before and after treatment. Researchers need to meticulously plan such studies by manipulating cognitive load in participants to study the effect of treatment on cognitive appraisals as was done by Kalisch et al. (2006). Once such future endeavors show successful results for anxiety treatment, practitioners will be more confident about the transdiagnostic processes that become atypical and give rise to cognitive biases. How do researchers and practitioners know which route to emotion (faster or slower) is involved in atypical functioning before embarking

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on such endeavors? This again calls for stronger links with neuropsychology and thorough assessments before chalking out a treatment plan. Finally, if both the routes are involved, then a mixture of techniques can be used. If the decision is to concentrate on both the routes, then it is essential to increase the load on perceptual and cognitive processes parametrically in an orthogonal manner; this is a very important concept because if both kinds of load were to be increased simultaneously, then it would become difficult to discern the effect of each individually. Moreover, since VR allows for interoceptive exposure, which becomes important given the fact that bodily sensations are interpreted as signs of fear in the presence of feared object, it would make sense to study the effect of treatment on the schematic level while the bodily responses are also monitored. If the treatment also shows improvement in bodily responses, then one can be even more confident of the VR intervention.

social Issues Before VR could become a part of mainstream use, researchers and practitioners need to overcome several social obstacles. In many traditional schools of therapies, a personal relationship between the therapist and the client is given a high degree of importance. For some, VR could be viewed as disruptive to this relationship. This issue is even more important for a culture that does not emphasize individualism, for instance in some Eastern societies. In this scenario, it becomes important to consider even technologically less developed societies. Apart from this hindrance, any new therapy initially faces resistance from the broader clinical society. This was even true for behavioral therapy when it was introduced, and hence in the field of mental health, there are other issues that determine the acceptance of a new rehabilitative method rather than just documented efficacy. Until the relevant social problems connected to VR are solved, the best course of action

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might be to adopt VR in conjunction with other traditional modes of rehabilitation.

technological Issues Research on social and clinical issues is not enough to promote VR; it is also essential to concentrate on the technological aspects of it. Currently, VR devices and protocols lack standardization, while many others are developed for a specific context making generalization poor (Riva, 2005). Though VR systems cost less than real world simulators, VR is expensive considering that many are built for specific purposes only. In addition, VR is very time-consuming to build.

concLusIon Given that VR research proceeds along three different directions, the future of VR as a rehabilitative tool is promising. Current research efforts and scientific discussions do focus on VR and human cognition, but these have so far remained isolated from each other. But the advent of cognitive science and multidisciplinary frameworks calls for a better cooperation between the two. First, fruitful research direction in this regard will be to focus on transdiagnostic processes that cut across various disorders and need to be targeted with rehabilitative efforts. This will bring down the cost of building rehabilitative tools for specific contexts and will also save precious time. Next, once the transdiagnostic processes have been examined, practitioners would apply these as models of human cognition that explain typical and atypical cognition. There have been few theories, and some popular ones have been described, but still a lot work needs to be done to develop them further and make them the basis of cognitive rehabilitation with VR. Once such efforts are in place, we will truly be able to understand comorbidity, generalize knowledge, and bring down the cost of treating various disorders. The day is not far off

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when mass rehabilitation over the Internet would be possible with such exciting tools!

reFerences Bishop, S. J., Jenkins, R., & Lawrence, A. D. (2007). Neural processing of fearful faces: Effects of anxiety are gated by perceptual capacity limitations. Cerebral Cortex, 17(7), 1595–1603. doi:10.1093/cercor/bhl070 Clare, L., & Woods, R. T. (2004). Cognitive training and cognitive rehabilitation for people with early-stage Alzheimer’s disease: A review. Neuropsychological Rehabilitation, 14(4), 385–401. doi:10.1080/09602010443000074

Lavie, N. (1995). Perceptual load as a necessary condition for selective attention. Journal of Experimental Psychology. Human Perception and Performance, 21(3), 451–468. doi:10.1037/00961523.21.3.451 Lavie, N. (2000). Selective attention and cognitive control: Dissociating attentional functions through different types of load. In Monsell, S., & Driver, J. (Eds.), Control of cognitive processes: Attention & performance XVIII (pp. 175–194). Cambridge, MA: MIT Press. Lavie, N. (2001). The role of capacity limits in selective attention: Behavioural evidence and implications for neural activity. In Braun, J., & Koch, C. (Eds.), Visual attention and cortical circuits (pp. 49–68). Cambridge, MA: MIT Press.

Emmelkamp, P. M., Krijn, M., Hulsbosch, A. M., de Vries, S., Schuemie, M. J., & van der Mast, C. A. (2002). Virtual reality treatment versus exposure in vivo: A comparative evaluation in acrophobia. Behaviour Research and Therapy, 40(5), 509–516. doi:10.1016/S0005-7967(01)00023-7

Lavie, N., & Cox, S. (1997). On the efficiency of visual selective attention: Efficient visual search leads to inefficient distractor rejection. Psychological Science, 8(5), 395–398. doi:10.1111/j.1467-9280.1997.tb00432.x

Garcia-Palacios, A., Hoffman, H., Carlin, A., Furness, T. A., & Botella, C. (2002). Virtual reality in the treatment of spider phobia: A controlled study. Behaviour Research and Therapy, 40(9), 983–993. doi:10.1016/S0005-7967(01)00068-7

Lavie, N., Hirst, A., Fockert, J. W. D., & Viding, E. (2004). Load theory of selective attention and cognitive control. Journal of Experimental Psychology. General, 133(3), 339–354. doi:10.1037/0096-3445.133.3.339

Hirose, M., Taniguchi, M., Nakagaki, Y., & Nihei, K. (1994). Virtual playground and communication environments for children. IEICE Transactions on Information & Systems. E (Norwalk, Conn.), 77D(12), 1330–1334.

LeDoux, J. E. (1995). Emotion: clues from the brain. Annual Review of Psychology, 46, 209–235. doi:10.1146/annurev.ps.46.020195.001233

Kalisch, R., Wiech, K., Critchley, H. D., & Dolan, R. J. (2006). Levels of appraisal: A medial prefrontal role in high-level appraisal of emotional material. NeuroImage, 30(4), 1458–1466. doi:10.1016/j.neuroimage.2005.11.011 Lavie, N., & Tsal. (1994). Perceptual load as a major determinant of the locus of selection in visual attention. Perception & Psychophysics, 56(2), 183–197.

Lewis, R. B. (1998).Assistive technology and learning disabilities: Today’s realities and tomorrow’s promises. Journal of Learning Disabilities, 31(1), 16–26, 54. doi:10.1177/002221949803100103 Mansell, W., Harvey, A., Watkins, E. R., & Shafran, R. (2008). Cognitive behavioral processes across psychological disorders: A review of the utility and validity of the transdiagnostic approach. International Journal of Cognitive Therapy, 1(3), 181–191. doi:10.1521/ijct.2008.1.3.181

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Mathews, A., & Machintosh, B. (1998). Cognitive model of selective processing in anxiety. Cognitive Therapy and Research, 22(6), 539–560. doi:10.1023/A:1018738019346 Max, M. L., & Burke, J. C. (1997). Virtual reality for autism communication and education, with lessons for medical training simulators. In Morgan, K. S., Hoffman, H. M., Stredney, D., & Weghorst, S. J. (Eds.), Studies in health technologies and informatics, 39. Burke, VA: IOS Press. Maylor, E. A., & Lavie, N. (1998). The influence of perceptual load on age differences in selective attention. Psychology and Aging, 13(4), 563–573. doi:10.1037/0882-7974.13.4.563 McLellan, D. L. (1991). Functional recovery and the principles of disability medicine. In Swash, M., & Oxbury, J. (Eds.), Clinical Neurology (Vol. 1, pp. 768–790). London: Churchill Livingstone. Power, M., & Dalegleish, T. (1997). Cognition and emotion: From order to disorder. London: The Psychology Press. Prigatano, G. P. (1999). Principles of neuropsychological rehabilitation. New York: Oxford University Press. Riva, G. (2005). Virtual reality in psychotherapy [Review]. Cyberpsychology & Behavior, 8(3), 220–230. doi:10.1089/cpb.2005.8.220 Riva, G., Bacchetta, M., Baru, M., Rinaldi, S., & Molinari, E. (1999). Virtual reality based experiential cognitive treatment of anorexia nervosa. Journal of Behavior Therapy and Experimental Psychiatry, 30(3), 221–230. doi:10.1016/S00057916(99)00018-X Rose, F. D., Attree, E. A., & Johnson, D. A. (1996). Virtual reality: An assistive technology in neurological rehabilitation. Current Opinion in Neurology, 9(6), 461–467.

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Rothbaum, B. O., Hodges, L., Smith, S., Lee, J. H., & Price, L. (2000). A controlled study of virtual reality exposure therapy for the fear of flying. Journal of Consulting and Clinical Psychology, 68(6), 1020–1026. doi:10.1037/0022006X.68.6.1020 Roy, S., Légeron, P., Klinger, E., Chemin, I., Lauer, F., & Nugues, P. (2003). Definition of a VR−based protocol for the treatment of social phobia. Cyberpsychology & Behavior, 6(4), 411–420. doi:10.1089/109493103322278808 Schultheis, M. T., & Rizzo, A. A. (2001). The application of virtual reality technology in rehabilitation. Rehabilitation Psychology, 46(3), 296–311. doi:10.1037/0090-5550.46.3.296 Stephenson, J. (1995). Sick kids find help in a cyberspace world. Journal of the American Medical Association, 274(24), 1899–1901. doi:10.1001/ jama.274.24.1899 Vincelli, F., Choi, Y. H., Molinari, E., Wiederhold, B. K., & Rive, G. (2000). Experiential cognitive therapy for the treatment of panic disorder with agoraphobia: Definition of a clinical protocol. Cyberpsychology & Behavior, 3(3), 375–385. doi:10.1089/10949310050078823 Wilson, B. A. (1997). Cognitive rehabilitation: How it is and how it might be. Journal of the International Neuropsychological Society, 3(5), 487–496.

AddItIonAL reAdIng Baumgartner, T., Speck, D., Wettstein, D., Masnari, O., Beeli, G., & Jäncke, L. (2008). Feeling present in arousing virtual reality worlds: Prefrontal brain regions differentially orchestrate presence experience in adults and children. Frontiers in Human Neuroscience, 2(8). doi:.doi:10.3389/ neuro.09.008.2008

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Buxbaum, L. J., Palermo, M. A., Mastrogiovanni, D., Read, M. S., Rosenberg-Pitonyak, E., Rizzo, A. A., & Coslett, H. B. (2008). Assessment of spatial attention and neglect with a virtual wheelchair navigation task. Journal of Clinical and Experimental Neuropsychology, 30(6), 650–660. doi:10.1080/13803390701625821 Capodieci, S., Pinelli, P., Zara, D., Gamberini, L., & Riva, G. (2001). Music-enhanced immersive virtual reality in the rehabilitation of memory related cognitive processes and functional Abilities: A case report. Presence (Cambridge, Mass.), 10(4), 450–462. doi:10.1162/1054746011470217 Glantz, K., Durlach, N. I., Barnett, R. C., & Aviles, W. A. (1996). Virtual reality (VR) for psychotherapy: From the physical to the social environment. Psychotherapy (Chicago, Ill.), 33(3), 464–473. doi:10.1037/0033-3204.33.3.464 Harvey, A. G., Watkins, E. R., Mansell, W., & Shafran, R. (2004). Cognitive behavioral processes across psychological disorders: A transdiagnostic approach to research and treatment. Oxford, UK: Oxford University Press. Khetrapal, N. (2007a). Antisocial behavior: Potential treatment with biofeedback. Journal of Cognitive Rehabilitation, 25(1), 4–9. Khetrapal, N. (2007b). SPAARS Approach: Integrated cognitive model of emotion of Attention Deficit/Hyperactivity Disorder. Europe’s Journal of Psychology. Khetrapal, N. (in press). SPAARS Approach: Implications for Psychopathy. Poiesis & Praxis: International Journal of Technology Assessment and Ethics of Science. Lavie, N., & Fockert, J. W. D. (2005). The role of working memory in attentional capture. Psychonomic Bulletin & Review, 12(4), 669–674. LeDoux, J. E. (1996). The emotional brain. New York: Simon & Schuster.

McGee, J. S., van der Zaag, C., Buckwalter, J. G., Thiebaux, M., Van Rooyen, A., & Neumann, U. (2000). Issues for the Assessment of Visuospatial Skills in Older Adults Using Virtual Environment Technology. Cyberpsychology & Behavior, 3(3), 469–482. doi:10.1089/10949310050078931 Parsons, T. D., & Rizzo, A. A. (2008). Initial validation of a virtual environment for assessment of memory functioning: Virtual reality cognitive performance assessment test. Cyberpsychology & Behavior, 11(1), 17–25. doi:10.1089/ cpb.2007.9934 Renaud, P., Bouchard, S., & Proulx, R. (2002). Behavioral avoidance dynamics in the presence of a virtual spider. Information Technology in Biomedicine. IEEE Transactions, 6(3), 235–243. Riva, G. (1998). From toys to brain: Virtual reality applications in neuroscience. Virtual Reality (Waltham Cross), 3(4), 259–266. doi:10.1007/ BF01408706 Riva, G., Botella, C., Légeron, P., & Optale, G. (Eds.). (2004). Cybertherapy: Internet and virtual reality as assessment and rehabilitation tools for clinical psychology and neuroscience. Amsterdam: IOS Press. Riva, G., Molinari, E., & Vincelli, F. (2002). Interaction and presence in the clinical relationship: Virtual Reality (VR) as communicative medium between patient and therapist. IEEE Transactions on Information Technology in Biomedicine, 6(3), 1–8. doi:10.1109/TITB.2002.802370 Riva, G., Wiederhold, B. K., & Molinari, E. (Eds.). (1998). Virtual Environments in Clinical Psychology and Neuroscience. Amsterdam: IOS Press. Srinivasan, N., Baijal, S., & Khetrapal, N. (in press). Effects of emotions on selective attention and control. In Srinivasan, N., Kar, B. R., & Pandey, J. (Eds.), Advances in cognitive science (Vol. 2). New Delhi: SAGE.

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Strickland, D., Marcus, L., Mesibov, G. B., & Hogan, K. (1996). Brief report: Two case studies using virtual reality as a learning tool for autistic children. Journal of Autism and Developmental Disorders, 26(6), 651–660. doi:10.1007/ BF02172354

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Williams, J. M., Watts, F. N., MacLeod, C., & Mathews, A. (1997). Cognitive psychology and emotional disorders (2nd ed.). Chichester, UK: John Wiley & Sons.

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Chapter 7

Cognitive Load and Disorientation Issues in Hypermedia as Assistive Technology Muhammet Demirbilek Suleyman Demirel University, Turkey

AbstrAct Advances in information and communication technologies have raised the quality of inclusive education programs. Inclusive education, a recent advance in educational technology, has served to increase the ability of students with special needs. Hypermedia as an assistive technology has the potential to teach and train individuals with disabilities. However, like every technology, hypermedia itself is not problemfree. Disorientation and cognitive load are two of the most challenging problems related to hypermedia learning environments. The purpose of this chapter is to highlight disorientation and cognitive load problems in hypermedia learning environments where learners usually face a serious problem while navigating such environments.

IntroductIon Information and communication technologies, and in particular computers, have an undeniable impact on integrating learners with barriers into the mainstream education system. One of the most useful information and communication technologies for teachers of individuals with disabilities is hypermedia learning environments (HLEs). Hypermedia learning environments can be the vehicle for inclusive education as an assistive technology (AT). DOI: 10.4018/978-1-61520-817-3.ch007

Hypermedia presents information in an interactive way, and it is accessible to all types of learners. It provides a combination of text, sound, graphics, and motion video that can be controlled by the user. With a minimum of training, hypermedia can be used to create very individualized learning environments and tools. This gives teachers the capability to create computer programs to teach the specific objectives that are needed to advance their curricula and individualized learning plans. Hypermedia learning environments can also be used to compensate for some disabilities (Perkins, 1995).

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Cognitive Load and Disorientation Issues in Hypermedia as Assistive Technology

AssIstIve tecHnoLogIes In today’s information age, AT is not a luxury for students with disabilities. Assistive technology is a necessity for their growth and development. The use of AT enables these students to participate in activities typical of their age group. Assistive technology also provides a way by which these students can succeed academically as well as socially. Basically, the use of AT enables these students to do things and experience successes they would otherwise have been unable to do (Kelker, 1997). Assistive technology provides creative solutions that enable individuals with disabilities to be more independent, productive, and integrated into the mainstream of society and community life. The benefits of AT have been recognized as a vital part of special education. Assistive technologies include devices used by children and adults with disabilities. Namely, these types of devices are designed to compensate for functional limitations and to enhance and increase learning, independence, mobility, communication, and environmental control and choice. Weikle and Hadadian (2003) reported that there is valuable evidence supporting the use of AT devices for communication, as functional tools, to promote social outcomes, and as retention aids for learning activities in young children with disabilities. The Technology-Related Assistance for Individuals with Disabilities Act of 1988 (Public Law, 100- 407, 1988) describes an AT device as “any item, piece of equipment, or product system whether acquired off the shelf, modified, or customized that is used to increase, maintain or improve functional capabilities of individuals with disabilities.” In very basic terms, AT can be thought of as products that assist in eliminating the effects of a disability or most simply as products that make life easier for persons with disabilities. This broad definition comprises thousands of devices—both high- and low-tech—that can be

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classified in categories such as writing, computer access, reading, communication, and electronic aids for daily living, mobility, and leisure. Ultimately, with this extreme amount of information, it takes adequate knowledge of AT to best determine the AT needs of students with disabilities. As a category of Assistive Technology Aids and Devices, Educational and Vocational Aids include computers, adaptive software and job modifications. If used appropriately, AT can facilitate a child’s development by providing access to developmentally appropriate activities (Simms, 2003). Behrmann (1998) emphasizes the importance of AT as a means of inclusion into age-appropriate classrooms as well. Assistive technologies can provide the tools to bring more young children with disabilities into the general educational setting (Behrmann, 1998). The benefits of AT for students are cognitive as well as social and emotional. Hetzroni and Schrieber (2004) state that with the use of a word processor, students were able to produce material that was more acceptable and coherent in comparison to prior work samples.

HyPermedIA LeArnIng envIronments What is hypermedia? The history of hypermedia has roots traced back to 1945. Vannevar Bush proposed a machine called “Memex” in his Atlantic Monthly article titled “As we may think” (Dix, Finlay, Abowd & Beale, 1998). According to Bush, “a memex is a device in which an individual stores all his books, records and communications and which is mechanized so that it may be consulted with exceeding speed and flexibility. It is an enlarged intimate supplement to his memory” (Bush, 1945). After 50 years, Bush’s vision turned into effective models. Today’s technology allows reading, browsing, and linking in a non-linear electronic environment.

Cognitive Load and Disorientation Issues in Hypermedia as Assistive Technology

Hypermedia is a combination of networks of nodes including information (e.g., text, graphics, video, sound, etc.) for the purpose of facilitating access to, and manipulation of, the information encapsulated by the data. While hypertext is a text-only electronic environment, hypermedia encompasses other media such as graphics, video, and sound. The World Wide Web is a version of hypermedia extended to a huge network of computers connecting millions of users from all around the world. Hypermedia is different from traditional paper. While information on traditional paper is limited to a linear, sequential format, hypermedia is free from such linear restrictions (Eveland & Dunwoody, 2001). Hypermedia is a more general concept than hypertext. Hypermedia is a combination of multimedia components using computers’ interactive characteristics, dynamic display, and user interface. Hypermedia is an extension of hypertext, including: visual information, sound, video, animation, and other forms of data. Basically, hypermedia refers to the non-linear format of all forms of electronic media and text (Dix et al., 1998); thus making the World Wide Web a multimedia-based (non-linear) HLE. Web browsers are the tools used to access information across the Web. A node is an individual unit of text within a hypertext document. Nodes contain text information sometimes enriched with media. Links refers to electronic connections among nodes.

Hypermedia Features The features of HLEs are non-linearity (Foltz, 1996), flexibility (Conklin, 1987; Kim, 2000), learner control (Marchionini, 1988), variety of media (Marchionini, 1988), navigation, backtracking, annotation, and structure (Beiber, 2000), to name a few. Non-linearity allows the user to control what path to take when searching for information (Foltz,

1996). Hypermedia is flexible in terms of representing information, navigating the structure, and storing the data. Media can be represented in a variety of forms. Hypermedia gives flexibility and freedom to the user for learning and information retrieval (Conklin, 1987). The user has flexibility in choosing the sequence in which to access information (Kim, 2000). Hypermedia learning environments let the learner control navigation, media, and content selection. Hypermedia offers such a high level of learner control that users are required to apply higher-order thinking (Marchionini, 1988). Hypermedia has the capability to associate links with other links, graphics, and audio and video files. Hypermedia may contain a variety of media, such as graphics, pictures, video, and audio. Marchionini (1988) suggests that “hypermedia systems allow huge collections of information in a variety of media to be stored in an extremely compact form that can be accessed easily and rapidly” (p.9). Navigation allows users to explore links, backtracking allows users to return to the previously visited nodes, annotation allows users to bookmark and comment, whiles structural features enable uses to navigate through local and global paths (Beiber, 2000). Hypermedia learning environments contains nodes of information connected by links. A node may be text, a graphics, an audio clip, a video clip, a photo, or a combination of these components. A link is an electronic connection between two nodes. Hypermedia learning environments offer great potential for individualized learning. Adaptive characteristics of hypermedia allow instructors to adapt course presentation, navigation, and content to suit individual students’ needs and preferences. Having adaptive features, hypermedia has the ability to accommodate students’ individual learning differences and to help students with disabilities develop complex learning skills to acquire complex knowledge.

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Human memory and Hypermedia Human memory is associative. It works by associating pieces of information with other information and creating complex knowledge structures in memory (Lowe & Hall, 1999). Like human memory, hypermedia interconnects nodes using computer supported links and allows people to partially mimic the writing and reading processes as they take place during cognition (Lowe & Hall, 1999). By creating non-linear information structures—associating chunks of information in different ways using links in combination with media consisting of text, images, video, sound, and animation—a person can enrich the representation of information. Therefore, structured HLEs may help learners to create their own representation of knowledge and to integrate it into existing knowledge structures. The proposed memory models for humans are generally based on information-processing theory. Jonassen (1989) stated that learning occurs when new information is linked to existing knowledge, structured by associative networks. The semantic network structure and non-linearity features of HLEs resembling theories of memory and cognition may be a fruitful educational tool. It has been claimed that the idea of the structure of human memory and the process of learning is consistent with the process of using HLEs (Jonassen, 1989; Marchionini, 1988). Both hypermedia and human memory are created by nodes of information connected by links (Eveland & Dunwoody, 2001). The similarity between memory and hypermedia may allow the designer and the learner to establish essential relationships between memory and hypermedia. On the contrary, physical textbooks and media can only allow the learner to represent information in a linear way. The principle of the semantic-network model suggests that a key to learning new information is associating it to existing knowledge, by semantically related links (Daniels, 1996). Norman

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(1983) stated that as more complex connections among existing knowledge is stored in memory and as new information, the more learners will retain in memory. Research on learning shows that meaningful learning is accomplished when new information is associated to existing knowledge or node structures (Caudhill & Butler, 1990; Jonassen, 1989). Hypermedia also has an ability to incorporate various media, interactivity, vast data sources, distributed data sources, and powerful search engines. These make hypermedia a very powerful tool to create, store, access, and manipulate information.

usability Issues with Hypermedia Usability in hypermedia refers to developing easy, efficient, memorable, error-free, and pleasant user experiences (Neilsen, 1995). A HLE has an interface element with which the user interacts. Windows, (i.e. computer dialogue boxes) are used extensively in HLEs as a part of the user interface to present graphics, images, text, audio, and video. Windows include nodes and links between them. The user interface is a key factor to HLEs, in terms of usability, efficiency, user comfort, and orientation. Navigation disorientation and cognitive overload are major problems that limit the usefulness of hypermedia (Conklin, 1987; Neilsen, 1995; Dix et al, 1998; McDonald & Stevenson 1996; McDonald & Stevenson 1998). Researchers have looked for solutions to these problems in HLEs. Developing well-structured and well-designed, effective HLEs is not an easy process because of the number of associative links that exist among nodes, non-linearity, and the number of design possibilities. Providing screen displays to construct an operating environment for the user, configuring a clear visual image, and creating a working context for the user’s action are the goals of graphic user interface design (Lynch, 1994).

Cognitive Load and Disorientation Issues in Hypermedia as Assistive Technology

disorientation in Hypermedia Learning environments Disorientation refers to an experience by users not knowing where they are within hypermedia and not knowing how to move to a desired location (Theng, Jones, & Thimbley, 1995a). As expected, the experience of being lost in hypermedia may lead users to feel that they are wasting time, overlooking important information, and may influence the way they interact with hypermedia (Theng, 1997). Consequently, the disorientation problem has the potential of interrupting navigation and browsing in HLEs (McDonald & Stevenson 1998). Elm and Woods (1985) outlined three different forms of disorientation in HLEs. These are: (a) not knowing where to go next; (b) knowing where to go, but not knowing how to get there; and (c) not knowing where one is in the overall structure of the document. Disorientation is one of the most cited problems with HLEs. In fact, learners’ disorientation is a commonly reported problem in hypermedia research (Daniels & Moore 2000; Neilsen, 1995). For example, studies by Nielsen (1990) showed that 56 percent of readers of HLEs agreed that they were often confused about where they were. Many researchers also observed that users may become confused, lost, or disoriented in hypermedia systems (Elm & Woods, 1985; Conklin, 1987; Neilsen, 1990; Gupta & Gramopadhye, 1995; McDonald & Stevenson, 1996; McDonald & Stevenson, 1998; Theng, 1997; Dias & Sousa, 1997; Ahuja & Webster, 2001; Baylor, 2001; Chen, 2002). Gupta and Gramopadhye (1995) mentioned two categories of hypermedia related problems: (a) implementation dependent and (b) endemic. The implementation dependent category contains display restrictions and browser limitations. The endemic category includes disorientation and cognitive overload that impact the usability of HLEs. Authors stated that the endemic problems are more challenging than the implementation

dependent problems in terms of limiting the usefulness of HLEs. Furthermore, Foss (1989) characterized the disorientation problem and the undesirable results of navigating noticed in users during the use of hypermedia system into two categories: (a) the embedded digression / choice multiplicity problem and the (b) art museum phenomenon. The embedded digression/choice multiplicity problem refers to the user feeling distracted, lost, and forgetful of his paths and goals when he pursues multiple ways and movements that take him away from the main topic. The embedded digression problem is associated with difficulties occurring from the abundance of path choices that hypermedia causes. The art museum phenomenon, on the other hand, is a metaphor of what occurs in a similar way when spending a whole day visiting an art museum without giving special attention to a particular drawing or a model. The next day the visitor probably would not be able to describe any painting that he saw in the museum (Dias & Sousa, 1997). In the context of HLEs, the art museum phenomenon refers to problems related to the act of browsing and seeking information and involves the user’s ability to recognize which nodes have been visited or which parts remain to be visited. Foss (1989) defined the problems that disoriented users may also suffer in HLEs. Limitations on short-term memory of humans may lead to the following problems: •

• • • •

Arriving at a specific point in a hypertext document then forgetting what was done there. Forgetting to return to a departure point. Forgetting to pursue departures that were planned earlier. Not knowing if there are any other relevant frames in the document. Not remembering which sections have been visited or altered.

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Trip and Roby (1990) also point out that disorientation will cause amplified cognitive overload that may reduce the mental resources available to process information.

cognitive Load in Hypermedia Learning environments Cognitive load is a term that refers to the load on working memory during instruction (Sweller, 1998). In a hypermedia learning environment, cognitive overload can be defined as being confused or overwhelmed by the available options (Murray, 2001). Cognitive overload can effect orientation of users within HLEs. Cognitive overload refers to being overwhelmed or confused by the options available in multi-path, multi-tool environments such as hypermedia (Murray, 2001). Thuring, Hannemann, and Haake (1995) stated that increased cognitive load results in an inability to orient within hypermedia or navigate through hypermedia. Cognitive overload is one of the main obstacles to learning (Clark, 2003). Cognitive overload happens when the learner is “bombarded with too much information at once” (Clark, 2003, p. 3). Additionally, Daniels and Moore (2000) stated that cognitive overload is one of the main barriers for hypermedia users. Furthermore, researchers noted that the nonlinearity aspect of hypermedia system often results in learner disorientation and cognitive overload (Beasley & Waugh 1995; Conklin, 1987; Tripp & Roby, 1990; Zhu, 1999). Cognitive load theory was broadly elaborated by John Sweller in (1988). The theory sheds light on the limitations of working memory capacity (Sweller, 1988; Sweller, 1994; Sweller & Chandler, 1994). There are three types of cognitive load: (a) intrinsic, (b) extraneous, and (c) germane (Sweller, Van Merriënboer, & Paas, 1998). “Intrinsic load refers to the complexity of learning material.” (Renkl & Atkinson, 2003, p. 17). Extraneous load refers to the complexity

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of mental activities during learning (Renkl & Atkinson, 2003). And germane load refers to the capacity of working memory (Renkl & Atkinson, 2003). Brunken, Plass, & Leuter (2003) stated that learner experience, prior domain specific knowledge, and individual differences influence cognitive load that results in more effort, more errors, and less knowledge acquisition. Mayer and Moreno (1998) and Mousavi, Low, and Sweller (1995) investigated ways to reduce cognitive overload and found that physical integration of visual and verbal information (i.e., split-attention effect), representing information both visual and auditory (i.e., modality effect), and abandoning verbal information (i.e., redundancy effect) are the ways to decrease cognitive overload. Cognitive load theory highlights several practices that can be applied to inclusive education and using hypermedia as an AT to train and to improve performance of students with disabilities. There are methodologies for reducing the effects of the extraneous cognitive load of instructional materials to ensure optimal learning. These effects include split attention, redundancy, and modality.

The Split-Attention Effect The split-attention effect can be defined as how the use of materials that require learners to split their attention between two sources of information causing a higher cognitive load on working memory, impedes the learning process (Chandler & Sweller, 1992; Mayer & Moreno, 2003).

The Redundancy Effect An illustration of the redundancy effect is when one source of instruction, whether textual or graphic, provides full intelligibility, suggesting that one source of instruction should be used (Chandler & Sweller, 1991). Redundant sources should be removed from the instructional materials

Cognitive Load and Disorientation Issues in Hypermedia as Assistive Technology

in order to reduce cognitive load (Mayer, Heiser, & Lonn, 2001).

The Modality Effect According to the modality principle, learning is more efficient when multiple sensory pathways are used to present information (Moreno & Mayer, 1999; Mousavi, Low, & Sweller, 1995).

Hypermedia in Inclusive education Hypermedia learning environments have gained popularity since the Internet was introduced to schools. Hypermedia learning environments have been used as tutorials for classes to create interactive and individualized lessons. Hypermedia can be used to communicate and instruct as to improve access or productivity. Hypermedia learning environments can be used in different ways to train or teach individuals who have special education needs. According to Perkins (1991, 1993) these ways include the creation of computer-aided instruction as a communication device and as a menu to launch other applications. It also includes stacks that can be operated by students with cognitive disabilities, communication disorders, physical disabilities, and those students who are unable to read. Hypermedia learning environments can provide educators the ability to author their own tutorials and training to teach specific objectives in their classrooms (Perkins, 1993, 1991). Due to its flexibility, hypermedia can be one of the best tools for teachers and parents to utilize in aiding individuals with disabilities. Studies show that the introduction of technology, such as hypermediabased interactive learning environments in at-risk settings, enhances both self-image and locus of control with pupils engaged in computer-applied instructional activities (Furst, 1993; Klein, 1992). Hypermedia can be used to teach and train individuals with disabilities such as those unable to

read, with communications disorders, and those with cognitive or physical disabilities. Through non-linearity of hypermedia, learners who have certain disabilities can choose different ways to pursue the subject matter based upon their own interests and objectives. Thus, hypermedia environment can better accommodate individuals’ different needs and different learning styles and is more suitable for discovery learning (Liu, 1994). The associativity of hypermedia is similar to the functions of human memory. With this feature, related information can be linked together to form a network. This feature can enable learners to construct their own knowledge base, by making meaningful connections among the ideas as they see fit. Students can navigate from one node to another without any limitation. This feature allows a teacher to present the to-be-learned subject in different ways. The efficiency of hypermedia allows teachers to present the information in different forms such as text, graphics, video, sound, and animation in a single page. These features make hypermedia a powerful tool in inclusive education. Along with these advantages, however, hypermedia is not free from disadvantages. Disorientation and cognitive load are the main disadvantages of HLEs. Learners with disabilities can easily become lost (disoriented) in the hypermedia learning context. The complex and non-linear structure of HLEs may also lead inclusive education students to cognitive overload.

concLusIon When HLEs are not well structured for usability through adherence to instructional design principles, the probability of learner disorientation and cognitive overload is very high during navigation. Nunes and Fowell (1996) describe that these problems may result in the learning process being interrupted. Learners may end up studying less

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meaningful topics and omit crucial ones (Nunes & Fowell, 1996). These are the consequences of being disoriented and experiencing cognitive overload while in HLEs. Nunes and Fowel (1996) also indicate that disorientated learners have trouble finding specific information, even if they know that it is present. Therefore, learners may fail to see how parts of the knowledge base are related and may even omit large, relevant sections of information (Hammon, 1993). As a result of cognitive overload, learners may become unclear of their learning objectives or how to accomplish them. Thus, learners may fail to become involved in the learning process (Nunes & Fowel, 1996). Interface design and usability are important components in hypermedia design. Appropriate and structured interface design helps to minimize problems in HLEs. Furthermore, having multimedia capabilities, high level interactivity, and the power of association, hypermedia can empower individuals with disabilities by providing flexible and interactive learning environments. Similarities of hypermedia with the human memory system seem to be particularly appropriate for disabled individuals’ learning, as it provides not only a vivid and natural environment for the accumulation of the facts, but also tools to synthesize and integrate new knowledge, and reconstruct existing knowledge. Finally, hypermedia can create an educational environment that can meet the needs of students with special needs. In conclusion, hypermedia may have many benefits when properly employed in educating individuals with special needs by providing a secure learning environment. Hypermedia may act as an intermediary in communicating with others and may develop social skills and facilitate group work; hypermedia may support basic literacy and numeracy; hypermedia may assist students with special needs in organizing their thoughts and time more effectively; and hypermedia may assist students to develop fine motor skills through graphical navigation, such as in using a mouse to drag and drop objects on a screen, move a cursor, and so on.

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reFerences Ahuja, J. S., & Webster, J. (2001). Perceived disorientation: An examination of a new measure to assess web design effectiveness. Interacting with Computers, 14(1), 15–29. doi:10.1016/S09535438(01)00048-0 Baylor, A. L. (2001). Incidental learning and perceived disorientation in a web-based environment: Internal and external factors. Journal of Educational Multimedia and Hypermedia, 10(3), 227–251. Beasley, R., & Waugh, M. (1995). Cognitive mapping architectures and hypermedia disorientation: An empirical study. Journal of Educational Multimedia and Hypermedia, 4(2/3), 239–255. Behrmann, M. (1998). Assistive technology for young children in special education. Yearbook (Association for Supervision and Curriculum Development), 73-93. Wilson Web Database. Brunken, R., Plass, J. L., & Leutner, D. (2003). Direct measurement of cognitive load in multimedia learning. Educational Psychologist, 38(1), 53–61. doi:10.1207/S15326985EP3801_7 Bush, V. (1945) As we may think. Atlantic Monthly. Retrieved September 9, 2008, from http://www. theatlantic.com/doc/194507/bush Caudhill, M., & Butler, C. (1990). Naturally intelligent systems. Cambridge, MA: MIT Press. Chandler, P., & Sweller, J. (1991). Cognitive load theory and the format of instruction. Cognition and Instruction, 8(4), 293–332. doi:10.1207/ s1532690xci0804_2 Chandler, P., & Sweller, J. (1992). The split-attention effect as a factor in the design of instruction. The British Journal of Educational Psychology, 62, 233–246.

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Chen, S. Y. (2002). A cognitive model for non-linear learning in hypermedia programs. British Journal of Educational Technology, 33(4), 449–460. doi:10.1111/1467-8535.00281 Clark, R. C. (2003). Authorware, multimedia, and instructional methods. Retrieved December 3, 2008, from http://www.macromedia.com/support/ authorware/basics/instruct/index.html Conklin, J. (1987, September 20). Hypertext-an introduction and survey. IEEE Computer, 17-41. Daniels, H. L. (1996). Interaction of cognitive style and learner control of presentation mode in a hypermedia environment. Unpublished Doctoral dissertation, Virginia Polytechnic Institute and State University, Blacksburg, VA. Daniels, H. L., & Moore, D. M. (2000). Interaction of cognitive style and learner control in a hypermedia environment. International Journal of Instructional Media, 27(4), 369–383. Dias, P., & Sousa, A. P. (1997). Understanding navigation and disorientation in hypermedia learning environments. Journal of Educational Multimedia and Hypermedia, 6(2), 173–185. Dix, A. D., Finlay, E. J., Abowd, D. G., & Beale, R. (1998). Human-computer interaction. London: Prentice Hall Europe. Elm, W., & Woods, D. (1985). Getting lost: A case study in interface design. In Proceedings of the human factors society 29th Annual Meeting (pp. 927-931). Eveland, W. P. Jr, & Dunwoody, S. (2001). User control and structural isomorphism or disorientation and cognitive load? Learning from the web versus print. Communication Research, 28(1), 48–78. doi:10.1177/009365001028001002 Foltz, P. W. (1996). Comprehension, coherence and strategies in hypertext and linear text. In Rouet, J. F., Levonen, J. J., Dillon, A. P., & Spiro, R. J. (Eds.), Hypertext and cognition. Hillsdale, NJ: Lawrence Erlbaum Associates.

Foss, C. (1989). Tools for reading and browsing hypertext. Information processing management. In S. McDonald & R. J. Stevenson (1996). Disorientation in hypertext: The effects of three text structures on navigation performance. Applied Ergonomics, 27(1), 61–68. Furst, M. (1993). Building self-esteem. Academic Therapy, 19(1), 11–15. Gupta, M., & Gramopadhye, A. K. (1995). An evaluation of different navigational tools in using hypertext. Computers & Industrial Engineering, 29(1-4), 437–441. doi:10.1016/0360-8352(95)00113-F Hammond, N. (1993). Learning with hypertext: Problems, principles and prospects. In McKnight, C., Dillon, A., & Richardson, J. (Eds.), Hypertext: A psychological perspective (pp. 51–69). London: Ellis Horwood. Hetzroni, O., & Schrieber, B. (2004). Word processing as an assistive technology tool for enhancing academic outcomes of students with writing disabilities in the general classroom. Journal of Learning Disabilities, 37(2), 143–154. doi:10.11 77/00222194040370020501 Jonassen, D. (1989). Hypertext/Hypermedia. Englewood Cliffs, NJ: Educational Technology Publications. Kelker, K. A. (1997). Family guide to assistive technology. Parents, Let’s Unite for Kids (PLUK). Retrieved December 1, 2008, from http://www. pluk.org/AT1.html Kim, K. (2000). Effects of cognitive style on web search and navigation. World Conference on Educational Multimedia, Hypermedia and Telecommunications (EMEDIA), 2000(1), 531-536. Klein, L. R. (1992). Self-concept enhancement, computer education, and remediation: A study of the relationship between a multifaceted intervention program and academic achievement. Unpublished doctoral dissertation, University of Pennsylvania, Philadelphia, PA.

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Liu, M. (1994). Hypermedia-assisted-instruction and second language learning: A semantic-networkbased approach. Computers in the Schools, 10(3/4), 293–312. Lowe, D., & Hall, W. (1999). Hypermedia and the Web: An engineering approach. London: Wiley. Lynch, P. J. (1994). Visual design for the user interface: Design fundamentals. The Journal of Biocommunication, 21(1), 22–30. Marchionini, G. (1988). Hypermedia and learning. Freedom and chaos. Educational Technology, 28(11), 8–12. Mayer, R., Heiser, J., & Lonn, S. (2001). Cognitive constraints on multimedia learning: When presenting more material results in less understanding. Journal of Educational Psychology, 93, 187–198. doi:10.1037/0022-0663.93.1.187 Mayer, R. E., & Moreno, R. (1998). A split-attention effect in multimedia learning: Evidence for dual processing systems in working memory. Journal of Educational Psychology, 90(2), 312–320. doi:10.1037/0022-0663.90.2.312 Mayer, R. E., & Moreno, R. (2003). Nine ways to reduce cognitive load in multimedia learning. Educational Psychologist, 38, 43–52. doi:10.1207/ S15326985EP3801_6 McDonald, S., & Stevenson, R. J. (1996). Disorientation in hypertext: The effects of three text structures on navigation performance. Applied Ergonomics, 27(1), 61–68. doi:10.1016/00036870(95)00073-9 McDonald, S., & Stevenson, R. J. (1998). The effects of text structure and prior knowledge on navigation in hypertext. Human Factors, 40(1), 18–27. doi:10.1518/001872098779480541 Moreno, R., & Mayer, R. (1999). Cognitive principles of multimedia learning: The role of modality and contiguity. Journal of Educational Psychology, 91, 358–368. doi:10.1037/0022-0663.91.2.358

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Mousavi, S., Low, R., & Sweller, J. (1995). Reducing cognitive load by mixing auditory and visual presentation modes. Journal of Educational Psychology, 87(2), 319–334. doi:10.1037/00220663.87.2.319 Murray, T. (2001). Characteristics and affordances of adaptive hyperbooks. Proceedings of WebNet 2001, Orlando, FL. Neilsen, J. (1990). The art of navigating through hypertext. Communications of the ACM, 33(3), 298–310. Neilsen, J. (1995). Multimedia and hypertext: The Internet and beyond. Cambridge, MA: AP Professional. Norman, D. A. (1983). Some observations on Mental Models. In Gentner, D., & Stevens, A. L. (Eds.), Mental models (pp. 7–14). Mahwah, NJ: Lawrence Erlbaum Associates Inc. Nunes, J. M., & Fowell, S. P. (1996). Hypermedia as an experiential learning tool: A theoretical model. Information Research, 2(1). Perkins, B. (1995). Integrating hypermedia and assistive technology: An overview of possibilities. Information Technology and Disabilities, 2(2). Retrieved December 20, 2008, from http://www. isc.rit.edu/~easi/itd/itdv02n2/perkins.html Perkins, R. (1991). Using HyperStudio to create lessons that use alternative input devices. In D. Carey, R. Carey, D. A. Willis, & J. Willis (Eds.), Technology and teacher education. Annual 1991: Proceedings of the Annual Conference of the Society for Teacher Education (pp. 80-83). ERIC Document Reproduction Service No. ED 343 562. Perkins, R. (1993). Integrating alternative input devices and hypermedia for use by exceptional individuals. Computers in the Schools, 10(1-4).

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Public Law 100-407 (1988). Technology-Related Assistance for Individuals with Disabilities Act of 1988. Retrieved October, 12, 2009, from http:// www.ok.gov/abletech/documents/Tech%20ActIndividuals%20with%20Disabilities.pdf Renkl, A., & Atkinson, R. K. (2003). Structuring the transition from example study to problem solving in cognitive skill acquisition: A cognitive load perspective. Educational Psychologist, 30(1), 15–22. doi:10.1207/S15326985EP3801_3 Simms, B. (2003). Assistive technology for early childhood. [from Wilson Web Database.]. Exceptional Parent, 33(8), 72–73. Retrieved on July 14, 2004. Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12, 257–285. Sweller, J. (1994). Cognitive load theory, learning difficulty, and instructional design. Learning and Instruction, 4, 295–312. doi:10.1016/09594752(94)90003-5 Sweller, J., & Chandler, P. (1994). Why some material is difficult to learn. Cognition and Instruction, 12(3), 185–233. doi:10.1207/ s1532690xci1203_1 Sweller, J., Van Merriënboer, J., & Paas, F. (1998). Cognitive architecture and instructional design. Educational Psychology Review, 10, 251–296. doi:10.1023/A:1022193728205 Theng, Y. L. (1997), Addressing the ‘lost in hyperspace’ problem in hypertext. PhD Thesis, Middlesex University (London). Theng, Y. L., Jones, M., & Thimbleby, H. (1995a). Reducing information overload: A comparative study of hypertext systems. IEEE Colloquium on Information Overload, 95(223), 6/1-6/5.

Thuring, M., Hannemann, J., & Haake, J. M. (1995). Hypermedia and cognition: Designing for comprehension. Communications of the ACM, 38(8), 57–66. doi:10.1145/208344.208348 Tripp, S. D., & Roby, W. (1990). Orientation and disorientation in a hypertext lexicon. Journal of Computer-Based Instruction, 17(4), 120–124. Weikle, B., & Hadadian, A. (2003). Can assistive technology help us to not leave any child behind? Preventing School Failure, 47(4), 181–186. doi:10.1080/10459880309603365 Zhu, E. (1999). Hypermedia interface design: The effects of number of links and granularity of nodes. Journal of Educational Multimedia and Hypermedia, 8(3), 331–359.

key terms And deFInItIons Assistive Technology: Assistive technology is “any item, piece of equipment, or product system whether acquired off the shelf, modified, or customized that is used to increase, maintain or improve functional capabilities of individuals with disabilities” (Public Law, 100- 407, 1988). Hypertext: Hypertext is a collection of text that can be linked to other text in an unlimited non-linear fashion. Hypermedia: Hypermedia is a combination of networks of nodes, including information (e.g., text, graphics, video, sound, etc.), for the purpose of facilitating access to, and manipulation of, the information encapsulated by the data. Disorientation: Disorientation refers to an experience by users not knowing where they are within hypermedia and not knowing how to move to a desired location. Cognitive Load: Cognitive load refers to the load on working memory during instruction.

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Section 3

Software and Devices

The chapters in Section 3 focus on the use of assistive technology tools in conjunction with the use of a multi-sensory environment or multi-sensory pedagogy. The purpose is to address the essential characteristics of assistive technology implementation, such as software and devices, embedded in inclusive settings and its relevance to practitioners’ collective and individual responsibilities in this area. Little is known about coupling software and devices to the related research. Section 3 pursues new research directions that augment the benefits of assistive technology tools in inclusive education. The chapters in Section 3 mainly attempt to develop promising approaches to implementing software and devices to answer the following research questions: (a) Who should use software or devices as assistive technology for intervention? (b) How should ‘‘using software or devices as assistive technology’’ be operationalized and measured? (c) What intervention or staff development program should be conducted to decrease the prevalence of malfunctioning software or devices during assistive technology implementation? (d) How should the best match between software and devices and students with disabilities be defined? Thus, the major themes of Section 3 are research, implementation, intervention, and assessment. In conclusion, the chapters in Section 3 assert that “Technology makes things easier for everyone. Assistive technology makes things possible for individuals with disabilities.”

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Chapter 8

Multi-Sensory Environments and Augmentative Communication Tools Cynthia L. Wagner Lifeworks Services, USA Jennifer Delisi Lifeworks Services, USA

AbstrAct This chapter discusses the use of augmentative communication tools in conjunction with use of a multisensory environment. Though little has been written about the pairing, the authors discuss related literature, the history of their program’s use, the emerging communicators with whom they notice a great benefit, and the challenges of implementation. The purpose of this chapter is to open the discussion about the relationship between the two, to examine some of the related research, and to propose new research directions which could benefit adults who face communication challenges due to sensory issues. The focus is on the issues faced by adults with developmental disabilities and autism.

IntroductIon Lifeworks is a non-profit organization that helps people with disabilities live fuller lives that are integrated into the flow of community experience. Lifeworks provides the tools clients need to build the lives they want to live, through employment at area businesses, customized support services, and social enrichment opportunities. Our goal is to support clients to achieve their communication goals using the tools that suit them best. DOI: 10.4018/978-1-61520-817-3.ch008

Every day we take in sensory information through sight, sound, taste, smell, and touch. Some people with developmental disabilities, or those on the autism spectrum, face sensory challenges. Sensory sensitivity makes it difficult to communicate if you cannot focus or attend to detail. Integration of senses allows a person to take in what is going on around them and communicate effectively. The authors implemented a program addressing the sensory needs with communication goals. This chapter is based on multi-sensory environments (MSEs) which were introduced in 2007 in our

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day program setting for adults with developmental disabilities, autism, and/or traumatic brain injuries. We will discuss basic sensory needs, how they can be addressed in a MSE, and relate to better use of augmentative communication tools. Helping people to fulfill their sensory needs and communicate to their full potential empowers them to achieve their hopes and dreams.

bAckground Communication difficulties can be caused by physical impairments, cognitive impairments, and/or sensory impairments. Physical impairments can impact the productive communication skills of a person with communication challenges. Such impairments may prevent them from physically producing certain sounds. These impairments also can limit use of augmentative communication tools because the person may have difficulty pointing to objects, manipulating their hands to form words in sign language, or accessing a communication device through alternative access methods such as switches or a head mouse. For some people with developmental disabilities and autism, physical impairments complicating communication may not be visible. Cognitive impairments can affect language acquisition in multiple ways. For people with Down syndrome (DS), short-term memory may be a concern (Iglesia, Buceta, & Campos, 2005). Short-term memory is how we initially store new verbal vocabulary, navigate through a new communication device, or remember the meaning of new picture symbols. Another concern is the processing of language. Research “suggests that participants with DS have a deficit in verbal processing” (Iglesia et al., 2005, p. 201). This has also been discussed for individuals with other cognitive impairments. Much of the new vocabulary we acquire comes from things we have heard others say. Motor speech deficits, such as apraxia, can cause difficulty with multiple types

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of production issues. Koul, Schlosser, and Sancibrian (2001) discuss motor issues specifically in relation to people with autism, but it affects individuals with other disorders as well. When looking at selection options for communication devices, for example, “The movement of the body part or body-part extension (e.g., the headstick) must be sufficiently controllable so that only a single item is activated with each depression” (Beukelman & Mirenda, 1992, p. 58). Finally, sensory impairments prevent us from acquiring all the information that the environment presents. Iglesia et al. (2005) state that “if more senses are engaged in receiving the information (e.g., sight, hearing), the recall of story details will be facilitated” (p. 199). The opposite is true as well—when fewer senses are engaged in receiving the information, we take in fewer details. These details could be facial expressions which denote sarcasm, inflections which communicate questions versus statements, or endings of words which detail the tense. This is not just the case for visual impairments and auditory impairments, but also for those who have Central Auditory Processing Disorder, those not taking in enough of a particular sense, and for those who take in too much of one sense. Physical and cognitive impairments affecting communication are those which have more traditionally been addressed through speech therapy. As more has become known about the nature of sensory impairments and how they relate to communication, clinicians have been better able to address these needs. Studies are being done which are investigating the relationship between sensory impairments and language acquisition, but this is a complex issue. Each diagnosis (such as DS, autism, etc.) appears to have pieces of sensory issues affecting their language impairments (when they are present), but isolating each of these issues and accounting for the individuality of the way they present in each person is a challenge. In terms of augmentative communication tools with these types of diagnoses, Beukelman and Mirenda

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(1992) found that “examining the requirements (sensory, motor, cognitive, and language) and the effects (rate, accuracy, and fatigue) of various access options is still limited” (p. 67). Seventeen years later we have a few more studies, but not as many as necessary.

sensory All behavior is accompanied by an autonomic nervous system reaction. The sympathetic, parasympathetic, and reticular activating systems make up the autonomic nervous system, located in the brain stem. The sympathetic system is responsible for “fright, flight or fight” arousal. The body reacts to adrenaline release by sweating, dilating pupils, increasing heart rate, and respiration. The parasympathetic system works with the sympathetic providing balance for arousal levels. Together they work for the just right combination that allows for doing and learning. The reticular activating system is responsible for sleep/wake cycles and modulates sensitivity to sensory signals depending on importance for survival. The limbic system is located just above the brain stem and is responsible for the emotional component of behavior. Past experiences create a memory that sets the basic mood for present behavior and reactions to events. New sensory input is interpreted by comparing it to past experiences. These systems work together using an unconscious process to prepare a person for fleeing, or on a conscious cognitive level, for higher function (Messbauer 2005). How we respond to our environment depends on how we are taking in, and processing, sensations from receptors throughout our body. Vestibular sensations are closely associated with auditory sensations, arising from the inner ear, informing the brain of movement, and influencing all other systems. Proprioceptive sensations arise from receptors in our tendons and ligaments around our joints and tell our brain where our body parts are. Proprioception helps us to feel grounded and secure, modulating our vestibular system.

Tactile sensations are located in the skin and are made up of light and pressure touch. Light touch activates the autonomic nervous system, eliciting a sympathetic response. Pressure touch occurs through joint as muscle sensations, eliciting a parasympathetic response. People can react differently when these sensations are processed and perceived as too much or too little. Many of our clients experience some kind of sensory processing sensitivity. “When the brain is not processing sensory input well, it usually is not directing behavior effectively. Without good sensory integration, learning is difficult and the individual often feels uncomfortable about himself, and cannot easily cope with ordinary demands and stresses” (Ayres, 1985, p. 51). When a person is uncomfortable in his or her body they can be defensive. The nature of this defensiveness may be, for example, vestibular, visual, auditory, or tactile in nature. What sometimes appears to be learning or behavioral issue may actually be a sensory processing issue. Gravitational insecurity can be caused by poor processing of vestibular sensation. This can make a person unsure of where their body is in space, leading to fear, clumsiness and difficulty with social relationships. Visual perception problems can cause someone to become lost easily and decrease their willingness to be in strange places or try new things (Ayres, 1985). Auditory defensiveness reduces the verbal communication perceived by the listener. A defensive person may not actually cover his or her ears or look away, but may focus peripherally or on another object. We have observed that being tactilely defensive may prevent a person from touching a communication device. Interestingly, some defensive behaviors may only be present at certain times or situations. Overall, defensiveness can make a person focus so much on avoidance behaviors they are unable to attend to communication. It decreases a person’s interaction with people and objects, thereby limiting the opportunities to practice communication skills. When we can help a client relax and

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decrease their defensiveness, they are better able to increase integration of senses and awareness of their environment. This can ultimately lead to increased communication skills.

communication and developmental disabilities Only a few of the individuals we currently serve at Lifeworks had access to a wide variety of augmentative communication tools while in the public school system. Some of our clients lived in state hospitals; others were in school programs which were just beginning to have students with special needs in the public schools. Access to augmentative communication tools is always limited to what is available to that individual, what the supporting staff know about, and what is invented at the point that people are seeking solutions. New pieces of technology, software, and techniques are being developed all the time, but new solutions for an individual are not always being sought out. Because of the move to community integration, communication requirements for people with disabilities changed dramatically. Adoption of a community-referenced approach to instruction has a direct impact on the quantity and quality of the participation and communication opportunities that are available. Suddenly, the individual needs to order food in a restaurant, cheer for the basketball team, ask for help at the library, greet the school secretary when bringing the attendance list, chat with co-workers at break time – the list of natural opportunities for things to say and people to say them to becomes endless (Beukelman & Mirenda, 1992, pp. 254-255). Some of the communication challenges people are facing now will not occur in 30 years. In the coming years, the majority of individuals being served in day programs will be those who have always lived at home and have always gone to

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public school. That being said, the continual invention of new ways to communicate through assistive technology, and the developments in treatment through MSEs and other techniques, which aid life-long learning, will ensure that there will always be individuals who require more opportunities and tools than are available while they are in school. There have been studies done about communication skills of people with developmental disabilities and autism. Some of these studies have included adults or have solely studied them. There are both positive findings, and interesting discoveries: Despite the variety of participants and methodologies used, research findings are broadly consistent. First, people with intellectual disabilities can and do acquire basic pragmatic language skills, although more subtle aspects of conversational competence are less commonly displayed. Second, the communicative environments of children and adults with intellectual disabilities appear to inhibit the acquisition and display of pragmatic skills (Hatton, 1998, p. 79). Pragmatic skills are “the knowledge of how communication works” (Beukelman & Mirenda, 1992, p. 337). There are some draw backs to the available literature in this area. “Relatively few studies have investigated the pragmatic language use of adults with intellectual disabilities” (Hatton, 1998, p.84). The studies that have been done with adults with cognitive impairments are relatively few, and in each the sample size is small. Iglesia et al. (2005) discuss this in reference to studies of people with DS, but it applies to other groups as well. More research needs to be done, so that intervention success can be measured. This should not disqualify the already published studies which show that adults with cognitive impairments do increase their communication skills in adulthood.

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There are also no comparative data from the population without disability against which to judge the conversational competence of people with intellectual disabilities…(making) it difficult to determine the extent to which ‘incompetent’conversations are due to the incompetence of people with intellectual disabilities, the stereotypes of people without disabilities, or the interactions between the two (Hatton, 1998, p. 87). At Lifeworks, we began to use the term “emerging communicator” to identify adults who were developing communication skills later than during the developmental norms. Others in the fields of speech therapy and augmentative communication use that term with a slight difference. Dowden (1999, as cited in UW Augcomm, n.d.) defines an emerging communicator as “An individual who does not yet have any reliable means of symbolic communication, although he/she typically has non-symbolic communication. This communication, for example using gestures and facial expressions, can be very useful with highly familiar partners, but it tends to be limited to the ‘here and now’ or rely heavily on the partner’s shared knowledge.” Adults in our program generally fall into two categories: those who have some good communication skills and those with quite limited skills. The third group, emerging communicators, are often overlooked. They have quite limited skills (for a variety of reasons), but display hints that they have a greater ability than we had previously helped them access. This differs from Dowden’s (1999, as cited in UW Augcomm, n.d.) definition in that they may be communicating using sign language, picture symbols, augmentative communication devices, and/or speech; but they have a limited vocabulary. Sometimes the individual has a moderate vocabulary and ability to communicate, but they are ready to add more. These opportunities for new language development are occurring quite a bit later than the developmental norms. For example, some people in our program

have expanded their vocabulary verbally or with the support of augmentative communication tools. When time in the MSE is paired with the appropriate communication tools, a person’s communication skills may expand, and there may be an increase in the type of conversations in which the person participates. When this occurs at 40 years of age, for a person with a developmental disability, it is an exciting development. We do fall into line with some of Dowden’s (1999, as cited in UW Augcomm, n.d.) thinking, when stating “some emerging communicators fall within this category because they do not yet have access to appropriate AAC strategies and technologies.” If we expand the concept of technologies to also include access to the equipment in a MSE, as well as qualified therapists and staff who work in an interdisciplinary model, then this brings our concepts of “emerging communicator” closer together. The types of skill development emerging communicators increase could include an increase in vocabulary, sentence length, pragmatics, and/ or social-communication skills.

multi-sensory environments Multi-Sensory Environments used at Lifeworks evolved from the European Snoezelen concept. As stated by Messbauer (2008) for the American Association of Multi-Sensory Environments: It is a dedicated room that attempts to block out noise, control space, temperature and lighting. It brings multi-sensory equipment together in one place to stimulate the senses, promoting pleasure and feelings of well-being. It can be utilized as part of the learning or treatment experience or for leisure and relaxation. It is controlled sensory input, especially designed to promote choice, interaction, and relationships through planned stimulation of the senses. It relieves stress, anxiety and pain. MSEs have been shown to help with autism, brain injury, challenging behaviors, de-

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mentia, developmental disabilities, mental illness, PTSD, special education. It aims to maximize a person’s potential to focus, and then act on this change through an adaptive response to their environment. Multi-Sensory Environments help change behavior, increase focus and attention, and add to feelings of positive self-esteem and well-being (Messbauer, 2008). Equipment used in the MSE works to alert the brain and create a memorable experience. The solar projector throws images on the wall that can be changed by replacing the image wheels to alter arousal levels. A six foot tall bubble tube with changing lights provides intensity and vibration with auditory and tactile opportunities. A two hundred strand light spray with color changes engages the tactile sense and provides proprioceptive input when it is laid across someone’s lap. A vibro-acoustic recliner or mat uses sound vibration to relax and help define body awareness. Mirrors provide multiple-imagery and add to the complexity of the room. A motorized mirror ball can intensify visual and vestibular input to the nervous system. A Catherine-type wheel, which is choice driven, can be used for evaluation, exploration, and changing arousal level. Power links to various pieces of equipment are used to encourage interaction and shape behavior. The equipment in the MSE is introduced slowly, one piece at a time, for client evaluation, self-direction, and motivation (Messbauer, 2005). Lifeworks began by establishing an MSE in one of our centers. We brought our clients into the MSE individually and in small groups. In tracking our statistics, we were able to determine that behavioral incidents in the center decreased by 50% overall, regardless of whether the clients had been in the MSE or not. Our clients and staff enjoyed days that were calmer and allowed for more productive programming. This amazing transformation enabled us to write grants to help fund MSEs at four additional sites.

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The MSE definitely has a documented calming effect. In a study of 15 children with traumatic brain injury, it was found that the MSE evoked a relaxation response as well as decreased heart rate and agitated behaviors (Hotz et al., 2006). There has been a contribution to a sense of control as well as a calming response noted in children with Rett syndrome (Lotan & Shaprio, 2005). In addition to decreasing stress, MSEs have been used to help decrease self-injurious behaviors and agitation. A statistically significant reduction in self-injury was found following MSE exposure with adults with severe or profound mental retardation and mental illness (Singh, 2004). In a group study of 24 participants with moderate to severe dementia, greater independence in activities of daily living was observed, as well as reduced agitation and apathy (Staal, 2005). One study did find carryover for two of three participants in post-session engagement as well as daily frequency of challenging behaviors on days following their MSE and OT sessions (Kaplan, 2005). There is much anecdotal success with behavioral improvements using the MSE. There are, however, few published studies demonstrating statistical significance. The MSE has also been beneficial in increasing communication. The sensory systems— auditory, vestibular, proprioceptive, tactile, and visual—develop interdependently. The auditory and vestibular systems work closely together. Speech and language depend upon the integration of auditory sensations within the vestibular system (Ayres, 1985, p. 63). A number of studies have shown sensory integration to be significant in developing language skills. Ayres and Mailloux (1981) found a consistent increase in the rate of growth in language comprehension and expression in children receiving occupational therapy sensory integration treatment. In a study of children attending school for remedial education, language was found to be the primary deficit area, acknowledging the interrelationship among auditory, visual, somatosensory, motor, and lan-

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guage skills. Integration of the sensory and motor systems weighs heavily in the development of academic skills (Kruger, 2001). Using the MSE contributes to integration of senses by the use of sensory pleasurable experiences. The client chooses which piece of equipment to use as a mode of sensory input as well as how much they receive. By stimulating the visual, vestibular, and auditory systems, clients can increase their ability to communicate their needs. The neuroplastic quality of the brain allows for growth in areas that have been damaged or not previously accessed. A person is encouraged to use the MSE to reduce stress, promote pleasure, control their own environment, and support motivation, creating an environment where they will be more accepting of treatment, thereby making that treatment more effective (Messbauer, 2005).

Augmentative communication Augmentative communication tools include gesture and sign language, picture symbols, and voice-output devices. They can range from quite simple, to quite complex. The work of Christopher Nolan, Anne McDonald, and others who use ‘low technology’ (i.e., non-electronic) systems reminds us that the ultimate goal of an AAC intervention is not to find a technological solution to the communication problem, but to enable the individual to efficiently and effectively engage in a variety of interactions (Beukelman & Mirenda, 1992, p.7). Tool selection is based on many things, and is usually assessed by a speech and language pathologist. Selection is based on the skills of the individual in the areas of motor skills, cognitive skills, visual and auditory. All of these skills are impacted by sensory challenges, as stated earlier. The development of communication skills within the MSE is similar to the process of learning

to communicate as a young child. “Initially, selfdirected child behaviours are treated by caregivers as having a communicative intent, introducing the child to the notion that language can be used to do things” (Hatton, 1998, p. 81). In the MSE, moving towards an object indicates enjoyment or attraction. This can be built upon by using a switch which activates that piece of equipment. Later, using sign language, picture symbols, or voiceoutput devices to request “more” of the desired activity, the more integrated individual has moved from a self-directed behavior, to a communication which can now be understood by others. As this integrated motion and intent of communication is practiced, it leads to further integration, and natural development of skills. Generalization can occur within the room, and more communication skills can be developed. This type of intervention (starting with items of high interest, though not in an MSE) was studied by Koul, Schlosser, and Sancibrian (2001), when looking at individuals with Rett Syndrome. This study found that “individuals with Rett syndrome acquire initial lexical items with an opaque symbol-referent relationship more readily if the referents are of high interest” (Koul et al., 2001, pp. 164-165). Further support for this concept comes from Beukelman and Mirenda (1992): There is simply no doubt about it: The availability of genuine and motivating communication opportunities in integrated and inclusive settings is at least as important to the success of a communication intervention as is the availability of an appropriate access system (p. 258). Koul et al. (2001) also state that the advantage to “the relatively ‘unnatural’ behavioral approaches offer the advantage of eliminating any distracters and making the linguistic stimuli highly salient” (p. 165). The concept of distractibility and impact of stimuli was also discussed by Kruger, Kruger, Hugo and Campbell (2001). In reference to problems with attention during their study, they

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wrote “this fact suggests that attention skills are also important in academic performance and for language ability, central auditory processing, and sensory integration” (Kruger et al., 2001, p. 96). The MSEs have the advantage that the therapist is manipulating the room to have the optimum amount of stimuli for that individual, and can ensure that the focus is on the items of interest, and distractions are eliminated. Cognitive skills such as choice-making, reasoning, and planning often require us to communicate with others, take in information before using it to problem-solve, and then communicate back what we came up with to others. As a person’s body is working more efficiently once their sensory needs have been addressed and they have gained the appropriate communication skills through verbal or augmentative communication tools, they are now able to participate more actively in these types of higher cognitive tasks. Addressing both sensory and communication needs in this way requires a team approach. The team needs to address the needs of the whole person, in as many environments as possible. This enables everyone to get a more complete picture of both the person’s skills and areas that need to be developed. Team members may include an occupational therapist, speech therapist, music therapist, physical therapist, parents or guardian, staff/teachers, social worker, and most importantly—the individual. In day programs for adults with developmental disabilities, this team meets for an annual meeting. Combining MSEs with the use of augmentative communication tools often requires more frequent communication among team members. This concept of a team approach has been looked at by others, but not in terms of combining MSE and augmentative communication tools. In referring to treating people with CAPD, language disorders, sensory integration dysfunction and learning disabilities, an interdisciplinary approach is:

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The most favored approach. .. Unfortunately, it requires more funds and skilled human resources than are presently available. .. An effective, resource-efficient, transdisciplinary model for helping children with CAPD, language disorders, LD, and sensory integration dysfunction will aid in providing an evaluation and intervention program that may be easily implemented using existing resources (Kruger et al., 2001, p. 87). Despite the different disciplines being examined in the interdisciplinary research, many of the complications and issues are the same. Kruger et al. (2001) discuss how the “individual perspectives” of different specialists has them providing “isolated and inefficient treatment” (p. 97). Pena and Quinn (2003) state “effective collaboration between teachers and SLPs can have positive benefits for children with language impairment in daily communicative events and academic achievement” (p. 53). “For groups that function as teams, collaboration is a dynamic learning process” (Pena & Quinn, Winter 2003, p. 61). Each team member at Lifeworks interacts with the individual in different circumstances, requiring different vocabulary, different socialcommunication events, and they see the individual working on these skills in different environments. Each has valuable input, and can positively impact the communication development of the individual as they progress. We are all learning, as well, as a part of the process, especially since certain team members are more experienced with particular types of augmentative communication tools. The therapists bring in cutting edge treatment techniques, and the individual, the direct care staff, and family or guardian are often implementing similar strategies in the creative fashion required in the day-to-day usage of these tools. A device lending library, or access to one, is a fundamental piece to this approach. Sometimes adults with developmental disabilities have difficulty being approved through medical assistance for devices in a timely manner. Others have a

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slower learning curve and need more opportunity to practice with a device before being able to prove it is a good choice for them. Also, if working in an MSE, they may need multiple devices in a short period of time. Lending libraries enable more flexibility during this time of learning, and prevent the purchase of a device which would be only a short-term investment. Lifeworks has a range of devices in their lending library, which include voice output devices, alternative access methods such as switches, software such as those to make picture symbols and displays, and others. We are grateful to our donors and those who have given us grants to purchase this equipment. When we do not have something in our own library, we access outside lending libraries, and have really appreciated their support. Finally, some portions of the therapy work we are able to do at Lifeworks is due to being free from the confines of working within a direct billing system, such as through medical assistance or insurance billing. Though coverage is available for adults with developmental disabilities and autism to see a speech therapist, it is difficult to obtain funding for other traditional therapies. Donations and grants have enabled us to equip our MSEs, our device lending library, and fund a portion of our therapy staff salaries. In addition, this type of team approach in an interdisciplinary fashion is difficult to fund when the therapists are contracted for individual or group treatment. Looking at communication, we need to start with the senses as integrated as possible, which sometimes requires multiple therapists working together at different points in the process. To make reimbursement for these services possible, the entire system will need to change to accommodate these treatment techniques. Though there are more costs up front, in the long run, people who can communicate their needs more effectively will draw less on the health care system and can be more active members of society.

Future reseArcH dIrectIons More research is necessary to support the advantages of access to augmentative communication tools for adult emerging communicators. There is some research supporting the use of MSEs to integrate the senses, however, more needs to be done regarding how they specifically impact communication skills. This research would validate using the MSE in this manner, making reimbursement easier for these services. Ultimately, additional documentation will support increased access and improved techniques for individuals with communication challenges.

concLusIon This chapter puts forward the idea that use of a MSE to decrease defensiveness in the body can promote integration of the senses, and lead a person to be in a better position to communicate their wants and needs. We have also noted that adults with developmental disabilities or autism can sometimes be overlooked as emerging communicators. Shifting this view will increase their access to new tools and techniques for enhancing communication skills. “People with severe disabilities can live, work, play, communicate, and form relationships with a wide variety of people in their communities, schools, and workplaces, and they deserve to be provided with opportunities to do so” (Beukelman & Mirenda, 1992, p. 254).

reFerences Augcomm, U. W. (n.d.). Augmentative and alternative communication at the University of Washington, Seattle. Retrieved October 5, 2009, from http://depts.washington.edu/augcomm/00_ general/glossary.htm

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Ayres, A. J. (1985). Sensory integration and the child. Los Angeles, CA: Western Psychological Services. Ayres, A. J., & Maillous, Z. (1981). Influence of sensory integration procedures on language development. The American Journal of Occupational Therapy., 35(6), 383–390. Beukelman, D. R., & Mirenda, P. (1992). Augmentative and alternative communication: Management of severe communication disorders in children and adults. Baltimore, MD: Paul H. Brookes Publishing Co., Inc. Hatton, C. (1998). Pragmatic language skills in people with intellectual disabilities: A review. Journal of Intellectual & Developmental Disability, 23(1), 79–100. doi:10.1080/13668259800033601 Hotz, G. A., Castelblanco, A., Lara, I. M., Weiss, A. D., Duncan, R., & Kuluz, J. W. (2006). Snoezelen: A controlled multi-sensory stimulation therapy for children recovering from severe brain injury. Brain Injury : [BI], 20(8), 879–888. doi:10.1080/02699050600832635 Iglesia, J., Buceta, M., & Campos, A. (2005). Prose learning in children and adults with Down syndrome: The use of visual and mental image strategies to improve recall. Journal of Intellectual & Developmental Disability, 30(4), 199–206. doi:10.1080/13668250500349391 Kaplan, H., Clopton, M., Kaplan, M., Messbauer, L., & McPherson, K. (2006). Snoezelen multi-sensory environments: Task engagement and generalization. Research in Developmental Disabilities, 27, 443–455. doi:10.1016/j. ridd.2005.05.007 Koul, R., Schlosser, R., & Sancibrian, S. (2001). Effects of symbol, referent, and instructional variables on the acquisition of aided and unaided symbols by individuals with autism spectrum disorders. Focus on Autism and Other Developmental Disabilities, 16(3), 162–169. doi:10.1177/108835760101600304 130

Kruger, R., Kruger, J., Hugo, R., & Campbell, N. (2001). Relationship patterns between central auditory processing disorders and language disorders, learning disabilities, and sensory integration dysfunction. Communication Disorders Quarterly, 22(Winter), 87–98. doi:10.1177/152574010102200205 Lotan, M., & Shaprio, M. (2005). Management of young children with Rett Disorder in the controlled multi-sensory (Snoezelen) environment. Brain & Development, 27, 88–94. doi:10.1016/j. braindev.2005.03.021 Messbauer, L. (2005). The art and science of multisensory environments. Presentation at workshop in Queens, NY. Messbauer, L. (2008). What is a multi-sensory or Snoezelen room? American Association of Multi Sensory Environments. Retrieved from http:// www.aamse.us/faq.php Pena, E., & Quinn, R. (2003). Developing effective collaboration teams in speech-language pathology: A case study. Communication Disorders Quarterly, 24(2), 53–63. doi:10.1177/15257401 030240020201 Singh, N., Lancioni, G. E., Winton, A. S. W., Molina, E., Sage, M., Brown, S., & Groeneweg, J. (2004). Effects of Snoezelen room, activities of daily living skills training, and vocational skills training on aggression and self-injury by adults with mental retardation and mental illness. Research in Developmental Disabilities, 25, 285–293. doi:10.1016/j.ridd.2003.08.003 Staal, J. A., Sacks, A., Matheis, R., Calia, T., Hanif, H., Collier, L., & Kofman, E. (2005, July). The effects of Snoezelen (Multi-Sensory Behavior Therapy) and psychiatric care on agitation, apathy, and activities of daily living in dementia patients on a short term geriatric psychiatric inpatient unit. Poster session presented at the Alzheimer’s Association International Conference, Washington, DC.

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key terms And deFInItIons Augmentative Communication Tools: Picture symbols, sign language and gesture, voice output devices, which can be used to assist in communication. Autism: A developmental brain disorder characterized by impaired social interaction and communication, and restricted and repetitive behavior. The autism spectrum includes Asperger’s Syndrome, Rett Syndrome, Childhood Disintegrative Disorder and Pervasive Developmental Disorder—Not Otherwise Specified. Developmental Disability: Lifelong disability due to cognitive and/or physical impairments beginning early in life.

Multi-Sensory Environment: A designated space designed to alert, or calm the senses. Proprioception: Sensory information received from joints and muscles telling the body about pressure, movement and changes in position in space. Sensory Issues: Difficulty taking in and interpreting sights, sounds, touch, taste and movement. Vestibular: Input from the inner ear telling the body about balance, change in gravity, movement around the body as well as movement of the body.

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Chapter 9

Using Software to Deliver Language Intervention in Inclusionary Settings Mary Sweig Wilson Laureate Learning Systems, Inc., USA Jeffrey Pascoe Laureate Learning Systems, Inc., USA

AbstrAct Language intervention focusing on syntax is an essential component of programs designed to meet the educational needs of children with language disabilities as it provides a foundation for improved communication and literacy. Yet there are challenges to providing individualized syntax intervention on a daily basis in inclusionary settings. The use of assistive technology in the form of language intervention software provides one means to address these challenges. This chapter describes the background, rationale, and use of software designed to provide receptive syntax intervention to build sentence comprehension and use in pre-school and elementary children with disabilities. The software is also appropriate for at-risk students in districts providing early intervening services in a response to intervention model as well as English language learners. Included is an overview of advances in linguistic theory and research that have dramatically increased our understanding of language and how it is acquired by typically and atypically developing children, and which informed the curricular design of the software described. The results of field-testing under naturalistic conditions in classrooms, where regular use of the software was associated with accelerated language development, are also reviewed.

IntroductIon Since the landmark passage of Public Law 94-142 (Education of All Handicapped Children Act) in 1975, society has supported the belief that all children are entitled to a public education. The IndividuDOI: 10.4018/978-1-61520-817-3.ch009

als with Disabilities Education Act (IDEA, 2004) is the direct descendent of PL94-142 and the current law ensuring services to children with disabilities. The law governs how states and public agencies provide early intervention and special education to the millions of eligible children from birth to 21. Students from 3-21 receive special education and related services through Part B of IDEA. The

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Using Software to Deliver Language Intervention in Inclusionary Settings

most important mandate in the law covering Part B is that students with disabilities are entitled to a free appropriate public education (FAPE) in the least restrictive environment (LRE). While “inclusion” does not appear in the legislation, clearly LRE means that to the extent possible children with disabilities should be educated with their neurotypically developing peers. As a society, we don’t believe that children with disabilities should be isolated from their peers but many schools encounter difficulties in providing education to children with disabilities in the general education classroom. Despite general commitment to integration, difficulties are frequently encountered in meeting the needs of children with disabilities in inclusionary environments. Among the difficulties are feelings of regular educators that they lack the skills to deal with special needs students in their classrooms (Hanson, Horn, Sandall, Beckman, Morgan, Marquaart, Darnwell, & Chou, 2001). Children with disabilities are most successfully included when regular and special educators work together on developing classroom-teaching strategies (Goodman & Williams, 2007; McCormick, Won, & Yogi, 2003). One promising approach to meeting the needs of students with disabilities in the general education classroom is through the use of assistive technology (AT) in the form of language intervention software. Before adopting software for use in the classroom, however, speech-language pathologists and special educators must be sure that the programs will deliver research-based intervention that can address a student’s language acquisition needs. This chapter will describe the background, rationale, and use of software designed to provide receptive syntax intervention to build sentence comprehension and use in pre-school and elementary children with disabilities. The programs are also appropriate for at-risk students in districts providing early intervening services in a response to intervention (RTI) model as well as students who are English language learners.

bAckground Advances in linguistic theory and psycholinguistic research over the past quarter century have dramatically increased our understanding of language and how it is acquired by typically and atypically developing children. Children all over the world learning any one of thousands of different languages do so in a remarkably similar manner. First words emerge, word combinations occur, and syntax is mastered at about the same age regardless of the language or culture. What exactly is the nature of the human biological endowment that enables very young children to acquire their first language on such a strikingly consistent timetable? Since its inception (Chomsky, 1955; 1957), generative grammar theory has tried to explain this phenomenon (see Chomsky, 2004 for a brief review). A fundamental assertion emerging from this work is that the rapidity and uniformity of first language acquisition is possible because human infants are born with an innate language faculty (Universal Grammar) that drives and shapes the course of language development (Hauser, Chomsky, & Fitch, 2002). Although this premise was in doubt fifty years ago, today it is accepted with discussion centered only on the precise nature of this innate endowment (Boeckx & Piattelli-Palmarini, 2005; Jenkins, 2004; Laka, 2009). Because our inborn human language capacity orchestrates language acquisition, neurotypically developing children need only language exposure to acquire language, at least insofar as acquisition of the formal grammar component (vocabulary and syntax) of language is concerned. The grammar of a language is composed of the lexicon (the “dictionary” of lexical items/words in the language) and the syntactic computational system that assembles lexical items into sentences. The important distinction here is that, while the ability to use words for communication in social settings, (i.e., pragmatics) is developed through communicative interaction, acquisition of the grammar of a

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language is accomplished through listening; it is dependent upon receptive language input (Pinker, 1994; Radford, 1990; Wexler, 1998). Problems with acquiring the grammatical component of language are characteristic of a broad range of children with language impairments regardless of etiology. For example, while the communication profiles of children with Autism Spectrum Disorders, specific language impairment, Down Syndrome, and deafness may differ, their patterns of language acquisition and deficits are similar (Geurts & Embrechts, 2008; Tager-Flusberg & Calkins, 1990; Tager-Flusberg, 2004). The LanguageLinks®: Syntax Assessment & Intervention and Prepositions! programs (Wilson & Fox, 2007a; 2007b) are designed to assess and train the syntax forms that these children typically struggle with, and yet need to become competent communicators. In designing and developing LanguageLinks and Prepositions!, the goal was to use evidence-based instructional strategies to deliver a syntax assessment and intervention curriculum based on current linguistic theory, language acquisition research, and clinical research. Here we will review the theoretical and research bases of LanguageLinks and Prepositions! programs, present field-testing data demonstrating their effectiveness, and review their use in instructional programs.

universal grammar Principles and Parameters Linguists and biologists believe the innate Universal Grammar that humans are born with is composed of principles that are not dependent upon language input, and a small set of parameters that vary in a binary fashion across languages (Baker, 2001; Hornstein, Nunes, & Grohmann, 2005). Universal principles unite all languages. They don’t have to be learned because they are an invariant component of the genetically endowed language faculty and consequently are known without language experience. One important

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universal principle is the Structure Dependence Principle, holding that all grammatical operations are structure dependent. Regardless of language, all syntactic operations are sensitive to the grammatical structure of the sentences to which they apply. For example, in English we form a yes/no question by interrogative inversion: She is working at home. → Is she working at home? Children will love this game. → Will children love this game? Small children who play with dolls are fun to watch. → Are small children who play with dolls fun to watch? In forming a question from a statement, we don’t simply move the second word to the front of the sentence as it may appear in the first two sentences above; rather the operation is structure dependent. In the case of a standard yes/no question, we move the auxiliary (is, are) or modal (will, might, should) in front of the subject phrase. Unlike universal principles that require no language experience, parameters do require language input or primary linguistic data for their setting. Since all parameters have two possible settings, children need language input to select the proper setting. A fixed set of parameters account for most of the syntactic variations among human languages (Atkinson, 1992; Baker, 2001; Chomsky, 1981; Crain, 1991; Leonard & Loeb, 1988; Radford, 1990; 2004; Roeper & Williams, 1987; Wexler, 1998). Parameters determine such things as word order in a language and whether question words (e.g., who, what, how) move to the front of a sentence (they do in English, they don’t in Chinese). The Minimalist Program (Chomsky, 1995) provides a framework for much of the current linguistic research concerning universal principles and parameters. Important in the Minimalist Program is the concept of heads. The head of a phrase is the key word that determines the properties of the phrase. The universal Headedness Principle stipulates that every phrase must have a head;

Using Software to Deliver Language Intervention in Inclusionary Settings

when two elements combine, one becomes the head. Two parameters that determine word order in a language are associated with this principle. English follows a pattern of subject-verb-object (SVO). This order is determined by two different parameters. The Head-Directionality Parameter determines whether a head of the phrase comes before or after its complement (Object). In English, the head comes before its complement(s). In English we say “hit the ball” where “hit” is the Verb head and “the ball” is its Complement so English is a “head first” language. The specifier-head or subject side parameter determines whether specifiers (subjects) come before or after the head of the phrase. English is a “specifier-first” language in that specifiers or subjects come before their head. For example, in English we say “The boy hit the ball” where “The boy” is the specifier and comes before the Verb “hit.” The two parameters, heads and specifiers, along with their settings determine word order in all languages. The acquisition of language competence can be viewed as a matter of “setting” grammatical parameters through exposure to appropriate receptive language input, combined with the learning of a lexicon. In children with language disorders, exposure to the language surrounding them, that is, primary linguistic data alone, is clearly not adequate. Understanding parameters and the receptive language experiences that “trigger” or “set” them can lead to intervention strategies that are more effective because they target the specific linguistic experiences that may optimize or correct the process of language acquisition on a fundamental (versus symptomatic) level. This suggests that the most successful language intervention should emphasize linguistic input that is likely to interact with innate factors shaping language acquisition, and is likely to “set” the grammatical parameters of the child’s native language (Atkinson, 1992; Hyams, 1986; Lightfoot, 1991; Roeper & Williams, 1987; Roeper, 2007).

the Lexicon In the Minimalist model, the lexicon (the mental dictionary of lexical items or words with their linguistic properties) has taken on a greater role in grammar than it had in earlier generative grammar theory. Each representation of a word in the lexicon consists not only of phonological and semantic properties (sound and meaning), but also syntactic features such as categorial membership (i.e., whether it is a noun, verb, determiner, etc.), inflectional behavior (e.g., how it is marked for number, person, and gender), and in the case of verbs, syntactic argument structure (e.g., run requires only one argument, a subject “The girl runs”; kiss requires two arguments, a subject and an object “The father kisses the baby”; and give typically requires three arguments “The girl gives the baby a toy”). In other words, the Minimalist Program assumes that a complete lexical entry includes the specific roles a word can play in the structure of language and the appropriate form of that word in a given grammatical context. Unlike in past generative grammar theories, lexical entries are now posited to enter the grammatical computational system or sentence forming process already marked with syntactic features (Abraham, Epstein, Thráinsson, & Zwart, 1996; Chomsky, 1995). Developing an early core lexicon is an important step in the acquisition of language. Many think of word learning as simply a process of linking a word’s sound to meaning. The acquisition of word meaning, however, describes only part of what a child is learning even in the single-word stage of language development. Contemporary linguistic theory emphasizes that the child must also be learning the syntactic features of words in relation to the parameter settings of the language being acquired—the grammatical options that distinguish one language from another. Further, children are learning a great deal about the inflec-

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tional properties of the language they are acquiring. That includes such things as how a language marks number agreement of subjects and verbs (e.g., “The boy_ runs / The boys run_”) and how time is expressed (e.g., “The boy is playing / The boy played”). That some grammatical learning occurs during the single-word stage is evidenced by the rapid progression of syntactic competence: typically, at about 12 months a child will begin to produce isolated words with no evidence of grammatical marking. Within another six months or so, however, the child will begin to produce forms such as Determiner “No” (e.g., “No shoe”), the progressive Verb marker -ing (e.g., “running”), and the Genitive or Possessive ‘s (e.g., “the boy’s ball”). There is evidence that by this time a number of crucial parameters have already been set. Hirsh-Pasek, Golinkoff, and colleagues showed that when children as young as sixteen months (still in the one word stage) were presented with televisions showing Big Bird tickling Cookie Monster and vice versa, and then were told, “Oh look! Big Bird is tickling Cookie Monster!” or vice versa, they preferentially attended to the appropriate visual stimulus (Hirsh-Pasek, Golinkoff, Fletcher, DeGaspe-Beaubien, & Cauley, 1985; Hirsh-Pasek & Golinkoff, 1996). This finding demonstrated that both word order parameters had already been set. Further evidence that these parameters are fixed by the time typically developing children enter the two-word stage is provided by the fact that the word order of their utterances adheres to the word order of their native language from the outset, which in the case of English is SVO (Fodor, 2009; Radford, 1990). Within the Principles and Parameters Theory, the lexicon is divided into Lexical Category words (e.g., nouns, verbs, adjectives) and Functional Category words and forms (e.g., determiners, tense, complementizers) that serve essentially grammatical functions. Adger (2003) says that one way to think about Functional Categories “...is that they erect a syntactic skeleton above lexical categories which serves to hold together

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the various syntactic relations that take place in the phrase” (p. 165). The Functional Categories include determiners, tense (in earlier work called inflection or INFL), and complementizers: •

Determiners are associated with nouns and are so-called because they specify (or determine) that to which a Noun expression refers. Determiners include, for example, articles (a, the), prenominal determiners (this, that, these, those) and pronouns (I, you, me, his, her). A Determiner Phrase (DP) is headed by a determiner. Tense is associated with verbs and refers to elements that inflect verbs for tense and agreement. Tense includes, for example, the regular past tense -ed, infinitival to, auxiliary be, and third person singular -s. A Tense Phrase (TP) includes a verb and its inflectional elements. Complementizers include words such as that, if, and whether which serve to introduce and characterize complement clauses in several ways. Also included are various operations involved in the formation of questions (e.g., Interrogative Reversals and Wh-Questions).

•

•

Figure 1 lists Functional Category examples of determiners, tense, and complementizers. Even those not familiar with the current linguistic distinction between Functional and Lexical Categories will immediately recognize that the forms listed in Table 1 are especially problematic for students with language impairments as well as English language learners. The list also provides some explanation of grammatical errors. For Table 1. N

V

Ball

Roll

comes to be replaced by

DP

TP

The ball

isrolling

Using Software to Deliver Language Intervention in Inclusionary Settings

example, children with language impairments sometimes persist in use of accusative case pronouns in the subject position which requires nominative case (“Her” vs. “She”). You’ll note that tense is responsible for checking or valuing nominative case. Children who are not correctly inflecting Verbs thus may use the default English accusative case in the subject position saying, “Him big.” Once they are tense marking (e.g., including copular “be” in this case), they will begin to correctly use nominative case as in “He is big.” This has clinical implications in that work on nominative case clearly should be preceded by work on one or more Tense elements. If nouns, verbs, and adjectives belong to the Lexical Category and determiners, tense, and complementizers belong to the Functional Category, where do prepositions fit in? Prepositions present a challenge to the simple notion of a Lexical - Functional dichotomy. On the one hand, prepositions are typically regarded as a fourth LexicalCategory. Consistent with this categorization is the observation that many prepositions, as with Lexical items in general but not Functional items, have intrinsic semantic content that makes an important contribution to sentence meaning. In other ways, however, prepositions have more in common with the Functional Categories and there is a growing tendency to regard them as such (e.g., Baker, 2003; Littlefield, 2005; Moro, 2008). There are numerous arguments for this view, just a few of which are mentioned here. For example, unlike the Lexical Categories, which are always growing via the addition of new Nouns (computer, cell phone), Verbs (snowboarding, faxing) and Adjectives (groovy, spacey), prepositions are more like Functional categories in that they comprise a closed class; there are relatively few of them (roughly 50 in English, and far fewer in most other languages) and there is little or no tendency to coin new ones. Some have argued that this could to some extent be attributable to the limited set of relationships available to be encoded, but there certainly would seem to

be room for coining at least a few new prepositions now and then; particularly since many of them are currently used to indicate rather diverse relationships (e.g., on the floor/ceiling/spot; on time; on topic; out of the house, out of time, out of kindness). Also unlike Lexical items, prepositions do not accept derivational affixes. nouns, verbs and adjectives can move from one Lexical Category to another by adding an appropriate derivational affix (e.g., -ize, -able, -ish, -ity...; pressure – pressurize; book - bookish), but prepositions cannot; they are always prepositions. The fact that prepositions do not conform to all of the typical features of items in either the Lexical or Functional categories has led some researchers to suggest that the category of prepositions ought to be divided according to the relative proportion of a preposition’s lexical and functional features (Corver & van Riemsdijk, 2001; Littlefield, 2005). In this scheme one would classify semantically rich prepositions as being Lexical, and other prepositions that serve primarily syntactic roles as being Functional. Supporting the validity of this division is evidence from studies of the language of individuals with aphasia (e.g., Froud, 2001), as well as from analyses of children’s first language acquisition (e.g., Littlefield, 2006). Unlike in earlier versions of generative grammar, in current linguistic theory Functional Category words as well as Lexical Category words can serve as the head of a phrase. The concept of heads is very important in linguistic theory. The universal Headedness Principle states that every syntactic structure is a projection of a Head word. Here again we see the importance of the lexicon in current thinking. In forming sentences, the lexicon is key. Those of us who serve children with language disorders should be greatly encouraged with this emphasis on the lexicon. The lexicon, after all, is learned. The learning of Functional Category lexical forms is a component of syntax mastery. Therefore, by emphasizing receptive

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Figure 1. Functional categories with examples

mastery of Functional Category lexical forms we can facilitate syntax acquisition. While many of a child’s earliest multi-morpheme utterances may consist of bare noun and verb phrases, Functional Categories are apparent from the time typically developing children enter the two-word stage (Bohnacker, 1997; Brown, 1973; Engle, 1978; Spaulding, 1980). Indeed, one clinical marker for children with language impairments is the absence or relative infrequency of Functional Category elements in their speech (Leonard, 1998; Trantham & Pedersen, 1976). As the Functional Categories are acquired, the hierarchical nature of sentences emerges. Although

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children in the early word combination stage may produce bare noun and verb phrases, these do not exist in adult English. In sentences generated by competent language users, nouns combine or merge with determiners and become Determiner Phrases. This is true even if there is no overt determiner in a phrase. Similarly, verbs combine or merge with tense elements and become Tense Phrases. Hence, the example in Table 1 (functional elements in bold). This developmental step generally does not proceed smoothly for children with language disorders. In fact, one certain conclusion that can be drawn from the research is that Functional

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Categories are especially problematic for children with language disorders (Bedore & Leonard, 1998; Leonard 1995, 1998; Leonard, Camarata, Pawtowska, Brown, & Camarata, 2006; Rice, 1998; Rice, Wexler, & Cleave, 1995; Rice, Wexler, & Hershberger, 1998; Roeper & Seymour, 1994; Seymour, Roeper, & deVilliers, 2003; Wilson, 2000; Wilson & Pascoe, 1999).

generating sentences Linguists working in the Minimalist Program have made tremendous progress in advancing our understanding of language and its acquisition. In this section we will discuss how linguists describe the generation of sentences. This linguistic view may seem far removed from our subjective experience of producing language, but in fact it provides new insights into the production and comprehension of sentences in all languages. The model also provides direction to scientists working on the biology of language. For example, neuropsychologists have shown that the distinctions between the neural circuitry used to produce nouns and verbs demonstrates that lexical entries code not only semantic information but grammatical properties as well (Caramazza & Shapiro, 2004). Additionally, studies of adults with Broca’s aphasia have revealed very specific syntactic deficits as a result of brain lesions. These deficits are adequately described in terms of aspects of syntactic formulation and comprehension of sentences within the Minimalist Program (Grodzinsky, 2004; 2006). In earlier generative grammar theory, Phrase Structure and Transformational Rules, were the mechanisms proposed for sentence generation. In the Minimalist Program the Computational system of human language (CHL) generates sentences from a lexical array in a principled economical fashion. Two necessary components in sentence generation and comprehension are the lexicon and the syntactic computational system. The first step in generating a sentence is to get the words from the lexicon that will make up the sentence. Linguists

say that we first make a copy of each lexical item that will be used in the sentence from the lexicon and indicate how many times each will be used. In the sentence “He is hitting the ball” the lexical array or numeration would be: the1 he1 is1 hitting1 ball1 Once a lexical numeration has been copied from the lexicon, the syntactic computational system combines words using two operations: Merge combines elements in a binary fashion. Move copies and then repositions words and/or phrases. More recently linguists have begun referring to these two operations as External Merge (Merge) and Internal Merge (Move) because in the case of Merge new material is brought into the structure while in the case of Move material is repositioned (Chomsky, 2002; 2009; Radford, 2009). Using these operations, the computational system builds sentence structures that can be interpreted for sound and meaning. Unlike in earlier versions of generative grammar where sentences were built from the top down, within the Minimalist model sentences are built from the bottom up. To generate the sentence “He is hitting the ball”1 the computational system would first Merge “ball” with “the.” When two elements are combined, one becomes the head that dominates the structure. For example, when “ball” combines or Merges with “the” to form the phrase “the ball,” the head is the determiner “the.” When a noun Merges with a determiner the Functional Category determiner becomes the head. The phrase has the following structure (Figure 2). This is commonly diagramed with abbreviations for determiner, noun, and phrase (Figure 3). With the Merge of “the” with “ball,” we now have a Determiner Phrase (DP) whose head is “the.” The next step would be to Merge the DP

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Figure 2.

Figure 3.

“the ball” which is the complement with the verb “hitting” to form (Figure 4). Then the subject or specifier “he” would be Merged with “hitting the ball” to form the verb phrase (Figure 5). “He” starts out in the specifier position of the verb phrase (VP) where the verb assigns it the Thematic Role of Agent. Although “he” starts in the specifier of the verb phrase, it will later be copied and moved into the specifier position of the tense phrase. The next step would be to Merge the VP with auxiliary “is,” the tense element in the sentence (Figure 6). Now we will need to Move “he” into the tense specifier position. We have to do this in order to have the Nominative Case feature valued by the tense element. You recall it is the tense element that checks for Nominative Case. Unlike many other languages, case in English is only overtly marked on pronouns. Nouns are also marked, but the marking is covert in English.

A simplified diagram of the sentence “He is hitting the ball” follows (Figure 7). In current linguistic theory, even though there is no complementizer in the sentence He is hitting the ball, it has the following structure (Figure 8). The syntactic structures generated by Merge and Move must be interpreted into sound and meaning. The syntactic component interfaces with the external sound or Articulatory-Perceptual system via Phonetic Form (PF). It interfaces with the external meaning or Conceptual-Intentional system via Logical Form (LF). An important characteristic of these syntactic structures then is that the Phonetic Form structure can contain only the sound information necessary to decode/encode a sentence and the Logical Form representation can contain only semantic information. This is because our cognitive system can only interpret meaningful information in a Logical Form. You’ll recall that in the Minimalist model lexical items

Figure 4.

Figure 5.

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Figure 6.

Figure 7.

Figure 8.

enter the syntactic computational system with all their grammatical features. Some of these features are interpretable at the Conceptual-Intentional system interface and some are not. To provide an example, consider the sentence…“He is big.” The pronoun “he” has the following features: 3rd person, masculine, singular, nominative case. The first three features are valued but the case feature is unvalued. The copula “is” in contrast

enters the derivation carrying the valued feature present tense and unvalued person and number features. Grammatical features that come into the derivation valued are viewed as interpretable to the Conceptual-Intentional system. They have meaning. Unvalued features cannot be interpreted and play no role in semantic interpretation. Agreement involves having the tense element (“is”) value the unvalued case on the subject so it can be spelled

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out at the PF interface as the nominative case pronoun “he.” Similarly, the unvalued person and number features on the verb “be” will be valued to reflect agreement with the 3rd person singular subject, “he,” which means it will be spoken as “is.” The case feature on the pronoun and the person and number features on the verb will be immediately deleted after these operations making them “invisible” to the syntactic and semantic components (Radford, 2009). The Minimalist Program is still in its infancy but the insights into language and language acquisition it has provided have inspired the development of promising new approaches to language intervention. In the next section we will discuss the instructional research bases for LanguageLinks and Prepositions!

Instructional research Linguistic theory should guide the choice of content in any language intervention plan, but how to deliver that content should be driven by what we have learned from research into the effectiveness of various instructional methods. While pragmatic competence in social situations revolves around expressive use of language, research has shown that language (vocabulary and syntax) is acquired through listening, not speaking. Language input provides the data necessary for lexical learning and to trigger parameter setting. Pinker (1994) stated this succinctly when he wrote, “It is not surprising that grammar development does not depend on overt practice, because actually saying something aloud, as opposed to listening to what other people say, does not provide the child with information about the language he or she is trying to learn.” (Pinker 1994, p. 280). Critically then, receptive language training, whether it is in the realm of vocabulary or syntax, should play a central role in any intervention plan for children with language impairments regard-

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less of etiology. While the ultimate goal may be to develop communicative competence, that goal cannot be reached without first establishing language competence. Studies have validated the receptive approach to developing language competence. Research has shown that receptive procedures are in fact more effective than expressive imitation procedures in language intervention and can produce gains in production as well as comprehension (Courtright & Courtright, 1976; 1979; Zimmerman & Pike, 1972; Zimmerman & Rosenthal, 1974). The well-established learning principles of behavioral analysis (Holland & Skinner, 1961) provide a foundation for instructional design in all of Laureate’s language assessment and intervention programs including LanguageLinks and Prepositions!. The programs also use principles of explicit or discrete trial instruction which uses carefully controlled instruction and stimulus presentation. Over the past thirty years, research has demonstrated that explicit instruction is effective in teaching a variety of language skills (Justice, Chow, Capellini, Flanigan, & Colton, 2003; Maurice, Green, & Luce, 1996; Wilson, 1977). The language intervention programs also include several kinds of instructional support in training. When pretrial instruction is included, the target stimulus is presented and the target language is spoken before the student is asked to respond. Cueing to the Correct Response (CCR) is also provided on lower training levels. This consists of a variety of visual and auditory attention focusing techniques such as an animated character or an arrow appearing above the correct response target. In addition, two kinds of instructional feedback are used in the programs. Even after CCR has been faded, it is still provided following an incorrect response or if no response is made. This always occurs in the earliest vocabulary training programs and is gradually faded as the student advances in syntax. The student is then given a second chance to respond. The second kind of

Using Software to Deliver Language Intervention in Inclusionary Settings

feedback is Knowledge of the Correct Response (KCR). In KCR, the learner is always told the correct answer, either as part of the reinforcement sequence following a correct response, or as informational feedback following an incorrect response. In all cases, at the end of each trial the learner receives informational feedback indicating the correct response. In our own research, we have found that training just using feedback alone for instruction was effective (Wilson & Fox, 1983). There have been other demonstrations of the effectiveness of these procedures as well, across a range of computer administered instructional programs (Gilman, 1969; Tait, Hartley, & Anderson, 1973; Wilson & Fox, 1981), including Laureate’s language development software (e.g., Finn, Futernick, & MacEachern, 2005; Gale, Crofford, & Gillam, 1999; Gillam, Crofford, Gale, & Hoffman, 2001; Gillam & Loeb, 2005; Gillam, Loeb, Hoffman, Bohman, Champlin, Thibodeau, Widen, Brandl, & Friel-Patti, 2008; Miller, 1993). The use of computer-based language intervention software offers many advantages to clinicians, educators, parents, and administrators. Software programs can provide the highly structured interactions needed to illustrate the formal aspects of language. Additionally, computers provide a cost-efficient delivery system for individualized language intervention. Children can use language intervention software in classrooms and homes and thereby receive individualized services beyond those delivered by a speech-language pathologist. Children also enjoy working with properly designed educational software. One investigation found that three to six year old children with Autism Spectrum Disorder were more attentive and motivated when using a computer, and actually learned and retained more vocabulary than they did during one-on-one instruction with a teacher (Moore & Calvert, 2000). Most importantly, research has shown that language intervention software works. Significantly improved language development and communication skills have

been documented when regular use of language intervention software was added to the ongoing special education curriculum in a typical classroom setting. Moreover, using language intervention software with non-professional adult assistance, children with special needs can make language gains comparable to those seen during individual language therapy with a speech-language pathologist (Gale, Crofford, & Gillam, 1999; Gillam & Loeb, 2005; Gillam, Loeb, Hoffman et al., 2008; Howard, 1986; Schery & O’Connor, 1995; Steiner & Larson, 1991; Wilson & Fox, 1983; 1986).

Applying theory and research To acquire a language, children must be exposed to primary linguistic data (i.e., language input). Based on this input, they must learn the lexicon, set parameters, and become competent users of the computational system to generate sentences. Children with language disorders can experience difficulties with any or all of these linguistic processes. As discussed earlier, receptive language training is best suited to developing a lexicon, setting parameters, and establishing syntactic competence. As such, receptive language intervention should be an essential component in all programs for children with language disorders until they have mastered grammar. For busy clinicians and educators, finding time to provide evidence-based receptive language intervention is difficult. That’s where software can really help. In typically developing children, determiners, tense, and prepositions begin appearing in the early two-word stage. Once a child with a language disorder has entered into the two-word stage, targeted training on Functional Category forms and Prepositions should be provided. Learning determiner, tense, and preposition forms is a critical step in the mastery of syntax. To facilitate the acquisition of these forms, children with language disorders must systematically be exposed to sentences that feature them in highly salient contexts. The LanguageLinks: Syntax Assessment & Intervention

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and Prepositions! programs are designed to help children with syntactic deficits achieve language competence using this approach. These are the first comprehensive syntax intervention programs to be based on current linguistic theory, instructional research, and have field test data to support their use. Figure 9 lists the grammatical forms trained in Levels 1-6 of LanguageLinks, presented as they are trained, in developmental order. Each of the Levels in LanguageLinks contains six Modules, each of which trains either two or three grammatically contrasting determiner or tense forms. The LanguageLinks system will take children with language impairments from the early two-word development stage through the mastery of a broad range of syntactic forms in the determiner and tense categories. In addition to determiners and tense forms, prepositions play an important role in early syntax development. Learning prepositions is an essential step in language mastery since prepositions often make an essential contribution to sentence meaning by signifying relative temporal and spatial relationships of many kinds, as well as relations involving cause, purpose, manner, means, viewpoints, and much more. Fundamentally, prepositions serve to indicate a relationship between elements in a sentence, with one of these elements being the prepositional complement or object (Quirk, Greenbaum, Leech, & Svartvik, 1985). This being the case, it is necessary that prepositions have a complement. Thus, an important step in syntax acquisition involves learning prepositions and their use with complements in prepositional phrases. Prepositions! Sterling Edition was designed to teach ten spatial prepositions (in, on, under, in front of, in back of, next to, above, below, behind, and between) and their use in sentences, a necessary step in the mastery of syntax and toward school success. Spatial or locative prepositions are especially important in early language development. Semantically, these are used to express concepts of location or position. As such, knowledge of spatial

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prepositions plays an important role in ostensive word learning, and is critical to commenting on the position of objects in the environment. Prepositions enter the lexicon early in the word combination stage. The prepositions “in” and “on” are typically cited as the two earliest developing spatial prepositions. These were among the 14 grammatical morphemes studied in Brown’s classic 1973 book A First Language: The Early Stages (1973). Many spatial prepositions consist of a single word (in, on) and are classified as simple, while others consist of a two- or three-word sequence (next to, in front of) and are classified as complex. The earliest prepositions to be acquired are simple ones, although other simple prepositions develop after children have learned some complex forms. For example “behind” develops later than “in back of” (Stemach & Williams, 1988). The six Modules in Prepositions! train 10 essential prepositions in a variety of contexts. Like all the other Sterling Edition language intervention programs, LanguageLinks and Prepositions! both use an expert Optimized Intervention® system to automatically deliver both assessment and intervention-based on student responses.

Optimized Intervention® Optimized Intervention efficiently assesses students then enters them into training at an appropriate level. This system was originally inspired by methodology developed by the Software Technology Branch of the National Aeronautics and Space Administration (NASA) at the Johnson Space Center (Way, 1993). This group had developed software to train space shuttle astronauts that incorporated many useful features. In particular, the software was able to codify the knowledge and skills of professionals to be used to present customized lesson content, evaluate progress during a lesson, and revise the curriculum-based on individual patterns of strengths and weaknesses. In the 1990’s, representatives from NASA and

Using Software to Deliver Language Intervention in Inclusionary Settings

Figure 9. LanguageLinks: syntax assessment & intervention levels and modules

a panel of special educators from the Center for Special Education Technology and the Council for Exceptional Children identified the emerging language problems of children with disabilities as a critical problem in special education that might productively be addressed using NASA’s methodology. Subsequently, Laureate Learning Systems was invited to enter into a Technology Transfer Agreement with NASA. Since that time, Laureate has developed and field-tested a long series of Optimized Intervention systems for language intervention. Critical to this extended endeavor was the support of the National Institutes of Health, including Small Business Innovation Research (SBIR) awards from the National Institute on Deafness and Other Communication Disorders (NIDCD) and the National Institute on Child Health and Human Development (NICHD).2

The Optimized Intervention systems in Laureate’s Sterling Edition software are the culmination of these research and development efforts. The systems use artificial intelligence methodology to select appropriate training material and to adjust instructional support in relation to emerging skills and competencies, resulting in highly individualized and efficient language instruction. The systems also feature extensive data collection and reporting capabilities, thereby greatly simplifying the process of tracking student progress and generating reports detailing areas of strength and weakness. Each Sterling Edition language intervention program has an Optimized Intervention system uniquely designed to test and train its curricular targets in developmental order. All programs begin by probe testing the target words, concepts, or syntactic forms in developmental 145

Using Software to Deliver Language Intervention in Inclusionary Settings

order to ascertain the appropriate place to begin training. Once training begins, Optimized Intervention determines what material a student needs to work on and how much instructional support the student may require to make progress. When using the Optimized Intervention activity in LanguageLinks and Prepositions!, Probe testing to determine where to begin training on a form ends after the third error. Testing continues for all 10 stimuli for a form if the student makes two or fewer errors. Even if a student achieves a score of 80% or higher on one form, it still goes into training if the student fails to demonstrate knowledge of the other form(s) in the Module. Since the forms in a Module present a grammatical contrast, we believe it is important for students to be exposed to all the contrasting forms. Students must be able to discriminate the contrasts in any form family. This also serves to rule out the possibility that a response bias, e.g., always choosing just one of the forms in a family, could be misconstrued as knowledge of the form. For example, in the Module which tests and trains the Me/You contrast, most children who do not know the forms will make errors on both, but there are some children who always choose the item in the foreground (Find the hot chocolate for you) while others always choose the object that the speaker on the screen holding (Find the hot chocolate for me). These latter two groups of children will have a score of 100% on one of the forms, yet clearly do not understand the contrast. Optimized Intervention training continues until a student has demonstrated mastery over all forms in a Module. If the student continues to fail to reach Criterion for a given form or forms in a Module, training on that Module is postponed. Training is resumed after the student has gone through the other Modules on the Level in the case of LanguageLinks, or the remaining Modules in the program for Prepositions! The power of the Optimized Intervention system combined with its ease of use means that speech-language pathologists and other profes-

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sionals can confidently recommend the use of Sterling Edition programs in classrooms, thereby increasing the amount of individualized language intervention services provided in inclusionary settings. Optimized Intervention assures that the program content is being delivered in a sound progression and manner. The extensive data collection and reporting capabilities of the programs ensure that the recommending professional can review in detail a student’s performance within and across sessions. Increasing the amount of individualized language services provided means that students will meet their goals more quickly. While increasing services by providing one on one professional treatment on a daily basis is often prohibitively expensive, that is not the case with computer delivered services. With LanguageLinks and Prepositions!, services can be delivered on a daily basis to all students who could benefit from the training the system provides. It can provide the intensive receptive language intervention needed to establish language competence while freeing the professional to work on additional important goals.

Field testing research on LanguageLinks and Prepositions! In 2005, a field study was conducted in the Medford Massachusetts Public Schools Early Education Program using prototype Modules from what would later become LanguageLinks and Prepositions! (Finn, Futernick, & MacEachern, 2005). Current linguistic theory and research highlights the importance of syntactic competence, but mastery of syntax is especially problematic for children with language impairments. Given the syntax deficits students with language impairments have, it was hypothesized that the use of syntax intervention software designed to train Functional Category determiner and tense forms as well as prepositions would result in greater increases in language scores than use of software designed for vocabulary and concept building.

Using Software to Deliver Language Intervention in Inclusionary Settings

In the Medford study, subjects were 22 preschool children (5 females, 17 males) with initial ages of 3;0 to 4;10 (Mean=4;0). They had been classified as having language impairments prior to enrollment. Subjects were from five classes led by three different teachers. All classrooms included typically developing peers in addition to the children on IEPs. In one classroom, the only special education students were those with an Autism Spectrum Disorder diagnosis. The other classrooms had a mixture of children with Specific Language Impairments, Pervasive Developmental Disorders, and Developmental Disorders. All were receiving speech-language pathology services as part of their program. The language status of each subject was evaluated using the Comprehensive Assessment of Spoken Language (CASL) (Carrow-Woolfolk, 1999). Standard scores on the core tests (Basic Concepts, Syntax Construction, Pragmatic Judgment) for subjects’ age levels were determined and Core Composite (CC) standard scores were calculated. Subjects were matched based on age, CC score, and classroom, and then randomly assigned to the experimental or control group. Classroom computers were set up to run the software. Subjects in the experimental group used prototype Modules from the LanguageLinks and Prepositions! syntax intervention system. Those in the control group used other Laureate programs designed to train vocabulary and categorization. Teachers were asked to use the appropriate software with each subject for approximately 15 minutes per day, several times per week if possible. Children’s interest level and attention span were to be taken into account, however, and no child was to be compelled to participate. Software use continued for 12 weeks. After this, subjects were once again evaluated using the CASL. Children’s CC standard scores before and after software use were analyzed using a two-way (group x trials) mixed design analysis of variance. All but two children had improved CC standard scores at the end of the 12-week study. Overall

gains in scores averaged 7.045 ± 1.58 points (mean ± SEM). This increase was significant (Trials, F(1,20)=22.6, p<0.001). The interaction between treatment group (syntax vs. control) and trials (pre- and post-testing) was not significant, but was in the predicted direction and closely approached conventional levels of significance (group x trials, F(1,20)=3.73, p=0.067). The CC standard scores of children in the experimental group increased by an average of 9.91 ± 2.2 over the 12 weeks. The scores of children in the control group increased by an average of 4.18 ± 2.0. Contributing to the overall improvement in CC standard scores were increases in standard scores on each of the lexical/semantic (Basic), Syntactic, and Pragmatic core subtests. In post hoc analyses, overall increases in Syntactic and Pragmatic but not Basic standard scores were found to be significant (p<.01). On each subtest, score increases were larger among children using the syntax software (Figure 10). Considered in terms of Test-Age Equivalents, advances in the functional language of children using the control software averaged 5.3 months across the three core subtests, while advances of those using the syntax software averaged 8.7 months (Figure 11). While the effectiveness of using language intervention software has been demonstrated previously, those experiments have often involved impracticably intensive intervention schedules or other artificial circumstances. The outcome of the Medford study using the prototype LanguageLinks and Prepositions! software is noteworthy because the intervention was conducted under entirely

Figure 10. Increases in CASL subtest standard scores and CC standard scores of children in each treatment group (mean ± SEM)

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Figure 11. Change in test-age equivalents of subtest raw scores pre- versus post-intervention (Adapted from Finn, Futernick, & MacEachern, 2005)

naturalistic conditions with the aim of maximizing validity. The results demonstrate that syntax assessment and intervention software can provide effective intensified language intervention services in the classroom. In 2008 an additional study using LanguageLinks and Prepositions! was conducted at Clarke School for the Deaf in Northampton Massachusetts (Merchant, de Villiers, & Smith, 2008). Ten oral deaf kindergarten and first grade students served as subjects (ages 5;0-7;0). The children were pre-tested on vocabulary using the Expressive One-Word Picture Vocabulary Test (EOWPVT(Gardner, 1990) and on expressive morphosyntax using a portion of the Diagnostic Evaluation of Language Variation (DELV) (Seymour, Roeper, & de Villiers, 2003). Pre-test scores (time 1) were used to divide the students into two groups with an attempt to balance the two groups by language ability. One group then used the LanguageLinks syntax training software and the second group worked with software that trained vocabulary. After 10 weeks (time 2) all subjects were re-tested with the EOWPVT and the DELV. The groups then traded software programs and received training for another 10 weeks, after which they were again tested (time 3). As such,

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all of the children received training with both the syntax and the vocabulary programs, but in a different order. The children’s scores on the expressive morphosyntax test (DELV) were significantly improved at the completion of the study. A paired ttest on scores at time 3 versus time 1 was significant (t(9)=2.61, p<.03). The more important question, however, was whether differences in children’s pre- and post-test scores on the DELV were simply due to the passage of time, or differed depending on whether they had been in LanguageLinks syntax training or vocabulary training for that period. Comparisons of pre- and post-training scores on the DELV revealed that improvements in expressive morphosyntax were significant when children had been in LanguageLinks syntax training (t(9)=2.53, p<.032) but not when they had been in vocabulary training (t(9)=.68, n.s.). Clearly, LanguageLinks syntax training per se was associated with significant improvements in expressive morphosyntax. What about expressive vocabulary growth? Since all children used both the syntax and vocabulary programs, a growth in vocabulary from time 1 to time 3 was predicted and this was found (t(9)=6.19, p<.001). Additional comparisons to

Using Software to Deliver Language Intervention in Inclusionary Settings

Figure 12. Pre- and post-test scores on the DELV morphosyntax production task (Adapted from Merchant, de Villiers, & Smith, 2008)

determine whether the two training programs had a differential effect on post-training EOWPVT scores revealed that improvements in expressive vocabulary were significant when children had been in vocabulary training (t(9)=3.5, p< .001) and when they had been in syntax training (t(9)=2.44, p<.04). Thus while differential improvements in expressive morphosyntax could clearly be attributed to LanguageLinks training, the analogous pattern was not seen with vocabulary training; vocabulary growth during the study was not dependent upon which program was being used. (see Figures 12 and 13) To summarize, this study found that the expressive morphosyntax scores of oral deaf children increased significantly after using LanguageLinks for 10 weeks, but not after using vocabulary software for a similar period of time. It is also notable and encouraging that, while the LanguageLinks software provides receptive syntax training, the measured gains were in expressive syntax. These two well-controlled field studies demonstrate the effectiveness of classroom use of LanguageLinks and Prepositions! in improving

the expressive syntax abilities of pre-school and school age children.

use in Instructional Programs LanguageLinks and Prepositions! were designed so that they can be used by children independently in their classrooms. Most professionals will use Optimized Intervention to provide intensive individualized intervention with appropriate lesson content and instructional support. Speechlanguage pathologists can also recommend classroom use of the programs knowing it will be easy to show teachers and teaching assistants how to use the software. Once the identifying information on a student has been entered and the appropriate settings chosen (e.g., response time, standard session length, interface), anyone can start the student on the program. No training is needed, as the person only has to choose the student’s name and program then click “GO.” A wide range of children can benefit from using these new syntax assessment and intervention programs designed to improve communication abilities. LanguageLinks and Prepositions! train

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Figure 13. Pre- and post-test scores on the EOWPVT vocabulary test (Adapted from Merchant, de Villiers, & Smith, 2008)

determiner, tense, and preposition forms that start to emerge when typically developing children enter the two-word stage. Thus the programs are appropriate for use with children as soon as they begin combining words. Children can use the programs until they have mastered all the forms covered. In typically developing children this would be around four years of age. In the case of children with language impairments, mastery might not emerge until well into the elementary school years. Regardless of etiology, children with language impairments have problems mastering grammatical forms. Therefore, LanguageLinks and Prepositions! are appropriate for children with Autism Spectrum disorders, developmental disabilities, specific language impairment, and hearing impairments among others. They are also appropriate for use with pre-school and elementary age English language learners. Additionally, syntax intervention is a missing component in many programs serving children at risk for reading failure in a RTI model. Yet mastery of syntax is critical to the development of reading comprehension (Scott, 2009). When individualized language intervention can be delivered on a daily basis in inclusionary settings, students benefit because 150

syntax mastery provides a foundation for improved communication as well as reading.

AcknoWLedgment Throughout the development of LanguageLinks and Prepositions! we worked closely with our consultants Jill de Villiers, Ph.D. of Smith College and Tom Roeper, Ph.D. of The University of Massachusetts. The research, development and field testing of the LanguageLinks and Prepositions! curriculum, Optimized Intervention, and the Sterling Administration System was supported in part by Small Business Innovation Research (SBIR) awards 1R43 DC02601-01A1, 2R44 DC02601-02, 1 R43 DC04487-01, and 2 R44 DC04487-02 from the National Institutes of Health.

reFerences Abraham, W., Epstein, S., Thráinsson, H., & Zwart, C. (Eds.). (1996). Minimal ideas: Syntactic studies in the minimalist framework. Amsterdam: John Benjamins Publishing Co.

Using Software to Deliver Language Intervention in Inclusionary Settings

Adger, D. (2003). Core syntax: A minimalist approach. New York: Oxford University Press.

Chomsky, N. (1957). Syntactic structures. The Hague: Mouton & Co.

Atkinson, M. (1992) Children’s syntax: An introduction to principles and parameters theory. Oxford, UK.

Chomsky, N. (1981). Lectures on government and binding. Dordrecht, The Netherlands: Foris.

Baker, M. C. (2001). The atoms of language. New York: Basic Books. Baker, M. C. (2003). Lexical categories: Verbs, nouns, and adjectives. Cambridge, UK: Cambridge University Press. doi:10.1017/ CBO9780511615047 Bedore, L., & Leonard, L. (1998). Specific language impairment and grammatical morphology: A discriminate function analysis. Journal of Speech and Hearing Research, 41, 1185–1192. Boeckx, C., & Piattelli-Palmarini, M. (2005). Language as a natural object – linguistics as a natural science. Linguistic Review, 22, 447–466. doi:10.1515/tlir.2005.22.2-4.447 Bohnacker, U. (1997). Determiner phrases and the debate on functional categories in early child language. Language Acquisition, 6(1), 49–90. doi:10.1207/s15327817la0601_3 Brown, R. (1973). A First Language: The early stages. Cambridge, MA: Harvard University Press. Caramazza, A., & Shapiro, K. (2004). The representation of grammatical knowledge in the brain. In Jenkins, L. (Ed.), Variation and universals in biolinguistics (pp. 147–167). Amsterdam: Elsevier B.V. Carrow-Woolfolk, E. (1999). CASL: Comprehensive assessment of spoken language. Circle Pines, MN: American Guidance Service. Chomsky, N. (1955). The logical structure of linguistic theory. Cambridge, MA: Mimeographed Monograph, MIT Library.

Chomsky, N. (1995). The minimalist program. Cambridge, MA: MIT Press. Chomsky, N. (2002). An interview on minimalism. In Chomsky, N. (Ed.), On nature and language (pp. 92–161). Cambridge, UK: Cambridge University Press. doi:10.1017/CBO9780511613876.005 Chomsky, N. (2004). Language and mind: Current thoughts on ancient problems. In Jenkins, L. (Ed.), Variation and universals in biolinguistics (pp. 379–405). Cambridge, MA: Elsevier. Chomsky, N. (2009). Introduction. In PiattelliPalmarini, M., Uriagereka, J., & Salaburu, P. (Eds.), Of minds & language: A dialogue with Noam Chomsky in the Basque Country (pp. 13–43). Oxford: Oxford University Press. Corver, N., & van Riemsdijk, H. (Eds.). (2001). Semi-lexical categories (Studies in Generative Grammar 59). Berlin: Mouton de Gruyter. Courtright, J., & Courtright, I. (1976). Imitative modeling as a theoretical base for instructing language-disordered children. Journal of Speech and Hearing Research, 19, 655–663. Courtright, J., & Courtright, I. (1979). Imitative modeling as a language intervention strategy: The effects of two mediating variables. Journal of Speech and Hearing Research, 22, 389–402. Crain, S. (1991). Language acquisition in the absence of experience. The Behavioral and Brain Sciences, 14, 597–650. Engle, C. (1978). A Single Subject Study of Multimorpheme Structures in Early Language Development. Unpublished Master of Science Thesis, University of Vermont.

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Finn, D., Futernick, A., & MacEachern, S. (2005). Efficacy of language intervention software in preschool classrooms. Paper presented at the annual meeting of the American Speech-Language-Hearing Association, San Diego, November, 2005. Fodor, J. D. (2009). Syntax Acquisition: An evaluation measure after all? In Piattelli-Palmarini, M., Uriagereka, J., & Salaburu, P. (Eds.), Of minds & language: A dialogue with Noam Chomsky in the Basque Country (pp. 256–277). Oxford, UK: Oxford University Press. Froud, K. (2001). Prepositions and the lexical/ functional divide: Aphasic evidence. Lingua, 111, 1–28. doi:10.1016/S0024-3841(00)00026-7 Gale, M., Crofford, J., & Gillam, R. (1999). Fast ForWord vs. Laureate Learning Systems: Comparative outcomes. Paper presented at the annual meeting of the American SpeechLanguage-Hearing Association, San Francisco, November, 1999. Gardner, M. F. (1990). Expressive One-Word Picture Vocabulary Test-Revised. Novato, CA: Academic Therapy Publications. Geurts, H. M., & Embrechts, M. (2008). Language profiles in ASD, SLI, and ADHD. Journal of Autism and Developmental Disorders, 38, 1931–1943. doi:10.1007/s10803-008-0587-1 Gillam, R., Crofford, J., Gale, M., & Hoffman, L. (2001). Language change following computerassisted language instruction with Fast ForWord or Laureate Learning Systems software. American Journal of Speech-Language Pathology, 10, 231–247. doi:10.1044/1058-0360(2001/021) Gillam, R., & Loeb, D. (2005). A comparison of language intervention programs. Paper presented at the American Speech-Language-Hearing Association Schools Conference, Indianapolis, July 2005.

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Gillam, R. B., Loeb, D. F., Hoffman, L. M., Bohman, T., Champlin, C., & Thibodeau, L. (2008). The Efficacy of Fast ForWord-Language Intervention in School-Age Children with Language Impairment: A Randomized Clinical Trial. Journal of Speech-Language-Hearing Research, 51, 97–119. doi:10.1044/1092-4388(2008/007) Gilman, A. (1969). Comparison of several feedback methods for correcting errors by computerassisted instruction. Journal of Educational Psychology, 60, 503–508. doi:10.1037/h0028501 Goodman, G., & Williams, C. M. (2007). Interventions for increasing the academic engagement of students with autism spectrum disorders in inclusive classrooms. Teaching Exceptional Children, 39, 53–61. Grodzinsky, Y. (2004). Variation in Broca’s Region: Preliminary cross-methodological comparisons. In Jenkins, L. (Ed.), Variation and universals in biolinguistics (pp. 172–189). Oxford: Elsevier B.V. Grodzinsky, Y. (2006). A blueprint for a brain map of syntax. In Grodzinsky, Y., & Amunts, K. (Eds.), Broca’s Region (pp. 83–107). New York: Oxford University Press. doi:10.1093/acprof:os o/9780195177640.003.0006 Hanson, M., Horn, E., Sandall, S., Beckman, P., Morgan, M., & Marquaart, J. (2001). After preschool inclusion: children’s educational pathways over the early school years. Exceptional Children, 68, 65–83. Hauser, M. D., Chomsky, N., & Fitch, W. T. (2002). The faculty of language: What is it, who has it, and how did it evolve? Science, 298, 1569–1579. doi:10.1126/science.298.5598.1569 Hirsh-Pasek, K., Golinkoff, R., Fletcher, P., DeGaspe-Beaubien, F., & Cauley, K. (1985). In the beginning: One-word speakers comprehend word order. Paper presented at the Boston Child Language Conference, Boston, October 1985.

Using Software to Deliver Language Intervention in Inclusionary Settings

Hirsh-Pasek, K., & Golinkoff, R. M. (1996). The origins of grammar: Evidence from early language comprehension. Cambridge, MA: The MIT Press. Holland, J., & Skinner, B. F. (1961). The analysis of behavior. New York: McGraw-Hill. Hornstein, N., Nunes, J., & Grohmann, K. (2005). Understanding minimalism. New York: Cambridge University Press. Howard, R. (1986). Microcomputer applications in speech pathology. In Northern, J. (Ed.), The personal computer for speech, language, and hearing professionals (pp. 101–112). Boston: Little, Brown & Company. Hyams, N. (1986). Language acquisition and the theory of parameters. Cambridge, MA: The MIT Press. Jenkins, L. (Ed.). (2004). Variation and universals in biolinguistics. Amsterdam: Elsevier B.V. Justice, L., Chow, S., Capellini, C., Flanigan, K., & Colton, S. (2003). Emergent literacy intervention for vulnerable preschoolers: relative effects of two approaches. American Journal of Speech-Language Pathology, 12, 320–332. doi:10.1044/1058-0360(2003/078) Laka, I. (2009). What is there in Universal Grammar? On innate and specific aspects of language. In Piattelli-Palmarini, M., Uriagereka, J., & Salaburu, P. (Eds.), Of minds & language: A dialogue with Noam Chomsky in the Basque Country (pp. 329–343). Oxford: Oxford University Press. Leonard, L. (1995). Functional categories in the grammars of children with specific language impairments. Journal of Speech and Hearing Research, 38, 1270–1283. Leonard, L. (1998). Children with specific language impairment. Cambridge, MA: MIT Press.

Leonard, L., Camarata, S., Pawtowska, M., Brown, B., & Camarata, M. (2006). Tense and agreement morphemes in the speech of children with specific language impairment during intervention: Phase 2. Journal of Speech and Hearing Research, 49, 749–770. doi:10.1044/1092-4388(2006/054) Leonard, L., & Loeb, D. (1988). Governmentbinding theory and some of its applications: a tutorial. Journal of Speech and Hearing Research, 31, 515–524. Lightfoot, D. (1991). How to set parameters: Arguments from language change. Cambridge, MA: MIT Press. Littlefield, H. (2005). Lexical and Functional Prepositions in Acquisition: Evidence for a Hybrid Category. Boston University Conference on Language Development 29, Online Proceedings Supplement. Littlefield, H. (2006). Syntax and acquisition in the prepositional domain: Evidence from English for fine-grained syntactic categories. Dissertation, Boston University. Maurice, C., Green, G., & Luce, S. (Eds.). (1996). Behavioral intervention for young children with Autism. Austin, TX: Pro-ed. McCormick, L., Won, M., & Yogi, L. (2003). Individualization in the inclusive preschool: A planning process. Childhood Education, 79, 212–217. Merchant, G., de Villiers, J., & Smith, S. (2008). Optimized intervention software benefits grammar skills in young oral deaf children. Paper presented at the Council for Exceptional Children Convention and Expo, Boston, MA, April 2008. Miller, J. (1993). The effectiveness of computerassisted instruction in language intervention. Ph.D. dissertation, Department of Education, University of Kentucky, Lexington, KY.

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Using Software to Deliver Language Intervention in Inclusionary Settings

Moore, M., & Calvert, S. (2000). Vocabulary acquisition for children with autism: Teacher or computer instruction. Journal of Autism and Developmental Disorders, 30, 359–362. doi:10.1023/A:1005535602064

Roeper, T., & Seymour, H. (1994). The place of linguistic theory in the theory of language acquisition and language impairment. In Levy, Y. (Ed.), Other children, other languages (pp. 305–330). Hillsdale, NJ: Lawrence Erlbaum.

Moro, A. (2008). The boundaries of babel. Cambridge, MA: MIT Press.

Roeper, T., & Williams, E. (Eds.). (1987). Parameter setting. Dordrecht, The Netherlands: D. Reidel.

Pinker, S. (1994). The language instinct. New York: William Morrow. Quirk, R., Greenbaum, S., Leech, G., & Svartvik, J. (1985). A comprehensive grammar of the English language. New York: Longman, Inc. Radford, A. (1990). Syntactic theory and the acquisition of English syntax. Oxford, UK: Basil Blackwell Ltd. Radford, A. (2004). Minimalist syntax: Exploring the structure of English. Cambridge, UK: Cambridge University Press. Radford, A. (2009). Analyzing English sentences: A minimalist approach. Cambridge, UK: Cambridge University Press. Rice, M. (1998). In search of a grammatical marker of language impairment in children. Language Learning and Education (ASHA Special Interest Division 1), 5(1), 3-7. Rice, M., Wexler, K., & Cleave, P. (1995). Specific language impairment as a period of extended optional infinitive. Journal of Speech and Hearing Research, 38, 850–863. Rice, M., Wexler, K., & Hershberger, S. (1998). Tense over time: the longitudinal course of tense acquisition in children with specific language impairment. Journal of Speech and Hearing Research, 41, 1412–1431. Roeper, T. (2007). The prism of grammar. Cambridge, MA: MIT Press.

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Schery, T., & O’Connor, L. (1995). Computers as a context for language intervention. In Fey, M., Windsor, J., & Warren, S. (Eds.), Language intervention: Preschool through the elementary years (pp. 275–314). Baltimore: Brookes Publishing. Scott, C. (2009). A case for the sentence in reading comprehension. Language, Speech, and Hearing Services in Schools, 40, 184–191. doi:10.1044/0161-1461(2008/08-0042) Seymour, H., Roeper, T., & de Villiers, J. (2003). Diagnostic evaluation of language variation. San Antonio: The Psychological Corporation. Spaulding, K. (1980). Multimorpheme structures in emerging grammar: A single subject study. Unpublished Master of Science Thesis, University of Vermont. Steiner, S., & Larson, V. (1991). Integrating microcomputers into language intervention with children. Topics in Language Disorders, 11, 18–30. Stemach, G., & Williams, W. B. (1988). Word express: The 1st hundred words of spoken English. Novato, CA: Academic Therapy Publications. Tager-Flusberg, H. (2004). Language and communication disorders in autism spectrum disorders. In Bauman, M., & Kemper, T. (Eds.), The neurobiology of Autism (2nd ed., pp. 45–58). Baltimore, MD: Johns Hopkins University Press.

Using Software to Deliver Language Intervention in Inclusionary Settings

Tager-Flusberg, H., & Calkins, S. (1990). Does imitation facilitate the acquisition of grammar? Evidence from a study of autistic, Down syndrome and normal children. Journal of Child Language, 17, 591–606. doi:10.1017/S0305000900010898 Tait, K., Hartley, J., & Anderson, R. (1973). Feedback procedures in computer-assisted arithmetic instruction. The British Journal of Educational Psychology, 43, 161–171. Trantham, C., & Pedersen, J. (1976). Normal language development: The key to diagnosis and therapy for language-disordered children. Baltimore: The Williams & Wilkins Company. Way, R. (1993). Intelligent tutoring and training white paper. Houston, TX: National Aeronautics and Space Administration, Software Technology Branch. Wexler, K. (1998). Very early parameter setting and the unique checking constraint: A new explanation of the optional infinitive stage. Lingua, 106, 23–79. doi:10.1016/S0024-3841(98)00029-1 Wilson, M. (1977). Syntax Remediation: A generative grammar approach to language development. Cambridge, MA: Educator’s Publishing Service, Inc. Wilson, M. (2000). The Wilson Syntax Screening Test. San Antonio: The Psychological Corporation. Wilson, M., & Fox, B. (1981). A study of feedback effects in microcomputer administered receptive language training. Unpublished manuscript. Wilson, M., & Fox, B. (1983). Microcomputers: A clinical aid. In Winitz, H. (Ed.), Treating language disorders: For clinicians by clinicians (pp. 235–248). Baltimore: University Park Press. Wilson, M., & Fox, B. (1986). Microcomputer language assessment, intervention, and enhancement. In Northern, J. (Ed.), The personal computer for speech, language, and hearing professionals (pp. 101–111). Boston: Little, Brown & Company.

Wilson, M., & Fox, B. (2007a). LanguageLinks: Syntax Assessment and Intervention. Winooski, VT: Laureate Learning Systems, Inc. Wi l s o n , M . , & F o x , B . ( 2 0 0 7 b ) . Prepositions!Winooski, VT: Laureate Learning Systems, Inc. Wilson, M., & Pascoe, J. (1999). Evaluation of a grammatical markers screening test for specific language impairments. Paper presented at the annual meeting of the American SpeechLanguage-Hearing Association, San Francisco, November 1999. Zimmerman, B., & Pike, E. (1972). Effects of modeling and reinforcement on the acquisition and generalization of question-asking behavior. Child Development, 43, 892–907. doi:10.2307/1127640 Zimmerman, B., & Rosenthal, T. (1974). Observational learning of rule-governed behavior by children. Psychological Bulletin, 81, 29–42. doi:10.1037/h0035553

key terms And deFInItIons Complementizers: This syntactic category includes words such as that and which when they are used to introduce and characterize complement clauses in various ways, as well as a range of operations involved in the formation of questions. Determiners: This syntactic category is associated with Nouns and is so-called because Determiners specify (or determine) that to which a Noun expression refers. Determiners include, for example, articles and pronouns. Functional Categories: This part of the lexicon includes words and forms that serve essentially grammatical functions, such as Determiners, Tense, Complementizers.

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Lexical Categories: This part of the lexicon includes words that serve as Nouns, Verbs, and Adjectives. Optimized Intervention: This is a methodology developed to present language intervention curricula in a highly individualized and optimally efficient manner by automatically selecting appropriate training material and adjusting instructional support in relation to emerging skills and competencies. Tense: This syntactic category is associated with Verbs and refers to elements that inflect Verbs for tense and agreement. Tense includes, for example, the regular past tense -ed, auxiliary be, and third person singular -s. Universal Grammar: Contemporary linguistic theory describes Universal Grammar as consisting of a series of principles that govern

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the forms of that human language, and a set of parameters that vary across languages in binary fashion. All human languages have these principles and parameters in common.

endnotes 1

2

The diagram of this sentence has been simplified through the omission of the vP shell. Small Business Innovation Research (SBIR) grants 2R43 DC2709-01, 1R43 DC0260101A1, 2R44 DC02601-02, 1R43 DC0448701, 2R44 DC04487-02 from NIDCD, and 2R44 HD35255-02 and1R43 HD3333301A1 from NICHD.

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Chapter 10

Switch Technologies Cindy Nankee UTLL (Universal Technology for Learning & Living), USA

AbstrAct The purpose of this chapter is to provide information about the use of switches in the field of assistive technology. Information included in this chapter will benefit assistive technology professionals, case managers, educators, physical therapists, occupational therapists, speech and language pathologists, rehabilitation counselors as well as students of these professions and consumers. The information will apply to all age groups including birth to six, all levels of primary and secondary education, adulthood and senior services. This chapter will go from assessment to implementation. First this chapter will look at the background information including the what, why, when, and where of switches. Next, this chapter will provide instruction on a variety of assessments available to aid in matching an appropriate switch to a client’s skill set and task requirement. The chapter also discusses types of switches that can access toys, computers, communication devices, environmental controls, recreation, and mobility options. Finally, the chapter presents strategies for successful implementation including the prompt hierarchy, an action plan, data collection, and writing assistive technology into the Individualized Education Program.

IntroductIon A switch is a device or piece of equipment commonly used to turn things on and off as in a light switch. The light itself is a separate fixture with light bulbs and wiring and a plate for securing it to the ceiling with nuts and bolts. The light switch is DOI: 10.4018/978-1-61520-817-3.ch010

not the light fixture; the switch simply turns it on and off. A switch used as an assistive technology (AT) device turns things on and off as does a light switch. It is important to point this out when talking about switches and AT because using a switch with a student or client is not an activity, it is simply the access to the activity, turning it on and off, making the connection. A switch provides access to an activity for the physically and cognitively challenged.

Copyright © 2010, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

Switch Technologies

A switch may be a simple on and off connection or a complex electronic switch programmed to perform a multitude of functions. A switch is used in conjunction with other technologies, allowing access to a communication device or computer, making it possible for someone who is physically or cognitively challenged to interact with the same instructional technology the rest of their classmates have access to. Technology is so vast with definitions for an expansive list of technologies. The differentiating phrase for AT is in the IDEA (Individual with Disabilities Education Act) definition describing the user as “a person with a disability.” The identification of “a person with a disability” may range from mild to severe and may involve cognitive impairment or physical impairment or both. Individuals with disabilities have the potential to benefit from technology in many areas including communication, education, employment, and independent living. The intent of this chapter is not to delve into the definitions and historical background of AT, but to focus on the specifics of switch technologies. For an in-depth study of the historical background of AT and the historical legal mandates, Blackhurst (2004) writes a chapter on Historical Perspectives in the Handbook of Special Education Technology Research and Practice. The implementation path for information/ educational technology (IT/ET) may require acquisition of the technology, it may require instruction, a trial period with follow-up support and this is enough for the individual to benefit from the technologies available to help them become more informed, efficient and independent at school and in the work place. Individual’s with significant physical impairment may also benefit from the same technologies and implementation path including acquisition, instruction, trial and follow-up support, though may have the inability to access the technology due to physical or cognitive limitations. This is when switch technologies or access must be considered. The implementation of

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AT for access to communication, education, employment, and independent living for individuals is the focus of this chapter. The many applications of IT and ET available once access is achieved through switch technologies are extensive and will not be covered in this chapter. The objectives of this chapter are to: • •

•

•

Provide information of best practices in the area of switch technologies. Provide information of various switch technologies in order to assess clients and make appropriate recommendations. Provide information of appropriate assessments to be used in selecting and locating switches for maximum benefit to the client. Provide information in teaching strategies for successful switch use.

sWItcH bAsIcs What A switch is a device used to connect and disconnect an electrical circuit, for example a light switch. To further explain a switch as it is used as an AT device, the Merium-Webster dictionary defines assistive as designed or intended to assist disabled persons and defines technology as a manner of accomplishing a task especially using technical processes, methods, or knowledge. Havng said this, a switch used as an AT device would be a device used to connect and disconnect an electrical circuit, intended to assist disabled persons to accomplish a task especially using technical processes, methods, and knowledge. The key word and important point to understand in defining a switch as an AT device is that a switch is a “device”, not an activity. The device assists a person to accomplish something; it is the access to an activity. Access is the means by which a person controls an AT device. Computers, toys, EADL’s may all be accessed by

Switch Technologies

a switch. A power wheelchair may be accessed by a joystick, proximity or electronic switches. A communication device may be accessed by switch scanning with one or more switches.

Why The easiest and most efficient method to access a device or activity would be direct selection, or reaching out and directly touching the device. Assisted direct selection would be reaching out and touching the device with using a head pointer or other adapted pointing tool. A switch may be used because direct selection or assisted direct selection of a device or activity is not possible or not the best or most efficient access to a device.

When A switch may be used for play to activate toys, computer games or communication devices for social interaction. A switch may be used in education to access a computer to complete assignments in reading, writing, math, social studies, history, and to research the World Wide Web. A switch may be used to access a communication device for school, work, and home communications. A switch may be used to access recreation and the arts including musical devices and instruments. A switch may be used with environmental controls to access door openers, lights, safety devices, and home electronics. A switch is used to activate powered wheelchairs.

Where to start • • • • • •

Obtain knowledge: attend a training, read, check out switches from a Loan Library. Consult with the team: OT, PT, SLP, Teachers, AT. Rule out direct accessibility. Assessments Trial Use Access and mounting

Assessment An assessment is necessary in order to select an appropriate switch and match it to the task and the person’s skill level. Assessment may be performed using a specifically designed assessment or through trial and observation. Through assessment we want to find the most efficient and fastest accessibility that requires the least amount of effort. We need to determine the task requirement of the switch; what the switch will be activating—a communication device, a computer, a toy, or a wheelchair, to name only a few activities. We need to assess the person’s skill level for activating the switch. Will the person be able to locate the switch; are they capable of a momentary hit, a sustained hold as needed to drive a wheelchair or a quick release as in stopping a wheelchair? Are they able to visually, cognitively and motorically time a switch hit as needed for a scanning computer program or communication device? Occupational Therapists, Physical Therapists, Speech and Language Pathologist, and Assistive Technology Professionals of various backgrounds are all skilled in making objective observations in order to determine the most appropriate tool to complete the task. In order to perform an observation one must have access to various switches, equipment, devices, and software that will be activated by a switch. Professionals working in this field often collect various switches and items creating their own “assessment toolkit.” Another source to be explored is an equipment lending library developed in some states under grant funding. Also some vendors offer a trial period with their products. With appropriate switches and equipment on hand, the key to a productive observation is documentation. A one time observation may obtain important information but an extended trial period with documentation will more accurately determine the tools success in various environments and situations. An observation should be conducted in the environment that the equipment will be used in when possible.

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An example of a trial use guide is available as a free download through the Wisconsin Assistive Technology Initiative. There are assessments available on the market that are specifically designed to help determine appropriate equipment selection, gather data, create a report, and many also provide implementation strategies. The following assessments discussed here are just a few which may be beneficial in determining appropriate switch selection. Assessing Students’ Needs for Assistive Technology (ASNAT) 5th Edition (Reed; Wisconsin Assistive Technology Initiative, 2009). The ASNAT is a resource guide developed by Wisconsin Assistive Technology Initiative (WATI) to guide school district Assistive Technology Teams in assessing students’ needs for AT. The process focuses on team decision-making and follows the SETT (Student, Environment, Task, Tool) framework (Zabala, 1995). The SETT framework looks at the student, the environment, the task and tools. The manual includes chapters specific to the assessment process, background on the laws related to AT, overviews of AT for computer access, communication, reading, studying, math, recreation, leisure, ADL’s, positioning, seating and mobility, vision and hearing, documenting AT into the IEP (the Individualized Education Program) and funding. The appendix includes AT forms for gathering information, a decision-making guide, a trial use guide and an AT continuum. This assessment manual is available as a free download and also for purchase through the product sales link at www.wati.org. Every Move Counts, Clicks and Chats (EMC3) (Korsten, Foss, & Berry, 2008). EMC3 is an update and expansion of Every Move Counts, a non-traditional, sensory-based communication assessment and evidence-based intervention strategies for individuals with severe and profound sensory motor differences. The new manual has expanded beyond the communication assessment and strategies with Clicks addressing integration of purposeful switch use strategies and Chats

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matching interests and abilities to AT from beginning switch use to augmentative and alternative communication. The manual includes assessment strategies that are directly tied to intervention strategies, goals and corresponding implementation guidelines, data collection formats, sensory information, and a resource list. The strategies in this manual are appropriate for assessment, implementation and evaluation of effectiveness in the areas of low-tech/no-tech communication systems, environmental control via switch use, and voice output communication systems. Stages (Pugliese, 2008). Stages is a computerbased alternate assessment framework to help identify learning needs, assess skills, report progress over time, and select appropriate curriculum activities for learners with special needs. There are 7 stages that are developmental in nature including: cause/effect, language readiness, emerging language, early concepts, advanced concepts and communication, functional learning, and written expression. This assessment software generates a printable report including information on type of prompt, number of trials, correct responses, time on activity, and task completion. Stages is a beneficial alternate assessment which may be used to assess progress over time. Each Stage kit includes a CD and manual with directions, a script that guides implementation, and recommendations including a list of appropriate education software for each particular Stage. A current online list of accessible third-party educational software recommendations for each Stage is maintained online. A link to the software recommendations search tool may be found on the Stages website. The site contains other helpful resources such as a Stages skills checklist, an overview video and a handout that aligns Stages with curriculum activity templates found in Classroom Suite 4. Compass Access Assessment Software (Koester Performance Research, 2007). Compass Assessment Software provides a computerized assessment intended to evaluate a clients’ ability to use a computer. There are 8 skill sets in the categories of:

Switch Technologies

pointing, text entry, and switch use. Each set may be individually configured for font size, number of trials and type of feedback. Various input devices may be used including alternate keyboards, touch windows, trackballs, and switches. Compass records and creates a report on speed and accuracy performance and configuration specifics. Tests may be repeated over time to compare and track changes. Compass is a beneficial assessment tool in determining computer access, planning treatment strategies, and tracking effectiveness of an intervention strategy. SENSwitcher (Northern Grid for Learning, 2001). SENSwitcher is a suite of programs designed as a teaching and assessment tool for people with profound and multiple learning difficulties and those who need to develop skills with assistive input devices (switches) and very young children new to computers. SENSwitcher may be operated by a wide range of input devices and targets skills including purely experiential through cause-and-effect, switch building, timed activation, targeting, and row scanning. This program may be used directly online or downloaded to either a PC or Mac operating systems. This assessment tool is accompanied by an 18-page set of teacher’s notes together with assessment records, developmental skills progression models, and small step checklists.

types of switches • • • • •

Mechanical switches have movable parts requiring pressure to connect the circuit. Mercury or tilt switch is activated by the movement of mercury within a switch. Pneumatic switch is a sip and puff often used for W/C mobility. Electronic switches require power and are “capacitive” or activated by skin touch. Proximity switches have an adjustable range that may activated by a body part near, but not necessarily touching the switch.

•

• • •

Fiber Optic switch is a light beam and requires very minimal, but specific movement. Infra-red beam switch is a light beam. Sound activated switch such as the clapper. Wireless switches require as transmitter and receiver eliminating the cables.

ImPLementAtIon strAtegIes For success Implementation is an often overlooked detail, a detail that often is not appropriated time. All the right steps have been taken to assess a client, the correct tools have been purchased and delivered but without an implementation plan the rate of success is minimal and the rate of abandonment for AT is extremely high. The acquired tools need to be set up and staff, family, and the consumer need training. The IDEA definition of AT defines AT as a device and a service. The definition of AT service is far more lengthy and detailed than the definition of an AT device. The service of AT includes implementation, training and ongoing support. The first two categories of this section include basic set up information for mounting and connecting switches. The remainder of this section covers strategies for successful training and support.

mounting switches A switch may be mounted to a wheelchair, headrest, armrest, footrest, or on a lap tray. Switches may be mounted or positioned using dycem or shelf liner, velcro, and mounting brackets. There are various brackets on the market for mounting switches. One example is the Slim Armstrong; it is beneficial to be prepared with a small toolbox including allen wrenches, screw drivers, velcro, dycem, a few nuts, bolts, screws, and batteries.

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The ideal location for mounting or positioning a switch for physical access would require a small, voluntary, controlled movement that does not illicit reflexes. In order to assess for the optimum location for a switch, the client positioning must first be considered. Be sure to consult with Occupational Therapy and Physical Therapy for positioning considerations. According to Kangas (2008), the hierarchy of switch location would start with the head, including jaw, cheek, eyebrow, eye blink, and mouth, then the hand, then feet, and other upper or lower extremity locations such as the knee. Kangas’ rational for head before hand is that a switch access site at the head allow the hands freedom to perform other activity. Refer to additional readings for the article on Seating for Task Performance (see Kangas, 2002).

connecting switches Switches and devices are manufactured with a 1/8 or 1/4 inch jack or port. Adapters are available to go from 1/8” to 1/4” or the other way around. Mechanical switches will connect directly to a switch ready device. Battery operated devices may be adapted with a battery interrupter, a cable with a jack on one end and a small copper plate on the other end, which may be inserted at the site of the battery connection. In order to use a switch with the computer, a switch interface box is required. Most switch interface boxes use a USB connection and have several programmable ports for keyboard and mouse functions such as single-click, doubleclick, etc. Communication devices will accept a direct switch except in cases of the programmable electronic switches may need to go through a switch interface box. A switch may be connected to the wheelchair and programmed for multiple uses including driving the chair, controlling the computer, and communication devices, again in this case of multiple programming you may need a switch interface or a mouse emulator.

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team Approach/communication Meet frequently with team members, share the knowledge, use the same language, keep a journal, and involve the family.

engaging Activity Remember the switch is not the activity, make it interesting, know your students interests. There are various methods of switch use including: causeand-effect, choice making with a single switch, two switch or multiple switch use, and scanning with one or two switches. There are several variations to scanning including: automatic, step, inverse, linear, row-column, block, and frequency.

environment The AT tool being implemented is best done in the environment it will most frequently be used. If the computer is going to be used in a classroom, make the arrangements necessary for success. Instruct staff or peers in the tools your client is using. Make sure the physical layout is accessible for any equipment or wheelchair. Will the person be able to see and hear required instruction?

trial and error Try various switches from a loan library before purchasing. Try positioning the student/client in various ways for optimum motor control and try various positioning of the switches. Use the WATI Trial Use Guide (Reed; Wisconsin Assistive Technology Initiative, ASNAT, 2009) to gather data.

Practice and repetition Learning to use a switch may take time or it could have immediate success. The saying “If at first you don’t succeed, try, try again” applies to this implementation strategy. We must consider our

Switch Technologies

clients have good days and bad, and within that they have good times of the day and bad times. Trying an AT tool once is not a good indicator of its success. Select activities that provide ample opportunities to use throughout the day.

go forward.” “You hit that switch which made the music play.” For training purposes the use of descriptive feedback rather than praise helps clarify their actions when learning to activate a switch.

resources

•

Use the people around you, your team, seek out loan libraries, company trainings/representatives, and webinars.

Prompt Hierarchy The Prompt Hierarchy is a strategy taught in the WATI CCE Creating Communication Environments course. The prompt hierarchy is a strategy that has been used to teach communication techniques and it works equally well for teaching switch use. The prompt hierarchy for switch use teaches the educator how to appropriately train switch use and how to respond to the switch user, increasing the success and sustained use of a switch over time. There are four steps to the prompt hierarchy starting with encouraging switch use with an environmental cue, then an open question, a direct prompt and a full model prompt. Following is a more in-depth description of each of the four steps. Each level of the prompt hierarchy requires a pause following the prompt to allow for reaction time. The importance of pausing and remaining quiet, allowing the person to respond in the amount of time it takes them is a key factor to success. Each individual’s response time varies depending on physical abilities and cognitive processing. An assessment tool like Compass that gathers data on response time will be beneficial in determining an individual’s time requirements to respond. Another key to success in using the prompt hierarchy is the incorporation of descriptive feedback at each step. Descriptive feedback is a factual observation, clarifying the person’s actions. “You pressed that switch and it made the wheelchair

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•

Step one: Environmental Cue. Arrange or create opportunities in the environment to encourage and motivate switch use. Our environment drives our activity. We come to a door and we open it, a child sees an interesting toy and they pick it up, our job requires us to answer the phone, type on the computer, etc., we meet people and converse with them. The first step in the prompt hierarchy is setting up the environment to encourage, motivate and provide a purposeful reason for a person to activate the switch. Always pause after presenting the environmental cue to allow for response time and follow a response with descriptive feedback. If the person does not respond to the pause by making a response, move onto the next step. Step two: Open Question. If the person does not respond to the environmental cue, ask a what, why, who, when, where, or how question to prompt an interaction to the environmental cue using the switch. Always pause after presenting the open question to allow for response time and follow a response with descriptive feedback. If the person does not respond to the pause by making a response, move onto the next step. Step three: Request Prompt. Provide choices, a carrier phrase, initial sound, or visual cue. Always pause after presenting the request to allow for response time and follow a response with descriptive feedback. If the person does not respond to the pause by making a response, move onto the next step.

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Figure 1.

•

Step four: Full Model. This full model would be a demonstration of the desired activity using descriptive feedback as you demonstrate. The full model is also hand over hand assisting them in activating the switch while providing descriptive feedback. Always pause after presenting the full model to allow for response time and follow a response with descriptive feedback. If the person does not respond to the pause by making a response, repeat several times, relocate the positioning of the switch, select a different switch, and or try the training at another time and day.

is beneficial for purposes of programming, but more importantly, required for funding of some AT devices and services. Following is a more detailed description of written documentation including an informal action plan, writing AT into the IEP and the WATI Trial Use Guide.

Action Plan An action plan is an informal planning guide used to generate ideas and help focus and specify a task, the outcome, the tool, who will carry it through, and where and when the activity will be implemented.

documentation

AT in the IEP

An important part of implementation includes documenting the planned activity. Success in carry through is greatly increased when the best discussed plans are put in writing. Documentation may range from an informal work plan to a legal document required to meet federally mandated requirements. The Individual with Disabilities Education Act requires educational institutions to write an IEP, and for birth to three programs an IFSP (Individualized Family Service Plan), the department of Vocational Rehabilitation requires a IPE (Individual Plan for Employment). Data collection

The fact that AT under state and federal law, can be special education, a related service, a supplemental aid, or a supplemental service, has led to many questions as to how and where to include AT in the IEP. Please remember that there are many ways to correctly address AT in the IEP. The goal should be to make it as clear and understandable as possible for the parents and for future readers of the document. Sample forms of IEP in the state of Wisconsin may be located at Wisconsin Department of Instruction website http://dpi. wi.gov/index.html.

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One of the places AT needs to be addressed is on the Special Factors worksheet. Although this comes before other IEP pages in the packet, many IEP teams find it more logical to complete it after the goals and objectives are established. It is fine to set it aside and complete it at that time. This is a place where any AT (that the IEP team has decided is needed) should be listed. However, it is not necessary to repeat what is listed elsewhere, rather you could simply note: “See I-4” or “Refer to I-9”, wherever AT is already described. If AT is described only on I-4 and not on I-9, make sure that frequency, location, duration, and beginning date of services is included there. Assistive technology may be mentioned in the Present Level of Educational Performance if the student is currently utilizing it as a significant aspect of his or her performance. Assistive technology may appear as part of an Annual Goal or in one or more short-term objectives. This is appropriate when AT is an integral part of the child’s special education and related services, necessary to achieve one or more goals or objectives, and/or there are specific goals and objectives related to functional use of the AT. If AT is part of the transition planning, it may appear on the Transition Worksheet. Or be reflected under special education or related services. However, if it is already included elsewhere, in the student’s IEP, you may provide a cross reference. If the IEP team feels that AT is best included for this child under Related Services, it will be written here. Assistive technology is best listed here when it is not a primary part of the student’s educational program, but is necessary in order to access or benefit from the educational program, such as a walker or wheelchair. Frequency and amount of AT services must be identified when listed as a related service. If the AT is more appropriately viewed as a Supplementary Aid or Service, it will appear here.

It makes most sense to list it here when the AT tools and services enhance the placement of a student in the LRE (Least Restrictive Environment). It helps to remember that it should be listed here when it requires little instruction for the child to use and/or allows the student to be more independent, such as talking spell checker, portable word processor for a student who already knows how to use it.

Data Collection A step-by-step resource manual on effective data collection for AT is How Do You Know It? How Do You Show It? (see Reed, Bowser, & Korsten, 2002). This manual includes information on gathering data using interview, product review, and video. It includes identification of variables, what data is needed, reviewing of data, and using graphs. The manual also includes case studies and sample forms to illustrate data collection concepts. The WATI Trial Use Guide (Reed; Wisconsin Assistive Technology Initiative, ASNAT, 2009) is one format that may be used as a data collection tool. This form is found in the ASNAT manual from WATI and is also available as a free download at www.wati.org under supports, Assessing Students Needs for Assistive Technology. The trial Use Guide is a two part form, one that guides the team through a sequence of important questions that must be addressed prior to implementing trial use and the second part of the form is to summarize after the trial and formulate a recommendation to the IEP team. Much like an action plan, the questions that the Trial Use Guide poses include how the item will be acquired, will training be required, what support or management will be required for the item, who will be responsible, and start and ending dates. Data collected on the student use of the AT includes date and time used, location, tasks, and outcomes.

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Future reseArcH dIrectIons The historical progression of switch technologies in approximately a thirty-year period is significant; going from a simple mechanical switch to the electronic programmable switches running everything from communication devices to computers, to musical instruments and more. The sophistication of smart technologies will continue to advance switches and benefit the population of the physically and cognitively involved persons who could benefit from switch access to an insurmountable number of applications. The future trends for AT will be focused on data collection and research. The field of AT is young and in the early years placed minimal importance on research and data collection. The No Child Left Behind (NCLB) Act of 2001 has placed an emphasis on educational research and in some cases requires instruction be based on scientific research. The article Assistive Technology and Evidenced-based Practice, (see Edyburn, 2003) states that while group design studies are common in general education, in special education, differences in disabilities have made this measurement technique of limited use. As a result, few group studies have been conducted in AT due to fundamental challenges involved in identifying appropriate samples. Many companies of AT products do product specific research which is frequently posted on their websites or available upon request. I believe the importance of research and evidence-based strategies will be a driving factor in the future developments of AT.

concLusIon This chapter has provided information on best practices in the area of switch technologies including a background of the what, why, when, and where of switch accessibility, a summary of five popular assessment tools, an overview of types of switches, and training strategies for the successful

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sustained use of switches. As in all areas of technology the information on switch technologies is constantly progressing and changing with many sources for information. The goal of this chapter was to compile information in a concise step-bystep fashion with additional resources, readings, and references for further study. The background information in this chapter has provided the reader the information necessary in understanding what a switch is as applicable to AT, who it would benefit, and where to start in the process of applying this knowledge to the field of AT. The section on assessment has provided information on a variety of very different assessments to help match a consumer to the most appropriate device. A trained professional may assess a consumer through observation or using a marketed assessment tool. The correct matching of consumers skills to the required task and then to an appropriate tool begins with the assessment or evaluation and determines the successful sustained use of that tool. The information on types of switches in this chapter appears minimal in comparison to the number of switches available on the market. The information is focused on type with the understanding that within each type of switch there are many sizes, shapes, colors, and brand names. This chapter has given a great deal of attention to implementation strategies. Without successful implementation strategies, the success of the AT tool is minimal and the rate of abandonment is high. Staff, family, and consumers need training and continued follow-up support. When appropriating funds to purchase AT tools it is important to request the time and funds to fulfill the implementation phase. Assessment, acquisition, and implementation must all be given equal attention when striving for successful AT use. The developmental years of AT have focused on the tools, getting people trained on the tools, and passing legislation to further the acceptance for the need of AT. The development of technol-

Switch Technologies

ogy continues to become more sophisticated, and in many cases, easier to use. It is difficult to speculate how advanced these technologies will become and how far they will go in improving the quality of life for people with physical and cognitive disabilities. What is going to be vital in the future is that we justify these tools with research in order for their acceptance and sustained use in the world of education, employment, and independent living. The use of switches in the field of AT provides access to activity, information, education, environmental controls, communication, mobility, recreation, play and enjoyment. A child’s response to finally obtaining access to an activity like music, a story, a video game, educational opportunities on the computer, or mobility is to smile, laugh, even squeal, to learn and to become independent.

reFerences Blackhurst, A. (2004). Handbook of special education technology research and practice. Whitefish Bay, WI: Knowledge by Design, Inc. Edyburn, D. (2003). Assistive technology and evidenced-based practice. ConnSENCE Bulletin. Retrieved January 20, 2009, from http://www. connsensebulletin.com/edyatevidence.html Kangas, K. (2002). Seating for task performance. Rehab Management Journal. Retrieved January 14, 2009, from http://www.rehabpub.com/features/672002/8.asp Koester Performance Research. (2007). Compass assessment software: Spectronics. Ventura, CA: Inclusive Learning Technologies. Korsten, J., Foss, T., & Berry, T. L. (1993). Every move counts, clicks & chat. Overland Park, KS: CDS Printing.

Northern Grid for Learning. (2001). SENSwitcher. Gateshead, UK: Northern Grid for Learning. Retrieved January 21, 2009, from http://www. northerngrid.org/ngflwebsite/sen/intro.htm Pugliese, M. (2000). Stages. Bedford, MA: Cambium Learning Technologies. Reed, P. (2009). Wisconsin Assistive Technology. Initiative Created through WI DPI IDEA. Grant number 9906-23, Assessing Students’ Needs for Assistive Technology (ASNAT) (5th ed.). Milton, WI: WATI. Reed, P., Bowser, G., & Korsten, J. (2002). How do you know it? How do you show it? Wisconsin Assistive Technology Initiative. Created through WI DPI IDEA. Grant number 9906-23. Milton, WI: WATI. Zabala, J. S. (1995). The SETT framework: Critical areas to consider when making informed assistive technology decisions. Houston, TX: Region IV Education Service Center. ERIC Document Reproduction Service No. ED381962. Retrieved January 15, 2009, from http://www.joyzabala.com

AddItIonAL reAdIng Burkhart, L. (2006). Two switches to success! Increasing participation and cognitive engagement with two switch activities and two switch step scanning. Eldersburg, MD: Author. Canfield, H., & Locke, P. (1998). Book of possibilities. Minneapolis, MN: Ablenet, Inc. Edyburn, D., Higgins, K., & Boone, R. (2005). Handbook of special education technology research and practice. Whitefish Bay, WI: A Knowledge by Design, Inc. Publication. George, C., & Lacefield, W. (2001). Handbook of adaptive switches and augmentative communication Device. Lexington, KY: Academic Software, Inc.

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Herlihy, D. (2003). IntelliTools extreme! For classroom suite 3. Hoosick, NY: Connective Technology Solutions, Inc. Lange, M. (n.d.). Access to independence. Advance for Occupational therapy Practitioners. Retrieved January 14, 2009, from http://www. atilange.com Levin, J., & Enselein, K. (1990). Fun for everyone – A guide to adapted leisure activities for children with disabilities. Minneapolis, MN: Ablenet, Inc. Purcel, S., & Grant, D. (2007). Using assistive technology to meet literacy standards (Grades K-3, 4-6, 7-12). Verona, WI: Attainment Company, Inc. Reed, P. (2007). A resource guide for teachers and administrators about assistive technology. Wisconsin Assistive Technology Initiative. Created through WI DPI IDEA. Grant number 9906-23. Milton, WI: WATI.

key terms And deFInItIons Access: The method a person uses to control an activity.

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Assessment: A method of acquiring information about the consumer, the environment and the required task in order to recommend an appropriate AT tool. Assessment differs from evaluation in that it is not standardized and it is ongoing over time. Assistive Technology (AT): Any item, piece of equipment, or product system whether acquired commercially off the shelf, modified, or customized that is used to increase or improve functional capabilities of individuals with disabilities. Disability: The inability to perform a physical or mental activity in what is considered a normal level of performance. Environmental Controls: This may be a remote control system or computerized software that controls electronically operated devices including but not limited to: lights, doors, television, radio, and answering the phone. Implementation: Refers to putting into practice or carrying out a plan to effectively use, in this case, a switch as an AT device. Switch: In relation to AT, a switch is a device that provides access to an activity by connecting and disconnecting an electrical circuit.

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Chapter 11

Point-and-Chat®:

Instant Messaging for AAC Users Benjamin Slotznick Point-and-Read, Inc., USA

AbstrAct Point-and-Chat®, most simply, is the first software for Instant Messaging with a built-in screen reader, designed to be used in conjunction with Augmentative/Alternative Communication (AAC) devices. For many AAC users, especially those who have difficulty reading and writing, an AAC device is the primary or only way they can communicate with other people. This communication is primarily one-on-one and face-to-face. The goal of Point-and-Chat® is to take the skills that an AAC user has in producing the spoken word and provide scaffolding that will enable the AAC user to use those skills to communicate with the written word. The primary impediment to effective use of Point-and-Chat® by AAC users appears to be a lack of appropriate text-chat vocabularies for poor readers, including vocabulary strategies to re-establish conversations when the conversational thread has been lost.

IntroductIon Point-and-Chat®, most broadly, is software for communicating via electronic text (e.g., IM, Short Message Service (SMS) text messaging, and e-mail). It is specifically designed for people who can see and hear, but cannot read or who are having difficulty reading. For non-readers and poor readers, Point-and-Chat® includes a built-in screen reader so that received messages can be read aloud by a DOI: 10.4018/978-1-61520-817-3.ch011

synthesized computer voice. The built-in screen reader includes patented Point-and-Chat® features and other design choices that support people with cognitive limitations and multiple disabilities. For non-writers, Point-and-Chat® uses text messages created from already-familiar picture-based AAC software such as DesktopChat® from Saltillo Corporation (2008-2009). This chapter details the design choices and user interfaces used to reduce cognitive load and addresses the growing importance of instant messaging (IM)—including both the challenges and

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Point-and-Chat®

opportunities that IM presents to AAC users, especially those with multiple disabilities, reading difficulties, or cognitive limitations. It will become evident why it is important for AAC users (and even non-readers) to learn how to use IM and other electronic messaging, and how the interface design choices make Point-and-Chat® IM easy to learn. This chapter presents the results of a pilot study with Point-and-Chat®—funded in part by the National Center for Technology Innovation (NCTI)—and describes the avenue for further research that the study suggests.

tHe ImPortAnce oF communIcAtIng vIA InstAnt messAgIng And eLectronIc text The use of electronic text is increasingly ubiquitous—and not just among contemporary high-school students. It is becoming essential for many people across all walks of life, even if these people don’t write for a living. People who cannot use e-mail (and increasingly texting and IM) are becoming progressively more isolated. E-mail, IM, and texting are even replacing telephone and face-to-face communications for many, even to the point of texting each other when in the same room, such as during committee meetings. It is not just that electronic text communication is replacing verbal and written communication in familiar settings. In addition, e-mail, IM, and text messaging form the backbone of new opportunities for socialization, such as social networks and other online communities. Perhaps surprisingly, even though computers are frequently not so accessible to people with disabilities, communication using electronic text offers special advantages for AAC users. A brief exposition of the omnipresence of electronic communications will provide additional perspective. Most Americans use the Internet, in fact, 73% of all American adults use the Internet

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and 88% of Americans aged 12-29 use it. Most Americans use e-mail (90% of all Internet users). Most young adults use IM (62% of online young adults, aged 18-27). Half of online young adults use IM as much as or more than e-mail (Pew Internet & American Life project, 2009). For a student or young person who wants to communicate with peers, it is becoming increasingly important to be able to communicate via electronic text—and IM is just as important, or even more important, than e-mail. The explosion in communication technologies has certainly helped AAC users conduct face-toface communications, but otherwise they have remained at a communications disadvantage. Certainly, the development of electronic AAC devices has provided a voice for many individuals who had none. The introduction and improvement of their control interface using dynamic displays and of their vocalization via computer synthesized text-to-speech have exponentially increased the things they can say (manufacturers include but are not limited to Saltillo Corporation, PrentkeRomich, and Dynavox). Improved and more natural sounding voices have made participation in face-to-face conversations more natural as well. However, the synthesized voices, especially when played through the small speakers usually found on these devices, do not always transmit clearly over a telephone. Although some of the devices can be used to create text input for a computer, the user must be literate and tech savvy. In addition, though a few of the devices have specialized built-in SMS messaging or e-mail capabilities, none of them have built-in IM software. Point-and-Chat® is the first IM software designed specifically for AAC users, and designed to take input from their software and devices. Point-and-Chat® can also send and receive SMS messages and has a companion e-mail program with a similar interface. Electronic text communication may help AAC users by creating a more level playing field for people with disabilities in general and AAC us-

Point-and-Chat®

ers in particular. There are a number of ways in which e-mail and IM help AAC users converse as equals. E-mail and IM look the same from all senders. Not only does all text look the same, but all electronic conversations with peers—especially IM conversations—tend to display a grammatical informality and sentence fragmentation that may accompany beginner AAC use. Texting encourages time-saving grammatical and spelling shortcuts for all users. The rhythm of e-mail and IM conversation encourages non-instantaneous response and asynchronous conversation. The time it takes an AAC user to construct a verbal response to a question or statement may seem like a conversation-destroying lag in face-to-face (or phone-to-phone) communication, but these types of lags are typical in e-mail and IM, where everyone must push buttons on a computer device in order to converse. These lags are also typical, because most users are multi-tasking on their computers—watching a YouTube video, reading a celebrity website, watching TV all while engaging in several simultaneous IM conversations. Even lengthy lags are not unexpected. Additionally, e-mail and IM “conversations” can happen over distance and time—supporting mobility-impaired and stay-at-home users. Instant messaging, even more than e-mail or SMS messaging, offers further subtle, but important advantages for AAC users. The content of an IM conversation is very much like a one-on-one, face-to-face personal chat—proceeding in not just sentences, but exclamations, phrases and fragments of sentences. An AAC user already “knows” how to produce the text for the words he or she “speaks” in these sorts of conversations. Most children learn to speak easily, but expend years learning to read and write—and even then have difficulty putting words on paper. The difficulty is not just stringing the words together grammatically and in ways so very different from their conversations with friends. There is also the issue of “writer’s block.” Many kids (and adults) can tell you an engaging story, but have a hard

time putting the same words on paper or entering them in a computer. In contrast, once an AAC user has learned to tell you a story with his or her AAC device, the machine has already created the words as text objects. The words just have to be displayed or deployed in a useful manner. That is an important part of the Point-and-Chat® interface, grabbing and using the text words an AAC user already knows how to produce—even if the user does not know he or she is producing text.

tHe PoInt-And-cHAt®InterFAce The Point-and-Chat® interface consists of three parts: text input software-based on an AAC product such as Saltillo’s DesktopChat®, Point-and-Read® screen reader technology, and a new IM interface that requires that the user learn only a few more keystrokes. Saltillo’s DesktopChat® is used to create text messages in ways familiar to AAC users (see Figure 1). Figure 1. Screenshot of DesktopChat® (©2009 Saltillo Corporation. Used with permission.)

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Point-and-Chat®

Figure 2. Screenshot of Point-and-Chat® (on the left) with DesktopChat® (on the right) (©2009 Pointand-Read, Inc. and Saltillo Corporation. Used with permission.)

Clicking on or activating picture buttons creates text messages that the computer will read out loud. The buttons can be configured to individual needs with words, images, or both. Point-and-Chat® has two different methods by which text messages can be read out loud by the computer. With Point-and-Read® screen reader technology, the user can place the cursor over any part of a sentence. The computer will highlight that entire sentence. If the user keeps the cursor stationary for a moment (hovering over a part of the sentence), then the computer will read the sentence out loud. Alternatively, several button controls allow the user to read the next sentence (or the previous one) by clicking on or activating the control. In addition, incoming messages can be automatically read when they appear. The Pointand-Chat® IM interface is shown in Figure 2 on the left, with DesktopChat® on the right. To send an instant message, a text message is created with DesktopChat® using the skills the AAC user already has. The text message appears at the top of the DesktopChat® display. The text

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message is copied by Point-and-Chat® in the text editing box in the lower left. If the user is happy with the message, he or she just clicks or activates the SEND button (with the smiley face talking). If the user is not happy with the message, he or she can erase it, using the ERASE button (with the image of a pencil eraser). When the message is sent, it will disappear from the text editing box, and appear in the message box above. When Point-and-Chat® receives an incoming instant message, the message will automatically appear in the top message box (on the left) and right after the previous message. The user can choose to have the incoming message automatically read aloud. (Additionally, the user can listen to messages by mousing over them or clicking the NEXT, PREVIOUS, and REPEAT buttons.) For the most part, carrying on an IM conversation only requires the use of the AAC interface and one more button—the SEND button. The tabs on the left of the Point-and-Chat® interface indicate different active conversations. Clicking on or activating a tab will bring that

Point-and-Chat®

conversation to the top. If a message arrives for a conversation that is not on the top, its tab will be highlighted in green. To start an instant message conversation using Point-and-Chat®, the user opens the address book of contacts (sometimes called a “buddy list”) by clicking on or activating the CONTACTS button in the upper left corner of the Point-and-Chat® interface. This will show a picture-based table of contacts as shown in Figure 3. Click on or activate the picture of one of the contacts. This will open a new conversation with its own conversation tab. A red circle with a slash through a picture on the contacts table indicates that the contact is not currently online. A blank gray rectangle indicates that an active conversation with that contact has already been started (and the picture will appear on one of the tabs to the left). Throughout, large buttons with simple hardedge icons reduce visual clutter and ease cognitive strain. They also provide large targets for those with poor vision or poor hand-motor-control-andcoordination skills.

resuLts oF crItIcAL reseArcH A 2008 Technology in the Works grant from the NCTI was used to fund collaborative research among Point-and-Read, Inc., Saltillo Corporation, and Jeff Higginbotham of East, Inc. The research included: (a) adding capabilities to Point-and-Chat® so that when it was running on a desktop computer, it could be controlled by a nearby stand-alone AAC device; and (b) developing page sets for a stand-alone DynaVox DV4 (an AAC device) so that the DV4 could send proper control code sequences to the desktop computer. Just as importantly, a pilot usability study was conducted. In the pilot usability study, two AAC users were taught how to use Point-and-Chat®, how to transmit text messages from their DynaVox devices to Point-and-Chat® running on a nearby desktop computer and how to send control commands from their DynaVox devices to Point-and-Chat®. Researchers held online instant message chats with the participant-users. While the participants were able to use Point-and-Chat® they encountered some

Figure 3. Screen shot of Point-and-Chat® (on the left) with DesktopChat® (on the right) (©2009 Pointand-Read, Inc. and Saltillo Corporation. Used with permission.)

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Point-and-Chat®

problems. Many problems were fixed by creating simpler ways to accomplish tasks, correcting outof-sequence actions automatically and creating more help materials. However, the biggest issue was with the vocabulary page sets that participants had been using with their DynaVox devices. To quote the final report: Participants were frustrated that the personal vocabulary pages on their AAC devices were not always useful for instant messaging conversations. These pages had been tailored to face-toface communication and for particular subject matter. However, they proved less useful for instant messaging conversations. Participants also experienced difficulty choosing and switching between subjects and topics, and recovering conversation threads. Consequently a robust “chat” vocabulary needs to be devised for users. This vocabulary should not be subject specific, but rather provide short answers typical of IM conversation and also provide bridges to subject specific vocabulary (Slotznick, Hershberger, & Higginbotham, 2009). In retrospect this is not surprising. Participantusers had been accustomed to face-to-face conversations— not the disembodied conversations of IM or electronic text. Their conversations were ordinarily continued and advanced not only through their AAC devices but also through other verbal and gestural cues. These cues could be used to complete thoughts as well as recover lost trains of thought. However, when conversation threads were dropped in an online IM conversation, the participants did not have the verbal and gestural “tools” to fall back on or textual substitutes to re-direct the conversation. With IM and other text messaging, those cues will have to be developed and built into the vocabulary pages. Devising a cognitively simple vocabulary to accomplish these tasks was outside the scope of the NCTI research. However, this research is the first

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to identify the need for such a text-conversationspecific vocabulary for AAC users.

concLusIon Point-and-Chat® is the first IM software designed for users of AAC devices. It has been specifically designed to provide a simple graphical user interface with low cognitive load so that it can be used by people unfamiliar with computers, poor readers, non-readers, people with multiple disabilities, and people with cognitive disabilities. To be truly useful, however, simple adjunct vocabularies need to be developed to help users guide and navigate text-centric conversations.

reFerences Pew Internet & American Life project. (2009). Retrieved September 30, 2009, from http://www. pewinternet.org Saltillo. (2008-2009). Point-and-Chat. Retrieved September 30, 2009, from http:// www.saltillo.com/shop/catalog/product_info. php?cPath=24&products_id=137 Slotznick, B., Hershberger, D., & Higginbotham, J. (2009). Point-and-Chat: Instant messaging software for augmentative/alternative communications users. National Center for Technology Innovation, AIR SubGrant No. 00378-02411.002, AIR prime grant No. H327Z060003. Retrieved February 6, 2009, from http://www.nationaltechcenter.org/documents/point_and_chat_final_report.pdf

key terms And deFInItIons Augmentative/Alternative Communication (AAC): Methods of replacing speech and writing

Point-and-Chat®

for people who cannot speak or write; but more particularly for this chapter, high-tech electronic devices, often with touch screens and dynamic displays, that use computer-synthesized speech as a communication aid. Cognitive Load: The relative mental effort a user must expend in a specific situation or with a particular user interface to accomplish a task. Electronic Text: Text that has been encoded for digital electronic creation and transmission, often for display on cell phones or personal computers and their word processing software and often in the ASCII encoding format. E-Mail: A method of exchanging electronic text over the Internet, asynchronously like postal mail rather than in real time.

Instant Messaging (IM): A method of exchanging electronic text in real time over the Internet between two or more people, much like a text-based conversation. Screen Reader: A software application that uses computer synthesized speech to read aloud text that is received by a computer and displayed on the computer screen. SMS (as in SMS Text Messaging, SMS Messaging, or “Short Message Service”): Short electronic text messages (up to 160 characters) sent over a cell phone network usually between cell phones.

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Chapter 12

Assistive Technology for Deaf and Hard of Hearing Students Michael Fitzpatrick New Mexico State University, USA Raschelle Theoharis Gallaudet University, USA

AbstrAct Although the majority of deaf and hard of hearing (d/hh) students are educated in the public school system (Turnball, Turnball, & Wehmeyer, 2010) there is limited research and literature regarding how educators can effectively meet their educational needs by implementing assistive and instructional technologies into their curriculum. This chapter provides an overview of the various assistive and instructional technologies available to d/hh students and outlines how these students access and use technology. This chapter contributes to the fundamental ideal that integrating assistive and instructional technologies can greatly enhance the academic and social outcomes for d/hh students. It should be noted, that the Deaf community does not adhere to person first language because they do not view deafness as a disability but as a culture.

IntroductIon There is a new emphasis, based on federal mandates (discussed next), concerning and redefining “highly qualified teachers.” Educators of deaf and hard of hearing (d/hh) students have historically been classified as “highly qualified” upon earning a state license from an approved deaf education program (Luft, 2008). Within the last 20 years the preparation of educators for d/hh students has become an DOI: 10.4018/978-1-61520-817-3.ch012

increasingly difficult and complex process because it is intertwined with theories, knowledge, and skills related to deaf education, academic content, and other pedagogical areas (Paul & Quigley, 1990). Nevertheless upon graduation preservice educators were deemed “highly qualified.” Unlike the 1997 amendments to the Individuals with Disability Education Act, the reauthorization Individuals with Disabilities Improvement Act (IDEIA, 2004) required special educators to earn a disability-specific degree. Similarly, the No Child Left Behind Act (NCLB, 2002) has redefined the

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Assistive Technology for Deaf and Hard of Hearing Students

criteria for “highly qualified” (Smith, Desmone, & Ueno, 2005). Although NCLB has six key principles (Turnbull, Turnbull, Erwin, & Soodak, 2006), the focus of highly qualified teachers and accountability have specific and new implications for d/hh educators. In order to achieve the mandates of NCLB (2002) and IDEIA (2004), d/hh educators must have an in-depth understanding of both assistive technology (AT) and instructional technology (IT). When implemented with fidelity, AT and IT have the potential to increase the academic and social outcomes of d/hh students. Moreover, in alignment with IDEIA (2004), upon transiting from K-12 educational setting to either postsecondary institutions or cooperate America, d/hh individuals are ensured reasonable accommodations and modifications according to the American’s with Disabilities Act (ADA, 1990), which would include appropriate AT and IT (Rosen, 2007). Unfortunately a significant gap exists between empirical research and descriptive studies that report the efficacy of AT or IT use for d/hh students in the K-12 setting. The limited numbers of studies that have been conducted on AT and IT were completed at the K-12 level during the 1990s and mainly focused on cochlear implants. More recently Power, Power, and Horstmanshof (2007) reported that there is a dearth of research, studies, and published literature related to the ways d/hh community use technology. The lack of research, access, and understanding poses clear challenges for educators, d/hh students, and their families. Therefore, the purpose of this chapter is to provide an overview of various educational technologies for this student population.

bAckground In our society, technology rapidly changes our lives; this is particularly true within the deaf and hearing community (National Association of the

Deaf, 2008). For example, less than two decades ago d/hh Americans had to rely on neighbors or relatives to make a simple phone call (National Association of the Deaf, 2008). However, the rapid advancements in technology have been vital for increasing the life outcomes of individuals with a hearing loss. In a society oriented to speech and hearing communication, technology has aided and allowed d/hh individuals to become more independent and active participants. Moreover, advancements in technology have been made specifically to meet the unique needs of d/hh individuals. Similar to Universal Design for Learning, many technological advances that were specifically designed for d/ hh individuals provide benefits and convenience for everyone. For example, closed captioning was one dimension of technology specifically designed for d/hh individuals. However, the benefits of closed captioning are virtually limitless for the “hearing world.” This accommodation/modification and newer innovations such as the teletype (TTY), various alerting devices, improved hearing aids, assistive listening devices (ALD), and fax machines have positivity impacted the d/hh and “hearing world” simultaneously (Stewart & Kluwin, 2001). Additionally, Stewart and Kluwin (2001) reported that e-mail and on-line chats, videophones, videoconferencing, speech-to-text software, text-to-signs software, and palm-size pagers with key boards were created to meet the communication needs of d/hh people, yet these developments benefit everyone.

effects of technology on d/hh students To increase the academic achievement and socialization, for a subgroup that is typically known for their low reading levels and underachievement, current and future educators need to have indepth knowledge about (a) communication, (b) language, (c) social emotional, (d) educational,

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and (e) vocational development of d/hh students. In addition, similar to students with other disabilities, it is important for educators to be aware of how to identify, implement, and sustain AT and IT into the classroom and school setting for d/ hh students. Although the majority of research has been conducted with students with severe to profound hearing loss (Marschark, Lang, & Albertini, 2002), Eleweke and Rodda (2000) reported that approximately 94% of children have a hearing loss are diagnosed prior to their third birthday which results in delays in fluent language acquisition and hinders the development of communication skills (Figueras, Edwards, & Langdon, 2008; Rodda & Eleweke, 2000). In addition, regardless of when children acquired their hearing impairment (e.g., prelingual or postlingual) d/hh students typically encounter difficulties learning to read (Musselman, 2000) and write (Singleton, Morgan, DiGello, Wiles, & Rivers, 2004). With a median fourth grade reading level among deaf high school graduates (Marschark, Lang, & Albertini, 2002; Traxler, 2000), it is not surprising that d/hh adults are persistently underemployed and substantially receive lower incomes than individuals with “normal hearing.” Introducing assistive and instructional technology to d/hh students has greatly enhanced their academic outcomes, assisted with transitioning from school to work or college, and increased social awareness and skills of d/hh students (Akamatsu, Mayer, & Farrelly, 2006). As noted in previous chapters, AT has the potential for increasing access to the general education curriculum (Smith & Jones, 1999) and supports students with a variety of disabilities across all grade levels (Blackhurst & MacArthur, 1986; Michaels & Mcdermott, 2003; Smith, 2000). Specifically in the area of deaf education, AT has enabled d/hh students to visually access auditory forms of information (Roberson, 2001). However, in order to see effective outcomes of d/hh students,

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it is important for deaf educators to implement AT and IT devices and services effectively. The following sections provide an overview of how AT and IT have been used to increase the academic and social outcomes of d/hh students within the classroom and school setting. Each subsection provides an analysis of: (a) amplification (e.g., hearing aids, cochlear implants, and ALD); (b) environment (e.g., alerting devices and closed captioning); (c) communication (e.g., TTYs, e-mails, and text-messaging); and (d) Internet, programs, and software (e.g., captioned software, speech-to-text software, sign language software, and simulation software).

Amplification There are two primary objectives for providing amplification to d/hh individuals: (a) to make speech audible, without introducing distortion or discomfort; and (b) to restore a range of loudness experience (Tye-Murray, 2009). To accomplish these two key objectives, there are many different types of amplification systems (Klein & Parker, 2002). Cochlear implants, hearing aids, and frequency modulation systems (FM systems) are the most frequently used within the K-12 educational setting.

Cochlear Implants “Cochlear implants are biomedical electronic devices that convert sound into electrical current to stimulate remaining auditory nerve elements directly, thereby producing hearing sensations” (Beiter & Brimacombe, 2000, p. 473). Cochlear implants are comprised of five parts: a microphone, speech processor, transmitter, receiver/ stimulator, and electrodes (Klein & Parker, 2002). The receiver/simulator (this includes an antenna and miniaturized electronics) is surgically placed into the mastoid bones which are located slightly above the ear (Klein & Parker, 2002). A series of

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tiny electrodes (the electrode array) on an inch long wire is inserted into the cochlea. The external parts of the implant are the microphone (which is similar to a behind the ear hearing aid), the speech processor, and the transmitter (Klein & Parker, 2002). The transmitter is a small plastic ring that is placed on the scalp and is held to the receiver that is embedded under the skin (Klein & Parker, 2002). The microphone picks up the sound from the environment, changes it to an electronic signal, and then carries it through the connecting cables to the speech processor (TyeMurray, 2009). The processed signal goes from the speech processor to the electrode array, via a transmitter and an internal receiver. The signal typically is transmitted across the skin by an electromagnetic induction or radio frequency transmission. The signal then goes from the internal receiver to the electrode array. Then, the electrode array carries electrode pairs, tiny exposed balls or rings on the wire--which are comprised of positive and negative polarized contacts, which passes current. This current stimulates fibers on the auditory nerve (Tye-Murray, 2009). Thirty-years ago, cochlear implants were virtually unheard of, but today are common place (Tye-Murray, 2009). Moreover, this new procedure has already had a significant impact on the lives of profoundly deaf children and adults, by providing useful hearing to individuals whom hearing aids provide no benefit (Wheeler, Archbold, Gregory, & Skip, 2007). However, it is important to realize that cochlear implants are not appropriate for every individual with a hearing loss (Klein & Parker, 2002). Cochlear implants were created for individuals who are profoundly deaf, who do not have residual hearing, who do not benefit from hearing aids, and who make limited progress in the development of auditory skills (Klein & Parker, 2002; Tye-Murray, 2009). It is critical that family and professionals understand the commitment (e.g., time, effort, and money) and responsibilities that go along with the

cochlear implant process, beginning with surgery and following through the habilitation services (Klein & Parker, 2002; Tye-Murray, 2009). It has been recommended that families seek counseling because it provides information about receiving, maintaining, and using a cochlear implant so that the user is able to receive maximum benefits (Tye-Murray, 2009).

Hearing Aids The intent of a hearing aid is to make sound louder and if possible clearer to the listener (Dillon, 2001). The history of the hearing aid began in the 1600s. The trumpet, horn, funnel, and speaking tube were all means in which sounds could be amplified. However, the first wearable hearing aid that contained a microphone, battery, amplifier, and receiver (the components of “modern” hearing aids) were made in 1902 (Dillon, 2001). There are many different types of hearing aids: body aids, ear-level aids, in-the-ear aids, analog and digital hearing aids, and the most commonly used aid for children is the behind-the-ear (BTE) hearing aid (Klein & Parker, 2002). However, the type of hearing aid is typically based on the audiogram.

FM Systems Typical classrooms are filled with many distracting environmental and background noises (e.g., talking, paper rustling, shuffling feet, audio-visual equipment, doors opening and closing, and HVAC systems). Some of these noises and distractions can be as loud as the educator’s voice. In addition, educators who “roam” around the classroom, turn their backs to the students, or multitask while providing instruction can cause the loudness of their voice to vary and may detract from the effectiveness of hearing aids. For students with “normal hearing,” these noises for the most part are not distracting and do not cause problems (Boys Town National Research

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Hospital, 2009). However, for d/hh students these compounding factors can interfere with their ability to hear and understand the dissemination of information. As noted above, hearing aids amplify all sounds. Intuitively when hearing aids amplify the educator’s voice, they also make all of the background noises louder (Boys Town National Research Hospital, 2009). Fortunately FM systems can assist with these challenges. FM systems are commonly used in classroom settings and can be classified as either a personal FM trainer. This is a portable system that allows d/hh students the freedom to move to several different environments (e.g., a fieldtrip, play, or recess), while maintaining an excellent signalto-noise ratio (Klein & Parker, 2002). When using a personal FM system, the educator wears a microphone (transmitter) and the student wears a receiver, which is attached to the hearing aid (TyeMurray, 2009). The educator’s voice is modulated via a radio frequency that carriers and transmits the waves through the classroom to the child’s receiver. The receiver is set to match the FM frequency of the transmitter, which allows multiple FM units to be used at the same time within the same environment (Klein & Parker, 2002).

devices for the environment Although there are different levels of hearing loss among d/hh students (Wheeler-Scruggs, 2002), they typically encounter more difficulties within the classroom and school setting than their “normal hearing” peers (Liu, Chou, & Liu, 2006). Though early intervention programs (Hintermair, 2006; Zaidman-Zait & Dromi, 2007), technological advances (Ertmer, 2002), and support from their family (Ertmer & Mellon, 2001; Storbeck & Calvert-Evers, 2008) and community services (Munro-Ludders, Simpatico, & Zvetina, 2004; Rogers, Muir, & Evenson, 2003) exists for the home environment and provide d/hh children with opportunities for success, the children continue to face a multitude of challenges. However, regard-

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less of setting (e.g., school or home) it is important for educators to be knowledgeable about AT, IT, and environmental adaptations many d/hh students often require to function in a “hearing world.” This section provides a summary of various assistive and instructional technologies available to d/hh students to use at school and home. Similar to other disabilities, integrating technology in the classroom can aid d/hh students access to the general education curriculum (Stover & Pendegraft, 2005). Although many factors influence accessing and using AT effectively, Elliot, Foster, and Stinson (2003) reported that educators’ acceptance of technology has been attributed to the success of d/hh student’s working with AT. Ultimately, it is the educator’s responsibility to keep up with the changes in technological trends for d/hh students (Harrington & Powers, 2004). The following five AT devices and IT interventions are provided so educators become aware of what can be implemented into their classroom.

Note-Takers Despite having knowledge of new instructional methods, high school educators typically rely on lectures as the primary means to disseminate information (Elliot, Foster, & Stinson, 2002). Thus, note-taking remains a valued way for students to access the necessary information (Dunkel & Davy, 1989). Evidence suggests that students who take notes have the ability to recall and perform better on assessments (Kiewra, 1985). Unfortunately d/ hh students often have difficulties taking notes, even when using a hearing aid, FM system, interpreter, or other AT or IT devices. Although not as necessary or readily available throughout the elementary grades, note-takers may become extremely important for d/hh students upon entering middle and high school where notetaking is more prevalent. Although note-takers are unable to provide immediate information, d/ hh students can pick up a copy of the notes at the end of each class session and fill in the informa-

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tion they missed during the lecture (Stover & Pendegraft, 2005).

Computer-Aided Notetaking Computer-Aided Notetaking (CAN) has been available since the 1990s (Cuddihy, Fisher, Gordon, & Schumaker, 1994; James & Hammersley, 1993; Preminger & Leavit, 1997). However, many educators may not be aware of CAN. According to Stover and Pendegraft (2005), CAN is inexpensive, easy to implement, beneficial to d/hh students, and has evolved since its inception. Computer-Aided Notetaking requires two desktop or laptop computers, local area network, typist (similar to a scribe or stenographer), and it is suggested to purchase a computerized abbreviation software program (such as Typewell). The typist takes notes and d/hh students can either: (a) read the notes directly during class on his or her computer or (b) receive a printout of the notes after the class session.

Real-Time Captioning Captioning is similar to subtitling (Jensema, Danturthi, & Burch, 2000), but speech recognition technology is typically not used for real time captioning (RTC) (Bain, Basson, & Faisman, 2005). However, Stover, and Pendegraft (2005) suggested that many school districts that can afford the cost for captioning services are integrating RTC for their d/hh students. Professional captioners “capture” spoken language and instantaneously transcribe and transmit the information to d/hh students by using a specialized stenotype machine (Stover & Pendegraft, 2005). The stenotype machine is connected to a computer with translating software that translates shorthand into words. Unlike typing, Stover and Pendegraft, (2005) reported that captioners can create captions at speeds of more than 225 words per minute.

Closed Captioning Since the early 1970s technology for captioning television has benefited d/hh individuals. In 1993, closed captioned television decoders have been built into every television larger than 13 inches (Jensema, Sharkawy, Danturthi, Burch, & Hsu, 2000). Captioning is similar to subtitling. It is a process of converting audio to text and then displaying the text on the screen (Jensema et al., 2000). The text provides d/hh individuals with a visual display of dialogue, narration, and sound effects (Lewis & Jackson, 2001).

Alarm Systems Within the home, school, and work settings many d/hh individuals use alarm alerting devices in order to have access to auditory information (TyeMurray, 2009; Wheeler-Scruggs, 2002). Examples include: vibrating or flashing alarm clocks, where a vibration might occur under an individual’s pillow or a flashing light would signal when it is time to wake-up; a doorbell or telephone signaling device attached to a lamp, which signals when someone is at the door or calling; a smoke detector, that flashes to indicate the presence of smoke; and a baby monitor alerting system, where a parent is made aware of an infant crying in another room (Tye-Murray, 2009).

communication It is known that technological advancements can be both a means of inclusion and exclusion for individuals with a disability (Pilling & Barrett, 2008). A primary example is d/hh people. With the invention of the telephone, d/hh individuals were excluded from an activity that has become everyday and critical for most people (Pilling & Barrett, 2008). This is ironic, since Alexander Graham Bell, was so involved and concerned with improving the communication abilities among the Deaf community (Pilling & Barrett, 2008).

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In recent years, technological developments have addressed this situation (Pilling & Barrett, 2008). Despite the ways the Deaf community uses communication technologies, little research has been conducted on how they use electronic communication in their daily lives (Power et al., 2006). Currently, d/hh individuals have a variety of ways in which they communicate with others (Power et al., 2006). The Deaf community relies on TTYs, e-mails, and text-messaging to communicate with others. These communication devices are described next.

TTYs and Relay Services In the 1960s, a deaf man, Robert Weitbrecht, modified teletypewriters (TTYs) for use by deaf individuals to be used over standard telephone lines. TTYs, also known as Telecomunications device for the Deaf (TDD), is a telephone terminal comprised of a telephone, a keyboard, and a message display screen. The telephone handset fits into the cradle on the terminal. Both the person calling and the person receiving the call, must have the device, or a relay service must be used. The two individuals communicate by typing their message to each other. The messages appear on the message display screen (Tye-Murray, 2006). In the beginning, only those who had a TTY could communicate, so mostly the TTYs allowed d/hh individuals to communicate with one another. With the establishment of relay services, d/hh individuals can now communicate via a relay with hearing people who do not own a TTY (Power et al., 2006). In order for d/hh people to call hearing people using a TTY, relay services have been set-up in many parts of the world (Power et al., 2006). The relay operator, who has been trained in issues of confidentiality, takes either a voice or TTY call and connects it to the dialed number, using a computer for TTY and a microphone for voice the operator is able to transmit the call between the caller and the recipient (Power et al., 2006).

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Emails Traditionally, d/hh Americans relied on TTYs and relay systems to communicate with others. However, these devices have their limitations— either both individuals have to have the device or have to go through a third party, communication can only flow one direction at the time and no one can interrupt (which makes communication very slow), and these technologies rely heavily on written text (which puts high demands on the user’s receptive abilities) (Bowe, 2002). E-mail offers three advantages for d/hh individuals over traditional means. Unlike TTYs which require immediate responses, d/hh individuals have the opportunity to read the messages at their leisure and seek further understanding if necessary (Bowe, 2002). An individual can compose a message using spell check and editing functions. Finally, archiving or printing sent and received messages is easy (Bowe, 2002). More recently, instant messaging has been developed and allows a full-duplex service. An individual may compose and send an answer at the same time, even when reading an incoming message (Bowe, 2002). People are alerted to incoming messages throughout the day both ways of communicating are instantly available (Bowe, 2002).

Text-Messaging Deaf and hard of hearing students are often delayed in developing their independent living skills compared to their hearing peers (Calderon & Greenberg, 2003; Greenburg & Kusche, 1993). Parents of d/hh teens typically place more restrictions on activities outside the home (Akamatsu et al., 2006). These restrictions stem from parents who worry about their child’s inability to communicate and their general safety (Akamatsu et al., 2005). In a recent study, researchers found that parents were uniformly satisfied with the two-way text messaging system one school implemented. In

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addition, the system was also used by the school faculty and they found it extremely beneficial. Both reported they were able to have direct communication with the students; this communication eliminated safety concerns regarding fire alarms, emergency procedures, personal safety issues, and contributed to ease of coordination of everyone’s activities (Akamatsu et al., 2005). One student said, “The pagers helped me to send my dad and my dad is less worry. After school I allowed to play basketball, ball hockey with friends” (Akamatsu, et al., 2005, 125).

Internet, Programs, and Software Internet, programs, and software have been developed to meet the educational and learning needs of d/hh students. These programs include captioned software, speech-to-text software, sign language software, and simulation software. Although the authors could provide specific examples of various software and innovative ways to use the Internet in the classroom to meet the learning styles of d/ hh students, the purpose of this section was not to endorse or advocate one computerized software program or website over another.

Issues, controversIes, And ProbLems For society, technology has become an essential component of almost every educational, employment, community, recreational, and home environment (Burgstahler, 2003). Access to technology has proven to be beneficial for students with a range of abilities and disabilities. This access has the potential to increase independence; engagement; and participation in school, work, and the community for d/hh individuals. Although the benefits of technology may be greater for those with a hearing loss than for people without (Anderson-Inman, Knox-Quinn, & Szymnski, 1999; Blackhurst, Lahm, Harrison, & Changler, 1999; Hasselbring

& Glaser, 2000), individuals with disabilities are less than half as likely as their non-disabled peers to own computers and are one-quarter as likely to use the Internet (Burgstahler, 2003). Another significant barrier is the extensive number of AT devices that are now available. Since the passage of The Technology Related Assistance for Individuals with Disabilities Act (P. L. 100-407, 1988), there has been a sizeable increase in the number of assistive devices created for persons with disabilities including those with d/hh (Bausch & Hasselbring, 2004). ABLEDATA (2009), an on-line database for ATs, provides a list of over 25,000 devices. With the enormous number of options, AT decisions are not easy for educators to make (Bausch & Hasselbring, 2004), especially when considering not every d/hh student benefits from the same types of technology. For d/hh students to be successful users of AT, educators must think beyond the identification and the selection of the equipment. A third barrier to effectiveness of AT is the need to provide training in the use and practical ways to integrate the technology into daily life (Bausch & Hasselbring, 2004). Not only does appropriate training need to be provided to the students, it is imperative that those working with the student (general education teachers, special education teachers, d/hh teachers, paraprofessionals, speech language pathologist, audiologist, and family members) should also be trained in the operation, implementation, and problem-solving across environments and settings (McGregor & Pachuski, 1996).

solutions and Future research The following section outlines three potential solutions and areas future researchers should consider when working with d/hh students. These areas were developed after a review of relevant literature and focus on early identification, teacher preparation, and increasing the reading abilities of d/hh students.

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It is well documented that early identification and interventions are important when working with d/hh children (Meinke & Dice, 2007; Moeller, 2000; Storbeck et al., 2008; Yoshinaga-Itano, 2003; Yoshinaga-Itano, Coulter, & Thomson, 2000; Yoshinaga-Itano, Sedey, Coulter, & Mehl, 1998). Sadly, as noted throughout this chapter there is limited research and literature which supports the integration of AT and IT to stimulate academic, language, and social development of d/hh children from the onset of concern. Future solutions and research emphasis should be placed on developing intervention strategies focused on implementing and sustaining various technologies to increase capacity of d/hh students. According to Humphries and Allen (2008) the majority of teacher preparation programs fail to address innovative teaching practices for d/hh students. In addition, Easterbrooks (2001) reported that there are more controversies in deaf education than successes. From these perspectives it is necessary for teacher preparation programs and researchers to provide innovative teaching practices for their preservice educators. Programs should consider delving into the literature and determine how to employ AT and IT to maximize their preservice candidates to be visionaries in the field of deaf education. Similar to early interventions and teacher preparation (discussed earlier) teaching d/hh students to read at an early age is essential (Donne & Zigmond, 2008). Not only is reading an important life skill it improves language abilities among d/hh students (Hermans, Knoors, Ormel, & Verhoeven, 2008; Kirk, Gallagher, Anastasiow, & Coleman, 2006). Preservice and inservice educators should be vigilant when working with d/hh students to ensure they are learning to read despite not having the ability to hear. It is important to remember that the Deaf community has embraced various forms of text-based communication (discussed earlier) and being able to read, comprehend, and respond appropriately is essential to be successful in a society driven largely by text and symbols.

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summAry And concLusIon As discussed in previous chapters, AT devices and services (range from inexpensive, low technology devices to expensive, high-tech devices) have been mandated for several years. Currently, the law requires that every student with an Individualized Education Program (IEP) must be considered for AT devices and services (Bausch & Hasselbring, 2004). The consideration process of appropriate AT devices during the IEP meeting is vital to a student’s success, however implementing the AT properly and systematically is critical to increasing their academic and social outcomes (Bausch & Jones-Ault, 2008; Luft, 2008). The actual implementation is often difficult for deaf educators, due to the fact technology rapidly changes for d/hh students because they lack a strong foundation and understanding needed for implementation (Stewart & Kluwin, 2001). It is important that d/hh educators to be knowledgeable of the various amplification devises available in the K-12 educational setting. Further they should understand the purpose, types, components, and most importantly how they work. This chapter specifically looked at cochlear implants, hearing aids, and FM systems which are the most frequently used by d/hh students. In addition, it is important for educators and family members to remember amplification normally enables a person to hear most sounds, but if an individual is not wearing his or her hearing aid, does not have enough residual hearing, or if they are in another room some sounds may go unnoticed. To help with these situations, signaling devices can be set up to alert the d/hh individual to a telephone, alarm clock, door bell, or smoke alarm. These devices not only make them aware of what is happening in their environment, but also helps to keep d/hh individuals safe (Schow & Nerbonne, 1996; Tye-Murray, 2009). Finally, little research has been conducted on how d/hh students use electronic communication in their daily lives. However, these technologies

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have a huge impact on the lives of the Deaf community (Power et al., 2006). In addition to teaching academics and content knowledge, educators should focus on how to empower d/hh student’s socialization skills. Educators who are aware of the methods and technologies the Deaf community uses to communicate will assist in this process.

Bausch, M. E., & Jones-Ault, M. (2008). Assistive Technology Implementation Plan: A tool for improving outcomes. Teaching Exceptional Children, 41(1), 6–14.

reFerences

Blackhurst, A. E., Lahm, E. A., Harrison, E. M., & Chandler, W. G. (1999). A framework for aligning technology with transition competencies. Career Development for Exceptional Individuals, 22(2), 153–183. doi:10.1177/088572889902200203

ABLEDATA. (2009). [On-line database of assistive technology and rehabilitation equipment]. Retrieved February 3, 2009, from http://www. abledata.com Akamatsu, C. T., Mayer, C., & Farrelly, S. (2005). An investigation of two-way text messaging use with deaf students at the secondary level. Journal of Deaf Studies and Deaf Education, 11(1), 120–131. doi:10.1093/deafed/enj013 Americans with Disabilities Act of 1990, P.L. 101-336, 42 U.S.C.A. 12, 101-12, 213. Chicago: West Supplement. 1991. Anderson-Inman, L., Knox-Quinn, C., & Szymanski, M. (1999). Computer supported studying: Stories of successful transition to postsecondary education. Career Development for Exceptional Individuals, 22(2), 185–212. doi:10.1177/088572889902200204 Bain, K., Basson, S., & Faisman, A. (2005). Accessibility, transcription, and access everywhere [Electronic version]. IBM Systems Journal, 44(3), 589–603. doi:10.1147/sj.443.0589 Bausch, M. E., & Hasselbring, T. S. (2004). Assistive technology: Are the necessary skills and knowledge being developed at the preservice and inservice levels? Teacher Education and Special Education, 27(2), 97–104. doi:10.1177/088840640402700202

Beiter, L. J. (2000). Cochlear implants. In Alpiner, J., & Mcarthy, P. (Eds.), Rehabilitative audiology: Children and adults (3rd ed., pp. 473–496). Baltimore: Lippincott Williams & Wilkins.

Blackhurst, E. A., & MacArthur, C. (1986). Microcomputer use in special education personnel preparation programs. Teacher Education and Special Education, 7(3), 27–36. doi:10.1177/088840648600900104 Bowe, F. G. (2002). Deaf and hard-of-hearing Americans’ IM and e-mail use: A national survey. American Annals of the Deaf, 147, 6–10. Boys Town National Research Hospital. (2009). About hearing aids—FM systems for the classroom. Retrieved February 5, 2009, from http:// boystwonhospital.org/Hearing/hearingaids/ fmsystems.asp Burgstahler, S. (2003). The role of technology in preparing youth with disabilities for postsecondary education and employment [Electronic version]. Journal of Special Education Technology, 18(4), 7–19. Calderon, R., & Greenberg, M. (2003). Social and emotional development of deaf children: Family, school, and program effects. In Marschark, M., & Spenser, P. E. (Eds.), Oxford handbook of deaf studies, language and education (pp. 177–189). New York: Oxford University Press.

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Cuddihy, A., Fisher, B., Gordon, R., & Schumaker, E. (1994). C-note: A computerized notetaking system for hearing-impaired students in mainstream secondary education [Electronic version]. Information and Technology for the Disabled, 1(2), 45–52.

Ertmer, D. J., & Mellon, J. A. (2001). Beginning to talk at 20 months: Early vocal development in a young cochlear implant recipient. Journal of Speech, Language, and Hearing Research: JSLHR, 44(1), 192–206. doi:10.1044/10924388(2001/017)

Dillion, H. (2001). Hearing aids. Turramurra, Australia: Boomerang Press.

Figueras, B., Edwards, L., & Langdon, D. (2008). Executive function and language in deaf children [Electronic version]. Journal of Deaf Studies and Deaf Education, 13(3), 362–377. doi:10.1093/ deafed/enm067

Donne, V., & Zigmond, N. (2008). Engagement during reading instruction for students who are deaf or hard of hearing in public schools [Electronic version]. American Annals of the Deaf, 153(3), 294–303. doi:10.1353/aad.0.0044 Dunkel, P., & Davy, S. (1989). The heuristic of lecture note taking: Perceptions of American and international students regarding the value & practice of note taking [Electronic version]. English for Specific Purposes, 8, 33–50. doi:10.1016/08894906(89)90005-7 Easterbrooks, S. (2001). Veteran teachers of children who are deaf/hard of hearing describe language instructional practices: Implications for teacher preparation [Electronic version]. Teacher Education and Special Education, 24, 116–127. doi:10.1177/088840640102400206 Eleweke, C. J., & Rodda, M. (2000). Factors contributing to parents’ selection of a communication mode to use with their deaf children [Electronic version]. American Annals of the Deaf, 145(4), 375–383. Elliot, L., Foster, S., & Stinson, M. (2002). Student study habits using notes from a speech-to-text support service [Electronic version]. Exceptional Children, 69(1), 25–40. Ertmer, D. J. (2002). Technological innovations and intervention practices for children with cochlear implants [Electronic version]. Language, Speech, and Hearing Services in Schools, 33(3), 218–221. doi:10.1044/0161-1461(2002/019)

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Greenberg, M. T., & Kusche, C. A. (1993). Promoting social and emotional development in deaf children: The PATHS Project. Seattle, WA: University of Washington Press. Harrington, M. L., & Powers, A. R. (2004). Preparing teachers to meet the needs of children who have cochlear implants [Electronic version]. Teacher Education and Special Education, 27(4), 360–372. doi:10.1177/088840640402700404 Hasselbring, T. S., & Glaser, C. H. (2000). Use of computer technology to help students with special needs. The Future of Children, 10(2), 102–122. doi:10.2307/1602691 Hermans, D., Knoors, H., Ormel, E., & Verhoeven, L. (2008). The relationship between the reading and signing skills of deaf children in bilingual education programs [Electronic version]. Journal of Deaf Studies and Deaf Education, 13(4), 518–530. doi:10.1093/deafed/enn009 Hintermair, M. (2006). Parental resources, parental stress, and socioemotional development of deaf and hard of hearing children [Electronic version]. Journal of Deaf Studies and Deaf Education, 11(4), 493–513. doi:10.1093/deafed/enl005 Humphries, T., & Allen, B. M. (2008). Reorganizing teacher preparation in deaf education [Electronic version]. Sign Language Studies, 8(2), 160–180. doi:10.1353/sls.2008.0000

Assistive Technology for Deaf and Hard of Hearing Students

James, V., & Hammersley, M. (1993). Notebook computers as notetakers for handicapped students [Electronic version]. British Journal of Educational Technology, 24, 63–66. doi:10.1111/j.1467-8535.1993.tb00642.x

Luft, P. (2008). Examining educators of the Deaf as highly qualified teachers: Roles and responsibilities under IDEA and NCLB [Electronic version]. American Annals of the Deaf, 152(5), 429–440. doi:10.1353/aad.2008.0014

Jensema, C. J., Danturthi, R. S., & Burch, R. (2000). Time spent viewing captions on television programs [Electronic version]. American Annals of the Deaf, 145(5), 464–468.

Marschark, M., Lang, H., & Albertini, J. (2002). Educating deaf students: From research to practice. New York: Oxford University Press.

Jensema, C. J., Sharkawy, S. E., Danturthi, R. S., Burch, R., & Hsu, D. (2000). Eye movement patterns of captioned television viewers [Electronic version]. American Annals of the Deaf, 145(3), 275–285. Kiewra, K. A. (1985). Investigating notetaking and review: A depth of processing alternative [Electronic version]. Educational Psychologist, 20(1), 23–32. doi:10.1207/s15326985ep2001_4 Kirk, S. A., Gallagher, J. J., & Anastasiow, N. J. Coleman, M. R. (2006). Educating exceptional children (11th Ed.). Boston: Houghton Mifflin. Klein, D. H., & Parker, E. W. (2002). Spoken communication for students who are deaf or hard of hearing: A multidisciplinary approach. Hillsboro, OR: Butte Publications. Lewis, M. S., & Jackson, D. W. (2001). Televison literacy: Comprehension of program content using closed captions for the deaf. Journal of Deaf Studies and Deaf Education, 6(1), 43–53. doi:10.1093/deafed/6.1.43 Liu, C.-C., Chou, C.-C., & Liu, B.-J. (2006). Improving mathematics teaching and learning experiences for hard of hearing students with wireless technology-enhanced classrooms [Electronic version]. American Annals of the Deaf, 151(3), 345–355. doi:10.1353/aad.2006.0035

McGregor, G., & Pachuski, P. (1996). Assistive technology in schools: Are teachers ready, able, and supported? Journal of Special Education Technology, 13, 4–15. Meinke, D. K., & Dice, N. (2007). Comparison of audiometric screening criteria for the identification of noise-induced hearing loss in adolescents [Electronic version]. American Journal of Audiology, 16(2), S190–S202. doi:10.1044/10590889(2007/023) Michaels, C. A., & Mcdermott, J. (2003). Assistive technology integration in special education teacher preparation: Program coordinators’ perceptions of current attainment and importance. Journal of Special Education Technology, 18(3), 29–41. Moeller, M. P. (2000). Early intervention and language development in children who are deaf and hard of hearing [Electronic version]. Pediatrics, 106, E43. doi:10.1542/peds.106.3.e43 Munro-Ludders, B., Simpatico, T., & Zvetina, D. (2004). Making public mental-health services accessible to deaf consumers: Illinois deaf services 2000 [Electronic version]. American Annals of the Deaf, 148(5), 396–402. doi:10.1353/ aad.2004.0008 Musselman, C. (2000). How do children who can’t hear learn to read an alphabetic script? A review of the literature on reading and deafness [Electronic version]. Journal of Deaf Studies and Deaf Education, 5(1), 9–31. doi:10.1093/ deafed/5.1.9

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National Association of the Deaf. (2008). Assistive technology. Retrieved December 14, 2008, from http://www.nad.org/site/ pp.asp?c=folINKQMBF&b=180305 P. L. 107-110. (2002). The No Child Left Behind Act of 2001. Retrieved June 14, 2004, from http:// www.ed.gov/policy/elsec/leg/esea02/index.html P. L. 108-446. (2004). The Individuals with Disabilities Education Improvement Act. Retrieved July 5, 2005, from http://www.ed.gov/policy/ speced/guid/idea/idea2004.html Paul, P. V., & Quigley, S. P. (1990). Education and deafness. White Plains, NY: Longman. Pilling, D., & Barrett, P. (2008). Text communication preferences of deaf people in the United Kingdom. Journal of Deaf Studies and Deaf Education, 13(1), 92–103. doi:10.1093/deafed/ enm034 Power, M. R., Power, D., & Horstmanshof, L. (2007). Deaf people communicating via SMS, TTY, relay service, fax, and computers in Australia. Journal of Deaf Studies and Deaf Education, 12(1), 80–92. doi:10.1093/deafed/enl016 Preminger, J., & Leavit, H. (1997). Computerassisted remote transcription: A tool to aid people who are deaf or hard of hearing in the workplace [Electronic version]. The Volta Review, 99, 219–230. Roberson, L. (2001). Integration of computers and related technologies into deaf education teacher preparation programs [Electronic version]. American Annals of the Deaf, 146(1), 60–66. Rodda, M., & Eleweke, C. J. (2000). Literacy development in limited English proficiency deaf people: A review [Electronic version]. Deafness & Education International, 2(2), 101–113. doi:10.1002/dei.77

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Rogers, S., Muir, K., & Evenson, C. R. (2003). Signs of resilience: Assets that support deaf adults’ success in bridging the deaf and hearing worlds [Electronic version]. American Annals of the Deaf, 148(3), 222–232. doi:10.1353/aad.2003.0023 Rosen, J. (2007). Calling for consumer directed and inclusively designed technology [Electronic version]. Policy and Practice of Public Human Services, 65(3), 14–17. Schow, R. L., & Nerbonne, M. A. (1996). Introduction to audiologic rehabilitation. Needham Heights, MA: Allyn & Bacon. Singleton, J. L., Morgan, D., DiGello, E., Wiles, J., & Rivers, R. (2004). Vocabulary use by low, moderate, and high ASL-proficient writers compared to hearing ESL and monolingual speakers [Electronic version]. Journal of Deaf Studies and Deaf Education, 9(1), 86–103. doi:10.1093/ deafed/enh011 Smith, S. (2000). Teacher education—Associate editor’s column [Electronic version]. Journal of Special Education Technology, 15(1), 59–62. Smith, S. J., & Jones, E. P. (1999). Technology infusion: Preparing teachers through web-based cases [Electronic version]. Career Development for Exceptional Individuals, 22, 251–266. doi:10.1177/088572889902200207 Smith, T. M., Desimone, L. M., & Ueno, K. (2005). Highly qualified to do what? The relationship between NCLB teacher quality mandates and the use of reform-oriented instruction in middle school mathematics [Electronic version]. Educational Evaluation and Policy Analysis, 27(1), 75–109. doi:10.3102/01623737027001075 Stewart, D. A., & Kluwin, T. N. (2001). Teaching deaf and hard of hearing students: Content, strategies, and curriculum. Needham Heights, MA: Allyn & Bacon.

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Storbeck, C., & Calvert-Evers, J. (2008). Towards integrated practices in early detection of and intervention for deaf and hard of hearing children. American Annals of the Deaf, 153(3), 314–321. doi:10.1353/aad.0.0047 Stover, D. L., & Pendegraft, N. (2005). Revisiting computer-aided notetaking: Technological assistive devices for hearing-impaired students [Electronic version]. Clearing House (Menasha, Wis.), 79(2), 94–97. doi:10.3200/TCHS.79.2.94-97 Technology-Related Assistance for Individuals with Disabilities Act of 1988, PL 100-407. (August 19, 1988). Title 29, U.S.C. 2201 et seq: U.S. Statutes at Large, 102, 1044-1065. Traxler, C. B. (2000). Measuring up to performance standards in reading and mathematics: Achievement of selected deaf and hard-of-hearing students in the national norming of the 9th Edition Stanford Achievement Test. Journal of Deaf Studies and Deaf Education, 5, 337–348. doi:10.1093/ deafed/5.4.337 Turnbull, A., Turnbull, R., & Wehmeyer, M. L. (2010). Exceptional lives: Special education in today’s school (6th ed.). Upper Saddle River, NJ: Pearson. Turnbull, A. P., Turnbull, H. R., Erwin, E., & Soodak, L. (2006). Families, professionals, and exceptionality: Positive outcomes through partnership and trust. Columbus, OH: Merrill/ Prentice Hall.

Wheeler-Scruggs, K. (2002). Assessing the employment and independence of people who are deaf and low functioning [Electronic version]. American Annals of the Deaf, 147(4), 11–17. Yoshinaga-Itano, C. (2003). Early intervention after universal neonatal hearing screening: Impact on outcomes [Electronic version]. Mental Retardation and Developmental Disabilities Research Reviews, 9, 252–266. doi:10.1002/mrdd.10088 Yoshinaga-Itano, C., Coulter, D., & Thomson, V. (2000). The Colorado newborn hearing screening project: Effects on speech and language development for children with hearing loss [Electronic version]. Journal of Perinatology, 20, S132–S137. Zaidman-Zait, A., & Dromi, E. (2007). Analogous and distinctive patterns of prelinguistic communication in toddlers with and without hearing loss [Electronic version]. Journal of Speech, Language, and Hearing Research: JSLHR, 50(5), 1166–1180. doi:10.1044/1092-4388(2007/081)

AddItIonAL reAdIng Anderson, K. L., & Goldstein, H. (2004). Speech perception benefits of fm and infrared devices to children with hearing aids in a typical classroom [Electronic version]. Language, Speech, and Hearing Services in Schools, 35(2), 169–184. doi:10.1044/0161-1461(2004/017)

Tye-Murray, N. (2009). Foundations of aural rehabilitations: Children, adults, and their family members (3rd ed.). Clifton Park, NY: Delmar.

Bat-Chava, Y., Deignan, E., & Martin, D. (2002). Rehabilitation counselors’ knowledge of hearing loss and assistive technology [Electronic version]. Journal of Rehabilitation, 68(1), 33–44.

Wheeler, A., Archbold, S., Gregory, S., & Skipp, A. (2007). Cochlear implants: The young people’s perspective. Journal of Deaf Studies and Deaf Education, 12(3), 303–316. doi:10.1093/deafed/ enm018

Belcastro, F. P. (2004). Rural gifted students who are deaf or hard of hearing: How electronic technology can help [Electronic version]. American Annals of the Deaf, 149(4), 309–313. doi:10.1353/ aad.2005.0001

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Boutin, D. L., & Wilson, K. B. (2009). Professional jobs and hearing loss: A comparison of deaf and hard of hearing consumers [Electronic version]. Journal of Rehabilitation, 75(1), 36–40. Cawthon, S. W., & Wurtz, K. A. (2009). Alternate assessment use with students who are deaf or hard of hearing: An exploratory mixed-methods analysis of portfolio, checklists, and out-of-level test formats [Electronic version]. Journal of Deaf Studies and Deaf Education, 14(2), 155–177. doi:10.1093/deafed/enn027 Clark, J. (1994). Reading the silver screen [Electronic version]. Technology Review, 97, 18–19. Corbett, E. E., & Micheaux, P. A. (1996). How some schools for deaf and hard of hearing children are meeting the challenges of instructional technology [Electronic version]. American Annals of the Deaf, 141, 52–58. DeCaro, J. J. (2008). Globaleyes: A partnership between the Nippon Foundation (Japan) and the National Technical Institute for the Deaf (United States) [Electronic version]. American Annals of the Deaf, 152(5), 505–509. doi:10.1353/ aad.2008.0007 Easterbrooks, S. R., Stephenson, B. H., & Gale, E. (2008/2009). Veteran teachers, use of recommended practices in deaf education [Electronic version]. American Annals of the Deaf, 153(5), 461–473. doi:10.1353/aad.0.0070 Elliot, L. B., Foster, S., & Stinson, M. (2003). A qualitative study of teachers’ acceptance of a speech-to-text transcription system in high school and college classrooms [Electronic version]. Journal of Special Education Technology, 18(3), 45–59. Geyer, P. D., & Williams, E. (1999). The role of technical assistance centers in addressing employer concerns about accommodating workers who are deaf or hard of hearing [Electronic version]. Labor Law Journal, 50(4), 280–288.

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Harkins, J. E., Loeterman, M., & Lam, K. (1996). Instructional technology in schools educating deaf and hard of hearing children: a national survey [Electronic version]. American Annals of the Deaf, 141, 59–65. Jacobi, L. (2004). Chatting at Gallaudet [Electronic version]. Library Journal, 1976, 3. Johnson, L. (2004). Utah deaf videoconferencing model: Providing vocational services via technology [Electronic version]. Journal of Rehabilitation, 70(4), 33–37. Kirkland, C. E. (1999). Evaluation of captioning features to inform development of digital television captioning capabilities [Electronic version]. American Annals of the Deaf, 144(3), 250–260. Kluwin, T. N., & Noretsky, M. (2005). A mixedmethods study of teachers of the deaf learning to integrate computers into their teaching [Electronic version]. American Annals of the Deaf, 150(4), 350–357. doi:10.1353/aad.2005.0041 Lederberg, A. R., & Spencer, P. E. (2009). Wordlearning abilities in deaf and hard-of-hearing preschoolers: Effect of lexicon size and language modality [Electronic version]. Journal of Deaf Studies and Deaf Education, 14(1), 44–62. doi:10.1093/deafed/enn021 Menlove, M., & Hammond, M. (1998). Meeting the demands of ADA, IDEA, and other disability legislation in the design, development, and delivery of instruction [Electronic version]. Journal of Technology and Teacher Education, 6(1), 75–85. Mitchell, R. E. (2006). How many deaf people are there in the United States? Estimates from the survey of income and program participation [Electronic version]. Journal of Deaf Studies and Deaf Education, 11(1), 112–119. doi:10.1093/ deafed/enj004

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Passig, D., & Eden, S. (2000). Improving flexible thinking in deaf and hard of hearing children with virtual reality technology [Electronic version]. American Annals of the Deaf, 145(3), 286–291. Pillai, P. (1999). Using technology to educate deaf and hard of hearing children in rural Alaskan general education settings [Electronic version]. American Annals of the Deaf, 144(5), 373–378. Pratt, M. K. (2009). Swift translation [Electronic version]. Computerworld, 43(2), 24–26. Stoner, M. L., Easterbrooks, S. R., & Laughton, J. M. (2005). Handwritten and word-processed story retellings by school-aged students who are deaf [Electronic version]. Journal of Special Education Technology, 20(3), 35–44. Strassman, B. K., & D’Amore, M. (2002). The write technology [Electronic version]. Teaching Exceptional Children, 34(6), 28–31. Tevenal, S., & Villanueva, M. (2009). Are you getting the message? The effects of SimCom on the message received by deaf, hard of hearing, and hearing students [Electronic version]. Sign Language Studies, 9(3), 266–286. doi:10.1353/ sls.0.0015

key terms And deFInItIons Americans with Disabilities Act (ADA): The Americans with Disabilities Act of 1990 was enacted to provide equal opportunity to individuals with disabilities (P.L. 101-336).

Audiogram: An audiogram is a graphic representation of a person’s ability to hear sounds at different frequencies and intensities (Schow & Nerbonne, 1996; Tye-Murray, 2009). Behind-the-Ear (BTE): Behind-the-ear hearing aids contain a microphone, amplifier, and receiver that are all housed in the hearing aid case and fits behind the ear. Those parts are connected to custom earmold by a flexible tube (Schow & Nerbonne, 1996). Hearing Aid: Hearing aids are an electronic listening device designed to amplify and deliver sound from the environment to the listener. The device includes a microphone, amplifier, and a receiver (Tye-Murray, 2009). Postlingual: Postlingual is a hearing loss that occurs after an individual has acquired spoken language (Paul & Quigley, 1990; Tye-Murray, 2009). Prelingual: Prelingual is a hearing loss that occurs before an individual acquires spoken language (Paul & Quigley, 1990; Tye-Murray, 2009). Relay System: Relay systems are used by individuals who are deaf or have a significant hearing loss to use the telephone. The individual contacts a relay operator who transmits messages between the caller and the person called through teletype and/or voice (Tye-Murray, 2009). Telecomunication: Telecomunication device for the deaf (TDD, TT, TTY) are telephone devices for persons who are deaf or have a significant hearing loss in which messages are typed on a keyboard, transmitted, and displayed on a small monitor (Tye-Murray, 2009).

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Chapter 13

A Longitudinal Case Study on the Use of Assistive Technology to Support Cognitive Processes across Formal and Informal Educational Settings Vivian Johnson Hamline University, USA Carol Price Hamline University, USA

AbstrAct This chapter describes a chronology of increasingly sophisticated technological supports and interventions used across complex formal and informal educational settings with a 10th grade female student who has documented learning challenges. A progression from low technology devices to computerized, high technology assistive devices are employed to provide access to materials and to academic information over a period of 10 years. Understanding both the inner and outer context of this learner’s environment provides the reader with a background to process the progression of the use, improvement, and availability of assistive technology in the life of this user.

PurPose The National Center for Education Statistics (2008a; 2008b) cites that of the 49.8 children and youth enrolled in public schools, some 6.7 million receive special education services for classroom instruction and during assessments. While assistive technology (AT) can be included in an individualized educaDOI: 10.4018/978-1-61520-817-3.ch013

tional plan (IEP), parents and adult caregivers can also re-purpose common technology applications to support the learner. The purpose of this discourse is to present a chronology of one parent’s efforts to utilize both low and high technology across formal and informal educational settings over a ten-year period. Impact of legislative actions on the education of the student serves as the backdrop through which the affects of AT on the student’s cognitive process is viewed.

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A Longitudinal Case Study on the Use of Assistive Technology to Support Cognitive Processes

tHeoretIcAL FrAmeWork The female learner in this case study was born in 1992 and major pieces of legislation that define the context of her learning environment started in 1965 when the Elementary and Secondary Education Act (ESEA) was initiated. This legislation did little in terms of addressing accommodations to assist learners with special needs. It did, however, mandate the annual assessment in reading and mathematics of students who received services under Title I. Following ESEA for 10 years, children enrolled in special education classes were segregated from general education classes, save for classes in art, music, and physical education (ESEA, n.d.). During this time, students with significant cognitive disabilities were segregated from general education classes. The first legislative move toward equity for students with disabilities occurred in 1975 with the passage of Public Law 94-142 (Education of All Handicapped Children Act), codified as IDEA (Individuals with Disabilities Education Act) in 1997. Congress mandated that for states to receive federal funds, they must develop and implement policies that assure a free appropriate public education (FAPE) to all children with disabilities. The state plans must be consistent with the federal statute, Title 20 United States Code Section 1400 et.seq. (20 USC 1400). Assistive technology appears in the law in 1992 with the passage of the Technology Related Assistance for Individuals with Disabilities Act. This act provides financial support and assistance to states to support system change and advocacy for AT, which “it further defines any item, piece of equipment or product system, whether acquired commercially off the shelf, modified, or customized, that is used to increase, maintain, or improve functional capabilities of individuals with disabilities [20 U.S. C. Chapter 33, Section 1401 (250)].” In 1994, accountability for student progress appears as the Improving America’s Schools Act of 1994 (IASA). This law shifts the focus of test-

ing from individual student gains to looking at all students against state standards, and requires that valid and reliable tests be provided in reading/ language arts and mathematics at least once in each of three grade spans from grades 3-12. In 1995, IDEA reinforced the requirement for states to provide FAPE to children with disabilities in the least restrictive environment (LRE). In addition, it empowers parents and the local educational agency to make appropriate decisions about what constitutes Legislation of 1997 through 2001 applied only to students enrolled in public schools. Children in parochial or private institutions did not receive benefit from these laws. Emma is one such child. The Assistive Technology Act of 2004 ensures that individuals with disabilities have access to the technologies they need to help them in school, at home, at work, and in the community. The Individuals with Disabilities Improvement Act of 2004, passed by Congress, was designed to improve learning outcomes for infants, toddlers, children, and youth with disabilities; made the language and intent of IDEA 2004 consistent with NCLB; and ensured access to technology for individuals with disabilities. Federal legislation ensures access for public school students and for students with disabilities in private schools, however, these protections and services are not mandated. Part E of Title XIV—Uniform Provisions for the Participation of Private School Students requires Local Education Agencies (LEA) to “service eligible private school children who reside in the LEA” (USDE, n.d., p. 1 ¶ 3). Although this section of the law requires “timely and meaningful consultation” between the LEA and the private school, Part B of IDEA does not require “parentally placed students with disabilities to receive services provided to students enrolled in public schools” (USDE, nd, p. 3 ¶ 2). Further complicating the situation is that each state sets eligibility requirements for services to children and youth with disabilities. Emma did not receive the maximum benefit from federal

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legislation provisions for students with disabilities because she was enrolled in a private school and her parents were unwilling to have Emma miss significant parts of her school day in travel to a public school to obtain services. Nevertheless, legislation governing the provisions of services for students with disabilities does provide the context for increased emphases in AT. Students with disabilities typically have multiple service providers (e.g., occupational therapists, physical therapists, speech therapists, adaptive physical education teachers, etc.) in addition to general and special education teachers, but not all service providers are aware of how to implement AT appropriately into the student’s IEP. In a survey of the status of AT delivery in various school systems across the nation, Bausch, Ault, Evmenova, and Behrmann (2008) found that a large percent (19.6%) of services reported as AT services were not AT services; there is little integration and coordination among service providers; and almost half of respondents (40.2%) included services that were not ATs, that “may indicate a lack of awareness” (p.12).

emmA’s story: A cAse study oF one gIrL’s trIumPH over scHooL From the moment she was born, Emma was a ray of sunshine in the lives of her parents and of everyone with whom she came in contact. Entering preschool in December 1995, Emma’s future looks bright; she is a joyful, independent 3 year old who appears to be happy at pre-school. According to semester narrative reports by Emma’s teachers, she paces herself well, is easygoing and very expressive. Emma’s second year in preschool began in December 1996. Again narrative reports by her teacher report that she is a competent, ingenuous, self-assured child who is confident and outgoing with adults. Emma handles social frustration competently and shows most interest

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in art activities when combined with scientific aspect. Both Emma’s pre-school teachers and parents concern is focused on—“Could it be a hearing problem?” In December 1997, an audiology report reveals that Emma’s hearing is within normal limits. By March 1998, the narrative reports describe Emma as seeming to have a good year. She usually arrives at school quietly, but once here is ready to play and seems to enjoy school. She is very bright and perceptive—always ready to try an activity and to learn something new. Emma is very self-directed and competent. By May, she is very independent and capable; she uses a large vocabulary and has a natural desire to learn. Emma seems to crave knowledge and can remember more details about animals than her mother can. The next road in this journey was the IEP. Emma underwent a separate battery of tests and by end of first grade, Emma had been diagnosed with dyslexia, central auditory processing deficits, mild ADHD, large and small motor weakness (crossing the mid-line). Various interventions were employed to support Emma’s learning throughout elementary school such as books on tapes, vision therapy, the Wilson Reading Program (http://www.wilsonlanguage.com), summer enrichment programs at a residential language immersion camp, attendance at a summer camp for children with learning disabilities, and a one-on-one interactive metronome program. Sixth and seventh grades proved successful because Emma maintained an average of As and Bs, and in Grade 8 Emma took Algebra, with no special services. A series of interventions ranging from low technology to high technology supported Emma throughout her journey through academia. Low technology is defined as non-electronic educational supports that help the learning process (e.g., a highlighter, a pencil grip, a slotted window page cover, a paper dictionary, etc.); whereas, high technology is defined as electronic and computerized equipment or software that provides access to print

A Longitudinal Case Study on the Use of Assistive Technology to Support Cognitive Processes

Table 1. Emma’s Technology Use Progression of Technology Use from Pre-K to Grade 8 Time Period

Low Technology

High Technology

Pre-K to Grade 2

Practical, hands-on activities, use of art materials, use of creative play, and reading stories nightly. Emma and her father begin to create their own oral stories. Vision Therapy (spring of Grade 1). Books on Tape (Library for the Blind) Emma continues to use this technology until Grade 6.

Intense auditory intervention, Emma improved 2 standard deviations on auditory assessment compared to auditory assessment that occurred in the spring. Little high-tech technology is available during this stage of Emma’s development.

Grades 3–5 Groves Academy

Auditory instruction to increase fluency. Wilson Reading Program is used in school. Books on tapes.

Reading Pen Two—used only at home. Alpha Smart computer—Emma’s parents insist be included in her IEP and is provided by the public school system. Interactive Metronome—assists with pacing. Inspiration is introduced to Emma at this time.

Project-based instruction.

Alpha Smart —Emma uses it mostly for word processing. Dragon Naturally Speaking—Parents attempt to introduce this technology to Emma completely fails.

Grades 6–8

Grades 9–11

or virtual material (e.g., text reader, electronic dictionary, computer, etc). Table 1 presents a progression from low-tohigh technology interventions aligned with the time periods of Emma’s life. Table 1 presents a snapshot of the technology used by Emma during her formative years at school. What the table does not include are the endless hours of one-to-one instruction, assistance, and support provided to Emma by her parents, despite teachers’ reluctance to allow the use of certain AT devices in their classrooms.

dAtA sources Assistive technology defined Legislation as early as 1992 provides an official definition for AT (see the Technology Related Assistance for Individuals with Disabilities Act,

Laptop computer (required by the high school), online dictionaries, Quizlet, Write-A Novel-A-Month, dictionary pen, books on tape, tape recorders, pen readers, digital cameras/cell phone cameras, and electronic portable dictionaries, are introduced and utilized by Emma’s parents to maximize accessibility to print media.

cited earlier in this chapter); however, we contend that any device used to support a learner in accomplishing a goal is considered AT. For example, a rubber, plastic, or foam pencil grip is an AT if its use enables the individual to write.

technology tools We provide a sampling of some of the software available on the market that provides access to educational content. CAST UDL Book Builder™ (available at http:// bookbuilder.cast.org). Free online tool enables educators to develop their own digital books to support reading instruction for children aged 3 & up. CAST Strategy Tutor™ (available at http:// cst.cast.org/cst/guest/SPAGE,about). A free online tool to support students and teachers doing reading and research on the Internet, for children ages 10 and up.

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Texthelp’s Read&Write GOLD (available at http://www.readwritegold.com), and Kurzweil Educational Systems’ Kurzweil 3000 (available at http://www.kurzweiledu.com) are text reading, writing, and study skills software programs. ABLEDATA (available at http://www.abledata. com), provides objective information regarding AT devices, software, products, and rehabilitation equipment to consumers. Parents, Let’s Unite for Kids (PLUNK, available at http://www.plunk.org), is an organization that provides training, activities, information, and support to anyone with interest regarding children with disabilities or catastrophic illnesses.

next stePs We have presented a case study of one child—one family struggling for solutions that will unlock the learning potential for their intelligent, curious, remarkably talented, yet print-challenged daughter. To this end, we recommend the following: •

• •

•

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Teacher preparation institutions need to offer courses that provide prospective teachers with the knowledge and experience of AT devices and how to integrate them into daily instructions. Parents need to play an active role in the quest for AT for their child. Policy makers at the state level need to examine the purpose of policy that prohibits students with disabilities from using certain ATs on statewide assessments. District and school administrators need to ensure that schools have the infrastructure necessary to support various ATs.

reFerences Bausch, M. E., Ault, M. J., Evmenova, A. S., & Behrmann, M. M. (2008). Going beyond AT devices: Are AT services being considered? Journal of Special Education Technology, 23, 1–16. Elementary and Secondary Education Act, 1965. (n.d.). Retrieved on January 2, 2009, from http:// nces.ed.gov Michigan Department of Education. (2008). Public agency placement of students with disabilities in private schools. Retrieved on March 1, 2009, from http://www.michigan.gov National Center for Education Statistics. (2008a). Participation in education: Indicator 3, past and projected public school enrollments. Retrieved on January 2, 2009, from http://nces.ed.gov/programs/coe/2008/section1/indicator 03.asp National Center for Education Statistics. (2008b). Participation in education: Indicator 8, children and youth with disabilities in public schools. Retrieved on January 2, 2009, from http://nces. ed.gov/programs/coe/2008/section1/indicator 08.asp United States Department of Education. (n.d.). Part E of Title XIV—Uniform provisions for the participation of private school students. Retrieved on March 1, 2009, from http://www.ed.gov/pubs/ ServPrivate/paret4.html

key terms And deFInItIons Accommodations: Changes in instructional media or processes to provide all learners, especially those with disabilities, full access to the information. Assistive Technology (AT): “[A]ny item, piece of equipment or product system, whether acquired commercially off the shelf, modified, or customized, that is used to increase, maintain,

A Longitudinal Case Study on the Use of Assistive Technology to Support Cognitive Processes

or improve functional capabilities of individuals with disabilities” [20 U.S. C. Chapter 33, Section 1401 (250)]. Case Study: A flexible qualitative research approach that uses multiple data sources in investigating a question. Cognitive Process: Concepts of knowledge and the way individuals use that knowledge. Free Appropriate Public Education (FAPE): The right of all children with disabilities to be educated along with their non-disabled peers. High Technology Device: Electronic and computerized equipment or software that provides access to print or virtual material (e.g., text reader, electronic dictionary, computer, etc). Individual Education Plan (IEP): A prescribed program of instruction for students with disabilities who meet the requirements for services under IDEA. Interactive Metronome: A timing instrument used in therapy to improve planning and sequencing by using neuro-sensory and neuromotor exercises.

Language Immersion Camp: All-inclusive language, culture, and learning programs that foster literacy understanding through communication and cultural activities. Low Technology Device: Non-electronic educational supports that help the learning process (e.g. a highlighter, a pencil grip, a slotted window page cover, a paper dictionary, etc.). Least Restrictive Environment (LRE): A provision of the law that allows students with disabilities to be educated with their non-disabled peers. Narrative: Report that uses direct observational data to provide rich and detailed descriptions of learner progress to inform instructions and programming. Service Providers: Individuals who provide services to students with disabilities who have been identified as meeting requirements for services under IDEA 2007 (e.g., occupational therapists, physical therapists, speech therapists, adaptive physical education teachers, etc.).

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Section 4

Evaluation and Assessment

As is true with any innovation or intervention, evaluation is central to quality control. In the case of assistive technology, it is not as easily carried out during development as in some areas where there already exists a number of products that meet the same need. There are several reasons for this. First, the circumstance surrounding the need for assistive technologies can contribute to the challenges of evaluation. If there is a clear need for a particular device or technical process, and the technology already exists, the need may be so great that there is a rush to make it available for use. Or during the process of development, new technologies may emerge that result in either an assistive technology being moved to implementation too quickly or slowing the development process by switching to the new technology. In assessing the effectiveness of the assistive technology with the targeted user, there are additional factors that can complicate the evaluation process. Depending on the device or the intervention, it may be critical to evaluate its use under precise conditions and in use as intended. Testing can be complicated if the tool is to be tailored to personalized use versus one that can be used in some generic form where the individual intuitively makes decisions on its use. When evaluating tools and/or processes for individuals with special needs, it is often difficult to predict the authentic conditions under which the evaluation will be carried out. Additionally, ensuring use as intended becomes a concern. The latter is of particular concern if use is dependent on another person to train the ultimate user. Systemic to the development of assistive technologies is the focus on scalability and affordability which are interrelated. If the assistive technology can ultimately be developed to scale, the production costs are diminished. However, if each device or process must be produced individually, costs can easily inhibit implementation. Scalability and affordability should always be goals of inventors and developers in this area. That is not to say that in the development of prototypes that the first goal should not be to develop an effective solution using the best technology available. However, once in prototype form, the concern needs to address how best to make it available to those in need. The latter can be as challenging as the initial design and costs are always a factor. External funding is often the source of support, but that should not deter efforts to reduce the ultimate costs. In the context of assistive technologies that impact learning in an academic environment, many needs may be hidden due to a tendency to view low achievement from a global perspective. This may create a vulnerability in which the true needs of students become over-looked. At the postsecondary level, where students with high incidence disabilities tend not to disclose their disabilities, their needs often go unidentified, at least those needs that are in the form of assistive technologies. As sensitivity to universal design increases, awareness of opportunities to push the edge in the utilization of technology, combined with instructional design, will enhance learning. Closely related to evaluation and assessment is implementation and dissemination. While implementation is not a focus of this section, readers are encouraged to think about how evaluation and assessment can facilitate the technology benefits for the intended user. The nature of assistive technology influences how dissemination occurs. Some developers are more inclined than others to consider the commercial sector. For assistive technologies that are clearly scalable, and where the shelf life is somewhat questionable, it is essential for dissemination to be effective. Commercial vendors are in the business of dissemination, and depending on the arrangements, commercialization can result in a revenue stream to support subsequent research and development. The full range of distribution opportunities needs to be explored. There is merit is pursuing these partnerships and we now see more partnership types of relationships involving the commercial sector.

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Chapter 14

Impact of Text-to-Speech Software on Access to Print: A Longitudinal Study Joan B. Hodapp Area Education Agency 267, USA Cinda Rachow Area Education Agency 13, USA

AbstrAct This chapter discusses the outcomes of Iowa Text Reader Project’s 2006-2007 study that evaluated the impact of Kurzweil 3000 during the second year of implementation. This study evaluates the effectiveness of the text-to-speech (TTS) software as an accommodation to improve student access to core content with fluency and comprehension. Using the Time Series Concurrent and Differential Approach (Smith, 2000), this study examines students’ performance on comprehension passages read with and without the TTS software. A balance of perceptual and objective data measures provides data on other student outcomes. Twenty middle school special education students and nine teachers participated in the 27-week study.

IntroductIon In recent years there had been increased interest in the evaluation of the implementation and effectiveness of assistive technology (AT). Particularly, in these times of fiscal restraint educators are becoming acutely aware of the need to substantiate effective outcomes and wise allocation of resources. The 1997 and 2004 reauthorizations of Individuals with Disabilities Education Act (IDEA) mandated that AT devices and services be considered for each student with a disability when developing an Individualized DOI: 10.4018/978-1-61520-817-3.ch014

Education Plan. The inclusion of special education student achievement within the accountability of the No Child Left Behind (NCLB) Act of 2001 raised the level of concern. Now educators are required to use evidence-based interventions with proven effectiveness. Despite these mandates, only limited research has been conducted on the effectiveness of AT to improve student achievement outcomes (Edyburn, 2003, 2007a) with contradictory results (Sorrell, Bell, & McCallum, 2007; Strangman & Dalton, 2005). In a meta-analysis of 68 studies Alper and Raharinirina (2006) identified only 20 that evaluated the effectiveness of AT on the basic academic skills

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Impact of Text-to-Speech Software on Access to Print

of reading, math, spelling, and writing. Twelve of those studies addressed the content areas of math, spelling, or writing. Eight of the studies investigated reading skills. The results supported improvement in skills such as comprehension, decoding, and fluency. Balajthy (2005) reviewed the impact of text-to-speech (TTS) software with struggling readers reporting mixed results across various populations from improvements in comprehension depending on student ability level to poorer results for better readers. Strangman and Hall (2003) identified 13 studies related to the effectiveness of TTS software. However, across all these studies it was difficult to draw firm conclusions due to the diversity of disabilities, age span, technology devices, and lack of replication. Also lacking were data on the effects of attitudes and preferences on the integrity of implementation of AT (Alper & Raharinirina, 2006; Smith, 2000). In response to the need for more research-based interventions, there are an increasing number of studies of AT outcome measures being generated. In an action-based study, Dimmitt, Hodapp, Judas, Munn, and Rachow (2006) assessed the impact of the use of a TTS software program (Kurzweil 3000) on the reading skills of 73 middle school students on outcome measures of reading fluency and passage comprehension. The average reading rates improved by 16 words per minute in 23 weeks, which was 2.3 times faster than would be predicted by research on students with special needs (Fuchs, Fuchs, Walz, & Germann, 1993). The data also indicated a positive trend in the comprehension scores. The average comprehension score improved by 13 percent per student from 59 to 72 percent. Data showed it took 13 weeks for students’ comprehension scores on passages accessed by TTS software to exceed comprehension on print materials. The results demonstrate that the accommodation helps compensate for student reading deficits. Responses to online surveys demonstrated that students and teachers associated the use of the TTS software with improved academic performance, better on-task behavior,

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more engagement with the instructional material, and improved independent work completion. The study results relate to Parette, Peterson-Karlan, Wojcik, and Bardi’s (2007) discussion of the compensatory versus remedial function AT. Lance, McPhillips, Mulhern, and Wylie (2006) compared the performance of three groups (Read and Write Gold, Microsoft Word, and control groups) on literacy tests. After six training sessions of 45 minutes each, the AT group (Read and Write Gold) showed improvement on reading comprehension, homophone error detection, spelling error detection, and word meanings. The Microsoft group showed improvement on spelling error detection and word meanings with a poorer performance on homophone error detection. Meanwhile, the control group showed no improvement on any of these measures. One variable that was identified as linked to positive outcomes was the length of training and intervention (Strangman & Dalton, 2005). To make lasting gains in phonemic awareness, Olson, Wise, Ring, and Johnson (1997) reported that more than 25 hours of student training was required. Both Olson and Wise (1992) and Elbro, Rasmussen, and Spelling (1996) demonstrated results linking long intervention periods and extended training with the positive student gains when using TTS software. Gersten and Edyburn (2007) recommend a treatment interval of nine weeks at a minimum, but valued long-term interventions. Unlike most studies that focused on students with disabilities, Sorrell, Bell, and McCallum (2007) worked with 12 below average readers, grades 2 to 5 who were nominated as below average readers by their teachers. Two of the students were receiving special education services. Employing a counterbalanced randomized treatment design; they studied the impact of TTS software on reading rate and comprehension by randomly assigning participants to either a four-week 40-minute waiting period or treatment group. In this way all students eventually received access to Kurzweil 3000 (version 5) and avoided the problem of

Impact of Text-to-Speech Software on Access to Print

denying students access to the software. During the independent waiting period students engaged in independent silent reading activities using Accelerated Reader (AR) (2006) books. During the treatment period students used the TTS software to access accelerated reader books. No significant results were found. Results indicated differential effects on students depending on their reading rate. While slower readers increased reading rate as a function of the TTS, students reading at instructional level did not improve comprehension. Considering concerns about sample size, short intervention time, use of older software, concerns about the accuracy of the AR quizzes, and use of the technology with students for whom it was not designed, it is difficult to generalize the results to the populations for whom TTS is typically recommended. In light of the new body of literature addressing the measurement of implementation of AT and measurement of outcomes, new concerns arise (Edyburn, 2008). Specifically, the lack of validated measures (Gersten & Edyburn, 2007), failure to measure level of implementation prior to evaluating outcomes (Silverman, Stratman, & Smith, 2002), inadequate intervention duration (Gersten & Edyburn, 2007), and insufficient length of intervention to understand stages of technology acquisition (Edyburn, Fennema-Jansen, Harihan, & Smith, 2005) all raise concerns about the adequacy of existing results. Consistent across all these studies has been the call for more research into the impact of assistive AT on student academic outcomes (Edyburn, 2007b; Hammill, 2004). Not only is this a relatively new field, it has been challenged by a lack of appropriate research designs that could be used (Edyburn, 2007b). The ethics of denying or delaying AT devices or services to students participating as control subjects are considered to be questionable. Review of the literature raises concerns about the insufficient length of the interventions in previous research to ensure sufficient

learning acquisition of the TTS software to truly measure impact on skill development. The purpose of the 2005-2006 Iowa Text Reader Study, a longitudinal study, is to evaluate the effectiveness of a TTS software program (Kurzweil 3000) during the second year of implementation as an intervention to provide student access to the general education curriculum and close the achievement gap between students with disabilities and their age mates. Targeted outcome measures included fluency, passage comprehension, and student engagement such as task completion and on-task behavior. This study sought to examine the following questions: (a) Does the use of TTS software with study skills improved passage comprehension? (b) Does the use of TTS software with targeted study skills improved passage fluency? (c) Is there a selective impact on comprehension of recall versus inferential questions? (d) Are there stages of technology acquisition with TTS software?

bAckground A multidisciplinary study committee, under the auspices of the Iowa Department of Education, designed and managed the implementation of the Iowa Assistive Technology Text Reader Project. Assistive technology liaisons from across the state were trained, collected data, and supported the implementation with students and teachers. Classroom teachers then implemented the design in the classroom setting. Assistive technology liaisons with high levels of integrity of implementation of study procedures from the 2005-2006 Iowa Text Reader Study (Dimmitt, Hodapp, Judas, Munn, & Rachow, 2006) were recruited for the current study. When the AT liaisons were selected, their affiliated teachers and students were automatically included. These twenty students were from the original 61 students randomly selected for the 2005-2006 Iowa Text Reader Study.

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Data on 21 students, from the 2005-2006 study who did not participate in the current study, were monitored in a separate outcome study comparing performance of students who continued to have access to Kurzweil 3000 with those who did not (Hodapp, Judas, Rachow, Munn, & Dimmitt, 2007). The remaining 20 students from the original study were lost when AT liaisons or districts declined to participate for the second year. Reasons for declining participation included student improvement, student no longer needed software, change of staff, and lack of administrative support, hardware issues, or staff workload.

metHodoLogy The 2006-2007 Iowa Text Reader Study engaged twenty special education middle school students and nine special education teachers from eight Iowa school districts in this 27-week study. The participating teachers were the students’ current instructors. Written parental consent and district commitment were obtained prior to participation. Permission was sought from the parents of 21 eligible students. Ninety-five percent of the parents signed the consent to participate. Twelve boys (60%) and eight girls (40%) ages 12-14 participated. Ten (50%) were seventh graders. Ten (50%) were eighth graders. Eligibility criteria included participation in the previous 2005-2006 Iowa Text Reader Study, an Individual Education Program (IEP) with reading goals in the area of passage comprehension, reading fluency, or vocabulary, a mild disability (learning disability, behavioral disorder, or cognitive disability), and scores in the non-proficient range (below the 40th percentile) on the reading subtests of the Iowa Test of Basic Skills (ITBS). The 2006-2007 Text Reader Project included two levels of training. A six-hour refresher training session was provided to the AT contacts focusing on the use of Kurzweil 3000 and the implementation and outcome measures. This

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reviewed the content of the three-day training from fall, 2005. This included curriculum-based measurement strategies, implementation surveys, three target study skills, and student and teacher impact surveys. Navigating Kurzweil 3000 was reviewed. Implementers’ inter-rater reliability exceeded 0.8 on curriculum-based measurement practice probes. Standardization of administration was practiced. Mock interviews using the descriptive data collection tools were conducted to reach consistency. Procedures to access the online surveys were also practiced. The AT contacts then provided local training for the teachers and students who participated in the study. The required training guide binder with the content and format of the training was provided to each contact to be used with local teachers. It focused on navigation of Kurzweil 3000, the three required study skills (i.e., highlighting, identifying pre-reading questions, and identifying main ideas), and integration of the study skills into curriculum and instruction. The AT contacts provided biweekly consultation and coaching to the teachers. They also collected outcome data twice a month directly from the students. Teachers then provided 27 weeks of instruction in at least one the core content subjects of science or social studies. The 2006-2007 Text Reader Study employed the TSCD Approach (Smith, 2000) (see Figure 1.) to study the performance of students using TTS software by comparing student fluency and comprehension on passages accessed with or without TTS software. The students serve as their own control subjects in this design. The difference in performance levels with and without the technology measures the impact of the AT. The order of presentation of print versus TTS accessed passages was randomly varied. These repeated measures over time with and without AT provide evidence of the impact and outcome of AT use (Edyburn, 2005). The expectation would be that enhanced performance would be evident and the achievement gap would narrow.

Impact of Text-to-Speech Software on Access to Print

Figure 1.

For 27 weeks students used Kurzweil 3000 TTS software using the targeted study skills, to access readings in content curriculum such as social studies, science, language arts or other related material. Every other week, students read two different controlled vocabulary passages, one with and one without the use of TTS software. Then, the students’ reading performance (fluency and comprehension) on those passages was measured by the local AT contacts. Multiple measures of implementation and skill development were collected. Six times during the study the teachers completed a measure of implementation. The Level of Use Interview, a Concerns Based Adoption Model tool (Hord, Rutherford, Austin, & Hall, 1987), was used to monitor the implementation of the study components (see Figure 1). Hall and Hord (1987) recommended investigating the relationship between teacher progress in implementing change and student outcomes. The Level of Use Interview generated data on positive information and barriers for implementing the TTS software. The level of implementation of the teacher described in the interview identifies a specific level being used at that time (Anderson, 1997). The results are classified using six stages

of implementation. The Non-use level implies little knowledge with no intention to implement. Orientation requires teachers to begin seeking information and making the decision whether to implement. Preparation implies the teacher is planning to use the intervention. The Mechanical level indicates the teacher is using the intervention, but is struggling with logistics. Routine Use reflects frequent, fluid use. At the Refinement level teachers are making changes to the intervention based on student performance. The Integration level indicates the teacher collaboration with other instructors to expand the implementation. At the Renewal level, teachers desire to make major implementation changes or select alternatives. Teachers need to achieve the Routine level to have reached adequate competence to support the student use. Dimmitt, Hodapp, Judas, Munn, and Rachow (2006) found there was a highly significant correlation between level of use and student reading fluency outcomes (r (760 df) = 0.295535787, p < .0001). The analysis of this data was useful when coaching the implementer to problem-solve issues of concern for using the TTS software.

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As another measure of implementation, teachers submitted four portfolio artifacts demonstrating use of the required study skills. Six times during the study, students and teachers rated themselves on measures of student/teacher implementation (Digital Text Matrices, see Figures 2 and 3). The Student and Teacher Digital Text Matrices measured knowledge and implementation of the software, access to the software, and technology issues. Students worked with an AT contact to complete a Student Digital Matrix. The authors scored the completed matrices. Figure 2.

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At the conclusion of the study both students and teachers responded to perceptual data instruments (Student and Teacher Impact Surveys, see Figures 4 and 5). For further information on the implementation tools discussed see “Measure It, Monitor It: Tools for Monitoring Implementation of Text-to-Speech Software” (Rachow & Hodapp, in press). All measures were double checked by the authors for accuracy and timeliness of implementation. To study the routine use of TTS over an extended time, outcome measures were collected.

Impact of Text-to-Speech Software on Access to Print

Data were collected on student fluency and passage comprehension on carefully matched seventh grade Jamestown Reading Fluency (1996). The paper and scanned probes were matched for reading difficulty as measured by the Flesch-Kincaid Readability Measures. The reading difficulty of

the seventh grade reading passages varied. The probes were sequenced by increasing difficulty from the 6.9 grade level to the 8.9 grade level on both the print and scanned passages. The order of mode of presentation (print versus computer) was randomized. The print and scanned probes

Figure 3.

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Figure 4.

were provided to the implementers in individual student packets and on compact discs. The data were collected every other week by the AT contacts. The accuracy of scoring was double checked by the authors.

resuLts In order to evaluate the academic outcomes of TTS, the 2006-2007 Text Reader Study simultaneously measured levels of implementation using the Level of Use Interview as well as the Student and Teacher Matrices. This tool reflects the natural progression for individuals to master one level and then move to another level of implementation of the AT. According to Bausch and Ault (2008), proper implementation is critical for achieving effective outcomes. Using the Level of Use Interview the study monitored the levels of implementation six times during the 27-week 206

study. It was completed with three teachers (33%). Figure 6 displays the teacher progression implementing the TTS software. In their second year of use, teachers started in week 1 at the preparation level in contrast to beginning at the non-use level in their first year (Dimmitt et al., 2006). In week 5, 100% of the responding teachers were using the TTS software with routine use in their work with students and Kurzweil 3000. By week 11, 66% of the responding teachers were using the TTS software with routine use. At week 17, as additional core content or study skills features were implemented, the level of use was evenly divided between mechanical use and refinement. The rating during week 23 cycled to routine use, as teachers became more proficient with the new refinements. The data indicates that at week 27, 66% of the responding teachers again were implementing new ways to incorporate features of Kurzweil 3000 into their work.

Impact of Text-to-Speech Software on Access to Print

Figure 5.

The Teacher Digital Text Matrix measures both implementation and proficiency of use of the TTS software. Teacher scores reflect individual use and can be rated on a continuum from Beginning Facilitated Implementer (1-9), Emerging Facilitated Implementer (10-15), Proficient Facilitated Implementer (16-21), Proficient Independent Implementer (22- 27), to Skilled Independent Implementer (28-36). See Figure 7 for the teacher scores. Over the course of the study, the progression of individual implementer scores was varied. On average, teachers began at the Emerging Facilitated

Implementer level. No one scored himself or herself at the Beginning Facilitated Implementer level including teachers new to the study. By the end of the 27th-week, the average score ranked teachers in the Proficient Independent Implementer range. No one ranked himself or herself in the Skilled Independent Implementer range. The Student Digital Text Matrix measures both implementation and proficiency of use of the TTS software. Student scores reflect individual use and are rated on a continuum from Beginning Facilitated User (1 to 3), Emerging Facilitated User (4 to 6), Proficient Facilitated User (7 to

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Figure 6. Student digital text matrix scoring guide

Figure 7. Teacher digital text matrix scores

12), Proficient Independent User (13 to 18), to Skilled Independent User (19 to 24). See Figure 8 for student scores. Over the course of the second year of use, the average scores moved from the Beginning Facilitated User level to the Proficient Facilitated

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User level. Two students scored in the Proficient Independent user range. Participating students typically scored no higher than the Proficient Facilitated User level range due to limited opportunities to access technology, teacher changes,

Impact of Text-to-Speech Software on Access to Print

Figure 8. Student digital text matrix

teacher proficiency with the technology, and other systemic barriers. As the final measure of implementation, the four digital artifacts were submitted. Six teachers (67%) submitted digital text portfolio artifacts. The artifacts were evaluated using the Digital Text Artifact Rubric (see Figure 9). User proficiency ratings ranged from non-existent to skilled independent user. Artifacts from the first reporting period demonstrated limited use of highlighting. Artifacts from the second reporting period contained examples of bubble notes with text directions and study guides. These artifacts showed evidence of an organized system of highlighting. Artifacts from the final reporting period demonstrated examples of web-based documents that were student generated. The artifacts submitted at each reporting period paralleled the teachers’ self-assessment ratings of their level of use. The artifacts were useful in validating the levels of implementation reported by the teachers and AT contacts.

Using the Time Series Concurrent Differential Model (Smith, 2000), the 2006-2007 Iowa Text Reader Project measured the impact of the use of Kurzweil 3000 TTS software on students’ ability to access content with fluency and passage comprehension. Gersten, Baker, and Lloyd (2000) suggested collecting numerical data supplemented with rich descriptions of the learning experiences to uncover important relationships between outcome data and intervention procedures. Smith (2000) emphasized the increased importance of subjective data as part of student-focused services. Student or teacher perceptions of the technology may be strong indicators of continued implementation and success. When students were presented two passages of comparable difficulty, presented in print or computer format every other week, access fluency was measured by words read per minute and reader rate. The mode of presentation was randomized. On average, students accessed the computer passages at the rate of 160 words per minute while they read paper probes at an average rate of 79

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Figure 9.

words correct per minute (see Figure 10). The students maintained their reading fluency on paper passages even as passage difficulty increased. With scanned text, the students accessed twice the amount of material in the same amount of time. This accommodation addresses the difficulty

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students have reading the volume of assigned text in the typical core curriculum. This accommodation helps students compete with their peers who routinely read 150-160 words per minute. Performance of students on the passage comprehension probes, for both paper and scanned

Impact of Text-to-Speech Software on Access to Print

Figure 10.

computer formats, can be seen in Figure 11. The readability of the reading passages, both print and scanned, was matched and sequenced in order of increasing difficulty, from the 6.9 grade level to the 8.9 grade level. As can be seen in Figure 11, comprehension scores when students read print text declined as the reading difficulty increased. When accommodated with the Kurzweil 3000 software, the trendline of passage comprehension scores improved, even as the reading difficulty continued to increase. The slopes indicate a diverging pattern of the trendlines. Performance was better initially for print text as compared to scanned text. However, by week seven, as the students began to master the use of the TTS software, their comprehension trendline began to outpace the paper performance. The comprehension scores for the print probes dropped 11 points from the 58% to 47%. The comprehension scores for the scanned probes, however, improved 4 points from 54% to 58% as passage difficulty increased. This data suggests the TTS serves a

compensatory rather than a remedial function in supporting student access to content. The significance of these diverging trendlines was evaluated. For each student, for each week, the difference between his or her score on computer and paper probes was calculated. An analysis of variance revealed that these difference scores changed over time, and the result was highly significant, F score (4.712, p < .001), showing that the differences between paper and computer comprehension scores over time were significant. Figure 11 displays evidence of a pattern of regression over the summer from the previous school year. Possible factors could include regression and recoupment, new instructional staff, and increasingly demanding curriculum. However, the second year data shows a pattern of earlier crossover of trendlines. During their second year of use, crossover occurred at week seven where comprehension on computer assisted reading exceeded comprehension on paper probes. This

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Figure 11.

is contrast with the results of 2005-2006 Iowa Text Reader Study (Dimmitt et al., 2006), when students did not reach the tipping point (point at which student performance trendlines crossed and continued to diverge) until the thirteenth-week of intervention. To examine the difference in performance on fact recall versus inference comprehension questions, the data was further analyzed as displayed on Figure 12. In looking at the interaction of question type with presentation format, several interesting findings were apparent. Performance on fact comprehension questions was consistently stronger than inferential comprehension on both paper and computer probes. As the passages increased in difficulty, accuracy on paper probe fact questions dropped while accuracy on computer probe fact questions remained stable. Comprehension scores for fact questions on the paper probes dropped 17 points from 70% to 53%. Comprehension scores for fact questions on the computer probes remained

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steady at 62%. These results contrast with results of the 2005-2006 Iowa Text Reader Study (Dimmitt et al., 2006), where accuracy with fact questions on computer probes dropped 4 points. On computer and paper inferential questions, the trendlines diverged as passage difficulty increased. The initial scores on the inferential comprehension questions were the same for paper and computer probes. As passage difficulty increased the inferential trendlines diverged with performance on computer probes improving while paper probes decreased. Comprehension scores for inferential questions on the paper probes dropped 6 points (from 47% to 41%). Comprehension scores for inferential questions on computer probes increased 6 points (from 47% to 53%). This contrasts with the results of 2005-2006 Iowa Text Reader Study (Dimmitt et al., 2006), where accuracy with inferential questions on computer probes dropped one point. That indicates a change of trendline direction and a 7-point improvement in comprehension scores when comparing the two years. This reflects that

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Figure 12. Interaction of question type with presentation format

student performance on inferential questions (higher level thinking) improved. The statistical significance of these diverging trendlines for the interaction of question type and mode of presentation was evaluated. For each student, for each week, the difference between his or her score on computer versus paper probes and fact versus inference questions was calculated. An analysis of variance revealed that these difference scores changed over time, and the result was highly significant, F score (7.215, p < .0001), showing that the differences between paper and computer comprehension scores over time were significant. This is evidence of the empirical significance, as well as the educational significance of the effectiveness of this accommodation. To measure teacher opinions toward Kurzweil 3000 during their second year of use, the Teacher Impact Survey was conducted. Eight teachers (89%) completed the online survey—Teacher Impact Survey (see Figure 13). The teacher group

consisted of some first and second year implementers. Teachers continued to attribute strong positive impact on student reading, comprehension, and students’ ability to work independently. Decreases were observed in schools teachers had previously felt were impacted by the use of TTS, such as attendance and student self-confidence. To measure student attitudes toward Kurzweil 3000 during their second year of use, the Student Impact Survey was conducted. At the end of week 27, 20 students (100%) completed an online survey assessing their impressions of the project and the impact of the TTS software on their access to the general education curriculum. See Figure 14 for the results of the Student Impact Survey. During the second year of use, students continued to respond very positively to essential impact elements like understanding what was written in the text, helping with their reading, doing their work independently, and learning to use the software. The four highest scores, the Essential Impact Ele-

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Figure 13. Teacher impact survey

ments, are consistent with the factors shown to increase acceptability of interventions and integrity of implementation (Gresham, 1989). Students maintained consistently high levels of positive attitudes toward using TTS and perceptions of its impact. They did not appear to experience user fatigue, boredom, or satiation with the software. This suggests the positive impact of the TTS AT software reinforces the students’ continued use.

dIscussIon Very limited research has been conducted on the impact of AT on student reading content outcomes. Since traditional instructional strategies have had limited success for individuals with reading deficits, it is vital to find other strategies which provide cognitive access (Abell, Bauder, & Simmons, 2005). As Edyburn (2007) stated, little is known

about the effect of routine use of TTS and whether students will need different reading and literacy skills. Given this line of thinking, do teachers need new instructional and technology skills? This longitudinal study of the second year of use of TTS in core content subjects demonstrated significant results impacting students’ ability to access reading passage, improve overall comprehension as well as higher level thinking and improve student attitudes and engagement. Students accessed twice the amount of scanned text as print text in the same amount of time when using TTS software consistent with the findings of 2005-2006 Iowa Text Reader Study (Dimmitt et al., 2006). This accommodation supports students’ need to access core general education curriculum as well as the need to manage the pace and volume of content. This implies students will have more fluent access to the text, thereby freeing up cognitive resources that can be applied to comprehension. In

Figure 14. Teacher impact survey results: Essential impact elements

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a review of the literature, Strangman and Dalton (2005) found evidence that digital technologies have the potential to support struggling readers in both compensatory and remedial ways by not only providing access to text but helping students learn how to read with understanding. The study results found that even as students successfully accessed twice as much content in the same time period, their comprehension improved when supported with TTS software. For the first time, this study demonstrated the statistically significant impact of use of the text–to-speech software on student passage comprehension. This finding showed that the differences between paper and computer comprehension scores over time were significant when the Kurzweil 3000 supported access to the content. In other words, even as the students used the TTS software to access the curriculum materials at twice the rate, they were able to maintain or improve their comprehension levels on increasingly difficult material. This supports the supposition that TTS software may bypass or remediate decoding problems enabling students to focus cognitive resources on constructing meaning from the text (Strangman & Dalton, 2005). Another significant new finding was the impact of the TTS software on student comprehension scores for both factual and inferential questions. With the TTS software, factual comprehension scores were maintained while scores on the inferential comprehension tests improved even as the level of instruction increased. Without the accommodation, both comprehension scores on print text decreased. Here is dramatic evidence of an effective strategy to improve higher level thinking. The use of the TTS software with targeted study skills significantly improved comprehension on factual and inferential questions. These results are also educationally significant. From a teacher perspective, the students would be more likely to be able to access and understand the same material as their peers while working independently. The results demonstrate that students

can access the core materials at twice the rate, with understanding, at levels of higher thinking—thus allowing them to work more competitively in a general education setting. This study replicated findings that positive outcomes with TTS software are associated with extended training and use (Elbro, Rasmussen, & Spelling, 1996; Olson, Wise, & Ring, 1997; Olson & Wise, 1992; Strangman & Dalton, 2005). While, in the first year of use, students needed 11 weeks to show positive impact on passage comprehension (Dimmitt et al., 2006), the current study demonstrated that these same students in their second year of use of TTS experienced a seven-week regression over the summer. Additional research is needed to further examine the patterns of regression over school breaks. Also, future research into the effectiveness of TTS should provide sufficient length of intervention before evaluating impact (Olson, Wise, Ring, & Johnson, 1997). Edyburn (2007b) found little research has been done on the effects of routine use of reading technologies on student interest, motivation, and engagement. The current study demonstrates that over the two-year period participants maintained generally positive perceptions and attributed many positive outcomes to the use of the TTS software. Teacher reports mirrored the highly positive support on the three critical elements of whether it helped students read, increased student independence, and helped students understand their textbooks. The survey results replicated other positive outcomes teachers associated with the use of the TTS software including improved academic performance, better on-task behavior and more engagement in the instructional materials. These improvements suggest improved student engagement and increased access to core instruction and curriculum (Elkind, Cohen, & Murray, 1993). Strangman and Dalton (2005) suggest that improved engagement should be an important criterion used to evaluate the effectiveness of literacy instruction. In light of student-centered

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interventions, Smith (2000) posited that subjective outcome measures most accurately predict how successful learners will be with AT since their perceptions predict continued usage. These improvements suggest improved student engagement and increased access to core instruction and curriculum (Elkind, Cohen, & Murray, 1993). As individuals implement new innovations and as self and task concerns are largely resolved, individuals can then focus on the impact of the intervention (Hord, Rutherford, Austin, & Hall, 1987). This study demonstrated that as teachers move into more sophisticated use of the TTS software, new skills are assimilated into the teaching repertoire. However, there was evidence that lack of teacher proficiency created artificial ceilings for student progress. Strangman and Dalton (2005) reported that students with special needs did not use all resource features of the software without instructor support. When teachers lack the proficiency or fail to provide access, students will be unable to move to total independence. It appears further research is needed to determine the extent to which teachers need support and coaching as much as the students do to insure mastery and high levels of implementation. Even with a smaller research group, the experience of the Iowa Text Reader Study highlighted the successes and difficulties of conducting statewide action-based research. The training demands, the technological difficulties, and level of coaching needed to maintain the study’s integrity proved challenging. There were still difficulties with scheduling and managing the work in addition to teacher workload. Frustrations still remained over the difficulty in conducting research with human subjects and the inability to identify a control group, however, denial of an appropriate instructional accommodation to eligible students was not an option. While the use of the TSCD model allowed the students to serve as their own controls, future research is needed comparing subjects with and without the intervention of TTS software.

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summAry Students with special needs in this study clearly benefited from the routine use of TTS software to accommodate access to reading passages. Positive outcomes included improved fluency of access to content and improved passage comprehension. A surprising finding was the positive impact on comprehension of both factual and inferential questions. Evidence was provided that students require extended interaction with the software before there is evidence of an impact. Students need instructional supports to insure they will use all the features of the TTS software. Teacher proficiency levels create artificial ceilings when teachers fail to provide access or training opportunities for their students. In the second year of use, the students moved to more fluid use sooner than they did in the first year. In the second year of use, the teachers engaged more quickly and at higher levels of proficiency.

AcknoWLedgment This project was funded by the Iowa Department of Education under the leadership of Steve Maurer. The authors wish to recognize the expertise and work of Clair Judas, Sandy Dimmitt, and Cindy Munn, the other members of the project steering committee as well as the students, teachers, administrators, and AEA AT contacts who participated in this project.

reFerences Abell, M. M., Bauder, D. K., & Simmons, T. J. (2005). Access to the general curriculum: A curriculum and instruction perspective for educators. Intervention in School and Clinic, 41, 82–86. doi :10.1177/10534512050410020801

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Accelerated Reader. (2006). Renaissance Learning, Inc. Retrieved from http//www.renlearn.com/ ar.com/default/htm.

Edyburn, D. L. (2008). Measuring outcomes in Assistive Technology. Special Education Technology Practice, 10(4), 16–21.

Alper, S., & Raharinirina, S. (2006). Assistive technology for individuals with disabilities: A review and synthesis of the literature. Journal of Special Education Technology, 21(2), 47–64.

Edyburn, D. L., Fennema-Jansen, S., Harihan, P., & Smith, R. (2005). Assistive Technology outcomes: Implementation strategies for collecting data in schools. Assistive Technology Benefits and Outcomes. Retrieved from http://www/atia. org/atob/ATOBWeb/ATOBV2N1/Documents/ [email protected]

Anderson, S. (1997, Fall). Understanding teacher change: Revisiting the Concerns Based Adoption Model: Curriculum inquiry. Professional Development Collection. Balajthy, E. (2005, January/February). Textto-speech software for helping struggling readers. Reading Online, 8(4). Retrieved from http://www.readingonline.org/articles/artindex. asp?HRE=balajthy2/index.html. Bausch, M. E., & Ault, M. J. (2008). Assistive technology implementation plan: A tool for improving outcomes. Teaching Exceptional Children, 41(1), 6–14. Dimmitt, S., Hodapp, J., Judas, C., Munn, C., & Rachow, C. (2006). Iowa Text Reader Project impacts on student achievement. Closing the Gap, 24(6), 12–13. Edyburn, D. L. (2003). Measuring assistive technology outcomes: Key concepts. Journal of Special Education Technology, 18(1), 53–55. Edyburn, D. L. (2005). Technology enhanced performance. Special Education Technology Practice, 72(2), 16–25. Edyburn, D. L. (2007a). 2006 year in review: What have we learned lately? Paper presented at the 25th Annual Closing the Gap Conference, October 18, Minneapolis, MN. Edyburn, D. L. (2007b). Technology-enhanced reading performance: Defining a research agenda. Reading Research, 42(1), 146–152. doi:10.1598/ RRQ.42.1.7

Elbro, C., Rasmussen, I., & Spelling, B. (1996). Teaching reading to disabled readers with language disorders: A controlled evaluation of synthetic speech feedback. Scandinavian Journal of Psychology, 37, 140–155. doi:10.1111/j.1467-9450.1996. tb00647.x Elkind, J., Cohen, K., & Murray, C. (1993). Using computer-based readers to improve reading comprehension with students with Dyslexia. Annals of Dyslexia, 42, 238–259. doi:10.1007/ BF02928184 Fuchs, L., Fuchs, D., Hamlett, C. L., Walz, L., & Germann, G. (1993). Formative evaluation of academic progress: How much growth can we expect? School Psychology Review, 22, 1–30. Gersten, R., Baker, B., & Lloyd, J. W. (2000). Designing high-quality research in special education. The Journal of Special Education, 34(1), 2–18. doi:10.1177/002246690003400101 Gersten, R., & Edyburn, D. L. (2007). Enhancing the evidence base of special education technology research: Defining special education research quality indicators. Journal of Special Education Technology, 22(3), 3–18. Gresham, F. M. (1989). Assessment of treatment integrity in school consultation and prereferral intervention. School Psychology Review, 18, 37–50.

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Hall, G., & Hord, S. (1987). Change in schools: Facilitating the process. New York: State University Press. Hammill, D. (2004). What we know about correlates of reading. Exceptional Children, 70(4), 453–468. Hodapp, J., Judas, C., Rachow, C., Munn, C., & Dimmitt, S. (2007). Iowa Text Reader Project Year 3: Longitudinal results. Paper presented at the 25th Annual Closing the Gap Conference, October 20, Minneapolis, MN. Hord, S., Rutherford, W. L., Austin, L., & Hall, G. E. (1987). Taking charge of change. Alexandria, VA: Association of Supervision and Curriculum Development. Jamestown Reading Fluency. (1996). Glencoe Publishing. Retrieved from http://www.glencoe. com/gln/jamestown/reading_rate/reading_fluency.php Lance, A. A., McPhillips, M., Mulhern, G., & Wylie, J. (2006). Assistive software tools for secondary-level students with literacy difficulties. Journal of Special Education Technology, 21(3), 13–22. Olson, R. K., & Wise, B. (1992). Reading on the computer with orthographic and speech feedback. Reading and Writing: An Interdisciplinary Journal, 4, 107–144. doi:10.1007/BF01027488 Olson, R. K., Wise, B., Ring, J., & Johnson, M. (1997). Computer-based remedial training in phoneme awareness and phonological decoding: Effects on the post-training development of word recognition. Scientific Studies of Reading, 1, 235–253. doi:10.1207/s1532799xssr0103_4 Parette, H., Peterson-Karlan, G., Wojcik, B., & Bardi, N. (2007, September). Monitor that Progress! [from Academic Search Elite database.]. Teaching Exceptional Children, 40(1), 22–29. Retrieved January 3, 2009.

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Rachow, C., & Hodapp, J. (In press). Measure it, monitor it: Tools for monitoring implementation of text-to-speech software. Handbook of Assistive Technology (In press). Silverman, M. K., Stratman, K. F., & Smith, R. O. (2000). Measuring assistive technology outcomes in schools using functional assessment. Diagnostique, 25(4), 307–327. Smith, R. O. (2000). Measuring assistive technology Outcomes in education. Diagnostique, 25, 273–290. Sorrell, C. A., Bell, S. M., & McCallum, R. S. (2007). Reading rate and comprehension as a function of computerized versus traditional presentation mode: A preliminary study. Journal of Special Education Technology, 22(1), 1–12. Strangman, N., & Dalton, B. (2005). Technology for struggling readers: A review of the research. In Edyburn, D. L., Higgins, K., & Boone, R. (Eds.), Handbook of special education technology research and practice (pp. 545–569). Whitefish Bay, WI: Knowledge by Design. Strangman, N., & Hall, T. (2003). Text transformations. Wakefield, MA: National Center on Accessing the General Curriculum. Retrieved February 23, 2007, from http://www.cast.org/ publications/ncac/ncac textrans.html

key terms And deFInItIons Assistive Technology (AT): A category of technology used by persons with disabilities to provide access and help perform tasks in living, learning, and working as well as increase independence, and quality of life. Cognitive Access: Access to the information through alternate formats or strategies such as scaffolding, digit format, Braille, TTS software, or mental mapping.

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Implementation: Application of the innovation with strict compliance to the intervention schedule (i.e., fidelity (quality of application) and integrity (completely and as scheduled)). Outcome Measures: Technically adequate and sensitive measures of the effects of the technology on the targeted skill area. For example, if the target is improved reading skills, an appropriate outcome measure would include curriculum-based measurement data which has been proven to be reliable and valid. Progress Monitoring: Routine monitoring of assessment data used as formative data to make instructional decisions. It is most commonly associated with the use of curriculumbased measurement data with decision rules for instructional changes. Student performance

improves significantly when used with graphing and decision rules. Text-to-Speech Software: A category of software using scanned digitized text that can convert any written text into spoken word. It allows access to software and digital documents such as MS Word, web page, PDF files, and the Internet. Leading examples include Kurzweil 3000, Read and Write Gold, and Wynn Scan and Read Software. Time Sequence Differential Concurrent (TSCD) Model: A research design that compares student performance of the same task with and without technology to measure the impact of assistive technology.

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Tools for Monitoring Implementation of Text-to-Speech Software Joan B. Hodapp Area Education Agency 267, USA Cinda Rachow Area Education Agency 13, USA

AbstrAct This chapter addresses the importance of systematic assessment using a variety of tools to evaluate implementation and monitor the outcomes of assistive technology innovations. A variety of the tools and strategies—developed to monitor implementation and change, gather perceptual data, and collect academic outcome data—are discussed. These tools and strategies were developed and tested in the 2005-2006 and 2006-2007 Iowa Text Reader Studies. Applications of the tools are featured for various stakeholders, such as teachers, administrators, and researchers. Multiple research designs to determine the impact of assistive technology, including the Time Sequence Concurrent Differential Model, are contrasted.

IntroductIon The intent of this chapter is to share a variety of the tools and strategies developed to monitor implementation, gather perceptual data, and collect outcome data. These tools were tested in the 2005-2006 and 2006-2007 Iowa Text Reader Studies (Dimmitt, Hodapp, Judas, Munn, & Rachow, 2006; Hodapp, Rachow, Judas, Munn, & Dimmitt, 2007; Rachow & Hodapp, 2008). These tools focused on providing a convergence of data that are sensitive to change DOI: 10.4018/978-1-61520-817-3.ch015

from multiple sources and multiple stakeholders by triangulating the data. Instruments addressed include: implementation tools for text-to-speech software, both specific and universal; data analysis tools for individuals and groups; research models; innovative survey strategies; and rubrics for textto-speech teacher portfolio artifacts.

bAckground With the passage of the Education of All Handicapped Children Act (P.L.94-142) in 1975, the focus

Copyright © 2010, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

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and mandate for improving academic achievement for students with special needs have increasingly narrowed and become high stakes concerns for school districts. Initially, concerns were focused on providing student access to the general education curriculum. Now, the emphasis has moved to student outcomes documenting closure of the achievement gap between students with special needs and their typical peers by providing this cognitive access to the general education curriculum (Abell, Bauder, & Simmons, 2005; Hitchcock, Meyer, Rose, & Jackson, 2007). The inclusion, for the first time ever, of special education student achievement within the accountability of the No Child Left Behind (NCLB) Act of 2001 raised the level of concern for student proficiency from the individual to the systems level. Since the mandate of Individuals with Disabilities Education Act (IDEA) of 1994, and despite the requirement of NCLB to utilize research-based strategies, only limited research has been conducted in the fourteen years on the effectiveness of assistive technology (AT) to improve student achievement regardless of instructional area (Edyburn, 2003, 2007). DeRuyter (1994, 1997) attributed the paucity of research to lack of both subjective and objective measurement tools to support or deny the effectiveness of AT. Gersten and Edyburn (2007) attributed the overdependence of consumer satisfaction surveys to the lack of validated outcome measures. Numerous researchers have commented that more attention was paid to the device selection than implementation and outcome measurement (Bausch & Ault, 2008; Edyburn, 2008; Parette, Peterson-Karlan, Wojcik, & Bardi, 2007). Edyburn (2003) defined ten variables, such as change in function, change in participation, goal achievement and usage associated with AT use that could be indicators to help understand the outcomes. Indeed, it is only recently that the concept of an implementation plan including tools for measuring outcomes has been introduced into the literature (Bausch &

Ault, 2008; Edyburn, Fennema-Jansen, Harihan, & Smith, 2005; Malouf & Hauser, 2005).

Innovative tools to monitor Implementation of textto-speech software DeRuyter (1997) called for more accountability as well as development of performance and quality monitoring tools to prove the value and impact of AT. Edyburn (2008) delineated six variables that should be measured as part of an AT outcome measurement system. The variables included student performance, consumer satisfaction, quality of life, cost, goal achievement, and change in participation. Without an understanding of the level of implementation of an intervention, Silverman, Stratman, and Smith (2000) feel it is impossible to accurately measure the impact of an innovation. To measure implementation, including affective and behavioral dimensions of change in response to text-to-speech intervention, the Iowa Text Reader Studies designed several instruments based on the Concerns Based Adoption Model (CBAM) (Hord, Rutherford, Austin, & Hall, 1987). The Concerns Based Adoption Model was selected based on its reputation as a widely recognized and validated model for monitoring teachers’ responses to changes in curriculum and instruction. Anderson (1997) conducted a literature review on CBAM, which documented the robust and empirical foundations of this theoretical model. Anderson summarized CBAM’s five assumptions basic to educational change: (a) change is a process not an event, (b) change is accomplished by individuals, (c) change is a highly personal experience, (d) change involves developmental growth, and (e) change can be facilitate by interventions towards the individuals, innovations, and the context (p.333). The Iowa Text Reader Projects adapted the three primary tools CBAM developed to monitor change: Innovation Configuration, Stages of Concern Survey, and Level of Use Interview. The first tools to be discussed here are the Student

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Digital Text Matrix, Teacher Digital Text Matrix, Digital Text Artifact Matrix, and the Level of Use Survey. The matrices are modeled after the CBAM Innovation Configuration.

Figure 1.

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Student Digital Text Matrix The Student Digital Text Matrix records student progress in mastering the Kurzweil 3000 software across six domains. The Student Digital Text Matrix (see Figure 1) measures knowledge and implementation of the software, access to the

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software, and technology issues. The matrix was designed to be able to monitor individual change as well as system change. The matrix also provides data vital to setting outcome goals for terminal skill on software and application skills. Students completed the matrices six times during the school year. The self-assessment format of the Student Digital Text Matrix allows for reflection and goal setting. The resulting conversations provide immediate feedback and re-teaching opportunities. This provides an opportunity for consultation and intervention between student and teacher as part of the interactive change process. The data used could lead to direct instruction, accommodations or increased access to the hardware and software technology to encourage continued student skill development. Using the Student Digital Text Matrix Scoring Guide (see Figure 2), the matrix was scored and the Total Matrix Score was recorded. The student’s total score was then interpreted and assigned a rating from Non-User to Skilled Independent User. Student progress was analyzed on each matrix and longitudinally by charting scores over time. Student scores were grouped providing systems level analysis. This matrix provides formative student data on access and proficiency using the Kurzweil 3000 or other text-to-speech reader

software. This information informs the individual and systems level decision-making. Fuchs and Fuchs (1986) reported that when data were graphed as part of formative evaluation, average achievement outcomes improved almost .8 standard deviations than when not graphed. Figure 3 demonstrates use of graphing student proficiency on the Kurzweil 3000 software using the Student Digital Text Matrix to monitor progress and make implementation decisions. Using this monitoring strategy, Hodapp, Rachow, Judas, Munn, and Dimmitt (2007) determined that restrictions limiting student access to technology created artificial barriers to full implementation of advanced software features and skill development. As part of the implementation plan, follow-up focused on identifying causes and solutions for these barriers. In some cases the teachers needed additional training on the advanced features. In other cases, the barriers were due to lack of access to the technology that was remedied by granting student permission to use the scanners.

Teacher Digital Text Matrix The Teacher Digital Text Matrix (see Figure 4) provides a systematic way to monitor teacher mastery and implementation of text-to-speech software

Figure 2. Student digital text matrix scoring guide

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Figure 3.

across nine components to include knowledge of the software components, availability, access, scanning and editing, and awareness of embedded study skills. This tool also helps teachers organize, manage, and integrate their instructional plan for hardware and software mastery and instruction. Self-assessment using the Teacher Digital Text Matrix allows teachers to identify short and long-term goals, seek appropriate consultation, improve access to technology, or target specific student skill instruction. For example, Hoffman, Hartley, and Boone (2005) reported barriers to implementation still exist as late as 2002 in 8% of instructional classrooms where they lack Internet access. Another important factor is the ratio of students to instructional computers with Internet access. The ratio improved from 12.1 to 1 in 1998, to 4.4 in 2003, and to 3.8 to 1 in 2005 (U.S. Department of Education, 2006). Depending on local ratios, this would create barriers for successful implementation. This would be valuable data when consulting with administrators. Silverman, Stratman, and Smith (2000) reported these complex issues where the greatest barriers

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to the effective use of technology. As Love (2002) states, data can convince people of the need for change by identifying causes, pinpointing priorities, and guiding resource allocation. Each domain is scored and the Total Matrix Score calculated. Then, the teacher’s total score can be interpreted and assigned a rating ranking from Non-User to Skilled Independent User (see the Teacher Digital Text Matrix Scoring Guide, Figure 5). Possible teacher uses of the Matrix include self-assessment and progress monitoring. Formative data can be collected longitudinally by charting scores over time. The matrix provides formative data on access, management, and proficiency using the Kurzweil 3000 or other text-tospeech reader software. As part of a systems level implementation scores for staff could be grouped and graphed to provide systems level analysis. This information informs the individual and systems level decision-making. Data is provided on specific teacher’s skill development, and implementation, as well as system level information useful for resource allocations.

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Figure 4.

Digital Text Artifact Rubric Stiggins (1987) calls for authentic assessments that require students to apply the skills and knowledge they have mastered. Stoof, Martens, and Merrienboer (2007) used web-based technology to monitor authentic assessment using competence

mapping. The Digital Text Artifact Rubric (see Figure 6) measures skills and knowledge at two levels, one at the individual and other at the systems level. On the individual teacher level, the rubric provides a self-assessment tool for teacher use. The rubric defines and measures the application of skill features of the text-to-speech software.

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Figure 5. Teacher digital text matrix scoring guide

Using this data, teachers are able to monitor the quality of their artifacts and identify personal targets for ongoing successful implementation. By attaching the rubric as a reflection to their artifacts as part of their professional development portfolio, teachers help inform their administrators who might be less technologically proficient of the software features. It has the added benefit of positively structuring their evaluative feedback. This becomes increasingly important as more and more professionals use electronic portfolios documented with electronic artifacts. It also provides a sophisticated format beyond the traditional teacher logs administrators can use to view application of acquired skills as part of instruction and implementation. Administrators are more likely to support continued funding for software they see implemented. Finally, administrators can use the rubric to monitor the implementation by evaluating teacher group data to validate capital outlay to their board. In addition, researchers use the rubric to monitor the integrity and fidelity of implementation of their research design. Using the Digital Text Artifact Rubric, Rachow and Hodapp (2008) were able to monitor their research design integrity by assessing teacher instructional artifacts as evidence of mastery and use of required software features. The artifact could also provide

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a format for feedback and goal setting as part of the study. The Digital Text Artifact Rubric evaluates teacher artifacts across 7 domains aligned with the Kurzweil 3000 features. The domains rate teacher proficiency on the featured accommodations of the Kurzweil 3000. The Total Rubric Score is rated on a User Proficiency Scale from Non-existent to Skilled Independent User (see the Digital Text Artifact Matrix Scoring Guide, Figure 7). A more generic version entitled the Digital Text Artifact Rubric—Universal (see Figure 8) provides a similar format for progress monitoring with other text-to-speech software programs such as Read and Write Gold and Wynn Scan and Read Software (see Figure 9).

Level of use Interview Hord, Rutherford, Austin, and Hall (1987) developed the Level of Use (LOU) Interview to map the developmental pattern of teacher behaviors as part of the CBAM. While the Digital Text Matrix measures the implementation and mastery of the text-to-speech software, the Level of Use interview provides measurement of teacher behavior directly related to implementation of the software. Anderson (1997) described CBAM’s six stages of

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Figure 6.

use from Level 0, Non-use to Level 6, Renewal as a progression marking key decision points and resulting behaviors necessary to implement and sustain change. Hall and Louks (1977) report

that knowing the LOU score of implementers allows researchers or administrators to avoid negative assumptions or incorrect interpretations regarding users/nonusers performance. The pe-

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Figure 7. Digital text artifact rubric scoring guide

riodic interview tool also stimulates participant compliance as part of the implementation plan. Experience teaches that what gets monitored gets done. The interviewers use the interview to identify barriers to full implementation that can then be addressed. The Iowa Text Reader Studies (Dimmitt, Hodapp, Judas, Munn, & Rachow, 2006; Hodapp, Rachow, Judas, Munn, & Dimmitt, 2007; Rachow & Hodapp, 2008) adapted the CBAM Level of Use Interview format specific to the text-to-speech software. Early experience demonstrated that novice interviewers had trouble following the required branching question format. To reduce errors, the Iowa Text Reader Studies designed an online automatically branching question format. Also, use of an online format increases survey completion rates. In a comparison of paper, fax, or web-based surveys, Cobanoglu, Warde, and Moreo (2001) observed response rates of 26%, 17%, and 44% respectively. Also, the online Level of Use Interview automatically scored the interview thus reducing another source of variance in the data. The online Level of Use Interview (see Figure 10) provides the interviewer with the questions and responses. Then, based the teacher response automatically branches to the next appropriate

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question. At the conclusion, the online Level of Use Interview calculates the level of use from non-use to renewal. Administrators and researchers can also use the online Level of Use Interview data to track group data. This provides a visual representation of the movement of the level of sophistication of implementation. Figure 11 uses Level of Use Interview data to map the progress of implementation of the text-to-speech software over the eleven weeks. Analyzing the data in week one, we can clearly see the pattern of implementation. One half of the teachers were non-users. Three teachers needed more information to implement the program. Two teachers were using the software to support instruction in a step-by-step mechanical manner. One teacher had reached fluent and routine use of the software while one teacher was collaborating with others. By examining the transition of user level across the eleven weeks, the researcher/administrator recognizes that there are still two non-users due to hardware problems but the majority had moved to higher levels of implementation. Rather relying on opinion, this provides actual data to inform professional development and resource allocation decisions.

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Figure 8.

Innovative tools to gather Perceptual data on textto-speech software Participant satisfaction surveys provide another data source on the impact of AT. Balanced with

objective measures, DeRuyter (1997) reminds researchers “subjective measures, or how the consumer perceives the quality of the service of the product, are a reality and are inherent within outcome management research” (p.103). Marzano (2000) found collecting data from multiple sources 229

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Figure 9. Digital text artifact rubric scoring guide: Universal

Figure 10. Level of use survey demo

like direct data and perceptual data allows more comprehensive understanding of the outcomes and needs of an initiative. Iowa Text Reader Studies (Dimmitt, Hodapp, Judas, Munn, & Rachow, 2006; Hodapp, Rachow, Judas, Munn, & Dimmitt, 2007; Rachow & Hodapp, 2008) developed impact surveys to seek feedback data from both the students and teachers implementing the textto-speech software using an online format.

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Student Impact Survey The Student Impact Survey (see Figure 12) polled participant opinions on the following domains: enjoyment of use, ease of learning the program, ease of use with school work, impact on reading as well as a range of school behaviors like working independently, staying on task, and improving interest in their learning. The survey was completed online. The online survey automatically tabulated the results and summarized them graphically. Similar to the results of Cobanoglu, Warde, and Moreo (2001), response rates increased when the

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Figure 11.

Figure 12.

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Figure 13. Student impact survey

survey was provided online. Comparing student survey responses across two years of implementation provided longitudinal data on the attitude and behaviors after extended use (see Figure 13). Teacher Impact Survey. The Teacher Impact Survey also polled participant opinions. Teachers were asked for input on similar domains using an online survey. Again, the survey automatically scored, charted, and graphed results (see Figures 14 and 15).

Innovative tools to monitor Academic outcomes Impacted by text-to-speech software Educators and researchers have struggled to find outcome measures sensitive to change and to find research designs that allow for authentic assessment without denying students access to the AT that they require. The limited research on the effectiveness of AT is dominated by single subject design studies. Parette, Peterson-Karlan, Wojcik, and Bardi (2007) summarized substantive criticism of the use the ABAB multiple baseline or the ABA basic withdrawal research designs on basis of ethical and practical problems associated with

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removing opportunities for technology. Teachers and students object. How can you deny access to an accommodation to which the child is entitled? Also, neither design addresses the impact of longterm use of the technology. Sorrell, Bell, and McCallum (2007) employed a counterbalanced randomized treatment design to study the impact of TTS software on reading rate and comprehension by randomly assigning students to either a four-week waiting period or treatment group. In this way all students eventually received access to Kurzweil 3000 and avoided the problem of denying students access to the software. However, with longer treatment periods that model would not be palatable in an authentic or action-based research setting. Smith (2000) advocates for the use the Time Series Concurrent Differential (TSCD) model. In this design the subjects provide their own controls by having students perform the targeted skill with and without the use of AT. The difference in performance levels under the two conditions would represent the impact of the AT. The Iowa Text Reader Studies demonstrated use of the TSCD model (Rachow & Hodapp, 2008) (see Figure 16).

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Figure 14.

The TSCD model holds real promise for researchers examining the impact of AT on student performance. In addition, the model can be used to measure the effectiveness of a specific accommodation or device for individual students.

Curriculum-Based Measurement Probes To measure the outcome or impact of AT on academic skills, some researchers have relied on

standardized achievement tests. However, these are expensive, time consuming to administer, require trained administrators, and do not necessarily have adequate reliability and validity. Curriculum-Based Measurement (CBM) strategies provide reasonable assessment alternatives. With more than three decades of research showing strong validity and reliability, CBM offers quick, inexpensive, and sensitive measures of academics performance in the areas of reading, mathematics, and written language (Safer & Fleischman, 2005).

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Figure 15. Teacher impact survey results

Figure 16. Time series concurrent differential model

CBM is a form of authentic assessment that measures competence in reading, math, and written language (Deno, 2003). Parette, Peterson-Karlan, Wojcik, and Bardi (2007) cited the increasingly important role of CBM in the AT consideration process since NCLB requires accountability and the use of research-based strategies. In a metaanalysis study, Fuchs and Fuchs (1986) examined the effects of formative evaluation and reported that the use systematic formative evaluation and progress monitoring with CBM data raised student outcome measures by .7 standard deviations. In the area of reading, CBM offers outcome measures for reading fluency and comprehension. The reading fluency probe consists of timed reading passages at grade level (see Figure 17). The unit of measure is the number of words read aloud correctly during a one minute timed reading.

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Staff can be easily trained to administer and score CBM with strong inter-rater reliability making it easy to use in the classroom. Tools also exist for other academic areas such as math, spelling, and written language.

concLusIon In the fourteen years since AT and services have been mandated for eligible students, limited research into their effectiveness have been conducted. The field lacks research designs or measurement tools suited for the task. Without adequate tools to document implementation, any assumptions about outcomes are questionable. This chapter provides insights and explanations about field-tested tools coordinated to provide

Measure It, Monitor It

Figure 17.

comprehensive data on levels of implementation and targeted outcomes. Innovative strategies for data collection such as online surveys were recommended to reduce error, increase response rate, and increase efficiency. Further research is recommended using a coordinated assessment plan balancing perceptual data with objective data to create a comprehensive understanding of the impact of AT.

reFerences Abell, M. M., Bauder, D. K., & Simmons, T. J. (2005). Access to the general curriculum: A curriculum and instruction perspective for educators. Intervention in School and Clinic, 41, 82–86. doi :10.1177/10534512050410020801

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Anderson, S. (1997, Fall). Understanding teacher change: Revisiting the concerns based adoption model: Curriculum Inquiry. Retrieved December 18, 2008, from Professional Development Collection database. Bausch, M. E., & Ault, M. J. (2008). Assistive technology implementation plan: A tool for improving outcomes. Teaching Exceptional Children, 41(1), 6–14. Cobanoglu, C., Warde, B., & Moreo, P. J. (2001). A comparison of mail, fax, and web-based survey methods. International Journal of Market Research, 43(4), 441–452. Deno, S. L. (2003). Curriculum-based measures: Development and perspectives. Assessment for Effective Intervention, 28(3-4), 3–12. doi:10.1177/073724770302800302 Dept, U. S. of Education, National Center for Education Statistics. (2006). Internet access in public schools and classrooms. 1994-2005 (NCES 2007-020). Retrieved January 31, 2008, from http://nces.ed.gov/pubs2007/2007020.pdf DeRuyter, F. (1994). Assistive technology usage outcomes: A preliminary report. RESNA Annual Conference. Washington, DC: RESNA. DeRuyter, F. (1997). The importance of outcome measures for assistive technology service delivery systems. Technology and Disability, 6, 89–104. doi:10.1016/S1055-4181(96)00197-5 Dimmitt, S., Hodapp, J., Judas, C., Munn, C., & Rachow, C. (2006). Iowa Text Reader Project impacts on student achievement. Closing the Gap, 24(6), 12–13. Edyburn, D. L. (2003). Measuring assistive technology outcomes: Key concepts. Journal of Special Education Technology, 18(1), 53–55. Edyburn, D. L. (2007). Technology-enhanced reading performance: Defining a research agenda. Reading Research, 42(1), 146–152. doi:10.1598/ RRQ.42.1.7 236

Edyburn, D. L. (2008). Measuring outcomes in Assistive Technology. Special Education Technology Practice, 10(4), 16–21. Edyburn, D. L., Fennema-Jansen, S., Harihan, P., & Smith, R. (2005). Assistive technology outcomes: Implementation strategies for collecting data in schools. Assistive Technology Benefits and Outcomes. Retrieved from http://www/atia. org/atob/ATOBWeb/ATOBV2N1/Documents/ [email protected] Fuchs, L. S., & Fuchs, D. (1986). Effects of systematic formative evaluation: A meta-analysis. Exceptional Children, 53(3), 199–208. Gersten, R., & Edyburn, D. L. (2007). Enhancing the evidence base of special education technology research: Defining special education research quality indicators. Journal of Special Education Technology, 22(3), 3–18. Hall, G., & Louks, S. F. (1997). A developmental model for determining whether the treatment is actually implemented. American Educational Research Journal, 14(3), 263–273. Hitchcock, C., Meyer, A., Rose, D., & Jackson, R. (2007). Technical brief: Access, participation, and progress in the general curriculum. Retrieved April 19, 2008, from http://www.cast.org/publications/ncac/ncac_techbrief.html Hodapp, J., Judas, C., Rachow, C., Munn, C., & Dimmitt, S. (2007). Iowa Text Reader Project Year 3: Longitudinal results. Paper presented at the 25th Annual Closing the Gap Conference, October 20, Minneapolis, MN. Hoffman, B., Hartley, K., & Boone, R. (2005). Reaching accessibility: Guidelines for creating and refining digital learning materials. Intervention in School and Clinic, 40, 171–176. doi:10.1 177/10534512050400030601

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Hord, S., Rutherford, W. L., Austin, L., & Hall, G. E. (1987). Taking charge of change. Alexandria, VA: Association of Supervision and Curriculum Development. Love, N. (2002). Using data/getting results: A practical guide for school improvement in mathematics and science. Norwood, MA: ChristorpherGordon Publishers. Malouf, D. B., & Hauser, J. (2005). A federal program to support innovation and implementation of technology in special education. In Edyburn, D. L., Higgins, K., & Boone, R. (Eds.), Handbook of special education technology research and practice (pp. 47–59). Whitefish Bay, WI: Knowledge by Design. Marzano, R. (2000). A new era of school reform: Going where the research takes us. Aurora, CO: Mid-continent Research for Education and Learning. Parette, H., Peterson-Karlan, G., Wojcik, B., & Bardi, N. (2007, September). Monitor that progress! [from Academic Search Elite database.]. Teaching Exceptional Children, 40(1), 22–29. Retrieved January 3, 2009. Rachow, C., & Hodapp, J. (2008, October). Measure it, monitor it: Teacher tools for increasing access to print through use of text-to-speech software. Paper presented at 27th Annual Closing the Gap Conference, Minneapolis, MN. Safer, N., & Fleischman, S. (2005). Research matters: How progress monitoring improves instruction. Educational Leadership, 62(5), 81–83. Silverman, M. K., Stratman, K. F., & Smith, R. O. (2000). Measuring assistive technology outcomes in schools using functional assessment. Diagnostique, 25(4), 307–327. Smith, R. O. (2000). Measuring assistive technology outcomes in education. Diagnostique, 25, 273–290.

Sorrell, C. A., Bell, S. M., & McCallum, R. S. (2007). Reading rate and comprehension as a function of computerized versus traditional presentation mode: A preliminary study. Journal of Special Education Technology, 22(1), 1–12. Stiggins, R. J. (1987). The design and development of performance assessments. Educational Measurement: Issues and Practice, 6, 33–42. doi:10.1111/j.1745-3992.1987.tb00507.x Stoof, A., Martens, R., & Merriënboer, J. (2007, August). Web-based support for constructing competence maps: Design and formative evaluation. Educational Technology Research and Development, 55(4), 347–368. doi:10.1007/ s11423-006-9014-5

key terms And deFInItIons Assistive Technology (AT): A category of technology used by persons with disabilities to provide access and help performing tasks in living, learning, and working as well as increase independence, and quality of life. Authentic Assessment: Assessment that uses direct measurement to test the students’ ability to demonstrate mastery of the outcome objectives of the targeted instructional indicators. Implementation: Application of the innovation with strict compliance to the intervention schedule (i.e., fidelity (quality of application) and integrity (completely and as scheduled)). Outcome Measures: Technically adequate and sensitive measures of the effects of the technology on the targeted skill area. For example, if the target is improved reading skills, an appropriate outcome measure would include curriculum-based measurement data which has been proven to be reliable and valid. Progress Monitoring: Routine monitoring of assessment data used as formative data to make instructional decisions. It is most com-

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monly associated with the use of curriculumbased measurement data with decision rules for instructional changes. Student performance improves significantly when used with graphing and decision rules. Text-to-Speech Software: A category of software using scanned digitized text that can convert any written text into spoken word. It allows access to software and digital documents such as MS Word, web page, PDF files, and the

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Internet. Leading examples include Kurzweil 3000, Read and Write Gold, and Wynn Scan and Read Software. Time Sequence Differential Concurrent Model (TSCD): A research design that compares student performance of the same task with and without technology to measure the impact of assistive technology.

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Chapter 16

Evaluating Systemic Assistive Technology Needs Noel Estrada-Hernández University of Iowa, USA James R. Stachowiak University of Iowa, USA

AbstrAct This chapter will focus on the impact that teacher knowledge of and comfort with assistive technology has on the use of this technology by students with disabilities and how these factors are identified through conducting needs assessment-based research. This chapter begins with a discussion of what is assistive technology and the role it plays in the life of a person with a disability. This will include a discussion of the idea that the earlier AT is introduced to the individual, the more likely it will continue to be used and the larger effect it will have on the individual’s future education, employment, and independent living needs. Also, this chapter will introduce the concept and application of needs assessment, as well as the benefits of conducting this type of research to improve the quality of AT services. This discussion will be supported by an initial discussion of results and experiences in conducting the Iowa Assistive Technology Needs Assessment focusing on the methods used and limitations encountered while conducting this project. Finally, recommendations for future AT-based research will be provided. By the end of this chapter, readers will understand the pressing issues in AT training for teachers, how to determine what is needed, and what is being done to improve overall AT knowledge and comfort. DOI: 10.4018/978-1-61520-817-3.ch016

Copyright © 2010, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

Evaluating Systemic Assistive Technology Needs

IntroductIon Assistive technology and Persons with disabilities The Individuals with Disabilities Education Act (IDEA) of 1990 and its amended version in 2004 represent a step forward in eliminating some of the learning barriers experienced by students with disabilities in the United States. This legislation, Public Law 94-142, mandates that eligible students with disabilities have access to the same public school education as students without disabilities. In order to facilitate this access, schools/school districts are required to provide reasonable accommodations designed to address the student’s unique educational needs. One such accommodation is the use of assistive technology (AT). Although there is research that documents the role of AT in facilitating education, employment, and independent living outcomes of adults with disabilities, little attention has been paid to the identification of AT needs in the school system. According to the Technology-Related Assistance for Individuals With Disabilities Act of 1988, an AT device is defined as any item, piece of equipment, or product system, whether acquired commercially or off the shelf, modified or customized, that increases, maintains, or improves functional capabilities of individuals with disabilities (ATA, 2000; Bryant & Bryant, 2003; Tech Act; Public Law 100-407). This definition emphasizes what it is, how it is made, and the intended use of the technology. Legal mandates such as the Rehabilitation Act Amendments, the Individuals with Disabilities Education Act, and the Americans with Disabilities Act support the provision of AT services to individuals with disabilities to address educational, employment, and independent living needs. Examples of AT devices vary widely and include but are not limited to low-tech items such as pencil grips, crutches, large print, and Braille; mid-tech devices such as tape recorders, talking calculators, and manual

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wheelchairs; and high-tech devices such as power wheelchairs and computer applications such as scan and read, screen reader, or speech recognition programs. Traditionally related to the professions of rehabilitation counseling and special education, AT is often associated with the provision of and access to computer and related technologies for individuals with disabilities. Literature suggests that the earlier AT is introduced, the more likely the individual will acquire skills needed to succeed in different environments (Judge, Floyd, & Jeffs, 2008). Also, AT has the potential to increase developmental skills and provide solutions to behavior, attention, and communication challenges faced by students with disabilities or considered at-risk in early childhood settings (Parette & Stoner, 2008). The role of AT in school as well as other settings (e.g., home, work, community, etc.) is to include and integrate persons with disabilities by facilitating the completion of required environmental tasks. Research suggests that AT is a valuable asset in promoting the employability of persons with disabilities (Gamble & Satcher, 2002). AT has been regarded as a factor that would facilitate employment placement and improve job tenure (Langton & Ramseur, 2001). Other researchers such as Mull and Sitlington (2003) discussed the ways in which AT can be used to address the needs of students with disabilities during their elementary and high school years and in transition to postsecondary education. The rational being that if students with disabilities enter postsecondary education and obtain a degree, they may avoid entering into low pay entry jobs typically associated with this population (Estrada-Hernández, Wadsworth, Nietupski, Warth, & Winsdow, 2008; Frank & Sitlington, 2000; Siegel & Gaylord-Ross, 2001). Yet, research that documents the needs and potential effects of AT on the wages earned by students with disabilities after high school completion are limited. Often people with disabilities are limited in their abilities to exercise personal choice over

Evaluating Systemic Assistive Technology Needs

how many of their daily-life activities are carried out. This creates a problem in relation to the quality of life of these individuals. Fortunately, with the advances of technology, especially in the field of AT, many of these individuals are able to exercise more control and choice over various aspects of their daily environments (Bryant & Bryant, 2003). Activities of daily living may include tasks required for completing tasks such as eating, grooming, dressing, maintenance of one’s environment, and recreation activities. All these tasks are essential for all people and their proper execution provides an important sense of empowerment and self-care. AT devices such as adapted sports equipment, environmental control units, modified kitchen utensils or talking calculators are all examples of daily living tools that can facilitate a person with a disability living independently. This chapter has provided a brief introduction to AT and its use by persons with disabilities to address various essential human needs. The following sections will focus on the aspects of measuring AT needs and its many potential outcomes.

systematically measuring At needs Despite federal legislation that protects the educational rights of students with disabilities, the uneven and uninformed implementation of the laws means that school districts are still falling short of meeting students’ needs leading to academic failure and higher dropout rates. For example, in the state of Iowa during the 200203 school year 30% of students with disabilities dropped out of high school while the national median indicated the dropout rate was 35% (U.S. Department of Education, 2007). According to the National Longitudinal Transition Study 2, three out of ten students with disabilities have taken some post-secondary courses and one out of five was currently (at the time of the study) enrolled and receiving postsecondary education. These students represented less than half of their peers

without disabilities within the general population (Wagner, Newman, Cameto, Garza, & Levine, 2005). In essence, 30.6% of youth with disabilities have taken classes since high school and 19.4% are currently attending postsecondary institutions as compared to the 40.5% of youth currently attending postsecondary institutions in the general population (Wagner et al., 2005). In addition to this disparity, the role of AT in meeting the needs of students with disabilities is still a topic in need of much attention. In an attempt to document the AT needs of the school system, the Iowa Department of Education conducted the Iowa Assistive Technology Needs Assessment (Iowa Department of Education, 1997; 2001). Different personnel at the Area Education Agencies (AEAs), special education team members, school district administrators, teachers, parents, and other key personnel across the state involved with AT were surveyed on what they perceived were the AT needs of children and young adults with disabilities in Iowa. In summary, results of this assessment (N=733) suggested that: (a) there is a need for the provision of AT training not only at the preservice level, but at the professional level for teachers and other personnel involved in the evaluation, selection, and implementation of AT strategies; (b) there is a need for the identification of clear AT service provision patterns and identification of information related to AT within the school system, and (c) funding is still a barrier for the provision of effective AT services for Iowans with disabilities. Although this study solicited a variety of information, such as awareness and implementation of federal policies, current procedures used in AT assessments, coordination of services, parent involvement, training needed, and satisfaction with services; the instrument used and data collected, allowed for limited interpretations. Developing an understanding of the AT needs of students with disabilities and the school system will have important systemic effects with the ability to facilitate greater education and employment outcomes with this population. For

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that reason the rest of this section will address key elements of the contents of and methods used to conduct an AT need assessments. What is a needs assessment? The concept of needs assessment has recently become popular in social sciences and education research. Other disciplines such as marketing, communications, and public health have employed this process to determine gaps or needs for programs, services, or products. A needs assessment is defined as the utilization of social research methods to systematically investigate the effectiveness of social intervention programs designed to inform social actions in ways that improve social conditions (Rossi, Freeman, & Lipsey, 1997). According to Denard-Goldman and Jahn-Scmalz (2007) conducting effective needs assessments is an important activity that: identifies program planning needs, provides direction, focuses program design, defines goals, objectives, activities, program structures, and resource requirements, justifies continuation of existing programs, and determines a program’s value, significance, and worth [evaluation of program’s theory] (p. 225). Conducting needs assessment will provide information that indicates the current status of an existing condition. The evaluator is then able to compare this data to the status of the situation based on previously set goals. Planning a needs assessment should be a team effort considering the level of detail and resources that need to be put in place for the project to be successful. The first stage of conducting a needs assessment is the planning stage. It is in this stage that the researchers formulate the research concept, methods, and develop the survey that will best allow for the identification of the need(s) (Denard & Jahn, 2007). During this stage the researchers: •

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Identify the population or sample to be surveyed (consider conducting a power

•

•

•

• • •

analysis in order to identify a sample number representative of the population of interest). Identify adequate channels and requirements to access potential participants from the organization being assessed (e.g., school district or area education agency). Develop the survey instrument and identify the different levels of measurement (e.g., quantitative and/or qualitative data, or both). Define data collection and analysis procedures, considering both the potential use of technology and human resources for distribution and collection of surveys. Define a time-table on which all activities should take place. Identify any potential limitations of methodology selected. Prepare and submit all required Institutional Review Board materials.

Many researchers have advocated for the development of gap-based needs assessments. A gap-based needs assessment (Denard-Goldman & Jahn-Scmalz, 2007) requires the development of a survey that measures the response items on two different columns. One column will measure the current state of affairs, while the other will measure the ideal state of affairs (p. 226). The statistical difference between the two columns will be identified as the gap [need] and thus will lead to outcomes such as the creation or termination of a program, exploration of different techniques/ intervention methods, or the acquisition of new technologies or other materials. Developing gap-based needs assessments differs from the traditional unidimensional survey designed to measure levels of agreement or satisfaction in only one Likert scale.

Evaluating Systemic Assistive Technology Needs

tHe IoWA AssIstIve tecHnoLogy needs Assessment The study conducted by the authors in the State of Iowa included representation from schools in all 10 Area Educational Agencies as well as the Des Moines Public School District (Des Moines is not part of an AEA). This study, which intended to explore the status of AT utilization in K-12 schools, surveyed students with disabilities, their parents or legal guardians, special and general education teachers, school administrative personnel, and AT service providers in each AEA. The instruments used to collect the desired data were surveys consisting of 25-40 statements (numbers differed for each stakeholder group) to which the respondent indicated his/her level of agreement using a Likert scale. The statements were aimed at determining the stakeholders’ thoughts on the provision of AT in their school/school district. Each survey also contained three open-ended questions that allowed respondents to elaborate further on their thoughts and feelings on their school/schools district’s AT provision. The instruments for this project were developed via consensus with a panel of experts in the areas of education and AT. This panel was composed of individuals from across the State of Iowa and organized in collaboration with the Iowa Center for Assistive Technology Education and Research (ICATER) at the University of Iowa. Working with this panel of experts allowed the researchers to establish face and content validity for the needs assessment instruments (Heppner, Kivlighan, & Wampold, 1999). Surveys, which collected both quantitative and qualitative data, were distributed and collected via a web-based program or via a paper survey mailed to the participant when requested. Future researchers conducting data collection via surveys should explore the versatility of web-based survey programs. Using these survey programs simply requires a basic knowledge of descriptive statistics and basic computer and web application skills. Some advantages of using a web-based

survey instrument include: (a) The ability to easily reach various geographical areas; (b) Security applications that allow only one answer from one computer ISP address, creating an ability to control for number of survey entrants by one individual; (c) Convenience for the participant since it can be accessed at any time from any location with web access; (d) A reduction of costs associated with the reproduction and/or mailing of printed materials; and (e) The ability to easily send multiple reminders to fill out the survey along with a link to the survey via email, resulting in a higher response rate. During stage two, the researchers collect and analyze the survey data (Denard-Goldman & & Jahn-Scmalz, 2007). Researchers should make reference to their time-table to keep track of their survey-related activities. Depending on the level of measurement selected (e.g., quantitative and/or qualitative data, or both), the researchers will use different data analysis procedures and or computer software applications such as SPSS for all numeric data or Atlas TI for qualitative data (i.e., open-ended questions). During this stage the researchers should: • •

•

Calculate the response rate for their survey. Decide whether or not the response rate obtained is enough or if a second round of the survey should be collected. In some cases, this would be recommended in order to collect sufficient data to allow for interpretations or descriptions that will represent the population of interest accurately. Define and implement procedures to deal with missing data or incomplete surveys.

dAtA coLLectIon The Iowa Assistive Technology Needs Assessment was still in process during the writing of this chapter. At this point, data has been completely

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collected from some of the groups of interest, including the AT professionals and the school administrators. Data collection has begun from the parents of students with disabilities and both general and special education teachers. When collecting data, typically, an initial email is sent to everyone in the targeted stakeholder (administrators, teachers, parents, AT professionals, etc.) group describing the needs assessment process and the importance of their cooperation. This email also contains a link directing the stakeholder to their specified survey. Stakeholders are given the option of requesting a paper copy if they would rather fill out a paper version than an electronic one. Following the initial email, reminder emails containing the link are sent out both one and two weeks following the initial email. To this point in the data collection process, all of the school administrators, teachers, and AT professionals that have responded have done so via the electronic copy of the survey. Most of the data collected from each group was collected within the first two days following the initial email. Response rate tapered off during the rest of the week. An upsurge (although not as large as the initial surge) in survey returns was seen in the two days following the first reminder email and a smaller surge was seen again in the two days following the second reminder email. As with the first week of data collection, responses tended to taper off to zero over the rest of each other week. Parents have tended to be more likely to fill out the paper copy of the surveys. At this point in the data collection, roughly 95% of parent surveys that have been collected have been submitted via paper copies. The primary reason for this is the means by which the parents are accessed. To avoid breaching confidentiality in survey responses and violating the Family Educational Rights and Privacy Act, ICATER cannot obtain access to the direct contact information of parents with students on Individualized Education Plan (IEPs). To obtain data from these parents, ICATER works with the Parent Educator Connection (PEC) Group located

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within each AEA. The Iowa Center for Assistive Technology Education and Research provides the PEC groups with the surveys, which they distribute to the targeted parents. The PECs often request paper copies of the survey citing parents’ limited comfort with computers in general, limited access to a reliable Internet connection, and lack of trust for unfamiliar websites as reasons why parents are more likely to complete paper copies of the survey. Providing paper copies to parents via the PEC has removed ICATER’s ability to send reminder emails and thus slightly reduced the expected response rate. At this point in the data collection, quantitative data has been preliminarily analyzed using the statistics application of our web-based survey program. Descriptive statistics such as frequency counts, means, and standard deviations have been calculated in various variables. Qualitative data, obtained in various open-ended questions, have been analyzed using a Constant Comparative Method to identify the different themes. This qualitative data has the potential to confirm and expand the data collected on the survey. Initial results will be briefly discussed in the following section.

PreLImInAry resuLts Preliminary results of the Iowa Assistive Technology Needs Assessment tend to agree with previous research that has concluded that insufficient training has limited the number of teachers and therapists who are using AT in classroom settings (Judge, 2001). Further, teachers who are insecure about using technology are not likely to provide it to students who could benefit resulting in amendments to IDEA not being met (Abner & Lahm, 2002). The AT needs of students with disabilities are not going away. With more and more students with special needs entering mainstream classes, not only do special education teachers and therapists need to be aware of and comfortable with AT, but

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general education teachers must be as well. Although proficiency in AT for preservice teachers is emphasized in the 2001 Council for Exceptional Children (CEC) technology standards, only a few articles exist describing instructional methods for integrating AT into teacher education programs (Van Laarhoven, Munk, Zurita, Lynch, Zurita, & Smith, 2009). To properly prepare teachers to work with this critical technology, there needs to be an increased focus on teacher training in AT both at a professional development and a preservice level. The need for improved teacher training throughout Iowa is also evidenced in survey responses that indicated that many schools have AT devices and software in place, however they are not being used to their full potential, if at all, because AT professionals cannot be in the classroom on a daily basis. Iowa is divided into ten Area Education Agencies (AEAs) each covering large areas of the state and containing numerous school districts. These AEAs house the AT professionals who work with the schools. The AEA AT teams are small; especially when the physical size and number of districts served within each AEA are considered. Some AEA’s have over 3,000 students with AT written into their IEPs, yet have fewer than ten AT professionals to work with these students. These constraints make it impossible for the AEA AT professionals to work with every student with AT needs on a regular basis. Many teachers in these schools either do not have the required knowledge to effectively use the technology with the students as needed, or are not comfortable incorporating and using AT in class. Without the support and willingness to follow through of the classroom teachers, the work done by the AT professionals often leads to improper use, limited use, or AT abandonment. Thus, not only is it important to provide professional development training opportunities to teachers in the field, but it is critical to create a new generation of teachers, both general and special education, that are not only knowledgeable in the use of various types

of AT, but also comfortable enough to properly incorporate them in the classroom environment. To do this, it is imperative to incorporate AT education and training into preservice teacher education programs. When completing the Iowa Assistive Technology Needs Assessment, many teachers and administrators in Iowa indicated that they received little or no AT training at a preservice level. Research suggests that not many teacher preparation programs are currently addressing AT in their curriculums, so similar issues with AT knowledge and comfort can most likely be extrapolated to a national level. Those who did receive AT training at the preservice level tended to be special education majors and indicated that their AT training was minimal. To have an AT program in a K-12 school that meets the students’ needs, it is not sufficient for only special education teachers to understand and implement AT use. Many students who participate in general classes can benefit from AT and often have it written into their IEP or 504 plan. If AT is written into either plan, each teacher that works with that student should be implementing use of the specified device or software in the class. Some of the most commonly used AT software in schools are reading and writing tools that can be used to access general classes. As more and more students are becoming eligible to use AT in schools, it is imperative that all teachers learn what devices are available, for whom such devices would be beneficial, and how to integrate the technology effectively within educational programs (Wojcik, Peterson-Karlan, Watts, & Parette, 2004).

LImItAtIons And cHALLenges The discussion of conducting an effective AT needs assessment is not complete without identifying the challenges encountered during the research process. Denard-Goldman and Jahn-Scmalz (2007) stated that some of the limitations of traditional needs assessments, in contrast to gap-based needs

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assessments, are related to: (a) the fact that not enough attention has been paid by researchers to this modality; (b) surveys are designed to measure more “wants” than “needs”; (c) more resources or tools to develop and conduct needs assessments are needed that move the researchers from administering a survey and conducting focus groups into a variety of data collection methodologies. The Iowa Assistive Technology Needs Assessment was still in process as this chapter was written. Following are some of the challenges specifically encountered with this project. When collaborating with larger systems, such as a school district, timing for data collections is crucial. For example, if the researcher sends his or her survey too early or toward the end of the semester, likely participation rate will be low considering the other obligations teachers and administrators have during those parts of the semester. Also, researchers should become familiar with teacher and parent groups that could assist in collecting data or facilitating navigation of the system through the correct channels. For example, when surveying teachers or parents, local conferences specific to the targeted population provide access to a captive audience likely to participate in the study. In addition, it is important that the researcher has a follow-up mechanism and that at least three research invitation reminders are sent to potential participants. This will allow the researcher to increase their participation rate. In developing the Iowa Assistive Technology Needs Assessment, another challenge for the researchers was the fact that, as pointed by Denard-Goldman and Jahn-Scmalz (2007), there is only a handful of previously conducted AT needs assessments and only one known AT needs assessment that was conducted in the state of Iowa. This created several issues that the researchers needed to consider in the development and implementation of the study. Some of these include: (a) lack of a prior scheme to aid the navigation of the larger organization (in this case the Iowa Department of Education); (b) the lack of focus or wide range

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of “needs” identified by previously conducted AT needs assessments and how this will inform the instruments; (c) lack of clear research methodology (e.g., sampling including confidentiality considerations for students and parents, clear and simple instruments to assess AT needs or usage, and lack of statistical structure to make meaning of collected data); (d) limited research results from which to draw upon for this new study; and (e) identifying only the necessary groups of people to participate in this study. In order to address these issues the researchers consulted with a group of experts in both education and AT in the State of Iowa. Through this process the researchers were able to provide a focus to the survey methodology, instruments, and the overall theme of the project. Specific strategies included: First, developing a main project plan that indicated each task with an anticipated completion date, person in charge, resources needed, and contact information for various groups at the larger participating organization. Second, creating a subcommittee of representatives of identified stakeholder groups (e.g., parents, teachers, administrators, and AT professionals) to provide feedback on their respective surveys. Along with feedback from the main consulting team, this allowed the researchers to establish face and content validity for the instruments, while providing each stakeholder group a voice in this research process. Third, identifying different school groups (e.g., AT professionals group, parents’ group) that were able to assist in the dissemination of surveys. Considering their proximity to schools, administrative personnel (e.g., principals or vice principals) were able to assist in the dissemination of surveys to the teachers in their schools. Having the collaboration of these groups was an important asset for this study. It allowed the study to be conducted while adhering to the school/school’s district’s and families’ confidentiality standards. The researchers were also able to participate in various Parent-Teacher Conferences that allowed them to disseminate instruments while having

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the opportunity to verbally present the study to interested individuals.

Future reseArcH dIrectIons Assistive Technology is regarded as a tool for providing equal access for individuals with disabilities in various life activities. Attending to AT needs in K-12 educational settings has many important ramifications for future research. For instance results of the present study will serve to explore training needs at both preservice and professional levels. By identifying current AT training needs of education students or established professionals, training can be developed that matches the continuing developments in AT. Teachers should be able to incorporate these various technology applications to fully integrate students with disabilities in their classrooms. Concepts such as Universal Design and Universal Design for Learning will be key elements in these trainings. This will be followed by the exploration of AT use or identification of strategies to address other educational areas such as classroom assessment, educational attainment, or career exploration of students with disabilities. At the systemic level, identifying AT needs provides an idea of the services available, who is responsible for these services, and how they are being provided. This is important data to identify as it provides mechanisms to modify or create policies, or a best practice model, on AT service delivery that ultimately facilitates the independence and integration of students with disabilities.

concLusIon The use of AT by students with disabilities has the potential to have a significant impact on their quality of life. These technologies can aid a person by increasing his or her mobility and access to different education or popular materials (e.g.,

media), or by facilitating communication, employment, independent living, and recreation activities. With this potential impact, it is important to begin the proper use of AT as early as possible, which is often in a school setting. In order to facilitate proper use the proper needs have to be identified. Initial results of the Iowa Assistive Technology Needs Assessment suggest that AT usage is and will continue to be an important variable in the academic success of many students with disabilities in K-12 settings. Literature reviewed supports the fact that AT has the potential to allow these students to explore their skills as they contemplate future goals such as entering the job market or continuing post-secondary education.

reFerences Abner, G. H., & Lahm, E. A. (2002). Implementation of assistive technology with students who are visually impaired: teachers’ readiness. Journal of Visual Impairment & Blindness, 92, 98–105. Alliance for Technology Access. ATA, (2000). Current laws and legislation. In alliance for technology access (Eds). Computer and web resources for people with disabilities: A guide to exploring today’s Assistive Technology. Alameda, CA: Hunter House. Bryant, D. P., & Bryant, B. R. (2003). Assistive technology for people with disabilities. San Diego, CA: Allyn and Bacon. Denard-Goldman, K., & Jahn-Scmalz, K. (2007). “As you Likert it”: Conducting gap-based needs assessments. Health Promotion Practice, 8(3), 225–228. doi:10.1177/1524839907303608 Education for All Handicapped Children Act of 1975. (1975). Public Law 94-142.

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Estrada-Hernandez, N., Wadsworth, J. S., Nietupski, J., Warth, J., & Winslow, A. (2008). Employment or economic success? Experiences of youth with disabilities in transition from school to work. Journal of Employment Counseling, 45(1), 14–24. Frank, A. R., & Sitlington, P. L. (2000). Young adults with mental disabilities: Does transition planning make a difference? Education and Training in Mental Retardation and Developmental Disabilities, 35(2), 119–134. Gamble, D., & Satcher, J. (2002). Rehabilitation outcomes, expenditures, and the provision of assistive technology for persons with traumatic brain injury. Journal of Applied Rehabilitation Counseling, 33(3), 41–44. Heppner, P. P., Kivlighan, D. M. Jr, & Wampold, B. E. (1999). Validity issues in research design. In Heppner, P. P., Kivlighan, D. M. Jr, & Wampold, B. E. (Eds.), Research design in counseling (2nd ed., pp. 56–78). Belmont, CA: Wadsworth. Iowa Department of Education. (1997). Iowa IDEA 97 Implementation Plan. Des Moines, IA: Author. Iowa Department of Education. (2001). Iowa’s Quality Indicators for Assistive Technology (QIAT). Des Moines, IA: Author. Judge, S., Floyd, K., & Jeffs, T. (2008). Using an assistive technology toolkit to promote inclusion. Early Childhood Education Journal, 36(2), 121–126. doi:10.1007/s10643-008-0257-0 Judge, S. L. (2001). Computer applications for young children with disabilities: current status and future directions. Journal of Special Education Technology, 16(1), 29–40. Langton, A. J., & Ramseur, H. (2001). Enhancing employment outcomes through job accommodation and assistive technology resources and services. Journal of Vocational Rehabilitation, 16(1), 27–37.

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Mull, C. A., & Sitlington, P. L. (2003). The role of technology in the transition to postsecondary education of students with learning disabilities. The Journal of Special Education, 7(1), 26–32. doi:10.1177/00224669030370010301 Parette, H. P., & Stoner, J. B. (2008). Benefits of assistive technology user groups for early childhood education professionals. Early Childhood Education Journal, 35, 313–319. doi:10.1007/ s10643-007-0211-6 Rossi, P., Freeman, H., & Lipsey, M. (1998). Evaluation: A systematic approach (6th ed.). Newbury Park, CA: Sage. Siegel, S., & Gaylord-Ross, R. (2001). Factors associated with employment success among youth with disabilities. Journal of Learning Disabilities, 24(1), 40–47. doi:10.1177/002221949102400108 Technology-Related Assistance for Individuals with Disabilities Act of 1988 (Tech Act). (1988). Public Law 100-407. US Department of Education. (2007). Twentyseventh annual report to congress on the implementation of the Individuals with Disabilities Education Act. Washington, DC: Author. Retrieved on January 5, 2009, from http://www.ed.gov/offices/ OSERS/OSEP/Products/OSEP2007AnlRpt/ Van Laarhoven, T., Munk, D. D., Zurita, L. M., Lynch, K., Zurita, B., & Smith, T. (2009). The effectiveness of video tutorials for teaching preservice educators to use assistive technologies. Journal of Special Education Technology, 23(4), 31–45. Wagner, M., Newman, L., Cameto, R., Garza, N., & Levine, P. (2005). After high school: A first look at the postschool experiences of youth with disabilities. Menlo Park, CA: SRI International. Wojcik, B. W., Peterson-Karlan, G., Watts, E. H., & Parette, H. P. (2004). Assistive technology in a teacher education curriculum. Assistive Technology Outcomes and Benefits, 1, 21–32.

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AddItIonAL reAdIng Alper, S., & Raharinirina, S. (2006). Assistive technology for individuals with disabilities: A review and synthesis of the literature. Journal of Special Education Technology, 21(2), 47–64. Anderson, C., & Petch-Hogan. (2001). The impact of technology use in special education field experience on pre-service teacher’s perceived technology expertise. Journal of Special Education Technology, 16(3), 27–39. Bausch, M. E., & Hasselbring, T. S. (2004). Assistive technology: Are the necessary skills and knowledge being developed at the preset-vice and in service levels? Teacher Education and Special Education, 27, 97–104. doi:10.1177/088840640402700202 Belson, S. I. (2003). Technology for exceptional learners. Boston: Houghton Mifflin Company. Bryant, D. P., & Bryant, B. R. (2003). Assistive technology for people with disabilities. CA: Allyn and Bacon. Cook, A. M., & Hussey, S. M. (2002). Assistive technologies: Principles and practice (2nd ed.). St. Louis: Mosby. Dell, A. G., Newton, D. A., & Petroff, J. G. (2008). Assistive Technology in the classroom. Upper Saddle River, NJ: Pearson Education. Denard-Goldman, K., & Jahn-Scmalz, K. (2007). “As you Likert it”: conducting gap-based needs assessments. Health Promotion Practice, 8(3), 225–228. doi:10.1177/1524839907303608 Jeffs, T., & Banister, S. (2006). Enhancing collaboration and skill acquisition through the use of technology. Journal of Technology and Teacher Education, 14, 407-4 33. Judge, S., Floyd, K., & Jeffs, T. (2008). Using an assistive technology toolkit to promote inclusion. Early Childhood Education Journal, 36(2), 121–126. doi:10.1007/s10643-008-0257-0

Judge, S. L. (2001). Computer applications for young children with disabilities: current status and future directions. Journal of Special Education Technology, 16(1), 29–40. Lahm, E. A. (2005). Improving practice using assistive technology knowledge and skills. In Edyburn, D., Higgins, K., & Boone, R. (Eds.), Handbook of special education technology research and practice (pp. 721–746). Whitefish Bay, WI: Knowledge by Design. Male, M. (2002). Technology for inclusion: Meeting the special needs of all students. Boston: Allyn & Bacon. Maushak, N. J., Kelley, P., & Blodgett, T. (2001). Preparing teachers for the inclusive classroom: A preliminary study of attitudes and knowledge of assistive technology. Journal of Technology and Teacher Education, 9, 419–431. Michaels, C. A., & McDermott, J. (2003). Assistive technology integration in special education teacher preparation: Program coordinators’ perceptions of current attainment and importance. Journal of Special Education Technology, 18(3), 29–41. Olson, D. A., & DeRuyter (Eds.). (2002). Clinician’s guide to assistive technology. St. Louis: Mosby. Purcell, S. L., & Grant, D. (2002). Assistive technology solutions for IEP teams. Verona, WI: Attainment Co. Reed, P. R. (2001). A resource guide for teachers and administrators about assistive technology. Oshkosh, WI: Wisconsin Assistive Technology Initiative. Rose, D. H., & Meyer, A. (2002). Teaching every student in the digital age: Universal design for learning. Alexandria, VA: ASCD. Rossi, P., Freeman, H., & Lipsey, M. (1998). Evaluation: A systematic approach (6th ed.). Newbury Park, CA: Sage.

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Scherer, M. J. (Ed.). (2002). Assistive technology: Matching device and consumer for successful rehabilitation. Washington, DC: American Psychological Association. doi:10.1037/10420-000 Scherer, M. J. (2005). Living in the state of stuck (4th ed.). Cambridge, MA: Brookline Books. Stachowiak, J. R., & Achrazoglou, G. J. (2008). ICATER and mat lab: implementing innovative assistive technology training in a pre-service teacher education program. Closing the Gap, 26(3), 21–23. Van Laarhoven, T., Munk, D. D., Zurita, L. M., Lynch, K., Zurita, B., & Smith, T. (2009). The effectiveness of video tutorials for teaching preservice educators to use assistive technologies. Journal of Special Education Technology, 23(4), 31–45. Wojcik, B. W., Peterson-Karlan, G., Watts, E. H., & Parette, H. P. (2004). Assistive technology in a teacher education curriculum. Assistive Technology Outcomes and Benefits, 1, 21–32.

key terms And deFInItIons Assistive Technology (AT): As any item, piece of equipment, or product system, whether

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acquired commercially or off the shelf, modified or customized, that increases, maintains, or improves functional capabilities of individuals with disabilities. Content Validity: The property of an instrument or test’s content to capture the interested area to be measured. Face Validity: The property or appearance of an instrument or test to measure a construct. Needs Assessment: The utilization of social research methods to systematically investigate the effectiveness of social intervention programs designed to inform social actions in ways that improve social conditions. Reasonable Accommodation: A modification of work or school work that allow an individual with a disability to perform the required tasks at its best ability possible. Universal Design: The development of products and environments to be usable by all people. Universal Design for Learning: A process that creates flexible goals, teaching methods, and assessments that accommodate learner differences.

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Chapter 17

Developing Electronic Portfolios Mary Ann Lowe Nova Southeastern University, USA

AbstrAct Portfolios are widely used in many professional and academic areas; however there is minimal documentation for the use of portfolios by Assistive Technology / Augmentative Alternative Communication (AT/AAC) specialists. Assessment of AT/AAC progress is often difficult to document due to the limited capabilities of the written output. Specific AT/AAC systems are tailored to individual clients and may range from a low-tech communication book to a sophisticated hi-tech device/computer with specialized access techniques. As individuals transition to new opportunities, it is difficult to show documentation of progress or visually capture specific device/computer set-ups for replication. This chapter encourages service providers to develop electronic portfolios to assist families, future educators, and therapists to become familiar with the best practice AT techniques and strategies used for individuals with complex physical and communication needs.

IntroductIon Documentation of clinical and educational issues for individuals with Assistive Technology / Augmentative and Alternative Communication (AT/AAC) needs is problematic both for the professionals writing those reports, and the families trying to make sense of the reports they receive. First, it is difficult to describe and document different aspects of using

AT/AAC with students who have complex physical needs and communication impairments. There are three main issues relating to difficulties in adequately describing: (a) important student characteristics, (b) AT/AAC tools and strategies, and (c) skill level and progress. Furthermore, documents intended to convey this information are generally lengthy and complex, making it likely that the intended audience (e.g., parents and teachers) fail to read or understand parts of the document.

DOI: 10.4018/978-1-61520-817-3.ch017

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Developing Electronic Portfolios

For individuals with complex physical and communication challenges, the documentation of clinical and educational issues serves many critical functions. Such documentation is used to: (a) inform families of relevant issues, (b) obtain funding for services, and (c) convey important programmatic information to a wide variety of professionals serving these individuals. Current methods of clinical/educational documentation, such as progress charts and reports, are inadequate for individuals with complex needs. This is due to several factors. One problem is that the information is not easily conveyed in written form. Some information is better presented visually as opposed to linguistically—visual illustration of the no-tech communication that is used (e.g., manual signs, gestures, and signals), representational and organizational system used for the presentation of vocabulary on a low- or high-tech communication system, the form of accessing (e.g., direct or indirect access), the switch or device mounting, or other required AT. Secondly, written reports, which do provide adequate detail on the individual’s AT system, are generally lengthy and complex, making them difficult and time-consuming to digest. These reports are often not meaningful to the target audience (e.g., families and other professionals) and they tend to not read the report or read only parts of the report. They are often difficult to read, especially when medical and educational terminology is used. Because AT/AAC strategies and tools are often visually complex and quite dynamic, it is difficult to accurately describe them. Individuals who use AT or AAC have difficulty communicating their own device set-up or mounting system. AT/AAC strategies and materials may be described; however, it is difficult to visualize the exact set-up of materials or the individual who uses AAC application of them. Often, there are a numerous other strategies that are implemented without written documentation. If the individuals utilize a voice output communication aid (VOCA), the devices must be customized to the individuals’ specific

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needs. Angling a device or mounting the device on a table or wheelchair may be a requirement for success. It is difficult to accurately describe what specific tools are needed, what each tool looks like, how materials are constructed, why they are organized in a specific way, and how the individual implements them within their environment. Device mounting onto a wheelchair is specific for each individual who uses AAC and difficult to describe in a report. Wheelchair mounts can be placed on either side of the frame (e.g., right or left of the chair) or angled in numerous directions to provide ease of access for the individuals who use AAC. Accessing a VOCA or other forms of manual communication are often major obstacles that need to be described. Explanation of the exact method of using a direct access, such as using a mouthstick, a headpointer, a laser beam, or pointing with a finger or thumb, can be challenging. Placement (e.g., which side of the head or the exact angle) of each of the accessing devices is critical. An unconventional method of pointing for direct access (e.g., using a finger other than index or thumb) must be addressed. Other alternate access methods, such as eye gaze or scanning, offer other dilemmas for presenting an accurate description in a written format. Written expression is limited when technical issues—such as specific seating and positioning problems, individualized accessing dilemmas, the use of idiosyncratic gestures and manual signs, and the specific placement and usage of AT—are involved. This is especially true when using educational documents to explain technical directions, which are best accompanied by diagrams and/ or pictures to explain each step. When writing diagnostic and progress reports for individuals who use AT, pictures and diagrams are not the standard procedure. This problem may exist due to a variety of reasons. One reason is the lack of availability of equipment for producing diagrams or pictures. Another reason is the accessibility of equipment for developing and editing video clips that would provide a visual documentation

Developing Electronic Portfolios

of setup or for teaching AT strategies. Computer software and knowledge is necessary to compile the necessary information onto a medium that is usable for a viewing audience. Progress is difficult to measure and document for some individuals who use AT. Medical conditions may contribute to fluctuations in performance and often impede changes in progress over time. Often physical limitations may also require use of different accessing techniques. Cognitive limitations may result in slow progress that is difficult to document. Progress for long-range goals and short-term objectives is usually captured through written reports. Baseline levels of performance are measured and progress is followed by repeated data collection over a specified period of time. Improvement may be slow and often so subtle that it is complex to measure. Clinicians generally write daily log notes followed by periodic progress reports. As individuals who use AT transition to new educational situations or therapy settings, these progress reports generally accompany them to the new environment. This process of documenting information for an individual who uses AT must be completed by a competent AT specialist who understands all aspects of diagnostics, equipment programming and setup, the necessary tools for assisting with access, and the teaching of AT strategies for mastery of goals. Few individuals are equipped for this challenge. The process of documenting information for a visual representation, beyond the written report phase, is very time consuming.

titudes, and potential in a specific subject or skill area (Paulson, Paulson, & Meyer, 1990). Arter and Spandel (1992) suggested that portfolios, “should be continuous, capture a rich array of what students know and can do, involve realistic contexts, communicate to students and others what is valued, portray the process by which work is accomplished, and be integrated with instruction” (p.36). Portfolios can also be utilized as a functional assessment during speech-language evaluations and assessments, transition of students as they matriculate through the educational system, and the inclusion of students’ in regular education classes. In some situations, portfolios are considered to have assets, such as depth and quality of information, not present in other forms or measurement of documentation. These artifacts, where the individuals who use AT/AAC is the focal point of the collection of information, may contain documents that can be described and examined through numerous mediums (e.g., drawings, pictures, written expression). Portfolios are used in a variety of fields related to education and individuals with disabilities. In the field of education, for example, portfolios have been used at all age levels and for a variety of reasons. Less is known about the use of portfolios in the area of AT and speech and language. In the section that follows, portfolio applications are considered in special education, general education, and SLP.

education

HIstorIcAL PersPectIves

Assessment of Student Learning and Development

The need for more adequate means of documenting clinically and educationally relevant issues for individuals who use AT/AAC is clear. Portfolios are used for many purposes including collecting information and artifacts in a systematic and organized way to evidence and monitor the growth of an individual’s knowledge, skills, at-

Gelfer and Perkins (1998) share that young and old artists have long relied on portfolios to demonstrate their skills and achievements and to showcase their work. Portfolios can help provide artists with new insights, greater precision and technique, new organizational skills, new interests, and valuable analysis of their growth and development. In the

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same way, a student portfolio can be a meaningful collection of student work that exemplifies the student’s interests, attitudes, ranges of skills and development over a period of time. It will also record and reflect the growth of the student’s cognitive, social, emotional, physical, motor and creative development. Traditional educational assessment is based on collected assessment data, using norm-referenced, criterion-referenced, and academic testing of subject matter (McLoughlin & Lewis, 1994; Salend, 1998). Some regular education classrooms began a self-assessment process in the early 1990’s. The portfolio was touted as the “new wave” of assessment that included authentic and performancebased measures (Lankes, 1995). Not only is the portfolio an accumulation of group projects and student papers, it also features teachers’ evaluations and student self-reflections that exhibit the student’s efforts, progress, and achievements. Moving beyond the student portfolio, other beneficial implications for use of the portfolio are those of helping teachers plan for incoming students, portfolios as criteria for graduation eligibility, a showcase for an educational career, employment skills portfolios, and college admission portfolios. Lankes (1995) suggested that portfolios be saved in an electronic format. Niguidula (1997) studied the use of digital portfolios designed to provide a richer picture of the student’s work than traditional transcripts allow. The primary focus of the project was to examine the process of creating and utilizing digital portfolios. A digital portfolio is created and stored electronically on a computer as opposed to an electronic portfolio that is stored on a CD. Special software allows students to use the mediums of text, graphics, audio or video to collect and produce a final product for accountability. The positive aspects of using a digital portfolio were, the vision that a school must develop to use digital portfolios, the collection of student work, the technology required for the development of digital portfolios, the logistics of who will gather

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and input the selection of student work, and the culture of the school with discussing student work (e.g., relationships among students and teachers with respect to discussing student work). Students from 6 schools, ranging from elementary through high school, participated in the project by building their own digital portfolios. Using the specifically developed software for this tool, each student collected a set of “entries”, or pieces of work they completed during the school year. This work demonstrated a variety of mediums including text, graphics, audio, and/or video. Each school described the purpose for creating a portfolio in a different way and, thus, produced different types of portfolios. These included the collection of student work to celebrate accomplishments, an evaluation tool to demonstrate student achievements against some standards, and as a means of demonstrating that a student had accomplished the skills and acquired the knowledge expected of a graduate. Computer stations were developed for students to enter their own artifacts. The students were responsible for selecting the information that was required to fulfill their schools vision of the digital portfolio. Some entries contained the final product of a project as well as the student’s process in developing that product. Other entries were a work in progress that required continual entries to fulfill the requirement. In traditional schools, students find the school’s vision a mystery. In this project the digital portfolio was organized around the school’s vision with students clearly understanding the vision. Teacher surveys revealed that the digital portfolios brought a school’s vision and standards to life. Students took ownership of the development and maintenance of their digital portfolio and reported that development of a digital portfolio was easier than using paper. The author suggested that digital portfolios will make it easier to transmit information from the school to other audiences. One five-year study, completed in an elementary school, implemented an electronic portfolio system for kindergarten through the third grade.

Developing Electronic Portfolios

The authors described this electronic portfolio system as a way to store both two-dimensional information, such as writing and drawing, and full-motion video sequences for each student (Campbell, 1996). Children were videotaped performing particular developmental skills. Drawings or writings were scanned and the originals were returned to the student. These artifacts were saved on an optical disk. Teachers from all grade levels worked to determine what information would most effectively tell the story of a child’s growth at each grade level (e.g., kindergartners should be able to catch a ball, first graders should attempt to write and talk with an adult, second graders should be skipping, writing, and doing math). Some positive outcomes for the use of portfolios that were gleaned from the project were the use of the system to help make instructional decisions, and record keeping for language arts, writing, and spelling. Other noted features were the documentation of improvement of fine motor skills over time, and the ability to show, instead of only write about, interpersonal skills and children’s performances. The area of assessment of student learning and development portfolios provide a powerful tool for students. It allows them to view where they have been and ultimately make decisions about where they need to strive for improvement. The inclusion of the different media, scanned materials, and video clips to portray skills and progress is a focus that students can learn to self-analyze their skills in many life situations.

special education Inclusion Rogers-Dulan (1998) shared that using portfolios can be particularly helpful for students with special needs who are enrolled in inclusive classrooms. Portfolios allow for more equitable methods of assessment for different learning styles, recognize multiple intelligences, and offer ways to demon-

strate competence. Students take responsibility for collecting materials that will provide a clear purpose of the story to be told through the portfolio. Three major types of portfolios are: celebration (e.g., “What do I think is really special about my work, and why?”), time sequenced (e.g., reflects changes in academic performance over time) and the status report portfolio (e.g., documentation of achievement of specific curricular objectives). The time sequenced portfolio is one that can reflect a growth portfolio or a project portfolio. An analytic rubric for assessing items to be included in this portfolio was presented. The levels of achievement were presented as exemplary (e.g., “coherent”, “complete”, “clear”, “unambiguous”), competent (e.g., “fairly complete response to objective”), satisfactory (e.g., “minor flaws”, “few important areas missing”, and “needs improvement”), and unacceptable (e.g., “no important areas are identified”). The evaluative judgments for the project were based on two sets of performance criteria: steps completed within a specified time, and quality of work done at each step. It was reported that the student in this case study evidenced artistic talents to illustrate scenes that accompanied an oral report. The child also learned that working with a group gave him experience in planning a task and adhering to a timeline. Wesson and King (1996) suggest that portfolios reduce barriers to communication between exceptional and general educators by eliminating assessment jargon. The assessment focus is on the process of instruction and learning rather than on test results. Portfolios developed by and/or for students with special needs who are enrolled in inclusive classrooms, are adaptable, flexible, ongoing and cumulative. They provide a way for students to have the opportunity to participate and make choices through development of their own portfolio. Student participation requires manipulation of writing and art tools as well as the physical ability to collect artifacts and organize them into a portfolio.

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Transition In the field of special education, several creative ideas have been shared in the recent literature for developing portfolios for both the transition of a child as he matriculates through the educational system and for the integration of a child with disabilities into a preschool setting. Demchak and Greenfield (2000) described the concept of transition portfolios and the procedures for developing them. This article followed the suggestions of a teacher who developed a transition portfolio for a 14 year old student with severe multiple disabilities that include cognitive and motor impairments, limited verbal communication, a mild hearing loss, and a visual impairment. The authors described a transition portfolio as a strategy that documents critical information about a student. This type of portfolio differs from a student’s cumulative folder in that it does not contain test scores, however, it focuses on details that are critical to a student’s everyday functioning (e.g., the type of medications and the effect of these medications on the student’s behavior, positioning strategies) and learning (e.g., the student’s likes and dislikes, the student’s talents, educational programming suggestions, expressive and receptive communication methods, and reinforcement strategies). They suggested that an involved team of current teachers, paraprofessionals, support personnel, administrators, family members and peers as well as the student must drive the informationgathering process. The transition portfolio is developed to assist a teacher to see a student first as someone with personal characteristics, rather than just a student with a disability. Suggestions to be included in the portfolios were personal information, medical information, positioning strategies, educational programming suggestions, expressive and receptive communication methods, reinforcement strategies and positive behavioral support plans, and problem-solving techniques. As a summarization thought, the authors suggested that videos might be supplemented to provide a

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user-friendly document for a student’s new teacher, paraprofessional, and other service providers.

speech and Language Kratcoski (1998) discussed guidelines for the use of portfolios for conducting various types of speech-language evaluations and assessments in school settings. The focus for an evaluation was to determine the presence of a disorder and to determine the services that were needed. The focus of the functional assessment was to determine intervention goals and to develop a reflection profile of the strengths and needs of the learner. A case example was presented to demonstrate the specific guidelines for initiating the use of portfolios in case management procedures. Quantitative standardized testing did not qualify this child for speech-language intervention. The portfolio assessment emphasized data collection for the purpose of forming a hypothesis. It was proposed that the team then develop assessment questions directly related to the hypothesis. To answer the assessment questions, pertinent information was gathered (e.g., language samples, story retell samples, and observation notes) and placed in the portfolio. Interpreting the portfolio information confirmed or rejected the hypotheses. A problem-solving team then summarized and interpreted portfolio data to develop goals and objectives and ways to evaluate progress. This article, the only one relating specifically to speech and language, provided a way to develop a holistic view of a child and provide an authentic picture of the child’s true abilities and needs. Portfolios used for documentation to qualify a child for specific speech-language intervention can be very time consuming. Collection of pertinent information, analyzing the information and organizing it into a portfolio must be completed on an ongoing basis. A written report of summary must be submitted to a criteria committee to qualify the child for intervention. In conclusion, SLP’s have the responsibility to implement practices that authentically reflect

Developing Electronic Portfolios

the learning process and best address the needs of the child. Incorporating portfolios into service delivery with children who have communication disorders provides the vehicle for both assessment and evaluation. Portfolios are an asset to documenting numerous areas of education through the collection of information and artifacts. Students with special needs and educators/therapists can systematically document growth in knowledge, skills, attitudes, and potential in specific areas. The portfolio could be integrated into the evaluation and report writing process for individuals who use AT/AAC. Specific benefits may include changes in academic performance over time, documentation of achievement of specific curricular objectives, details of everyday functioning, the student’s behavior, particular things regarding a VOCA, and the student’s likes and dislikes. This would provide an excellent opportunity for families, educators, and therapists to share information and artifacts, which would enhance a portfolio for individuals who use AT/AAC. A picture portfolio (e.g., using photos and video) would provide a way to monitor progress as well as a realistic view of device and access set-up. Families, educators, and therapists who are involved with specific individuals who use AT/AAC would evaluate this portfolio process.

types of Portfolios

creAtIng eLectronIc PortFoLIos

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What is a Portfolio? Like a scrapbook, a portfolio is a compilation of work and artifacts collected over a period of time. This concrete evidence involves inquiry which is the “collecting, sorting, selecting, describing, analyzing, and evaluating evidence to answer questions” of the student’s accomplishments (Johnson, Mims-Cox, & Doyle-Nichols, p. 4). The key point in developing a portfolio is that these artifacts are organized to serve a purpose.

Portfolios can serve a variety of purposes for individuals using AT/AAC. They can serve as a collection of outstanding work, as an assessment tool (e.g., alternate assessment), to measure levels of competency, and to document educational and therapy techniques and equipment used for a student with complex needs (e.g., AT and AAC).

key Factors to consider When creating an electronic Portfolio There are critical issues that need to be addressed prior to beginning to create an electronic portfolio: • •

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What is the purpose of the electronic portfolio? Alternate Assessment Portfolio (Kentucky Department of Education, 2006-2007) is a valid and reliable means of assessment through the collection of assessment and instructional samples of a student throughout an academic year. Levels of competency as compared to goals and standards for the purpose of making educational decisions. Document educational and therapy techniques and equipment. What program should be used to develop the electronic portfolio? Select a software program that is readily available (e.g., Microsoft PowerPoint). Select a software program that is easy to use. Select a software program that has a “player” feature. This will allow individuals to view the electronic portfolio without having the specific software. Who is the audience that will be viewing the electronic portfolio? Parents and caregivers Education and therapy teams

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• • • • • • • •

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Transition teams Administration for assessment purposes What should be included in the electronic portfolio? Educational relevant material Artifacts that demonstrate best work. Photos/videos that “show and tell” AT/AAC set-ups of equipment and devices. Organization of the electronic portfolio: Table of contents to organize the electronic portfolio and to orient the viewer to the contents. Length of portfolio should be manageable. Comprehensive artifacts which will allow the viewer to retrieve valuable information. Criteria of what to include: ◦ Reports must be relevant ◦ Reports, pictures, videos must provide clear information to afford further understanding of the individual Confidentiality for educational and medical reports, photos, and videos of the specific student as well as classmates/friends that may be viewed in the electronic portfolio. Age of the individual that is the main focus of the electronic portfolio. Younger individual will include: birth history, medical history, developmental milestones, and early interventions. Older individual will include: birth history, medical history, AAC interventions, educational background, and possibly vocational training.

PortFoLIos tHAt Work electronic Portfolios for Interdisciplinary teams as children transition One study has been completed (Lowe, 2005) to develop and document a way that would allow service providers to gain a comprehensive understanding 258

of the communication used by people with AAC needs. An electronic portfolio, used as an alternative method of documentation, was developed to provide an authentic and effective written and visual representation for an individual who uses AAC. Manuals were provided with suggestions for the development of an electronic portfolio and specific instructions for using the prepared electronic portfolio. The project was implemented in two phases. Creation of the manual was the first phase and the development of the electronic portfolio was the second phase. The electronic portfolio was then evaluated for accuracy, clarity, comprehensiveness, the educational relevance and for usefulness, by numerous raters (e.g., families, caregivers, therapists, educators, and graduate students in the field of speech and language) who were familiar and unfamiliar with the child.

Manual Guidelines for selecting artifacts were established in the Manual for Developing an Electronic Portfolio. Criteria for inclusion of artifacts used in the portfolio were adhered to for each of the twelve areas. The twelve areas were: pertinent history, formal and informal testing, current communication status (i.e., receptive language and expressive language), AT (i.e. augmentative communication, AT aids, and computer), academic accomplishments, classroom behaviors, self-care skills, transition skills, motor skills (i.e., gross motor, fine motor, and oral motor), social skills, vocational skills, and recreational/leisure skills. The documentation was gathered from past reports (e.g., medical and school documents), written reports that documented AAC strategies, and photos and videos from past and present sources to document AAC strategies).

Preparation of Electronic Portfolio CD The Microsoft software program PowerPoint was chosen to prepare the electronic portfolios. A PowerPoint presentation shell of twenty-one slides

Developing Electronic Portfolios

Figure 1. Portfolio artifacts gathered for each child’s electronic portfolio

was prepared as the basic format for each of the portfolios. Each child’s portfolio was customized to represent their level of skills. Figure 1 provides a summation of the artifacts that were gathered for each of the six children. Samples of the children’s artwork were scanned for a visual representation of their work. Photographs and video clips of each child were taken and organized into specific areas of the portfolio. The photographs and video clips were chosen to best represent a skill (e.g., manual signing, communicating using a device, coloring, and using a utensil to eat), an interfering behavior (biting hand and not attending), or an activity (e.g., following a story, using an adapted software program on the computer, and using manipulative during singing) of the given child. Scripts were prepared to insert voice-over narration for each of the twelve areas. The script contained information about the individual child to further the understanding of the child during the academic classroom setting. Information and photos were also gathered from the children’s parents, regarding home and community activities, to be included in the script.

effectiveness along various dimensions. Specific directions were provided on each of the rating scales for the familiar and the unfamiliar participant who viewed the electronic portfolio. Group 1, familiar raters, determined if the information presented was accurate, clear, complete, educationally relevant, and useful for the specific child featured in the electronic portfolio. Group 2, unfamiliar raters, determined if the information was clear, complete, educationally relevant, and useful to people unfamiliar with the specific child for whom the portfolio was developed. The unfamiliar raters did not rate accuracy. In this way, information was gathered from individuals who were familiar and unfamiliar with the specific needs of the target child. Figure 2 provides a summary of Group 1 and Group 2 as it relates to overall satisfaction of completeness and usefulness of the CD. Figure 3 demonstrates that both the Group 1 and the Group 2 raters valued the photos and video clips to be higher than the written reports. The mean score for the photos and video clips was greater for both rating groups.

Research Findings Upon completion of the electronic portfolio, Groups 1 and 2 viewed the CD and rated their

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Figure 2. Percentage of overall satisfaction for completeness and usefulness of the electronic portfolio from total rating scores of group 1 and group 2 raters

Figure 3. Inter rater reliability between mean rating scores for group 1 and group 2 raters for reports vs. photos

summAry oF tHe study The results of the study of the development of an electronic portfolio were quite positive in demonstrating that this is an effective tool for service providers to accurately document AAC systems used by particular individuals who use AAC. Ratings of accuracy, clarity, completeness, educational relevancy and usefulness were high. The dynamic features (e.g., combining artifacts of reports, photos, videos, child’s best work and narration) of these electronic portfolios captured and preserved the individuals’ performance in an educational setting. Service providers concluded that this tool provided information for the development of an electronic portfolio in a succinct manner.

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summer Program: Interdisciplinary team Approach for a camp for children with special needs Camp Integrations is a one-week intensive, interdisciplinary treatment program for children diagnosed with autism spectrum disorders (ASD), developmental delays (DD), or learning disabilities (LD). It is staffed by licensed physical and occupational therapists, speech-language pathologists and psychologists. Its purpose is to provide intensive, interdisciplinary therapy to children in a typical social atmosphere of a summer camp to facilitate social interaction, improve self-esteem, promote communication, and advance motor skills. All activities are carried out in a group environment. The ratio of staff to child is oneto-one. Children participate in camp for 5 days, 7 hours per day.

Developing Electronic Portfolios

These children are often present with a wide range of impairments that interfere with independence in daily activities. Aggressive interventions such as physical, occupational, speech and language, and behavior therapy can greatly improve a child’s functioning. The daily activities included hipotherapy, aquatherapy, neuronet, yoga/pilates, and music therapy. This study represents continuation and improvement of a collaborative and interdisciplinary effort among university faculty, academic units, community partners, and students, to provide and evaluate a creative alternative to traditional therapy for an underserved population of children. At the end of the camp program, staff therapists collaborate to develop an individualized home program for each child based on his performance and progress during the program. The purpose of the home program was to promote continuation of interventions deemed beneficial for the child by staff, and to maintain and foster improvements from the camp program. Approximately one month following the camp, the children and parents received an individualized electronic portfolio with a photo journal of their child performing the skills and participating in each of the activities. The home program that was developed by the therapists is also part of the CD. As part of the photo journal, 25-30 individual pictures and camp group photos are included. The electronic portfolios were created using PowerPoint. The presentation was organized, according to specific activities, the same for each camper. The CDs were individualized with personal photos, camp group photos, and background music using the camp song. Along with the mailing of the CD, surveys are sent to the camper’s families for feedback on the electronic portfolio and the home program. Twenty-four of the thirty surveys were returned. Satisfaction for the electronic portfolios was positive in the areas of clarity, comprehensiveness, and usefulness for the camper’s home therapy team. Interesting comments included “My child insists

on viewing the CD every day since it arrived.”, and “Our son shares more about camp each time he sees his pictures.” One comment relayed that “I would like to have seen before and after photos to show improvement with activities.” Unfortunately, this was not possible since the camp was only one-week long.

concLusIon The road to AT/AAC documentation for individuals with complex physical and communication needs using electronic portfolios has been demonstrated to be effective. Using photos, videos, and written reports, AT/AAC systems can be captured to document the use and progress and to show setups for replication. Service providers will have the opportunity to visually see and understand the use of AT/AAC as children transition to new opportunities. This chapter outlined ways that portfolios have been used in education to demonstrate accuracy, clarity, completeness, educational relevance, and usefulness. Service providers can make a difference in the development of electronic portfolios to assist families, future educators, and therapists in the understanding of AT/AAC. Future research is required to determine if electronic portfolios would benefit individuals who use AT/AAC as they transition from class to class, school to school, school to work, or within work settings. The dynamic features and the plethora of information captured in an electronic portfolio would provide the service provider a complete picture for the individual who use AT/AAC.

reFerences Arter, A. J., & Spandel, V. (1992). Using portfolios of student work in instruction and assessment. Education Measurement: Issues and Practices, Spring, 36-44.

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Campbell, J. (1996). Electronic portfolios: A fiveyear history. Computers and Composition, 13, 185–194. doi:10.1016/S8755-4615(96)90008-0 Demchak, M., & Greenfield, R. (2000). A transition portfolio for Jeff, a student with multiple disabilities. Teaching Exceptional Children, 32(6), 44–49.

Morrison, R. (1999). Picture this! Using portfolios to facilitate the inclusion of children in preschool settings. Early Childhood Education Journal, 27(1), 45–48. doi:10.1023/A:1026023608023 Niguidula, D. (1997, November). Picturing performance with digital portfolios. Educational Leadership, 26–29.

Gelfer, J., & Perkins, P. (1998). Portfolios: Focus on young children. Teaching Exceptional Children, 31(2), 44–47.

Paulson, L., Paulson, P. R., & Meyer, C. (1990). What makes a portfolio a portfolio?Portland, OR: Multnomah.

Johnson, R. S., Mims-Cox, J. S., & Doyle-Nichols, A. (2006). Developing portfolios in education: A guide to reflection, inquiry, and assessment. Thousand Oaks, CA: Sage.

Rogers-Dulan, J. (1998). The power of portfolios in inclusive classrooms. Adventist Education, Summer, 24-28.

Kentucky Department of Education. (2006-2007). Kentucky Alternate Assessment Program. Retrieved February 8, 2009, from http://www.education.ky.gov/KDE/Administrative+Resources/ Testing+and+Reporting+/District+Support/Ken tucky+Alternate+Assessment+Program/ Kratcoski, A. (1998, January). Guidelines for using portfolios in assessment and evaluation. Language, Speech, and Hearing Services in Schools, 29, 3–10. Lankes, A. (1995September). Electronic portfolios: A new idea in assessment. ERIC Digest, 3-4. Lowe, M. A. (2005). The Development of electronic portfolios for individuals who use augmentative and alternative communication. Unpublished doctoral dissertation, Nova Southeastern University, Fort Lauderdale, Florida. McLoughlin, J., & Lewis, R. (1994). Assessing special students (4th ed.). Columbus, OH: Merrill. Milone, M. N. Jr. (1995). Electronic portfolios: Who’s doing them and how? Technology & Learning, 16(2), 28–36.

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Salend, S. (1998). Using portfolios to assess student performance. TEACHING Exception Children, 31(2), 36–43. Wesson, C., & King, R. (1996). Portfolio assessment and special education students. Teaching Exceptional Children, 28, 44–48.

key terms And deFInItIons Artifacts: Something that was created by an individual. This artifact that was created by an individual who uses AT will be captured using photography or video to be included in an electronic portfolio. Electronic Portfolio: A collection of a student’s work, which may include text, graphics, sound, and video, captured electronically using computer technology (Milone, 1995). This collection of work, which was created by an individual who uses AT, and other pertinent information can be gathered and compiled into a CD or DVD format. Portfolio: A collection of information and artifacts gathered in a systematic and organized way to demonstrate and monitor the growth of an individual’s knowledge, skills, attitudes, and potential in a specific subject or skill area (Paul-

Developing Electronic Portfolios

son, Paulson, & Meyer, 1990). This definition of a portfolio refers to a collection of reports for an individual and presented as a compilation for reading. This format is often inadequate due to

the inability of a developer to capture (e.g., photos and video clips) all the AT strategies and equipment management that would be provided in an electronic portfolio.

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Chapter 18

Assistive Technology Solutions for Individuals with Learning Problems: Conducting Assessments Using the Functional Evaluation for Assistive Technology (FEAT) Brian Bryant University of Texas, USA Soonhwa Seok eLearning Design Lab, University of Kansas, USA Diane Bryant University of Texas, USA

AbstrAct Assistive technology (AT) assessments involve a dynamic process among the evaluator, the AT user, and the AT device. When accomplished correctly, these assessments are person-centered and ecological, that is, they actively involve the individual being evaluated and incorporate the collection of data from numerous environments in which the person works, learns, and plays. This chapter provides information about how such an AT assessment can be conducted using the Functional Evaluation for Assistive Technology (FEAT; Raskind & Bryant, 2002). Readers are provided with an overview of the importance of person-centered assessments, and then are given a description of each of the FEAT components. A case study is also provided, wherein the process of an effective and efficient AT assessment is described. DOI: 10.4018/978-1-61520-817-3.ch018

Copyright © 2010, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

Assistive Technology Solutions for Individuals with Learning Problems

IntroductIon Assistive Technology (AT) evaluation is a dynamic process involving AT devices that are continuously being modified and improved and individuals who are in ever-changing environments and contexts. These dynamic influences affect those who are designing educational programs and those who are using the AT devices; and thereby also affect everyone involved with conducting AT evaluations. The Functional Evaluation for Assistive Technology (FEAT; Raskind & Bryant, 2002) addresses the dynamics of AT evaluations by providing an ecological assessment of the student’s multiple needs. Ecological assessments are considered a “method of assessing a student’s total environment to determine what factors are contributing to learning or behavioral problems” (Overton, 2009, p. 22). An ecological AT evaluation is one designed to comprehensively assess the efficacy of students’ interactions and the relationship among the person, technology, and the multiple environments in which the individual lives and works. This chapter will: (a) introduce the concept of an ecological AT assessment and the need for input from multiple individuals across multiple settings; (b) discuss the importance of a personcentered approach to assessment; (c) describe the framework whereby the FEAT helps identify a person-technology match; and (d) identify the FEAT components while providing a case study that demonstrates how the FEAT helps provide for a person-technology match that is appropriate across multiple contents.

bAckground the concept of ecological At Assessments Ecological assessments provide information about the multiple environmental factors (Greenwood

& Carta, 1987; Desouza & Sivewright, 1993) that affect students’ interactions as they complete the tasks or learn new behaviors. Ecological assessments allow the special education service team to match a child’s performance level and his or her needs with learning tasks, routines, and developmental needs in situated contexts. Thus, ecological assessment provides an all encompassing evaluation that considers all aspects of a student’s academic life that affect learning. Specifically, ecological assessment techniques: (a) allow data-based decision-making on students’ progress, product, and process, leading to modification of instruction and home/classroom settings; (b) enhance students’ self-determination skills as students develop their own learning preferences (Agran, Blanchard, & Wehmeyer, 2000; Palmer, Wehmeyer, Gibson, & Agran, 2004; Wehmeyer, Palmer, Agran, Mithaug, & Martin, 2000); and (c) enhance students’ problem solving skills in various contexts by raising questions, problem, problem solving, and consequence of the solution (Turnbull, Turnbull, & Wehmeyer, 2007).

Proactive Personcentered Approach Effective ecological assessment models create a proactive person-centered (student-centered and team-based) approach that allows for continuous adaptability and fine-tuning of all elements involved in the specific learning environment. In this section, we describe a proactive personcentered approach to AT evaluations by presenting two key features of a person-centered approach: (a) student participation and (b) team-based problem-solving.

Student Participation The first element of the proactive person-centered approach is student participation (American Educational Research Association, American Psychological Association, National Council

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on Measurement in Education, 1999). Research indicates that the best practice of and the most successful outcome from the assessment process are students’ involvement in planning and implementation (Brotherson & Berdine, 1993; Overton, 2009; Thoma, Rogan, & Baker, 2001). In the ecological models or frameworks, students are involved in identifying their needs, technology skill level, and degree of technology literacy based on their functional capabilities. Participation allows students to develop “goal directed, self-regulated, autonomous behavior” (Field, Martin, Miller, Ward, & Wehmeyer, 1998, p.2; Overton, 2009, p. 442) in the technology-person interaction.

Team-Based Problem-Solving The second element of the proactive personcentered approach is team-based problem-solving (Watts, O’Brian, & Wojcik, 2004). Team-based problem-solving is based on the multiple perspectives from the collaboration between the individualized education program (IEP) team and family collaboration (Bronfenbrenner, 1979; Edyburn, 2000; McLouglin & Lewis, 2005; Overton, 2009). The team and family make decisions on AT implementation based on their interactions with the student with special needs in home or classroom settings. They identify problems; assess the student, the technology and the environment; determine the characteristics of the student’s need; and match the student and technology (Bryant & Bryant, 2003; Calabrese, & Baldwin, 1993; Forbes & Forbes, 1994; Osenberg & Schmitt, 1996). The team designs student – technology functional units where the student and technology interact effectively (applied from Trepanier, 2005, p. 2).

the FeAt Framework The FEAT addresses the considerations involved in assessing the most appropriate technology

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tools for a student with special needs. Specifically, FEAT mainly emphasizes the best match between technology, context, function, and student (Bryant & Bryant, 2003). The FEAT framework incorporates four key elements (Individual, Task, Context, Device), all of which are represented by various FEAT components. Individual refers to the “Individual’s specific strengths, limitations, special abilities, prior experiences/ knowledge, and interests” (Raskind & Bryant, 2002, p. 5). Tasks are “functions to be performed (e.g., compensating for a reading, writing, or memory problem) and the requisite skills associated with the tasks/functions” (p. 5). Context refers to the “specific contexts of interaction (across settings – e.g., school, home, work; and over time – e.g., over a semester or a lifetime)” (p. 5). Finally, device relates to factors “(e.g., reliability, operational ease, technical support, cost)” (p. 5) associated with the AT device itself. An ecological AT evaluation not only has to examine each of these four elements, but also determine the interplay which exists among them.

A cAse study IntroducIng And utILIzIng tHe FeAt comPonents The FEAT is a comprehensive assessment instrument that can be used to help determine the appropriate AT devices for individuals with learning problems. The FEAT can help maximize the benefits of utilizing AT device by examining the specific demands of tasks within the contexts, strengths and special needs of individuals with learning problems, and characteristics of technology devices. Through carefully matching, the setting-specific demands, person-specific characteristics, and AT-specific features, the effective and appropriate AT device(s) can be identified to compensate for the difficulties of individuals with learning problems and meet the specific tasks and contexts. In this section we briefly describe the FEAT components.

Assistive Technology Solutions for Individuals with Learning Problems

The purpose of this section is to introduce the FEAT components while providing a case study using the FEAT. To do so, we borrow from Raskind and Bryant (2002) and their FEAT manual. The authors provide several figures describing a particular student, Ryan Reider. Ryan is a 12 year-old 7th grader attending school in Saugus, Massachusetts. Additional information about Ryan can be found on Appendix A, which is a completed Summary and Recommendations Booklet. Following the evaluation, the AT evaluator completed the Summary and Recommendations Booklet. Here, comments pertaining to each of the FEAT forms are summarized and recorded. We call your attention to Sections IX, X and XI, which are particularly pertinent. In Section IX, Ryan’s performance with the technology was compared to his performance without the technology on the Grays Silent Reading Test (Wiederholt & Blalock, 2000). His gain in comprehension (in this case, listening comprehension – but comprehension of text material nonetheless) provides evidence for using the technology. In Section X, information is provided about expectations that accompany technology use and how support can be provided if the technology fails or training is needed (which is almost always the case – teachers need to know how the technology benefits Ryan and also how they can integrate the technology into their teaching. Finally, Section XI involves follow-up evaluations. Simply providing the technology and assuming it will be beneficial is insufficient. Follow-ups are critical to determining the extent to which the technology is helpful, and if not, what can be done to make it so.

contextual matching Inventory Upon referral for an AT evaluation, Ryan’s teachers were interviewed to complete a Contextual Matching Inventory to identify the setting demands that Ryan is faced with on a daily basis in the classroom (see Appendix B). Any AT evaluation should consider the tasks in which the potential user is

typically engaged across settings and to identify whether the technology will be successful across these settings. The Contextual Matching Inventory consists of two parts: Part A is titled “Identification of Specific Settings and Demands” and includes 44 specific tasks (demands) that are rated across up to six settings; Part B is titled “Additional Issues Relating to Contextual Matching,” and the items in this section of the scale examine issues of importance in generalization discussions. While Part A of the inventory can be rated by professionals or by interviewing up to six professionals who interact with the individual being evaluated, Part B of the inventory is completed by the examiner who is most familiar with AT adaptations and barriers to their successful implementation. As can be seen in Appendix B, three teachers were interviewed, and it obvious by the information they provided that Ryan is expected to do typical tasks of middle schoolers, including listening to lectures, read and gain information form textbooks, and write to convey what he has learned to his teachers. Because of Ryan’s reading disability, it is clear that he would struggle because of the heavy emphasis on access to text material.

checklist of strengths and Limitations The Checklist of Strengths and Limitations (see Appendix C) is used to provide information about the strengths and limitations of the person being evaluated. Specific abilities and skills concerning academic behaviors associated with listening, speaking, reading, writing, mathematics, memory, organization, physical/motor, and behavior are listed and the raters are to place a check mark in the column to designate whether the academic behavior is weak, average, or strong with regard to the individual’s ability level in each area when compared to his or her peers. Ryan’s teachers were asked to complete the checklist for two reasons. First, the AT evalu-

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ation team made a conscious decision to seek input from Ryan’s teachers so that they could feel as though they occupied an important role in the evaluation. Second, it is important to gain as much information about Ryan as the team can get, and Ryan’s teachers are a valuable source of information. Research has indicated that teachers provide valid observations about student strengths and limitations (Hammill & Bryant, 1998). In examining the completed checklist the team was able to determine that Ryan has strengths in all areas except reading and writing, which is where his primary functional limitations exist. This information is helpful, because the team thinks that screen reading technology can benefit Ryan, but only if his listening and thinking skills are intact. Based on the information provided by the teachers, this is the case. Had Ryan demonstrated listening difficulties, having what is in print read aloud to him would serve little purpose—one limitation would be overcome, but Ryan’s listening problems would have made comprehending the spoken text difficult.

technology characteristics Inventory This scale is used to evaluate device-specific characteristics such as its reliability, dependability, operational ease, and so forth. Preferably, this evaluation occurs before the device is used as part of an evaluation to exclude any inappropriate devices. Having determined that speech synthesis software and optical character recognition technology might benefit Ryan, the team looked at several different technology options in order to find a good Ryan-technology match. In Appendix D we see one such device, marketed by the fictitious XL Technologies; which was evaluated using the Technology Characteristics Inventory. As already discussed, this inventory is designed to assess the functionality of the technology across several

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important characteristics. A review of Appendix D demonstrates that the device received high ratings in the areas examined.

checklist of technology experiences The Checklist of Technology Experiences (see Appendix E) is rated based on a conversation between the examiner and the individual being evaluated or the examiner’s knowledge of the person being evaluated. Even though it is possible that the examiner can fill out the scale based on the evaluator’s knowledge of the individual being evaluated, the inputs from the person being evaluated can be crucial, since the purpose of the scale is to identify the individual’s familiarity with devices and no one should know the information better than the consumer. So far we have information from Ryan’s teachers and the AT expert who evaluated the technology. But we have not heard from Ryan himself, an important contribution to an ecological assessment. An interview with Ryan concerning his experiences with technology is the focus of the Checklist of Technology Experiences. As we discussed earlier, this checklist is used to identify whether the student has used technology in the past and, if so, gauge whether he viewed these experiences positively or negatively. If Ryan’s previous experiences with technology have been negative, these may affect deliriously any future technology interventions. Conversely, positive past experiences would likely mean that Ryan will look forward to working with technology, especially if he feels that the technology will be helpful in overcoming his limitations (in this case, access to print). A review of Appendix E shows that Ryan has had little experience using technology, other than ordinary word processing. Perhaps because of his discomfort using a keyboard, and probably because of his difficulties putting his thoughts into print, Ryan’s experiences with the word processor has been less than pleasant.

Assistive Technology Solutions for Individuals with Learning Problems

Individual-technology evaluation scale and Individual-technology evaluation Worksheets The Individual-Technology Evaluation Scale (see Appendix F) provides information about the person’s interaction with the AT device that is being evaluated. To simplify the assessment process, even though more than one device is needed for a given task, this scale was designed to examine only one device at a time relative to one area of difficulty. The first part of the scale, Part A. Individual-Technology Match, asks a series of questions relating to compensatory effectiveness, interest, ease of use, comfort, operational ease/ proficiency, and behavioral responses. Part B of the scale, titled General Technological Literacy, is used to examine the student’s overall computer/ technological knowledge/literacy, overall ability to use computers/technology, and keyboarding proficiency if applicable. Finally, Part C of the scale, labeled Other Considerations, is to examine a number of positioning issues and other characteristics that are important to note as part of the evaluation. The Individual-Technology Evaluation Worksheets were developed for use in conjunction with the Individual-Technology Evaluation Scale. Separate worksheets are used for optical character recognition/speech synthesis, speech synthesis/screen reading systems, speech recognition systems, word prediction software, and spell checkers. Each worksheet is designed as a guide to assist the evaluator in considering the effect of various characteristics, operations, functions, and options that are unique to specific technologies and are critical in determining the individualtechnology match. Having gathered information from a variety of sources, the AT evaluation team is now ready to match Ryan to an AT device and evaluate whether the Ryan-technology match is a good

one. For this evaluation, we will use two forms: the Individual-Technology Evaluation Scale and the Optical Character Recognition/Speech Synthesis worksheet. The worksheet provides a step-by-step opportunity for the evaluator to examine key features of a Ryan-technology match (see Appendix G). As can be seen, observations cluster within three key areas: Technology Features/Options (e.g., speech rate, font style preferences, background and text color), User’s Reactions (e.g., how Ryan responds to the scanning speed and speech quality of the synthesis), and the User’s Ability (i.e., whether Ryan can recognize scanning areas and follow the cursor). Space is available at the end of the worksheet should the evaluator wish to record and examine other Ryan-technology match features. As Ryan interacts and uses the technology, the evaluator observes Ryan’s and records the observations on the Individual-Technology Evaluation Scale, as shown in Appendix F. Clearly, these two forms are the “nuts and bolts” of the evaluation, because they help the evaluator determine if the technology “works” for Ryan. One other comment deserves note. To the extent possible, AT evaluations should occur in as natural a context as possible. Thus, the evaluator chose to conduct the evaluation in Ryan’s science classroom, during a period in which the classroom was unoccupied. The optical character recognition (OCR) device was situated in a convenient location at the back of the classroom, and the evaluation took place there. In this section, we have presented a case study of one student’s AT needs. Using the FEAT components, the AT evaluation team can conduct an ecological evaluation that involves significant personnel (e.g., the teachers and Ryan) and determines (a) if technology is needed, and (b) what specific technology can be beneficial to Ryan’s academic success.

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reFerences Agran, M., Blanchard, C., & Wehmeyer, M. L. (2000). Promoting transition goals and selfdetermination through student-directed learning: The self-determined learning model of instruction. Education and Training in Mental Retardation and Developmental Disabilities, 35, 351–364. American Educational Research Association, American Psychological Association, National Council on Measurement in Education. (1999). Standards for educational and psychological testing. Washington, DC: American educational Research Association. (2004). Assistive Technology Act. Washington, DC: U.S. Congress. Bronfenbrenner, U. (1979). The ecology of human development: Experiments by nature and design. Cambridge, MA: Harvard University Press. Brotherson, M. J., & Berdine, W. H. (1993). Transition to adult services: Support for ongoing parent participation. Remedial and Special Education, 14(4), 44–52. doi:10.1177/074193259301400409 Bryant, D. P., & Bryant, B. R. (2003). Assistive technology for people with disabilities. New York: Allyn and Bacon.

Field, S., Martin, J., Miller, R., Ward, M., & Wehmeyer, M. (1998). A practical guide to teaching self-determination. Reston, VA: Council for Exceptional Children. Forbes, T. L., & Forbes, T. L. (1994). Ecotoxicology in theory and practice. London: Chapman & Hall. Greenwood, C. R., & Carta, J. J. (1987). An ecobehavioral analysis of instruction within special education. Focus on Exceptional Children, 19, 1–12. Hammill, D. D., & Bryant, B. R. (1998). Learning disabilities diagnostic inventory. Austin, TX: Pro-ed. McLoughlin, J. A., & Lewis, R. B. (2005). Assessing students with special needs (6th ed.). Upper Saddle River, NJ: Merrill. Osenberg, C. W., & Schmitt, R. J. (1996). Detecting ecological impacts caused by human activities. In Osenberg, C. W., & Schmitt, R. J. (Eds.), Concepts and applications in coastal habitats (pp. 3–16). San Diego, CA: Academic Press. Overton, T. (2009). Assessing learners with special needs. Upper Saddle River, NJ: Merrill.

Calabrese, E. J., & Baldwin, L. A. (1993). Performing ecological risk assessments. Chelsea, MI: Lewis Publishers.

Palmer, S. B., & Wehmeyer, M., L., Gibson, K., & Agran, M. (2004). Promoting access to the general curriculum by teaching self-determination skills. Exceptional Children, 70, 427–439.

Desouza, E. R., & Sivewright, D. (1993). An ecological approach to evaluating a special education program. Adolescence, 28, 517–525.

Raskind, M., & Bryant, B. R. (2002). Functional evaluation of assistive technology (FEAT). Austin, TX: Psycho-Educational Services.

Edyburn, D. L. (2000). 1999 in review: A synthesis of the special education technology literature. Journal of Special Education Technology, 15(1), 7–18.

Thoma, C. A., Rogan, P., & Baker, S. R. (2001). Student involvement in transition planning: Unheard voices. Education and Training in Mental Retardation and Developmental Disabilities, 36(1), 16–29.

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Trepanier, N. S. (2005). Toward an ecological risk assessment framework for special education. International Journal of Special Education, 20(1). Turnbull, A., Turnbull, R., & Wehmeyer, M. (2007). Exceptional lives (5th ed.). Upper Saddle River, NJ: Merrill. Watts, E. H., O’Brian, M., & Wojcik, B. W. (2004). Four models of assistive technology consideration: How do they compare to recommended educational assessment practices? Journal of Special Education Technology, 19(1). Wehmeyer, M. L., Palmer, S., Agran, M., Mithaug, D., & Martin, J. (2000). Promoting causal agency: The self-determined learning model of instruction. Exceptional Children, 66, 439–453. Wiederholt, J. L., & Blalock, V. (2000). Grays silent reading test. Austin, TX: Pro-ed.

key terms And deFInItIons Adaptations: Specific accommodations, modifications, and supports to help individuals compensate for functional limitations and challenges. Assistive Technology (AT) Devices: Federally defined as “any item, piece of equipment, or

product system, whether acquired commercially off the shelf, modified, or customized, that is used to increase, maintain or improve the functional capabilities of a child with a disability” (Assistive Technology Act, 2004). Data-based Decision-making: Involves making determinations that are based on hard evidence and facts rather than opinion or conjecture. Ecological Assessments: An assessment method that evaluates a student’s total environment to idenitfy what factors that contribute to learning or behavioral problems. Font: Typeface. IEP: Acronym for the Individualized Education Program, which identifies educational and related referrals for students and preschoolers with disabilities. OCR: Acronym for Optical Character Recognition, a system, that may be a piece of hardware plugged into a PC or software, which translates print into a format that can be “read and spoken” by the computer or translated into Braille. Person-technology Match: In assistive technology, this refers to the pairing of AT devices and services to a particular individual’s needs rather than to a “one size fits all” perspective. Scanning: An indirect method of computer access using software that automatically moves along available responses that the operator selects by activating a switch.

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APPendIx A. sAmPLe summAry And recommendAtIons bookLet InPut For ryAn’s At evALuAtIon Figure 1. (reprinted with permission from Raskind & Bryant, 2002)

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Section 5

Teacher Education

With the focus on inclusion of students with disabilities in general education classrooms, all teachers need to be more sensitive to the needs of students who require access to assistive technology resources. The challenge becomes how best to integrate the essential skills and knowledge on the many dimensions of assistive technology into the teacher education curriculum. The structure of teacher education varies across many cultures. Within the United States models of teacher education vary greatly. Some programs require five years of study integrated with extensive practicum experiences. Whereas, there are large numbers of alternative programs where students are able to obtain full licensure on a part-time basis while still being employed. Under the latter circumstance, and even in some four and five-year programs, it is difficult to create within the curriculum, sufficient opportunities to prepare teachers with the necessary background in assistive technologies due to time and/or course constraints in the program. There are also competing demands on program requirements for content knowledge across subject matter fields and special areas such as multicultural standards-based instruction. To be successful in integrating the necessary instruction on assistive technology, there must be advocates and models to examine. While these tend to come from special education, the power base often lies in the general education teacher education program. This is not unreasonable given the demand for teachers and the understaffing that tends to prevail in teacher education. It is not a case of undervaluing instruction on assistive technology. It is related to the need to know and understand how assistive technologies impact the lives of learners with disabilities. Students with more severe disabilities are often identified prior to school as having needs for assistive technologies and schools are required to be responsive. That does not mean that teachers are prepared to ensure the accommodations. However, because the need is established and more technological in nature, the school takes a more proactive approach. A better outcome would likely occur, especially for those students whose needs for assistive technology do not emerge until academic expectations increase, if teacher education was more effective in preparing all teachers for leadership roles in this area. The focus on cognition relative to assistive technology adds a dimension that broadens the benefit to all learners. Increased attention is given to cognitive science in the teaching of mathematics and science to all learners. Much of the work being done in the area of online instruction takes the form of cognitive tutorials including an emphasis on reducing the cognitive load. These approaches benefit most learners. This should enhance generalization to giving more attention to cognition and the development of assistive technologies. At the same time the probabilities should increase the reception of assistive technology as an integral part of the teacher education programs by all faculties. The chapters in this section provide specific examples of teacher education in assistive technology. Readers will find they build on the prior foci of the previous sections of the handbook. To a large extent, how they translate into ideas on teacher education will depend on the perspectives and experiences the reader brings to teacher education in assistive technology. This is also true in many areas of teacher education that are outside the subject matter content. To some extent, it is the lack of vesting responsibility for these areas of teacher education that are too often slighted in the preparation process. One can argue that the focus should be on helping all teachers to share in the responsibility.

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Chapter 19

Improving Assistive Technology Training in Teacher Education Programs: The Iowa Model James R. Stachowiak University of Iowa, USA Noel Estrada-Hernández University of Iowa, USA

AbstrAct Teacher knowledge of and comfort with assistive technology (AT) has a profound effect on the use of this technology by students with disabilities. Currently, very few teacher preparation programs effectively address AT with their students. This chapter will discuss how to improve AT training at both a preservice and continuing education level for teachers by focusing on the innovative initiatives being undertaken by the Iowa Center for Assistive Technology Education and Research in the preservice teacher education program at the University of Iowa. By the end of this chapter, readers will understand the pressing issues in AT training for teachers and what is being done to create a new generation of AT savvy teachers by improving overall AT knowledge and comfort levels.

IntroductIon The University of Iowa’s College of Education created the Iowa Center for Assistive Technology Education and Research (ICATER) in 2006 to respond to the stated need of increased preservice AT teacher training by those across the state who worked with AT on a regular basis. Assistive techDOI: 10.4018/978-1-61520-817-3.ch019

nology services in Iowa are provided by an Area Education Agency. The state is divided into ten Area Education Agencies (AEAs) each covering large areas and containing numerous school districts (Iowa Department of Education, 2009). Each AEA has an AT team, however, these teams are small; especially when the physical size and number of districts served within each AEA are considered. Some AEA’s have over 3,000 students with AT written into their Individualized Education Plan, yet

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have fewer than ten AT professionals to work with these students. These constraints make it impossible for the AEA AT professionals to work with every student with AT needs on a regular basis. Many teachers in these schools either do not have the required knowledge to effectively use the technology with the students as needed, or are not comfortable incorporating and using AT in class. Without the support and willingness to follow through of the classroom teachers, the work done by the AT professionals often leads to improper use, limited use, or AT abandonment (Cook & Hussey, 1995; Phillips, B., & Zhao, 1993). Thus, it was identified that not only is it important to provide professional development training opportunities to teachers in the field, but it is critical to create a new generation of teachers, both general and special education, that are not only knowledgeable in the use of various types of AT, but also comfortable enough to properly incorporate them in the classroom environment. To do this, it is imperative to incorporate AT education and training into preservice teacher education programs. Although proficiency in AT for preservice teachers is emphasized in the 2001 Council for Exceptional Children (CEC) technology standards, only a few articles exist describing instructional methods for integrating AT into teacher education programs (Van Laarhoven, Munk, Zurita, Lynch, Zurita, & Smith, 2009). The Iowa Center for Assistive Technology Education and Research took this relative vacuum of information on providing preservice teacher AT training as an opportunity to create a new model program involving a combination of both obtaining information through lectures and meaningful hands-on experiences with AT commonly found in school settings. This chapter will focus on these innovative initiatives being undertaken at the University of Iowa to improve teacher’s knowledge of and comfort with AT.

IcAter’s APProAcH to PreservIce At educAtIon Upon its creation, ICATER’s preeminent goal was to incorporate AT training and education into the curriculum of each of the college’s four departments; Teaching and Learning, Educational Policy and Leadership Studies, Counseling, Rehabilitation and Student Development, and Psychological and Quantitative Foundations with a focus on the Teaching and Learning program. The one constraint given was that due to an already crowded curriculum of required classes, a mandatory AT class could not be created. To meet the AT education need, ICATER has worked with faculty in each of the departments to create an AT lecture series addressing various AT topics in classes that College of Education students are required to take. The lecture series’ level of specificity is tailored to the needs of each individual group of students. The goal for each group is the same—to become aware of AT’s existence, its benefits, the barriers preventing successful use in K-12 schools, how the most commonly used devices and software packages in K-12 schools work, and who might benefit from the different types of AT. Even though the goals are the same, they are arrived at differently. For example, those majoring in special education will receive more AT training than those in general education. The training received by special education majors is also more specific than just an overview and introduction of the field. Those in general education receive training that is framed differently than those in administration programs. Those in the administration programs are given an overview of AT followed by a discussion of the administrator’s role in the AT process. Each group will receive training in the areas of AT most important to their future careers. To increase AT usage in schools, not only must general and special education teachers understand how to use various AT solutions, they also must be comfortable using such devices with students.

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Research is constantly reporting the need and importance of instructing teachers about the benefits of AT in schools (e.g., Smith & Kelley, 2007). ICATER has determined that supplementing information provided in lectures with meaningful hands-on experiences accomplishes this goal. Giving students the opportunity to experience AT in an exploratory lab setting provides meaningful insight into how AT works. These hands-on experiences also foster a level of confidence and comfort necessary to successfully implement AT in a classroom setting. Because of the benefits of hands-on experiences with AT tools, ICATER has created a required model hands-on project for both special and general education majors. Initial results of student evaluation surveys of the hands-on project validate the idea that hands-on experiences provide a more meaningful AT education while promoting a level of comfort with using AT. This model is briefly introduced in the following section.

creAtIng A modeL HAndson At Project The Iowa Center for Assistive Technology Education and Research has developed a model hands-on AT project in conjunction with the College of Education course, 07E:102 Technology in the Classroom, a required class for all students in the teacher preparation program. In this class, students learn about conventional technologies and how to effectively implement their use in the classroom. Technologies taught include PowerPoint, web page design, and digital video editing among others. Being a technology-based class, this was a natural fit for the inclusion of an AT project. The key components of this project include an introductory lecture, which is followed by the assignment of the technology, a required consultation with ICATER to learn the technology, checking out a computer with the technology, preparing and providing a demonstration of the

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technology for the rest of the class, videotaping and editing that demonstration, and posting it on the user’s ePortfolio site. To maximize the exposure to AT, when designing the project, it was decided that this project would be most effective if done in groups. Making the hands-on learning experience a group project provides students with a chance to bring their different strengths and insights to a group setting to work together to learn an unfamiliar technology. Each semester in the course, Technology in the Classroom, there are typically ten sections each with fifteen students for a total of 150 students. For the group project, each section is broken up into five groups of three. Each of these groups explore one of five themes of AT identified as commonly used in school settings. These AT themes include the following: physical access tools, speech recognition technology, reading and writing aids, visual access aids, and symbolbased learning/universal design for learning aids. To create a meaningful experience that would resonate with the students and to allow students to experience more than one type of AT, the AT project was designed so that the students would explore one type of AT and teach it to the rest of the class through a demonstration at the end of the project. Making students responsible for their peers’ learning through a demonstration has ensured the overall quality of both the preparation and the demonstration, benefiting all students in the class. In the end, each group will have an in depth understanding and comfort using at least one type of AT and they will have observed four other presentations, thus being exposed to demonstrations of five important types of AT commonly found in a school setting.

mAt LAb For the students to have a positive and meaningful hands-on experience with AT, all constraints on learning, in this case primarily time and space,

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Figure 1. MATLab contents

need to be removed. The ICATER lab is unable to accommodate more than four students at a time. Also, it is only open from 8:00am to 5:00pm Monday through Friday, which are typically not conducive times to do group work in a college setting. Thus, the ICATER lab is both a time and space constraint. To ensure a positive experience, ICATER created the Mobile Assistive Technology (MAT) Lab for use by students participating in this project. The MAT Lab is composed of twenty PC laptop computers loaded with various types of AT. Because it removes time and space constraints by allowing each group to take home their assigned AT to work at times conducive to their schedules, the MAT Lab has become the most critical element for the success of the hands-on AT project. The MAT Lab computers are designed around the AT themes identified in the AT projects: physical access, speech recognition, reading and writing aids, vision aids, and symbol-based learning/universal design for learning tools. See Figure 1 for a list of the AT included in the MAT Lab for each theme. These themes as well as the AT selected were chosen based on discussions with AT professionals

working in the school system in Iowa as well as representatives familiar with statewide AT usage from the Department of Education. The MAT Lab is versatile in that it contains a diversified selection of AT that teachers are most likely to use in a classroom setting.

IcAter’s modeL HAndson At Project The AT project in Technology in the Classroom starts with a 50 minute lecture titled, An Introduction to the Assistive Technology Project, given by a representative from ICATER. In this lecture, ICATER introduces the concept of AT, discusses the AT continuum, discusses the importance of all teachers understanding AT, and provides introductory descriptions of the types of AT that the class will be exploring. No demonstrations are provided at this time because the students are charged with providing these for the rest of the class. The importance of understanding the AT continuum is discussed because the tools used in

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this project are all considered high-tech and it is important to understand that low-tech solutions are often the most effective solutions for many students. The idea that students should be provided with the lowest tech AT necessary (whether that’s low- or high-tech AT) to meet their documented need is also discussed during this lecture. To end the lecture, the ICATER representative discusses the expectations of the project and explains the steps that each student will need to go through to successfully complete the project. At this point, students are put into groups and assigned their AT theme. Once the AT has been assigned to each group, the next step is a required consultation in the ICATER lab. For a beneficial hands-on experience and quality in class demonstrations, it is imperative that students understand their assigned technology. The required consultation lasts roughly one hour and serves as both a robust tutorial of some of software and hardware titles in their assigned AT theme and some suggestions as to what should be explored and explained during their demonstrations. Since this consultation is the first interaction students will have with the technology, they are expected to take notes on how the products work. The Iowa Center for Assistive Technology Education and Research also provides a tip sheet for reference after the consultation on how some of the more common features of each product work. Students are also asked to think about how that particular type of AT may be used in a classroom and incorporate that into their demonstration. This consultation session is the students’ best opportunity to ask questions about the tools that they will be working with; however, they are encouraged to return to ICATER with questions as they arise. Because in-class demonstration time is limited (no more than ten minutes), during the consultation, students are encouraged to explore in depth at least one of the AT software programs or devices they are shown (for example, students in the Reading and Writing Aids group are typically shown Kurzweil 3000, Read and Write Gold, and

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WordQ) and develop what they consider to be the most effective and educational demonstration for the rest of the class. To ensure that students attend a consultation, they are not allowed access to the MAT Lab until they have completed a consultation session, and without accessing the MAT Lab, they will be unable to complete the project. Following the consultation session, students are eligible to check out a laptop from the MAT Lab that contains the AT they are assigned to investigate. They typically sign these computers out for two weeks. During that two-week period, they are encouraged to do whatever they need to fully explore different options in the program. They are encouraged to change settings, try using it coinciding with different standard programs such as Internet Explorer or Microsoft Word, and if possible, simulate how someone with a disability would use that AT. For example, students exploring the visual access tools are encouraged to use the screen magnifiers without their glasses or to use the screen readers to complete a task with the monitor turned off. Students using the physical access tools such as the head-controlled mouse and onscreen keyboard or the speech recognition tools are encouraged to attempt writing a paper using these tools. By participating in these types of activities, students gain an appreciation for the difficulties encountered by those who use AT. Allowing the students to check out a computer for use outside of the ICATER lab, is critical to being able to provide this experience. Giving the students direct access to the AT via a laptop, they are more likely to spend time working with the program, gaining better insight and comfort with it and thus being better able to present the topic to the rest of the class. At the end of the two-week exploration period, two class periods are set aside for demonstrations. Each group presents to the rest of the class directly off of the computer they have been using. This ensures that they have access to any profile, modifications, or examples they have worked with, making the presentation run smoothly. The

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laptops are connected to a projector and projected onto a screen at the front of the class. Because it is important for the rest of the class to see the programs they did not work with in action, when giving the demonstration, the students must focus on demonstrating how the products work and are not allowed to use PowerPoint slides for explanation. During the demonstration, the students are required to answer some questions on important aspects of each AT device or software program they discuss, including: • • • • •

Who could benefit from this type of AT? How does this AT work? Is this particular AT easy to use from a student perspective and why? Is this particular AT easy to use from a teacher’s perspective and why? What difficulties arise when using this type of AT?

While the students are presenting their demonstration, they are also being videotaped. The videotaping portion of the project is used both to help teach the students how to edit video, seeing as that is a potentially powerful tool in the classroom, and as a tool to self-evaluate their presentation and teaching styles. Once the students have edited their video, they upload it to their ePortfolio site as an artifact demonstrating what they have learned about AT. Once on their ePortfolio, the video can be viewed by potential employers. This aspect of the project has helped lead to high quality demonstrations, not only due to a fear of portraying themselves in a negative light with a poor demonstration, but also to use their acquired knowledge as a potential tool to help standout in the ever expanding pool of candidates when applying for future teaching jobs. The students are also asked to write a short reflective essay on their experience using AT and how they feel it will help in their teaching careers. This is uploaded to the ePortfolio as an AT artifact as well.

HAnds-on At Project LImItAtIons Two primary questions arise about potential limitations surrounding the AT project: 1.

2.

Using all Windows-based computers, how does this project benefit teachers that will have Macintosh computers in their classrooms? With AT constantly changing, will the experiences of these students be obsolete by the time they are teachers?

The first question arises because the MAT Lab is composed entirely of Microsoft Windows-based computers and 40% of Iowa schools use Macintosh computers. Although students are not experiencing AT directly on Macintosh computers, many of their experiences can easily translate. Many Mac users have a Windows platform that can be used on their Mac. This platform will run Windows-based AT. Teachers that are not comfortable working with AT on the Mac platform can simply switch to the Windows platform. Also, AT programs that have both Windows and Mac versions often operate similarly. Students that have experienced AT on a Windows platform should be able to easily translate those experiences to a Mac. To address the concern of students working with AT that will become obsolete by the time they begin teaching, ICATER does update the MAT Lab AT software as often as possible. This guarantees that students have the opportunity to explore the most recent version of each software package. However, it is inevitable that this AT will change at some point following the students’ participation in the hands-on project. The goal of the hands-on project is not just to make students aware of how one type of AT works. It is to make students comfortable enough with AT in general to be able to explore, figure out, and use AT that is not necessarily familiar to them. The principles

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taught in this project should expand to any type or any version of AT.

evALuAtIng IcAter’s HAnds-on At Project Following the video editing portion of the AT project, students are asked to complete a survey to help evaluate the project. They are asked to answer questions about their AT knowledge and comfort level both prior to and following their participation in the project. They are also asked to indicate how comfortable they would be incorporating the AT they worked with in a future class as well as whether or not they learned something from the presentations by other groups in the class. Finally, they are asked to comment on their overall thoughts on the project, what they learned, and what can be done to improve and enhance the project in the future. These questions are asked directly after finishing the project, so they are expected to be somewhat influenced in that respect. Also, although they are not truly a measure of whether or not a teacher will actually incorporate AT into a future classroom, they are a good indicator of an improved knowledge and comfort which would likely lead to improved usage statistics. In the three semesters this project has been conducted, 390 students have participated with 376 filling out evaluation surveys. Prior to seeing results from these evaluations, it was expected that most students would not feel very knowledgeable about or comfortable with AT prior to participating in the project. It was also expected that following the project, their thoughts would change and they would consider themselves more knowledgeable and comfortable with AT. The results seen have generally coincided with what was expected. When asked to rank their general AT knowledge prior to participating in the project on a scale of “poor”, “below average”, “average”, “above average”, and “excellent only”, 18.8% of students rated themselves as average or above

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average, zero students rated their knowledge as excellent, and 81.2% rated their knowledge of AT to be either below average or poor (See Figure 2). When asked to rank their general knowledge of AT on the same scale following the project, only 4.3% ranked their overall knowledge either poor or below average, 31.9% ranked their knowledge as average, and 63.7% ranked their knowledge to be either above average or excellent. Regardless of whether or not their overall AT knowledge actually improved (and one can assume that it has), the shift in perception at least indicates that students are more confident in their AT knowledge following the project, which should translate into being more likely to use these tools as future teachers. Because the teacher’s comfort with AT plays a large role in whether or not it will be used in class, the evaluation also asked the teacher preparation students to rank their general comfort with AT both before and after the project on the poor, below average, average, above average, excellent scale. Prior to the project, only 4.3% of the students ranked their comfort level as above average or excellent, while 17.4% said their comfort level was average, and 78.3% said their comfort level was either poor or below average (see Figure 2). Although this is only one teacher prep program, we can expect that these sentiments would be fairly similar at most other institutions prior to the students receiving any formal or informal AT training. Also, if they do not receive AT training at a preservice level, these thoughts are unlikely to change much in a positive direction. These answers are coming from students typically between the ages of 19 and 23, a generation widely considered to be “tech savvy.” If similar studies were done on teachers already in the field that have not had AT training or experience, one could most likely expect even more to feel that their comfort level was poor or below average. When asked to rank their comfort level following the project, there was a fairly dramatic shift in the other direction. At this point, only 2.9% indicated that their comfort level was poor or below average while 35.3% claimed their comfort level

Improving Assistive Technology Training in Teacher Education Programs

Figure 2. Students’ perceived AT knowledge & comfort level pre and post project

was average, and 61.8% claimed their comfort level was either above average or excellent. This shows how meaningful many students find this hands-on project. To further determine the students’ feelings of comfort with AT, they are also asked to indicate their level of agreement on a scale ranging from strongly disagree to strongly agree with the following statement: “I would be comfortable integrating the AT my group demonstrated into a future classroom.” The results have been promising; 85.4% of the respondents either agreed or strongly agreed with that statement while only 4.3% either disagreed or strongly disagreed. Similar results have been obtained when asking students if they would feel comfortable incorporating AT in general in a future classroom. When asked this question, 79.7% either agreed or strongly agreed with the statement while only 2.9% either disagreed or strongly disagreed (see Figure 3). At the very least, this indicates that the students confidence and comfort level with AT is increasing following this project. Having a higher level of awareness, confidence, and comfort with AT makes these students more likely to incorporate AT as teachers when it would benefit a student in a future classroom. Again, to fully understand the effect that this project is having on K-12 students with disabilities, follow-up studies need to be conducted once the students currently participating in this

project actually become teachers and have the opportunity to incorporate AT into a classroom. It was also critical to determine how the structure of the project was perceived. Although each group only gets to experience using one type of AT, they get to observe demonstrations of four other types. To help validate that this is an effective way of providing AT education, the students were asked if they had learned something from the other groups’ presentations. Based on their responses, the demonstrations seem to be an effective. Only 1.4% either disagreed or strongly disagreed with the statement that they had learned something from the other group presentations, while 94.2% either agreed or strongly agreed with the statement (see Figure 3). To validate that the students are actually learning from the demonstrations in class, a short, multiple choice assessment to be carried out following the project is being developed. During the evaluation of the hands-on AT project, students are also asked to provide comments on what aspects of the project were useful, what could be done to improve the project, and what they would take away from the project for use in a future classroom. Their comments helped to better explain their overall thoughts on the effectiveness of the project. The first question asked was, “What did you find most useful about the project?” Some of the most common responses are as follows:

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Figure 3. Hands-on project student evaluation results

• • •

• • • • • •

“Being able to work directly with an AT program.” “Learning about technology that is available to the teacher.” “Getting a chance to actually experience using the AT kept me more interested than simply a lecture.” “Getting an idea of resources available to help students with disabilities.” “Learning about technology that I previously had no knowledge of.” “Presenting on something that I can actually use in a future classroom.” “How comfortable I now feel using AT.” “Learning how AT can help different learners in different situations.” “Being able to take the AT home to practice with it.”

As these comments show, the students valued the project for making them aware of and comfortable with using AT, which was the main goal. Many of the comments also addressed the structure of the project. Students generally liked that they got an opportunity to experience the AT and felt that using the AT held their interest and was more valuable than listening to a lecture. Also, many students valued the opportunity to take the AT home to practice. This validates both the thought that hands-on experiences are valuable learning opportunities and that the creation of the MAT Lab was a critical component of the AT project.

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The second question asked of the students was, “What is something that you learned about AT that you will be able to apply in a future classroom?” This question was asked to gauge how well each student had thought about classroom application while during the project. The following are some of their most common responses: •

• •

• • •

•

“I learned that not all AT is expensive and that some computers have built in AT options.” “I knew very little….now I feel that I have a good knowledge base to build on.” “The main thing I got out of the AT project was gaining confidence to use some of the devices in a classroom setting. I was under the impression that some of the technologies would be impossible to learn, but that is not at all the case.” “Everything, I knew nothing about AT prior to this semester.” “I have a new outlook on AT and how easy it can be to use.” “I learned that universally designed programs are great for students with and without disabilities. I also learned that it is not hard to learn about different types of assistive technology.” “I learned to be open minded about how technology can assist students in all areas.”

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Although many of the comments are more general than specific, they still indicate students are learning something about AT usage in the classroom during this project. Many students indicated that they learned how easy AT was to use, or how AT does not always need to be high-tech to be effective. Many also discussed ways that AT could be used to benefit all students in the class. The comments indicate a changing attitude toward AT. Although this does not guarantee future classroom use, the positive reflections may indicate that these students are more open to using AT in a classroom than those that have not participated in such a project. Finally, the students were asked to answer the question, “Do you have any suggestions of ways to improve this project for future sections?” Some students stated that the workload was too much and that they did not get many opportunities to work on the project in class. However, most of the students either commented that there was nothing that needed to be changed while others commented on the desire both to further learn about the AT they had not directly worked with and the desire to have more time to adequately present what they learned. The following are variations of some of the most common comments to this question in the evaluation:

anyone commented negatively. The most common comment was that the students wanted an opportunity to explore more than just one type of AT. Although at this time, this is not possible in the context of the project, ICATER has experienced an increase in the number of students visiting the lab on their own time to learn and discuss different types of AT. The hands-on project has succeed in raising the knowledge, confidence, and comfort level with AT for many of the students who have participated. This project evaluation shows that students feel that their AT knowledge and comfort is improved following the project and that they feel that the method of providing hands-on experiences is effective. However, more evaluation in the form of assessment needs to be done to determine if their AT knowledge is actually improving. Also, it would seem likely that as students’ comfort with AT increased, the likelihood that they would implement AT in future classrooms would as well. To determine if this project is actually having an effect on the usage of AT in Iowa’s K-12 schools, more research needs to be conducted.

•

The need to improve teacher knowledge and comfort with using AT that is already in the schools as well as the positive implications of providing preservice AT education through a combination of lectures and hands-on experiences can be summed up in a University of Iowa College of Education student’s (Mary) practicum experience following the completion of the hands-on AT project in Technology in the Classroom. For her project, Mary’s group explored and presented on reading and writing aids, primarily focusing on the scan and read program, Kurzweil 3000. This program allows the user to scan printed material into the computer transferring it into a digital format that can be read aloud and easily manipulated on a

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“Give the students a chance to try using other AT beside what they presented in class. This would give an opportunity for hand-on experience with more than one type of AT.” “Provide the students with longer presentation time, ten minutes is not enough to accurately display all that we have learned.” “Let us all play around with them a little following the presentations so that we all have a better feel for all of the AT.”

These comments show that students see value in this project. In fact, when given the opportunity to provide an improvement suggestion, hardly

IcAter’s At Project: mAry’s exPerIence

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computer for studying purposes. In this format, students with disabilities limiting their access to printed text can customize the program’s reading speed, reading unit, voice, and text highlighting color to meet their specific needs. At the same time, as she was working on this project, Mary was also taking her practicum class where she was required work alongside the classroom teacher at a local school. Although she didn’t specify the class she was working in, many of the assignments involved reading articles and either discussing or writing reflections on them. There was one student in the class, Dylan, who had autism as well as behavior issues and thus had difficulty participating in these types of classroom activities. One of Mary’s tasks was to work with Dylan to find a way to help him access the same work that the rest of the class had been doing. She tried reading the articles to him, but he did not respond well to that intervention. She eventually took him into the computer lab to attempt to provide a quieter environment for reading and saw a sign on a computer that read “Kurzweil 3000. Do not turn off.” Having just worked with the program in Technology in the Classroom, she sat Dylan down, showed him how the program worked and taught him to control and use it on his own. Within two class periods, he had used the program to read a five page article, which Mary claimed was much more than she had seen him do all semester. When she explained to the other teachers what she had him doing, they were amazed that she knew how Kurzweil worked. One even claimed that they had had the program for years but that no one knew how to use it properly. Also, the sign had been placed on the computer because someone had been afraid that if the computer had been turned off with Kurzweil on it, it would break. This indicated that not only did the teachers not understand how the program worked, but they were not comfortable using it. Mary showed the other teachers how Kurzweil worked and, with Mary’s help, they proceeded to use it successfully with Dylan for the rest of the semester. This experi-

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ence opened Mary’s eyes to both the benefits of AT and the need for teachers to understand and be comfortable with its usage. About her experience, Mary commented that “while it was frustrating to think that this technology could have been used successfully much earlier in Dylan’s academic career, I am thankful that I was able to introduce it to him. Showing other teachers how Kurzweil is used means that it will continue to be used and prove beneficial to Dylan’s learning. In a school environment where Dylan felt dejected by the accomplishments of others and unmotivated due to fear of failure, he is finally able to accomplish tasks independently thanks to AT” (Personal communication, May 2007). Dylan’s story is one that is too common among schools across the United States. The problem with AT is not always that the school does not have access to it. Much like Dylan’s school, many schools have AT available that would benefit students with disabilities. The problem is that outside of some special education teachers and district or area AT professionals, who cannot be with every student with a disability on a daily basis, most teachers do not know what AT is, how to use it, or are not comfortable enough with it to incorporate it into a classroom environment. A solution to this problem is increasing AT training at a preservice level. Often, training via lectures on AT is not enough. For teachers to be comfortable enough to use AT with students with disabilities, they need some hands-on experience. The model hands-on AT project that ICATER has incorporated into the teacher preparation program in the College of Education at the University of Iowa is one way, although more research on its effectiveness is needed, to prepare teachers to effectively use AT in a K-12 classroom setting.

concLusIon For AT to have a positive impact, teachers, both special and general education, must be willing to

Improving Assistive Technology Training in Teacher Education Programs

incorporate the necessary AT into the classroom environment. For many reasons, as determined in the Iowa Assistive Technology Needs Assessment, including the lack of preservice AT preparation, many teachers do not have the required knowledge or comfort level to effectively implement AT usage in their classrooms. Some colleges and universities have begun to recognize the need for AT training in their teacher preparation programs. In the College of Education at the University of Iowa, the ICATER has developed a model handson AT project that is required of every teacher preparation student. This project facilitates learning AT at a hands-on level and fosters a feeling of comfort with commonly used AT software and devices. The Iowa Center for Assistive Technology Education and Research’s project is just one example of how colleges and universities are addressing the need to prepare teachers to utilize AT in a classroom environment. Early evaluations of the project suggest that it is having a positive impact on the AT knowledge and comfort level of students graduating from the University of Iowa’s College of Education, but further research must be done on this and other methods used in teacher training programs to determine its ultimate impact on students with disabilities.

reFerences Cook, A. M., & Hussey, S. M. (1995). Assistive Technologies: Principles and practice. Saint Louis, MO: Mosby. Iowa Department of Education. (2009). Iowa area education agencies. Retrieved on February 9, 2009, FROM http://www.iowaaea.org/vnews/ display.v/ART/49525a79b9752 Phillips, B., & Zhao, H. (1993). Predictors of assistive technology abandonment. Assistive Technology, 5(1), 36–45.

Smith, D. W., & Kelley, P. (2007). A survey of assistive technology and teacher preparation programs for individuals with visual impairments. Journal of Visual Impairment & Blindness, 101(7), 429–433. Van Laarhoven, T., Munk, D. D., Zurita, L. M., Lynch, K., Zurita, B., & Smith, T. (2009). The effectiveness of video tutorials for teaching preservice educators to use assistive technologies. Journal of Special Education Technology, 23(4), 31–45.

key terms And deFInItIons Assistive Technology (AT) Continuum: A means of categorizing assistive technology devices based on their level of sophistication, amount of training needed to use and relative cost. On the continuum, a device could be considered no-tech, low-tech, mid-tech, or high-tech. ePortfolio: An electronic collection of traditional (essays, lesson plans, etc.) and multimedia (PowerPoint presentation, videos, etc.) examples of a teacher’s work. Mobile Assistive Technology Lab: A collection of laptop computers with different types of assistive technology that can be taken to and used in various settings for training. Screen Magnifying Software: Software that increases the size of images on a computer screen to a size that individuals with visual impairments can see. Screen Reading Software: Software that reads the content of a computer screen out loud, this can be used by individuals with difficulty reading and understanding text or by individuals with visual impairments for navigation purposes. Speech Recognition Software: Software that uses the user’s voice to input text into the computer or voice commands to control applications of the computer.

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Universal Design for Learning: A framework for applying universal design principles to curricula, instructional materials, educational activities, and assessments to make them accessible to all students regardless of ability or learning style.

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Chapter 20

Effects of Assistive Technologies Combined with Desktop Virtual Reality in Instructional Procedures (1) Gary Dotterer Oklahoma State University, USA

AbstrAct Based on research, desktop virtual reality (DVR) has been shown to have learning benefits over traditional methods of instruction. However, implementing assistive technology (ATs) in DVR would seem to enhance the learning process. This study aimed to examine effects of web-based DVR on learning performances. The literature reviewed for this particular study ultimately shows DVR to be beneficial in training in many fields found in the workforce. The overall advantages utilizing advanced technology in the form of DVR and ATs allow safe and controlled training environments, realistic simulations, and the ability to reconstruct learner processes and interactions.

IntroductIon Desktop virtual reality has been proven as a viable means of training in many industries, businesses, and professional environments. Because DVR is new in training and teaching, the addition of ATs further introduce more possibilities for those training individuals for the workforce. Because many individuals employed in business, industry, and specialized fields have some type of impairment, whether it is considered a minor impairment or severe, technology has provided the necessary tools DOI: 10.4018/978-1-61520-817-3.ch020

for those individuals to perform in the workforce. The contribution to new knowledge in training that utilizes DVR combined with AT (DVR/ATs) is the ability to immerse individuals in a safe environment while training for more dangerous or hazardous work areas. Individuals can take virtual tours, visit far away countries, and even explore new frontiers from the safety of their own desktop. These new advanced and innovative technologies combined together are so new that the potential for this type of training tool has yet to be determined. Providing learning opportunities for employees with disabilities have been limited in regards to technology and the type of procedures that could be

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Effects of Assistive Technologies Combined with Desktop Virtual Reality in Instructional Procedures (1)

constructed. Advancements and new technology can create environments conducive to assisting the disabled with training and developments of skill knowledge. It is important that employers consider this technology due to the lack of constraints in space and through properly constructed and developed instructional procedures desktop computers can affordably provide many training options for these individuals. Those who are not whole should be given every opportunity that others have to become fully humanized by the liberation of DVR through AT devices. Section 508 requires that governmental offices provide all employees equal access to electronic documentation. Desktop virtual reality/ATs provide alternative solutions that can be more beneficial if properly initiated. The strong learning potential of DVR has been shown through many training procedures and many people assume this technology cannot work for people with disabilities. However, this is not true, given new ATs that can make DVR possible for everyone.

reseArcH ProbLem In 1998, Congress passed an amendment to the Rehabilitation Act known as Section 508 requiring federal and state agencies, including educational institutions and specialized fields, to make their electronic and information technology accessible to people with disabilities. “Inaccessible technology interferes with an individual’s ability to obtain and use information quickly and easily” (IT Accessibility & Workforce Division, 2006, p.1). These federal, state, educational agencies are required to offer individuals with impairments hardware and software technologies that give equal access to Internet and Intranet websites, interactive forms, videos, audio files, digital documents, and other web-based tools. Much of this content depends on the user and their ability to see, hear, or navigate using AT input and output devices such as a screen reader, trackball,

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Braille board, and voice-recognition software as an alternative method to access online content. This non-compliance opens the door for litigation and learners who rely on AT devices are faced yet with another road block, although DVR/ATs may show to have advantages in training.

reseArcH PurPose Learners with impairment use ATs to access online learning content through input devices and software. According to Netherton and Deal (2006) ATs can be defined as, “…any piece of equipment or device that may be used by a person with a disability to perform specific tasks, improve functional capabilities, and become more independent. It can help…people with a wide range of cognitive, physical, or sensory disabilities” (p.11). Although these devices are used primarily for accessing electronic documents, bridging connectivity with desktop publishing software, and browsing Internet content, the literature shows that ATs are compatible with most digital online content, however, what has not been researched is the comparison of learning outcomes among instructional procedures: text-only, image-only, DVR/ATs, and hands-on instructional treatments. The purpose of this study was to determine, through dependent evidence or consequences that are observable, using a mixed method research design, the effects of four treatments on learner performance outcomes.

Hypothesis and conceptual research Framework The hypothesis and conceptual framework proposed in this study were formulated based on the previous research conducted by Ausburn and Ausburn (2004). The following hypothesis was derived:

Effects of Assistive Technologies Combined with Desktop Virtual Reality in Instructional Procedures (1)

Figure 1. Conceptual framework

H1: Learner outcomes from DVR/ATs instructional procedure design will show no significant difference to traditional hands-on instructional design learner outcomes. H2: Learner outcomes from DVR/ATs instructional procedure design will show no significant difference to text only instructional design learner outcomes. H3: Learner outcomes from DVR/ATs instructional procedure design will show no significant difference to image only instructional design learner outcomes. The conceptual framework for this study originated from three primary areas: (a) John Sweller’s (1988) Cognitive Load Theory, (b) Waller, Hunt, and Knapp (1967) Orientation and Wayfinding Theory, and (c) John Anderson’s (1996) Adaptive Character of Thought (ACT-R). Shown in Figure 1 are the theories that support outcomes found in the study. Input overload, lack of preparation, and insufficient training are possible causal effects

contributing to obtained learner performance. Cognitive Load Theory, as defined by Sweller (1988), proposes that optimum learning occurs in humans when the load on working memory is kept to a minimum to best facilitate the changes in long-term memory. Sweller contends that learning can take place if individuals are not exposed to too much input from different media sources simultaneously. The basic premise of cognitive load theory can be summarized as: “Working memory, in which all conscious cognitive processing occurs, can handle only a very limited number—possibly no more than two or three—of novel interacting elements” (Paas, Renkl, & Sweller, 2003, p. 2). By combining ATs and DVR in the same environment, the possibility of cognitive load may be exerted due to exposing simultaneously a visual, auditory, kinesthetic, and an unfamiliar setting. In this study, it was hypothesized that the large visual cognitive load of DVR might disadvantage the medium. A second theoretical thread came from Hunt and Waller’s (1999) work on orientation and wayfinding in visual environments. According to Hunt and Waller (1999), orientation is our awareness of the space around us, including the location of important objects in the environment. Orientation in space is crucial for finding one’s way (or wayfinding) from one location to another. As individuals enter unfamiliar environments disorientation can occur, thus causing frustration and a sense of helplessness. Geocentric and egocentric mapping are types of tools to overcome any wayfinding or orientation difficulties. Geocentric mapping orients the user in an up direction as a navigator relies on the top side of a map always pointing north. Egocentric mapping orients the user by placing a historical landsite or marking to denote the navigator’s position in relation to the rest of the map. In this study it was hypothesized that to be effective, VR must assist learners to orient and wayfind in the visual environment. If it fails to accomplish this, VR could have diminished effectiveness.

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The Adaptive Character of Thought (ACT-R) by John Anderson (1996) states, “…complex cognition arises from an interaction of procedural and declarative knowledge. Procedural knowledge is represented by units called production rules, and declarative knowledge is represented in units called chunks” (p.355). Anderson (1996) goes on to say, “The individual units are created by simple encodings of objects in the environment (chunks) or simple encodings of transformations in the environment (production rules). A great many such knowledge units underlie human cognition” (p.335). ACT-R is a cognitive architecture—a theory about how human cognition works. On the exterior, ACT-R looks like a programming language; however, its constructs reflect assumptions about human cognition. These assumptions are based on numerous facts derived from psychology experiments. Like a programming language, ACT-R is a framework: for different tasks (e.g., Tower of Hanoi, memory for text or for list of words, language comprehension, communication, aircraft controlling), researchers create models (aka programs) that are written in ACT-R and that, beside incorporating the ACT-R’s view of cognition, add their own assumptions about the particular task. Considering Sweller’s cognitive load theory and Anderson’s ACT-R theory, if the instructional procedure design is properly constructed, ATs combined with virtual environments can harmoniously work together and provide enhanced training, instruction, and skill development in many areas within a variety of businesses, industries, and corporate environments. The conceptual framework for this study proposed that DVR/ATs might pose learning difficulties unless carefully designed and implemented. Careful instructional design and presentation might help overcome potential cognitive overload, facilitate orientation and wayfinding, and help learners proceduralize manipulation of this complex medium.

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LIterAture revIeW Desktop virtual reality has evolved since its early days in the entertainment industry making its first appearance in video arcade games. Due to the development of sophisticated computer graphics and animation technology, PC-based environments that are realistic, flexible, interactive, and easily controlled by users have recently opened major new possibilities for what has been termed unwired, unencumbered, or DVR (Ausburn & Ausburn, 2004; Shneiderman, 1993). Desktop virtual reality requires mouse, joystick, or space/sensorball-controlled input to navigate through a 3D environment and a graphics monitor for display under computer control (Ausburn & Auburn, 2004). In DVR, the user employs a mouse or other navigation device to “...move and explore within a virtual environment on his/her computer screen as if actually moving within a place in the real world” (Ausburn, Ausburn, Cooper, Kroutter, & Sammons, 2007a, p. 9). QuickTime software installed on a regular PC controls a special video file known as a QuickTime Virtual Reality (QTVR) which gives individuals control through an input device to click and drag left to right or up and down in a virtual scene. In DVR, movement can include “rotating the panoramic image to simulate physical movements of the body and head, and zooming in and out to simulate movements toward and away from objects or parts of the scene” (Ausburn & Ausburn, 2008, p.57). Desktop virtual reality that uses a mouse for navigation simulates the action of walking or riding. An important question is whether this desktop simulation sufficiently represents interaction with the real world (Waller, Hunt, & Knapp, 1998). Bliss, Tidwell, and Guest (1997) addressed this issue and showed that for acquiring certain kinds of spatial knowledge, minimal navigational control with a mouse can be sufficient.

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Twenty-first century instructional procedures should adopt new immerging technologies as a means to engage students in interactive virtual environments. With DVR/ATs, the learning opportunities for individuals in workforce and career and technical education and at post-secondary institutions should be enhanced. These technologies are currently being utilized in education as separate methods of instruction, but combined they provide an interactive and safe way for students to learn. Recent research has demonstrated that under some conditions and for some learners, presenting complex technical environments via DVR has advantages over using traditional still imagery. This research has also shown that DVR has advantages during recall for object placement but introduces noise in the form of visual channel overload that can interfere with learning (Ausburn, Ausburn, Cooper, Kroutter, & Sammons, 2007b). Because many individuals employed in business, industry, and specialized fields have some type of impairment, whether it is considered a minor impairment or severe, technology has provided the necessary tools for those individuals to perform in the workforce. The contribution to new knowledge in technology center and in workforce training utilizing DVR/ATs is the ability to immerse individuals in a safe environment while training for more dangerous or hazardous work areas. Individuals can take virtual tours, visit far away countries, and even explore new frontiers from the safety of their own desktop. This study provides essential statistical analysis and recommendations that will allow for further studies in this complex, but user-friendly environment. This research was designed to launch in depth study in the future to assist those individuals with disabilities in education. Immersing individuals who may not be able to fully interact with their environment or surroundings may one day benefit from this study. Through the use of audio interaction, closed captioning, and DVR

combined in a web-based setting, the possibilities are promising. Upon successful design and implementation of instructional procedures that utilize DVR/ATs, the possibility of enhanced learning is increased. As a learning tool, DVR has demonstrated distinct opportunities across the educational spectrum (Dickey, 2005; Neel, 2006; Revenaugh, 2006; Shim, Kim, Kim, Park, Park, & Ryu, 2003; Smedley & Higgins, 2005; Vogel, Bowers, Meehan, Hoeft, & Bradley, 2004). Desktop virtual reality has also proved beneficial in professional occupational training in the medical field and engineering. In general, recent research supports the assertion that an abundance of possibilities exist for virtual reality as a training tool within the vocational and technical education field (Ausburn & Ausburn, 2006; Park, Jang, & Young, 2006; Seth & Smith, 2004; Tiala, 2007). The continuation of the study is contained in Chapter 21 of this handbook. Chapter 21 begins with the methodology, results and findings, discussion, future research directions, and conclusion sections.

reFerences Anderson, J. R. (1996). ACT: A simple theory of complex cognition. The American Psychologist, 51, 355–365. doi:10.1037/0003-066X.51.4.355 Ausburn, F. B., Ausburn, L. J., Cooper, J., Kroutter, P., & Sammons, G. (2007a). Virtual reality technology: Current status, applications, and directions for education research. OATE Journal: Oklahoma Association of Teacher Educators, 11, 7–14. Ausburn, F. B., Ausburn, L. J., Cooper, J., Kroutter, P., & Sammons, G. (2007b). Virtual reality in surgical technology education: A study in instructional theory and design. In Proceedings of the 2007 CTE Research and Professional Development Conference, Las Vegas, NV (pp. 218-233).

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Ausburn, L. J., & Ausburn, F. B. (2004). Desktop virtual reality: A powerful new technology for teaching and research in industrial teacher education. Journal of Industrial Teacher Education, 4(4), 33–58. Ausburn, L. J., & Ausburn, F. B. (2006, December). Effects of desktop virtual reality on learner performance and confidence in environment mastery: Opening a line of inquiry. Paper presented at the meeting of the Association of Career and Technical Education Research, Atlanta, Georgia. Ausburn, L. J., & Ausburn, F. B. (2008). Effects of desktop virtual reality on learner performance and confidence in environment mastery: Opening a line of inquiry. Journal of Industrial Teacher Education, 45(1), 54–87. Bliss, J. P., Tidwell, P. D., & Guest, M. A. (1997). The effectiveness of virtual reality for administering spatial navigation training to firefighters. Presence (Cambridge, Mass.), 6, 73–86. Dickey, M. (2005). Brave new (interactive) worlds: A review of the design affordances and constraints of two 3D virtual worlds as interactive learning environments. Interactive Learning Environments, 13(1-2), 121–137. doi:10.1080/10494820500173714 Hunt, E., & Waller, D. (1999). Orientation and wayfinding: A review. Seattle, WA: University of Washington. Retrieved March 3, 2008, from http://www.cs.umu.se/kurser/TDBD12/HT01/ papers/hunt99orientation.pdf IT Accessibility & Workforce Division. (2006). 508 Law. Washington, DC: Author. Retrieved September 3, 2008, from http://www.section508. gov/index.cfm?FuseAction=Content&ID=3 Neel, R. (2006). Consider the opportunities: A response to no child left behind. Education & Treatment of Children, 29(4), 533–548.

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Netherton, D., & Deal, W. (2006). Assistive technology in the classroom. Technology Teacher, 66(1), 10–15. Paas, R., Renkel, A., & Sweller, J. (2003). Cognitive load theory and instructional design: Recent developments. Educational Psychologist, 38(1), 1–3. doi:10.1207/S15326985EP3801_1 Park, C., Jang, G., & Young, C. (2006). Development of a virtual reality training system for live-line workers. International Journal of Human-Computer Interaction, 20(3), 285–303. doi:10.1207/s15327590ijhc2003_7 Revenaugh, M. (2006). K-8 virtual schools: A glimpse into the future. Educational Leadership, 63(4), 60–64. Seth, A., & Smith, S. (2004). PC-based virtual reality for CAD model viewing. The Journal of Technology Studies, 30(4), 32–37. Shim, K., Kim, H., Kim, J., Park, J., Park, Y., & Ryu, H. (2003). Application of virtual reality technology in biology education. Journal of Biological Education, 37(2), 71–73. Shneiderman, B. (Ed.). (1993). Encyclopedia of virtual environments (EVE). Human Interface Technology Lab, University of Washington. Retrieved February 8, 2004, from http://www.hitl. washington.edu/scivw/EVE Smedley, T., & Higgins, K. (2005). Virtual technology: Bringing the world into the special education classroom. Intervention in School and Clinic, 41(2), 114–119. doi:10.1177/105345120 50410020201 Sweller, J. (1988). Cognitive load during problemsolving: Effects on learning. Cognitive Science, 12(1), 257–285. Tiala, S. (2007). Integrating virtual reality into technology education labs. Technology Teacher, 66(4), 9–13.

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Vogel, J., Bowers, C., Meehan, C., Hoeft, R., & Bradley, K. (2004). Virtual reality for life skills education: Program evaluation. Deafness & Education International, 6(1), 39–50. doi:10.1002/ dei.162 Waller, D., Hunt, El, & Knapp, D. (1998). The transfer of spatial knowledge in virtual environment training. Presence (Cambridge, Mass.), 7(2), 129–143. doi:10.1162/105474698565631

key terms And deFInItIons ACT-R Theory: Derived by John Anderson in 1996 who proposed complex cognition arises from an interaction of procedural and declarative knowledge. Procedural knowledge is represented by units called production rules, and declarative knowledge is represented in units called chunks. Assistive Technology (AT): Provides individuals with learning, communication, and physical access difficulties the necessary hardware and software solutions to lead more productive and independent lives.

Closed Caption Video: Text that scrolls through a digital video file that gives auditory impaired individuals the opportunity to read dialogue. Cognitive Load Theory: Derived by John Sweller in 1988 that proposed optimum learning occurs in humans when the working load is kept to a minimum to best facilitate long-term memory. Desktop Virtual Reality (DVR): Refers to a computer program that creates a real or simulated imagery-based environment that is displayed through a desktop computer screen. Orientation and Wayfinding Theory: Derived by David Waller, Earl Hunt, and David Knapp in 1998 that proposed orientation in space is crucial for finding one’s way from one location to another. QuickTime Virtual Reality (QTVR): A special video file created by virtual reality software that gives users the ability to click and drag right or left, up and down by control movement through an input device. Virtual Reality (VR): A multi-imagery computer generated environment. Web-Based Treatments: Research instruments that are administered via the World Wide Web.

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Effects of Assistive Technologies Combined with Desktop Virtual Reality in Instructional Procedures (2) Gary Dotterer Oklahoma State University, USA

AbstrAct Twenty-four practical nursing and health careers students were introduced by random assignment to the four treatments. Specifically, the study compared the learning effects on an instrument connection procedure used in a medical setting of four different learning treatments: text-only instruction, imageonly instruction, desktop virtual reality (DVR) with assistive technologies (ATs) (i.e., audio combined with closed caption) instruction, and hands-on demonstration instruction. This study used descriptive statistics, analysis of variance (ANOVA), and qualitative comments and observation to discover important design and implementation challenges for DVR.

IntroductIon

metHodoLogy

In this chapter the methodology, results and findings, discussion, future research directions, and conclusion are presented as a follow-up to Chapter 20.

sample

DOI: 10.4018/978-1-61520-817-3.ch021

Twenty-four subjects from Northeast Technology Center in Oklahoma (USA) participated in this study. They were post-secondary Practical Nurs-

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Effects of Assistive Technologies Combined with Desktop Virtual Reality in Instructional Procedures (2)

ing students and Health Careers Occupations students aged 18 years or older, and were selected to participate based on the criterion of having no previous interaction with an electrocardiography machine (ECG or EKG).

testing Instruments and Procedures Subjects were randomly assigned to one of four web-based treatments: (a) text-only that included only text with no visual aides; (b) image-only that included visual imagery with no supportive text; (c) DVR/ATs that included a QuickTime Virtual Reality (QTVR) Movie, audio with closed captioning and text-based support for documentation; (d) hands-on instructional training that included instructor-presented instructional demonstration supported by text-based documentation. Figures 1, 2, and 3 illustrate the three media-based treatments. These treatments were presented via desktop computer. All four treatments were presented to subjects individually by the researcher. Students assigned to image-only and DVR/ ATs treatment were given a video to train them on interaction and navigational tools used by the QTVR Player. These subjects were allowed to view the instructional training video as long as they wanted. All students were individually given their assigned instructional presentation on

to how to hook up an EKG. Upon completion of their training treatment, students were individually shown the actual EKG, lead cables, sensors, and electrical power cord and ask to successfully hook up the machine to a mannequin according to what they learned from their treatment. Subjects were given a maximum of ten minutes to complete this task. This performance test was the source of the quantitative data for the study. Additional qualitative data were recording subjects’ verbal comments and researcher observations.

resuLts And FIndIngs Analysis of the number of correct responses on the hands-on EKG exercise was done with descriptive statistics and one-way ANOVA. Descriptive data are shown in Figure 4. ANOVA results are shown in Figure 5. There was a significant difference among the four instructional treatments (F = 31.43; df = 3; p = .000) with a very large effect size (η2 = .97) and a large corrected R2 (.80). These results allowed rejection of the null hypothesis that learners receiving text-only, image-only, DVR/ATs, and traditional hands-on instruction perform no differently. To locate the sources of significant differences among the four instructional treatments, post-hoc

Figure 1. Screen shot of the text-only instrument

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Figure 2. Screen shot of the image only instrument

Figure 3. Screen shot of the DVR/ATs combined on a web page

comparisons of the treatment groups were done with Tukey HSD and homogeneous subsets; these results are shown in Figures 6 and 7. These posthoc tests indicated that text-only treatment clearly stood alone as a significantly poorer treatment than any of the other three. The image-only treatment clustered with both the DVR with AT treatment from which it was not significantly different and the hands-on treatment from which it approached significance (p = .057). The hands-on treatment clearly was the best of the four; it was significantly better than the textonly (p = .000) and DVR (p = .004) treatments

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and approached significance with the image-only treatment (p = .057).

dIscussIon Based on the findings from the study, the results show that DVR/ATs performed poorly. The conceptual framework that guided the study lists cognitive load, wayfinding and orientation, and a procedural type design would be factors in this study. The study also produced outcomes that may need to be addressed in future research in this area.

Effects of Assistive Technologies Combined with Desktop Virtual Reality in Instructional Procedures (2)

Figure 4. Descriptive data for EKG hands-on exercise

Figure 5. One-way ANOVA data for EKG hands-on exercise score (# of correct responses)

Figure 6. Post-hoc comparisons among treatment groups (Tukey HSD) Dependent Variable: Score (# of correct responses) on Hands-on Exercise Tukey HSD

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Figure 7. Post-hoc comparisons among treatment groups (homogeneous subsets) Score (# of correct responses) on hands on exercise homogeneous subsets

H1: Learner outcomes from DVR/ATs instructional procedure design will show no significant difference to traditional hands-on instructional design learner outcomes.

H2: Learner outcomes from DVR/ATs instructional procedure design will show no significant difference to text-only instructional design learner outcomes.

As shown in Figure 5, individuals’ performance scores for DVR/ATs were much less than those receiving hands-on instructional design thus, a rejection of the null hypothesis that learners receiving DVR/ATs perform no differently. Taking into consideration the standard deviation, the differences were still below that of the hands-on instruction. Through observation of the subjects possible reasons for poor performance could be attributed to cognitive load and the lack of a procedural design element. One subject noted during the interview process that they did not know what to do. “It was frustrating, when I opened the web page there were no step-by-step instructions.” The practical nursing students are trained through proceduralized hands-on instruction as opposed to web-driven delivery methods. Other themes worth noting from the interviews were: “It was confusing”, “There was too much going on”, and “I did not know how to operate the DVR/ATs.”

Figure 7 shows there was significance at the .05 level that the individuals using DVR/ATs procedure out performed individual’s scores using the text-only treatment thus, a rejection of the alternate hypothesis that there was a difference between the two treatments. Subjects given the text-based treatment reported being frustrated during the procedure. They responded during the interview similar to those that were administered the DVR/ATs that they did not know what to do. Although the text explained how to hook up the EKG that actual placement of the leads was virtually impossible to duplicate. One participant completely quit because they felt inadequate.

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H3: Learner outcomes from DVR/ATs instructional procedure design will show no significant difference to image only instructional design learner outcomes? Although the DVR/ATs outperformed the text-only treatment, results showed that the image

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only treatment out-performed the DVR/ATs thus, a rejection of the null hypothesis that learners receiving DVR/ATs perform no differently. This was result was surprising. Although the subjects were only subjected to an image only procedure, they scored significantly better than those using the DVR/ATs. The subjects reported difficulty maneuvering using the image only treatment. They also felt lost and did not know what to do once they engaged in the procedure.

FurtHer reseArcH dIrectIons To improve learner engagement and performance with DVR, it is recommended to introduce a more detailed and comprehensive training program for teaching navigation in a virtual environment and to establish a clear set of learning objectives to ensure proceduralisation and increase confidence level using the tools associated with DVR. It is also recommended if DVR/ATs treatment is used as an instructional procedure in virtual environments, the learners should be given a mapping system to overcome orientation and wayfinding obstacles. Desktop virtual reality has shown strong potential for instruction in technical environments, with its ability to help learners’ master complex and even dangerous environments. However, this study indicates that the virtual reality (VR) medium requires careful instructional design and implementation if its potential is to be realized. Employers seeking to engage in development or adoption of DVR/ATs learning environments should look for instructional development personnel who have current knowledge and skills in designing and evaluating such environments. Considering the cognitive load, wayfinding, and proceduralisation theory, if properly constructed, the instructional procedures can assist HR personnel with training, instruction, and skill development in many areas within a variety of businesses, industries, and corporate environments. Employers that are required to develop

instructional procedures for those with disabilities can use DVR/ATs devices to immerse individuals in safe realistic environments or working with devices that are not readily available.

concLusIon Desktop virtual reality has shown promise and instructional benefits in previous studies. Based on these studies, DVR might have been expected in this study to be a viable substitution for handson training by showing no difference in learning performance. However, in this study not only did the DVR show significantly poorer results than hands-on training, but individuals with VR treatment did not even out perform individuals receiving the image-only treatment. Using follow-up qualitative interviews with subjects and researcher observations, it was seen that individuals assigned the DVR/ATs treatment ignored the VR and chose to revert back to more familiar and comfortable learning strategies by engaging the audio and closed caption areas of the treatment scenes. Students would not engage the VR area of the web page, and it was conclusive by observation and interview that despite receiving pre-task training in using VR, the students were confused and not comfortable using the QTVR movie within the web page. This could be interpreted as a cognitive overload problem for VR based on the cognitive load theory of Sweller. Students may have been overloaded by the VR and unable to proceduralize. Thus they did not engage with the DVR but reverted to the accompanying ATs in the form of audio and closed captioning which were more familiar and comfortable for these particular subjects. Another reason for the lack of success of the VR in this study could have been issues in orienting and wayfinding. Those who engaged in the QTVR found in the image-only and DVR/ATs treatments appeared to be lost, disoriented, and showed signs of apprehension due to unfamiliar setting and environment.

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Effects of Assistive Technologies Combined with Desktop Virtual Reality in Instructional Procedures (2)

Waller, Hunt, and Knapp (1998) asserted that orientation and wayfinding must be determined either by egocentric or geocentric mapping before engagement with virtual environments becomes a viable and familiar setting to engage. According to Artez and Wickens (1992), egocentric mapping orients an electronic map in the forward up view. Similar to a kiosk, a symbol such as an ‘X’ or ‘+’ places a user in the map, the user can orient themselves based on the symbol marking “You are here.” Geocentric mapping orients the map “north-up” with no reference to the location of the user. The treatments of this study did not appear to achieve this function. The qualitative interviews and observations also concluded that the poor outcomes of the text-only and DVR ATs treatments could be directly related to lack of proceduarlisation knowledge. Subjects verbally stated their lack of understanding of the procedure while engaged with the instructional procedure, which validated lack of understanding of the process.

reFerences Aretz, A. J., & Wickens, C. D. (1992). The mental rotation of map displays. Human Performance, 5(4), 303. Retrieved July 26, 2008, from http:// search.ebscohost.com/login.aspx?direct=true&d b=afh&AN=7310604&site=ehost-live Waller, D., Hunt, E., & Knapp, D. (1998). The transfer of spatial knowledge in virtual environment training. Presence (Cambridge, Mass.), 7(2), 129–143. doi:10.1162/105474698565631

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key terms And deFInItIons Assistive Technology (AT): Provides individuals with learning, communication, and physical access difficulties the necessary hardware and software solutions to lead more productive and independent lives. Closed Captioning: Overlaying words or symbols on a screen based on the dialogue heard from a video or television to assist individuals with auditory impairment. Cognitive Load Theory: Derived by John Sweller in 1988 that proposed optimum learning occurs in humans when the working load is kept to a minimum to best facilitate long-term memory. Desktop Virtual Reality (DVR): Refers to a computer program that creates a real or simulated imagery-based environment that is displayed through a desktop computer screen. Egocentric: The relationship of oneself to its surroundings in a mapped environment. Electrocardiography Machine (ECG or EKG): A machine used to monitor and record the electrical activity of the heart over time. Geocentric: Relationship of ones orientation based on a map pointing up in the North direction. Orientation and Wayfinding Theory: Derived by David Waller, Earl Hunt, and David Knapp in 1998 that proposed orientation in space is crucial for finding one’s way from one location to another. QuickTime Virtual Reality (QTVR): A special video file created by virtual reality software that gives users the ability to click and drag right or left, up and down by control movement through an input device. Virtual Reality (VR): A multi-imagery computer generated environment.

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Chapter 22

Response to Intervention: Assistive Technologies which can Help Teachers with Intervention Programming and Assessment Michael W. Dunn Washington State University Vancouver, USA

AbstrAct Response to intervention (RTI) is a method for classifying students with a learning disability. In collaboration with pertinent school staff, the general education teacher designs interventions for students who struggle with core academic skills such as reading, writing, and/or math; the teacher or other school personnel (e.g., paraprofessionals) then implements the interventions. If students do not improve, this data is used to substantiate the students’ classification with a learning disability. Providing individual or small-group interventions can pose a real challenge for general education teachers given the typical demands they face in managing a classroom. To help address this, assistive technology can provide a means for students to practice and develop skills as well as have ongoing data about their progress— without ongoing involvement by the teacher. Assistive technology can be an efficient component in the RTI process.

IntroductIon Assistive technologies represent a means to Help Promote students’ Learning Teachers and students can benefit from a variety of tools to help promote learning. Pencil grips, raised-line paper to help students produce text on DOI: 10.4018/978-1-61520-817-3.ch022

the written page, and computer software to offer children practice with academic skills, all represent potentially beneficial means to promote learning— especially those who struggle with reading, writing, and/or math (Polloway, Patton, & Serna, 2005). The practice of providing students with assistive technology (AT) tools is now specified in legislation (Individuals with Disabilities Education Act, 2004), which defines AT as “any item, piece of equipment or product system, whether acquired commercially off the shelf, modified or customized, that is used

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to increase, maintain, or improve the functional capabilities of children with disabilities.” If the school team states that a student with characteristics of having a disability would benefit from AT, the school is required by law to provide it at no charge to the family.

bAckground What is a Learning disability? The concept of a student having a learning disability is based on the principle of a child demonstrating unexpected under-achievement—when a student demonstrates an ability to converse with others and have appropriate social skills, but a certain area of academics (i.e., reading, writing, and/or math) provokes great difficulty for the student (Pennington, Peterson, & McGrath, 2009). The underlying rationale stems from difficulties with both cognition (i.e., a potential for learning) and academics (i.e., demonstrating academic ability). A student with a learning disability can demonstrate a disorder of psychological processes. In other words, a student would not process or interact with learning as other normally-achieving students would. For example, early-elementary children may not experiment with language such as making up rhyming words to create comical phrases (e.g., “Jillian Billian went to the millian to see her dillian”). Students with learning disabilities may also experience difficulties with expressive (i.e., speaking and writing) as well as receptive (i.e., listening and reading) language. Difficulties with working memory and phonemic-awareness skills could render retaining and understanding language a challenge. They may have problems decoding a word on a page, retaining the information they just heard, or storing information in the correct place within their long-term memory. Malfunctions of language and learning processes

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can make understanding and applying information difficult. In certain cases, classifying a student with a learning disability may not be appropriate. School teams may not identify children with a learning disability if their difficulties with academics can be attributed to another disability such as a hearing impairment, visual impairment, or mental retardation. It would be likely that these students would have difficulties with reading, writing, or math and adding the title of “learning disability” would not change this. To prevent reading, writing, and math needs from being neglected for a non-classified student with a learning disability, goals and objectives for these academic areas may be addressed in the Individual Education Plan with another disability classification such as hearing impairment, visual impairment, or mental retardation. Having conceptually defined a learning disability as that of unexpected under-achievement, students with a learning disability need to demonstrate an ability-achievement discrepancy. Traditionally, schools have used the “wait to fail” model of learning disabilities classification. Meaning, students typically are offered the opportunity to learn to read, write, and do math and if they finish two grade levels behind by the end of third grade, special-education personnel would administer tests of academic ability and intellectual potential (i.e., an IQ test). Students who attain a discrepancy of 15 points or more between the overall scores of both tests qualify for identification with a learning disability. However, the use of IQ tests as the prime determinant for classifying students with a learning disability is a very controversial practice (Gresham, 2002).

rationale for an Alternative model for Learning disability classification As early as the 1920s, learning disability researchers (e.g., Orton, 1925) had theorized that

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IQ was not consistently reflective of a student’s actual intellectual capacity. This view is shared by many modern-day reading researchers (Fletcher, Francis, Rourke, Shaywitz, & Shaywitz, 1992; Jiménez-Glez & Rodrigo-Lopez, 1994; Stanovich & Siegel, 1994; Tal & Siegel, 1996; Toth & Siegel, 1994). Although intelligence is considered to be a measure of a person’s learning potential by asking questions relating to logical reasoning, problem-solving, and critical thinking, IQ tests actually measure factual knowledge, definitions, and fine-motor coordination (Siegel, 1999). Typical questions on an IQ test include: word definitions, geography, and history, doing puzzles to assess fine-motor coordination, memory tasks where a student is to memorize a series of numbers for later recall, and doing math calculations mentally (without the use of paper). Problem-solving tasks such as strategizing through a math word problem or demonstrating an ability to complete a multistep task are not included. In some subtests, extra points are awarded for speed. A student with a slow, thorough style would not achieve as high a score as someone who is more expeditious. Therefore, intelligence tests are more a measure of what a student has already learned rather than what the student can learn in the future. It is a paradox that a student with characteristics of a learning disability who has struggled with literacy skills would be administered an intelligence test, given that the test’s questions include tasks directly related to learning to read such as memory and definitions of words (Siegel, 1999). Use of IQ tests also provokes issues of systemic overrepresentation of students of low socioeconomic status (SES) (Blair & Scott, 2002; Bradley, 1993; Bradley, Caldwell, Rock, Barnard, Gray, Hammond, Mitchell, Gottfried, Siegel, & Johnson, 1989; Molfese, DiLalla, & Lovelace, 1995; Schaimberg & Lee, 1991), Native Americans (Reschly, 2002), and Blacks (Lawson, Humphrey, Wood-Garnett, Fearn, Welch, GreeneBryant, & Avoké, 2002). IQ tests are premised on students’ having foundational language skills as

demonstrated by the middle-class, White majority. Some parents or guardians may not have the money to offer their children the opportunity to experience visits to the local museum, family vacations, community sports and clubs, or may not even be able to read and model literate practices to their children at home. These children become viewed as not being in sync with the expectations of school classroom practices. The students are later referred for special education services for which assessments (i.e., IQ tests) are administered. These tests are also based on the students having learned certain background knowledge deemed as “required” for an ability of learning to exist. By not having the “acceptable” language skills, these students become viewed as being at risk. Furthermore, IQ tests can be poor predictors of those students who would benefit from remediation (Van der Wissel, & Zegers, 1985). With the many issues with using IQ tests as the prime measure for classifying students with a learning disability, an alternative means was needed. Educators (Gresham, 2002) have advocated that a student’s assessments of progress with an intensive intervention aimed to address the area(s) of concern should replace the role of IQ in learning disability assessment. This intervention and assessment process is commonly referred to as response to intervention or RTI.

mAIn Focus oF tHe cHAPter response to Intervention as a means to define students with a Learning disability Response to intervention’s standard intervention and assessment process includes a three-tier progression of programming. As RTI is not a copyrighted program, districts have the freedom to design their own model. Some districts choose to have more than three tiers, but this can complicate the model’s components and process; Fuchs and

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Figure 1. Response to intervention logic model

Fuchs (2007) recommended having only three tiers to keep the model simple and clear for school staff (see Figure 1). In Tier 1, often labeled as RTI’s primary prevention level, students receive research/evidencebased instruction in the regular classroom. While defining what instruction should be considered as research/evidence-based has been the subject of long debate (Dewey, 1938; Goodman, 1967; Skinner, 1974; Vygotsky, 1987), researchers have suggested various strategies and curricular programs to help address the needs of students who struggle with reading, writing, and/or math. Educators (e.g., Graham & Harris, 2005; Henry & Redding, 2002; Wendling & Mather, 2009) have suggested many types of accommodation and modification strategies such as practicing the names and sounds of letters, reviewing the spelling of words, and word study so as to decipher the inferences of a math word problem. Peer-assisted learning strategies (PALS; Sáenz, Fuchs, & Fuchs, 2005), where a typically-achieving student is paired with a student who needs extra help addresses the needs of the student struggling with academic skills.

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To provide school staff with data indicating how students are performing with classroom instruction, children complete short assessments in reading, writing, and math (referred to as universal screenings) in September, January, and April. As RTI materials continue to develop, educators have suggested published and non-published materials for this purpose. In lieu of the format used in standardized tests, RTI employs assessments that reflect typical classroom tasks in reading, writing, and math; this assessment format is referred to as curriculum-based measurement (Deno, 2003). The University of Oregon has produced the Dynamic Indicators of Basic Early Literacy Skills (DIBELS) assessments for reading. A student would read a short 100-word passage which poses a small level of challenge. The assessment’s score would consist of the number of words that the student reads correctly in the first minute or the number of words the student used in retelling the story. Curriculum-based assessments for writing could have all students in a class write a short story based on a simple cartoon picture; the students’ scores could be the number of words spelled

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correctly or the quality of the students’ writing based on a 1-6 scale of writing proficiency (e.g., 6+1 Traits of Writing; http://www.thetraits.org/ index.php). For math, the teacher could give all of the students in a classroom a one-page list of math facts to compute (e.g., 4+7=) within one minute. For students who do not demonstrate good progress with general education classroom instruction, more intensive (i.e., smaller groups of children or more time for the student to work on improving a given skill area) programming in RTI’s second tier would be needed. In Tier 2, often labeled as RTI’s secondary prevention level, students receive intensive programming for their given areas of difficulty (e.g., reading, writing, and/or math) in one of various intervention models: standard-protocol approach, problem-solving approach, or a combination of the two. In a standard-protocol intervention approach, student groups are based on the children’s similar area(s) of need which substantiates their doing the same activities (Vellutino, Scanlon, Sipay, Small, Pratt, Chen, & Denckla, 1996). In a problem-solving intervention model, each student receives programming that is pertinent to that specific child’s area(s) of difficulty. The teacher, in collaboration with pertinent school staff, defines the issue(s) of difficulty for the student. An intervention plan is developed and implemented. After the end of the intervention timeline (e.g., up to 25 sessions, 20-50 minutes each), the student’s progress is reviewed. If the student made sufficient progress (e.g., improved to at least the bottom of average range of students in the general education classroom), the student would return to Tier 1 (i.e., general education classroom programming). If the student did not make progress, the intervention could be reconfigured and offered as many times as deemed appropriate by school staff. Reading Recovery (Clay, 1993), a first-grade reading and writing intervention program, would be one problem-solving intervention example.

Students participate in the program over 12-20 weeks for 30 minutes per day with one certified teacher trained in the Reading Recovery intervention strategies. In lieu of doing worksheets, students develop their decoding and comprehension skills by reading authentic children’s books. For words that pose a challenge, the Reading Recovery teacher develops mini lessons based on each child’s needs. Students also practice writing skills by composing phrases about the books that they read. If a student does not make good progress during the first 12-20 weeks, additional intervention sessions may be provided to help address the area(s) of difficulty. Reading Recovery has been the subject of extensive study; the U.S. Department of Education’s review of the program’s research literature concluded with their listing Reading Recovery as a research/evidence-based program on their What Works Clearinghouse website (http://ies.ed.gov/ncee/wwc/). For students who persist in demonstrating difficulties with reading, writing, and/or math after Tier 2, they may receive even more intensive programming in a third tier of intervention. Tier 3, often labeled as RTI’s tertiary prevention level, represents the most intensive format of instruction, but what type of instruction this tier should entail is the subject of debate (Haager, Klingner, & Vaughn, 2007; Jimerson, Burns, & VanDerHeyden, 2007). For example, Tier 3 could offer children a relatively more intensive academic-skills intervention than that offered in Tier 2, represent the assessment phase where school staff have the student complete diagnostic assessments so as to help clarify whether special education classification is warranted, or provide an intervention phase where students work to improve cognitive skills such as attentional and memory skills—often the underlying reasons for children’s academic difficulties. For this reason, Fuchs and Kearns (2008) contended that educators should not completely discard the use of IQ assessments. While using IQ scores as the prime means to classify students with a learning disability is not

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desirable, subtest measures such as rapid automatic naming of letters and numbers offer educators and parents insight into a student’s proficiency with memory skills. Defining such an area of weakness could help focus school resources on what could help the student improve and move back to Tier 1 general education classroom programming.

Issues, controversIes, And ProbLems With the demands on teachers’ time, How can they manage Intervention Programming? While RTI aims to discontinue undesirable practices, such as waiting until the end of third grade to refer students for possible learning disabilities classification (i.e., the wait-to-fail model) as well as primarily using IQ tests given their systemic biases, RTI also poses challenges (Fuchs, Mock, Morgan, & Young, 2003). The decision to make the shift from the wait-to-fail model to RTI is the first step for schools. Systemic institutional change can be difficult, and this is true for schools and teachers given the budgetary challenges that governments face (Gerber, 2005). Not only do educators need the opportunity to learn about the conceptual reasons as to why RTI is beneficial, they need to have the opportunity to receive professional development about how the model can work in their school (Fuchs et al., 2003). Teachers and administrators need to address whether their Tier 1 general education classroom programming is adequate. Meaning, does it represent what other teachers have in terms of materials as well as classroom practices and strategies to address students’ needs? If not, then the school needs to attain the needed resources and provide professional development so as to address this gap(s). What timeline would be appropriate for students’ receiving intervention programming? Who will monitor the provision of the interven-

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tion; will it actually be done? When should parents be consulted about their child’s participation in an intervention? Should parents have the option of requesting that their child have intervention programming? Once school staffs have completed intervention programming with a student, what cut-off would define whether the student would qualify for special education classification? Probably the most central question about intervention programming is who will provide it? How can teachers manage to provide intervention programming to students while all of the other routines and curriculum content/practices are needed for students in general education classrooms? When the Individuals with Disabilities Education Improvement Act (2004) provided states and districts with the option of using RTI, there was no provision of funding for teachers to learn about the model, attain curriculum resources to use in intervention programming, nor hire additional staff to manage the provision of interventions. These issues are compounded by the decision of some U.S. states, such as Delaware, to make RTI mandatory (Brownstein, 2007); teachers’ concern about how to manage the RTI model has even prompted it to be an issue in the collective bargaining process with districts. Given the demands on the time of school staff, one means to help provide intervention programming to students could be with skills-building software on computers.

soLutIons And recommendAtIons tiers 2 and 3 Intervention Programming with Assistive technology software The development of computer software for educational purposes has provided teachers with an efficient means to have students practice academic skills with minimal need of the teacher’s direction.

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For reading skills, Read Naturally (2009) and SuccessMaker Enterprise (2009) offer students a means to develop their reading decoding, fluency, and comprehension skills. These programs have the students take an initial pre-test to determine their baseline level of performance, and then complete sequential exercises to help them improve. For math, SuccessMaker Enterprise (2009) has activities that address computation and problemsolving skills. Writing is conceivably the most challenging of the three core academic skills as students need to have mastery in reading, idea generation, spelling, and an awareness of how texts are constructed (e.g., story structure: that a narrative text has a beginning [i.e., introduction], middle [i.e., main event], and an end [i.e., conclusion]) (Berninger & Winn, 2006), to name some examples, in order to be a proficient writer. While some computer programs can help address the mechanical aspects of writing (e.g., spelling), no known software exists that can help a student simultaneously improve in the various aspects of writing. Dialogue and collaboration with a more proficient writer (e.g., a student or the teacher) is needed. To help manage the more mechanical aspects of writing (e.g., spelling and editing of phrases), software such as CoWriter:SOLO (Don Johnson Developmental Equipment, Inc., 1992) or Neo2 mini-keyboards (Renaissance Learning, 2009), which have CoWriter:SOLO pre-installed, can provide students with a means to develop these skills. Neo2 offers teachers the option of creating short quizzes which students can do on this keyboard so as to have immediate feedback about students’ progress. Booker (1995) completed a six-week comparative study with 10 students aged 7-10 years. Students’ use of CoWriter:SOLO provided for improved spelling, mechanics, and reading decoding as well as students having reduced apprehension about writing. Microsoft Word (2007) does not offer a quiz feature similar to the Neo2, but some data can be attained for students’ writing such as: number of words writ-

ten, characters, paragraphs, and length of editing session. For cognitive-skills instruction as suggested for Tier 3, Challenging our Minds (http://www. challenging-our-minds.com/) offers students a means to improve skills such as attention and memory. Bracy, Oakes, Cooper, Watkins, Watkins, Brown, and Jewell (1999) found in their study of seventh- and eighth-grade students (N=80) that the experimental group using the software program significantly increased their intellectual functioning. For the software just described, the computer records students’ scores as they do activities; this data can be used by the teacher and school teams as curriculum-based measurement (CBM) data for defining students’ intervention progress. Assistive technology such as computer software could substantially help alleviate the demands on teachers to do all aspects of intervention programming. Depending on the academic areas of needs, the teacher may need to provide direct instruction such as in the area of writing in order for the integrity of the intervention to be maintained. A student who does not know how to begin planning a story would need modeling and multiple examples from the teacher so as to develop a sense of self-proficiency with this skill (Graham & Harris, 2005).

Future reseArcH And dIrectIons the need to develop rtI’s research base as well as What Interventions represent evidence-based Practice What represents research/evidence-based practice in education has been the subject of long debate (Odom, Brantlinger, Gersten, Horner, Thompson, & Harris, 2005). In 1977, the U.S. Department of Education made the decision to imply IQ as being the determining factor for classifying students with

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a learning disability (Fuchs et al., 2003). Federal policy did not require schools to use IQ/achievement discrepancy; it was the suggested method to use based on research at that time (e.g., Rutter & Yule, 1975). Subsequent research (e.g., Blair & Scott, 2002; Siegel, 1999) has made the opposite conclusion. Educators have now embraced RTI as the desired alternative without having a research base to substantiate RTI’s implementation. Given that the heart of RTI is the provision of intervention programming and having ongoing curriculum-based assessments of students’ progress, educators should implement research/ evidence-based programming, define interventions for students who need them, and then review if their programming proves effective. Collaborating with other schools/districts in this process would help generate large-scale data sets for analysis as well as promote professional dialogue about what format/components RTI should have. Since RTI is not a published program requiring schools to implement the model in one specific way, educators have the freedom to define their own model and components based on all available research and curriculum information.

concLusIon the challenge for teachers as the Providers of tiered Interventions for students Who struggle with Academics Teaching can be a challenging profession. Having twenty or more students in a class with various levels of ability and needs requires teachers to accommodate and modify so as to help each student improve. Given the stresses of managing curriculum content and behavior, RTI’s expectation of teachers providing intensive intervention programming makes the role of the teacher that much more challenging. To help address this concern, AT can offer students a means with im-

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proving academic skills without always requiring the teachers’ time and attention. If loaded on a laptop, the student could practice the skills both at home and at school in any convenient location. The potential for students’ improved skills warrants that teachers seriously consider AT as a component for intervention programming.

reFerences Americans with Disabilities Act of 1990. (2004). Pub. L. No. 101-336, 42 U.S.C. Sec. 12101 et seq. Berninger, V., & Winn, W. (2006). Implications of advancements in brain research and technology for writing development, writing instruction, and educational evolution. In MacArthur, C., Graham, S., & Fitzgerald, J. (Eds.), The handbook of writing research (pp. 96–114). New York: Guilford. Blair, C., & Scott, K. (2002). Proportion of LD placements associated with low socioeconomic status: Evidence for a gradient. The Journal of Special Education, 36(1), 14–22. doi:10.1177/00 224669020360010201 Booker, B. W. (1995). An evaluation of the [CoWriter:SOLO] Program & its implementation. The University of Western Ontario, London, Ontario. A directed research project submitted in partial fulfillment of the requirements for the degree of Master of Education, Faculty of Graduate Studies, University of Western Ontario, London, Ontario, Canada. Retrieved July 22, 2009, from http://www.donjohnston.com/pdf/cowriter/CoWriter_Research.pdf Bracy, O. L., Oakes, A. L., Cooper, R. S., Watkins, D., Watkins, M., Brown, D. E., & Jewell, C. (1999). The effects of cognitive rehabilitation therapy techniques for enhancing the cognitive/intellectual functioning of seventh and eighth grade children. Cognitive Technology, 4(1), 19-27. Retrieved February 7, 2009, from http://www.challengingour-minds.com/tour/CognitiveTechnology.pdf

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Bradley, R. (1993). Children’s home environments, health, behavior, and intervention efforts: A review using the HOME inventory as a marker measure. Genetic, Social, and General Psychology Monographs, 119, 439–490. Bradley, R., Caldwell, B., Rock, S., Barnard, K., Gray, C., & Hammond, M. (1989). Home environment and cognitive development in the first 3 years of life: A collaborative study involving six sites and three ethnic groups in North America. Developmental Psychology, 25, 217–235. doi:10.1037/0012-1649.25.2.217 Brownstein, A. (2007). ED touts IDEA set-aside as funding stream for Title I. Retrieved July 24, 2009, from http://www.thompson.com/public/ newsbrief.jsp?id=1626&cat=EDUCATION Clay, M. (1993). Reading Recovery: A guidebook for teachers in training. Portsmouth, NH: Heinemann. Deno, S. L. (2003). Developments in curriculumbased measurement. The Journal of Special Education, 37(3), 184–192. doi:10.1177/00224 669030370030801 Dewey, J. (1938). Experience in education. New York: Collier Books. Don Johnston Developmental Equipment, Inc. (1992). CoWriter:SOLO [Writing-assistance software]. Wauconda, IL: Author. Fletcher, J., Francis, D., Rourke, B., Shaywitz, S., & Shaywitz, B. (1992). The validity of discrepancy-based definitions of reading disabilities. Journal of Learning Disabilities, 25, 555–561. doi:10.1177/002221949202500903 Fuchs, D., & Kearns, D. M. (2008, February 29). Cognitive assessment in an RTI framework. Presentation at the Learning Disabilities Association of America Conference, Chicago, Illinois.

Fuchs, D., Mock, D., Morgan, P., & Young, C. (2003). Responsiveness-to-instruction: Definitions, evidence, and implications for learning disabilities construct. Learning Disabilities Research & Practice, 18(3), 157–171. doi:10.1111/15405826.00072 Fuchs, L. S., & Fuchs, D. (2007). A model for implementing responsiveness to intervention. Teaching Exceptional Children, 39(5), 14–20. Gerber, M. M. (2005). Teachers are still the test: Limitations of response to instruction strategies for identifying children with learning disabilities. Journal of Learning Disabilities, 38(6), 516–524. doi:10.1177/00222194050380060701 Goodman, K. (1967). Reading: A psychologlinguistic guessing game. The Journal of the Reading Specialist, 4, 126–135. Graham, S., & Harris, K. R. (2005). Writing better: Effective strategies for teaching students with learning difficulties. Baltimore: Paul H. Brookes Publishing Co. Gresham, F. (2002). Responsiveness to intervention: An alternative approach to the identification of learning disabilities. In Bradley, R., Danielson, L., & Hallahan, D. (Eds.), Identification of learning disabilities: Response to treatment (pp. 467–519). Mahwah, NJ: Erlbaum. Haager, D., Klingner, J., & Vaughn, S. (2007). Evidence-based practices for response to intervention. Baltimore, MD: Paul H. Brookes Publishing Co. Henry, M. K., & Redding, N. C. (2002). Patterns for success in reading and spelling: A multisensory approach to teaching phonics and word analysis. Austin, TX: Pro-Ed. Individuals with Disabilities Education Improvement Act of 2004. (2004). Pub. L. No. 108-446, 118 Stat. 2647

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Jiménez-Glez, J. E., & Rodrigo-López, M. R. (1994). Is it true that differences in reading performance between students with and without ID cannot be explained by IQ? Journal of Learning Disabilities, 27, 155–163. doi:10.1177/002221949402700304 Jimerson, S. R., Burns, M. K., & Van Der Heyden, A. M. (2007). Handbook of response to intervention: The science and practice of assessment and intervention. New York: Springer. Lawson, Q., Humphrey, L., Wood-Garnett, S., Fearn, K., Welch, C., Greene-Bryant, B., & Avoké, S. (2002). Addressing over-representation of African-American students in special education. Washington, DC: Council for Exceptional Children. Molfese, V., DiLalla, L., & Lovelace, L. (1995). Prenatal, home environment, and infant measures as successful predictors of preschool cognitive and verbal abilities. International Journal of Behavioral Development, 18, 1–19. Odom, S. L., Brantlinger, E., Gersten, R., Horner, R. H., Thompson, B., & Harris, K. R. (2005). Research in special education: Scientific methods and evidence-based practices. Exceptional Children, 71(2), 137–148. Orton, S. T.(1925). ‘Word-blindness’ in school children. Archives of Neurology and Psychiatry, 14, 285–516. Pennington, B. F., Peterson, R. L., & McGrath, L. M. (2009). Dyslexia. In Pennington, B. F. (Ed.), Diagnosing learning disorders: A neuropsychological framework (pp. 45–82). New York: The Guilford Press. Polloway, E. A., Patton, J. R., & Serna, L. (2005). Strategies for teaching learners with special needs. Upper Saddle River, NJ: Pearson. Read Naturally. (2009). Retrieved July 24, 2009, from http://www.readnaturally.com/products/ improvereading.htm

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Renaissance Learning. (2009). NEO Alphasmarts. Wisconsin Rapids, WI: Renaissance Learning. Reschly, D. (2002, February 22). Disproportional representation in special education. Presentation to the President’s Commission on Excellence in Special Education. Rutter, M., & Yule, W. (1975). The concept of specific reading retardation. Journal of Child Psychology and Psychiatry, and Allied Disciplines, 16, 181–197. doi:10.1111/j.1469-7610.1975. tb01269.x Sáenz, L. M., Fuchs, L. S., & Fuchs, D. (2005). Peer-Assisted Learning Strategies for English language learners with learning disabilities. Exceptional Children, 71(3), 231–247. Schaimberg, L., & Lee, C. (1991, April). Predictors of verbal intelligence and behavioral problems among 4-year-old children. Paper presented at the biennial meeting of the Society for Research in Child Development, Seattle, WA. Siegel, L. (1999). Issues in the definition and diagnosis of learning disabilities: A perspective on Guckenberger v. Boston University. Journal of Learning Disabilities, 32(4), 304–319. doi:10.1177/002221949903200405 Siegel, L. S. (1998). The discrepancy formula: Its use and abuse. In Shapiro, B., Accardo, P., & Capute, A. (Eds.), Specific reading disability: A view of the spectrum (pp. 123–135). Timonium, MD: York Press. Skinner, B. F. (1974). About behaviorism. New York: Random House, Inc. Stanovich, K. E., & Siegel, L. S. (1994). The phenotypic performance profile of readingdisabled children: A regression-based test of the phonological-core variable-difference model. Journal of Educational Psychology, 86, 24–53. doi:10.1037/0022-0663.86.1.24

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SuccessMaker Enterprise. (n.d.). Retrieved July 24, 2009, from http://www.pearsonschool.com/ index.cfm?locator=PSZ16c&PMDBSUBCATE GORYID=&PMDBSITEID=2781&PMDBSUB SOLUTIONID=&PMDBSOLUTIONID=6724& PMDBSUBJECTAREAID=&PMDBCATEGOR YID=1662&PMDbProgramId=32505 Tal, N. F., & Siegel, L. S. (1996). Pseudoword reading errors of poor, dyslexic and normally achieving readers on multisyllable pseudowords. Applied Psycholinguistics, 17, 215–232. doi:10.1017/ S0142716400007645 Toth, G., & Siegel, L. S. (1994). A critical evaluation of the IQ-achievement discrepancy based definition of dyslexia. In L. S. S. K. P. van den Bos, D. J., & D. L. S. Bakker (Eds.), Current directions in Dyslexia research (pp. 45–70). Lisse, The Netherlands: Swets & Zeitlinger. U.S. Office of Education. (1977, December 29). Assistance to states for education of handicapped children: Procedures for evaluating specific learning disabilities. [Washington, DC: U.S. Government Printing Office.]. Federal Register, 42(250), 65082–65085. Van der Wissel, A., & Zegers, F. E. (1985). Reading retardation revisited. The British Journal of Developmental Psychology, 3, 3–9. Vellutino, F., Scanlon, D., Sipay, E., Small, S., Pratt, S., Chen, R., & Denckla, M. B. (1996). Cognitive profiles of difficult-to-remediate and readily remediated poor readers: Early intervention as a vehicle for distinguishing between cognitive and experiential deficits as basic causes of specific reading disability. Journal of Educational Psychology, 88(4), 601–638. doi:10.1037/00220663.88.4.601 Vygotsky, L. (1987). Thinking and speech. In R. R. A. Carton (Ed.), Collected works of l. S. Vygotsky: Vol. 1: Problems of general psychology (pp. 39–285). New York: Plenum.

Wendling, B. J., & Mather, N. (2009). Essentials of evidence-based academic interventions (Kaufman, A. S., & Kaufman, N. L., Eds.). Hoboken, NJ: John Wiley & Sons. (2007). Word [computer software]. Redmond, WA: Microsoft Corporation.

AddItIonAL reAdIng Hosp, M. K., Hosp, J. L., & Howell, K. W. (2007). The ABCs of CBM: A practical guide to curriculum-based measurement. New York: The Guilford Press. MacArthur, C. A., Graham, S., & Fitzgerald, J. (Eds.), Handbook of writing instruction. New York: The Guilford Press. McCarney, S. B., Wunderlich, K. C., & House, S. M. (Eds.). (2006). Pre-referral intervention manual. Columbia, MO: Hawthorne Educational Services. Swanson, H., Harris, K., & Graham, S. (Eds.), Handbook of learning disabilities. New York: The Guilford Press.

key terms And deFInItIons Curriculum-Based Measurement (CBM): An assessment process which uses classroom materials to measure students progress over time (e.g., having a student read a slightly-challenging text and noting the number of words read correctly on a graph; this data would illustrate how the student has progressed over time). Intervention: A set of skills-building activities which the student completes during a portion of the school day (e.g., 20-50 minutes) to help improve academic abilities such as reading, writing, or math. IQ: Intelligence quotient. An assessment of a person’s potential/aptitude for learning. IQ tests

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have verbal (e.g., reading) and performance (e.g., block assembly) components. The overall score of these components represents the full-scale IQ score which has traditionally been compared with academic achievement to define a student’s IQ/achievement discrepancy score and possible learning disability classification. Many jurisdictions require 15 points or more as the required discrepancy or cut-off; with only 14 points, a student would often not qualify. Problem-Solving Approach: An RTI format which has the school team create a unique set of activities and assessments to help a child improve in a given area(s) of academic need. Response to Intervention (RTI): An intervention and assessment model which uses classroom materials and activities to help children improve in an area(s) of academic difficulty.

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Standard-Protocol Approach: An RTI format which uses a defined set of activities and assessments to help a group of children improve in a given area(s) of similar academic need. If the student has not made sufficient progress by the end of the intervention timeline (e.g., 30-minute sessions over 25 days), additional sessions can be provided if the school team feels that doing this would be warranted. Tier: One of the three phases of the RTI model: Tier 1 (general education classroom instruction), Tier 2 (e.g., small-group intervention programming), and Tier 3 (even smaller group intervention programming).

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Chapter 23

Assistive Technology for Teacher Education: From Research to Curriculum Marcie M. Belfi University of Texas, USA Kristen E. Jones University of Texas, USA

AbstrAct The purpose of this chapter is to provide teacher educators with current research related to assistive technology (AT) in K-12 schools. The first two sections present findings from the literature, first related to providing AT to culturally and linguistically diverse populations within a family context, and secondly to helping students with learning disabilities use AT for writing. Implications for practice are discussed. This chapter concludes with an overview of a curriculum model for training preservice teachers to become familiar with AT across the lifespan, choose appropriate AT for their students, and be able to practically use AT in the classroom.

IntroductIon Teacher educators can instruct preservice teachers using hands-on methods and training to effectively integrate assistive technology (AT) products into the classroom for their students that have disabilities. This chapter discusses some of the methods used. The first part of this chapter is a review of literature on AT for culturally and linguistically diverse (CLD) populations of students. Augmentative and alternative communication (AAC) for students from CLD backgrounds and their families is discussed. DOI: 10.4018/978-1-61520-817-3.ch023

Teacher educators are given insight on training preservice teachers who work with CLD students that use AT. The next section deals with a review of the literature and focuses on AT for students with learning disabilities (LDs). Students with LDs often lack psychological motivation to learn to write due to previous failures in school. AT is considered by some, one method to mitigate psychological barriers for students to learn to write proficiently (Zhang, 2000). These benefits will be discussed. The last section describes the curriculum of the AT orientation program in the College of Education at the University of Texas in Austin (UT). The pro-

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gram developed at UT introduces preservice teachers to some of the AT they are likely to encounter in schools. The AT orientation program utilizes hands-on activities to ensure active participation of preservice teachers. The effectiveness of the program is determined from a survey students complete at the end of the training. This section provides an overview of how preservice teachers can be trained to use AT in the schools. To ensure that students with disabilities receive the necessary services, current legislation requires that service providers have AT competencies (Tech Act, 2004; CEC, 2003). However, research suggests that many preservice teachers are not well trained to provide services on assessment, selection, and application of AT (Bausch & Hasselbring, 2004). The need for an AT orientation program as a prerequisite for preservice teachers who work with students with disabilities is vital for the success of these students in the classroom. The selection process for appropriate AT for students is made increasingly more difficult due to the rapid development of new technology (Bausch & Hasselbring, 2004). When selecting appropriate AT for students with disabilities in the classroom, technology that teachers and administrators are already familiar with is usually much more of a deciding factor in the selection process than newer AT that may be more suitable (Bausch & Hasselbring, 2004). However, even if teachers have a full range of available technology, but do not have adequate training to know which device to select, there may be reduced benefit to the student. This chapter also details ways that colleges or universities can create a training center utilizing appropriate curriculum and up-to-date technology. The idea of the training center is to better ensure that preservice teachers enter schools with sufficient background and hands-on experience to meet the AT challenges of diverse learners.

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reseArcH I Assistive technology for culturally and Linguistically diverse Populations It is important to consider AT for teacher preparation within CLD populations. The term CLD is used to refer to individuals or populations that are non-white, of ethnic origins outside of the United States, or with limited English language. In Binger and Light’s (2006) study of demographics, it was found that 15% of preschoolers receiving AAC services were of non-white ethnicity. Because of the increasing heterogeneity of the demographics of students served in special education programs in public schools in the United States, this section addresses some of the perceptions and possible misconceptions of families from CLD backgrounds who have children with a disability receiving AT support. Because of the changing demographics of the population, today’s teacher will more likely teach in a class that is not homogeneously White. According to Utley, Delquadri, Obiakor, and Mims (2000), compounding this population statistic, only 14% of special education teachers are from CLD backgrounds, while over 32% of the students receiving special education services are from CLD backgrounds. A large component of AT is AAC. Augmentative and alternative communication assists people with more severe communication disabilities, providing them the tools to participate more fully in such daily activities as interpersonal interaction, learning, education, and personal care management. According to Bryant and Bryant (2003), an AAC system refers to an individual’s complete functional communication system that includes a communicative technique, a symbol set or system, and a communication/interaction behavior. When AAC users are from CLD backgrounds, their com-

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munication needs will also be diverse. Within the context of the entire family, and reaching beyond individual student requirements for academic and social success, the question that should also be addressed is: “What are the families’ perceptions regarding the use of AT in CLD populations?”

method Included in this synthesis are studies published in peer-reviewed journals from 1996-2006 that addressed families’ perceptions regarding the use of AT with school-age individuals within CLD populations. Only studies that examined all disability types qualifying for AT were accepted and all research designs were accepted. The studies were located using the following search procedures. A computer search of ERIC and InfoTrac was conducted to locate studies using a list of descriptors (augment* and alt* communication, AT, special education technology, immigrant, migrant, minority, multicultural education, special education or disab*, diversity, latin*, Mexican, Mexican-American, Spanish-speak*, Indian, American-Indian, Asian-American, African-American, Black). Of the articles identified through the search procedures, six abstracts were located that seemed to meet the criteria. Two of the articles were position papers. A total of four articles met the criteria of being actual studies, and were included in the literature review.

results Triangulation was used in all studies as a means of producing validity; however, different studies had differing ways of triangulation. Two of the studies described the method in detail and data collection was more rigorous resulting in a higher degree of confidence in their findings. McCord and Soto (2004) had a five-step analytical process and Parette, Brotherson, and Huer (2000). used five different levels of analysis. These two studies warranted the most confidence because of the level

of transparency and detail in the methodology. Across the four studies two participants were identified with cerebral palsy, two with quadriplegic cerebral palsy, and one with post-meningitis quadriplegia. Family members of those receiving AT were from the following ethnic backgrounds: Mexican-American, Navajo/Native American, Hispanic, Asian, and African-American. The ages of students were from seven to twenty years old. All students in three of the studies used a communication board either at home, at school, or both (Huer, Parette, & Saenz, 2001; McCord, & Soto, 2004; Stuart & Parette, 2002). Parette et al. (2000) reported aggregated findings in which students were evaluated for use of AAC devices, but did not necessarily receive the devices. Devices reported in the studies included— AlphaTalker, DeltaTalker, Dynavox, Liberator VOCA and other VOCA. Parette et al. (2000) also indicated the use of generic communication boards along with AlphaTalker, DeltaTalker, Dynavox, Liberator and VOCA. Students’ experiences on the use of the devices ranged from those receiving devices with no prior experience (Parette et al., 2000), to those with up to eight years of experience using the AAC technology (McCord & Soto, 2004). (see Figure 1) Across the four studies, the needs of the families were also considered. Parents from two studies expressed the opinion that the AAC device was not appropriate for their child’s use at home (Huer et al., 2001; McCord & Soto, 2004). Both of these studies focused exclusively on families representing Mexican-American populations. Other needs besides technology were also expressed across all ethnic populations involved in the studies, and included learning and training obstacles (Huer et al., 2001; Parette et al., 2000; Stuart & Parette, 2002). Training was an issue across cultural groups. Parette et al. (2000) reported the need for AAC device training across Native American, Hispanic, Asian, and African American populations. Specifically, help using and maintaining the augmentation device was

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Figure 1. Ethnicity, diagnosis, SES, and device type

a concern of most. Navajo family members expressed the desire to be trained not only in using the AAC equipment, but also in maintenance, so they would be able to make repairs if the equipment broke down (Stuart & Parette, 2002). Huer et al. (2001) reported a need for training in the Mexican-American population, and specifically noted that training was not available in the native language (Spanish). It was also noted that even after an initial introduction to the equipment, family members needed ongoing training to be able to add messages to communication devices. However, since the data was not disaggregated across the groups, it is unclear whether some groups struggled with learning and training issues more than others.

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Two of the four studies reported the need for communication with professionals (Huer et al., 2001; Parette et al., 2000). In both of these studies, families described feelings of awkwardness in asking questions to professionals. There was some confusion about the use of the device in the home. Also, professionals had not explained issues such as ownership of the device, liability for damage or loss, as well as programming and repair. McCord and Soto (2004) and separately Huer et al. (2001) reported families not wanting to use the device in the home since it was not programmed with messages in their native language.

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discussion

reseArcH II

This synthesis points out the need for future research to address the needs of parents, including exploration of strategies for making AAC more culturally acceptable for use in the home. One of the questions to ask for future research is, “How could AAC be introduced to families and modified to be applicable in the home?” “How would training parents in their native language and programming AAC devices with language spoken in the home increase parental acceptance and ease of use of AAC devices?” Finally, new investigations may need to be conducted to determine how recent technology has changed the outcomes of AAC devices when used by the student in the home. The concerns of family members revealed implications for current practice. Professionals need to be trained to work with families from CLD backgrounds. There are several communication issues that become more evident from the literature. First, service providers and facilitators of AT may need to foster an environment where questions are encouraged. Professionals also need to explain in more detail such issues of responsibility for the equipment, including ownership, insurance, financial issues, as well as maintenance and repair options. Finally, professionals should not just hand family members paperwork explaining these issues—there should be a translator who is bicultural (one who not only knows the language, but also has knowledge of the culture) if the AAC service provider does not have the language and cultural skills. Professionals familiar with technology may take for granted that everyone comes in with a different knowledge base. However, professionals should ask themselves questions such as: what would you need if you were this family? Would you want to carry this equipment? Would it fit in your car? If you were older and not familiar with technology, how would you understand this device?

Assistive technology for students with Learning disabilities A second area of research that is applicable to teachers and service providers is the area of LDs. Students with LDs are not initially recognized as candidates for AT (Hasselbring & Bausch, 2006). These students are often overlooked in terms of AT needs, apparently because of the distinction drawn between special education and general education, and the fact that students with LDs usually spend most of their time in the general education classroom (Hasselbring & Bausch, 2006). According to Lerner (2003), nearly 80 percent of students with disabilities are unable to read grade-level material. Students with LDs may benefit from technology such as word processors, word prediction, speech synthesizer, and speech recognition software. Word prediction software may help students who have severe spelling difficulties (MacArthur, Ferretti, Okolo, & Cavalier, 2001). Some of the barriers to the use of AT both in school and at home have to do with parental lack of knowledge as well as school funding, available classroom time, and teacher training. Parents are often uninformed of the benefits of their child using AT, and their rights to an AT evaluation (Bryant & Bryant, 1998). One of the most significant barriers to the successful integration of AT is knowledge and training. Lee and Vega (2005) reported that teacher preparation programs do not adequately prepare special education teachers or general education teachers in the use of AT devices. Furthermore, schools sometimes discourage special educators from making suggestions that will incur a financial expense to the school (Bryant & Bryant, 1998). IDEA 2004 legislation supports personnel preparation in the “innovative uses and application of technology, including universally designed tech-

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nologies, AT devices, and AT services” (“Building a Legacy: IDEA 2004”, 2004). Students with LDs face other challenges when it comes to writing proficiency. Important are issues such as motivation, lack of self-esteem, and writing difficulties. Handwriting, spelling, grammar, editing and revising are additional areas of difficulty for students with LDs (Graham & Harris, 2003). Unlike those without LDs, students with LDs have a previous history of failure with the writing process often resulting in greater anxiety. This added anxiety could add to further avoidance of nearly all types of written expression (Zhang, 2000). These students may experience feelings of low self-esteem and do not believe their writing has value to be shared with others (Zhang, 2000). Motivation is also an important factor that is well known to influence student performance, and teachers can use computers to motivate students and improve self-esteem (Woodward & Reith, 1997). Student motivation may also be enhanced by a combination of graphics, sound and video. However, graphics, sound and video use may be a distraction to some students resulting in the student spending less time writing and revising (MacArthur et al., 2001). Because many students with LDs have poor handwriting, technologies such as word processors are a good way to assist students in the writing process (Woodward & Reith, 1997). Using a word processor, some students may be better able to read rough drafts of their work with the outcome a better final composition. MacArthur et al. (2001) described several benefits for students who use word processors. One benefit is students are better able to edit neatly without having to recopy the entire document or erasing and rewriting large portions of text. This encourages students to put more effort into revisions. Another benefit is that the paper is attractive and has fewer spelling errors. Because the computer screen is easy to see for most students, and the keyboard does not discriminate handwriting types, students can

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more easily collaborate and assist each other in the composition process. In order for students to truly benefit from AT, the teacher must be able to select appropriate technology for the students as well as be able to integrate the technology into classroom instruction (Bryant & Bryant, 1998). General education teachers must learn to use AT, go to trainings, and stay up-to-date with new technology that can assist students with LDs (Hasselbring & Bausch, 2006; Lee & Vega, 2005).

method Published peer-reviewed journal articles from 1996-2006 that addressed AT and writing for students with LDs were considered for this review. Studies that did not directly deal with students and their use of AT for writing, such as studies dealing with teachers’ attitudes or school support were not included. Data was collected using computerized search engines including ERIC database and Academic OneFile. Search terms included: AT, assist* technology, learning disability, learning disab*, augment* and alt* communication, special education, and technology. Ancestry searches were also performed to locate other articles. Of the articles identified through the search procedures, seven abstracts were located that met the inclusion criteria. Two articles were previous syntheses. One was discarded because the subjects were not persons, but dealt with misspellings made by students. A total of four articles were included that met the criteria for the report. The four studies chosen examined the use of AT in writing for students with LDs.

results Across three of the studies, thirteen participants were identified with LDs as a primary diagnosis (MacArthur, 1998; MacArthur, 1999; Zhang, 2000). In one of the studies (Bahr, Nelson, &

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Figure 2. LD and AT intervention and participant characteristics

van Meter, 1996), participants were described as either having a diagnosis of LDs in writing, or having a diagnosis of a language impairment in writing and receiving services from a speech and language pathologist. However, the data from this specific study was not disaggregated. The demographics of participants were reported in three of the four studies (MacArthur, 1998; MacArthur, 1999; Bahr et al., 1996). These studies included fourteen participants who were White, two African Americans, and one Native American. All participants were between the ages of nine and thirteen. In all studies, students were free to write about whatever they wanted, and the studies used seven different software programs (see Figure 2), including MacWrite II, My Words, CoWriter, WriteOutloud, ROBO-Writer, Once Upon a Time, and FrEd Writer. The two studies conducted by Charles MacArthur included in this synthesis evaluated student journal writing. In 1998, MacArthur examined the use of My Words with Smoothtalker, which uses speech synthesis to pronounce each word as it is typed, and focused on the use of journals for dialogue between a student and a teacher. In a

1999 study, MacArthur examined student journal writing across handwriting, word processor, and word processor with speech synthesis and word prediction. Zhang (2000) examined free writing with the use of the ROBO-Writer, which is a writing program that uses speech synthesis, onscreen dictionary and writing lists. Bahr et al. (1996) compared graphics-based and text-based writing software. The overall results indicated that legibility and spelling were greatly improved by the use of word prediction and speech synthesis. Macarthur’s (1999) follow-up study compared handwritten journal entries, those used with a simple word processor, and those written using a word processor with word prediction using CoWriter and Write Outloud. In the first part of this study, no differences among conditions were found for legibility. In the second part of the study, improvements in both legibility and spelling were noted for two of the three students. Students wrote two to three times slower with word prediction than with handwriting. Two of the students were twice as fast using handwriting than with the word processor and word prediction.

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Zhang (2000) used a researcher-designed writing curriculum based on the program Robo-Writer specifically for use with the five students in the study. Students either chose their own topic for writing or were assigned a topic that was related to students’ personal experiences. The Robo-Writer software provided audio feedback that helped students notice misspelled words and sentences that did not make sense. Student behavior was an important aspect of this study. The most frequent complaints were not having a topic or not knowing what to write about, along with having no motivation to write anything. The use of preservice teachers in the study helped to facilitate students’ idea generation and provide encouragement. Of all features in this study, the most helpful was the audio feedback, which allowed students to hear their mistakes. Students had a positive attitude about the writing experience because of the professional output of their stories. Students seemed more eager to share their writing with teachers, peers, and family. One of the problems the author noted in this study was that the teacher and preservice teachers were not very familiar with technology. Consequently, there was not a continuation of use of Robo-Writer after the completion of the study. It was not mentioned whether the teachers used other technology in place of Robo-Writer following the study. Bahr et al. (1996) compared graphics-based and text-based writing software in a study that was conducted as an after school program. The purpose of this study was to compare the effects of two software-based planning tools on the storywriting skills of students with LDs. There were no significant differences in terms of writing skills between software programs. Along with the standardized writing measures, the students’ teachers were given questionnaires about students’ writing and computer use. Questions dealt with students’ time spent doing handwriting activities, creative writing, and computer usage. The two software programs used in this study were Once Upon a

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Time, which was a graphics-based writing software, and FrEdWriter, which was the text-based writing software. The students were allowed to use the two programs to write about their own topics and could write stories of any length. Between the text-based and graphics-based software there were no significant differences for the total number of words that students produced, or total percentage of different words. However, with the graphicsbased software, the participants produced a higher percentage of complex incorrect sentences. An interesting finding is that students were reluctant to revise their work, requiring more prompting from the research assistants, and preferring to start a new story than to put more effort into revisions. Some students were encouraged that they would be publishing their work, sharing it with others, and as a consequence put more effort in revising and editing their work.

discussion The findings from the four studies reported overall positive results with the use of AT in the writing process for students with LDs. In 1998, MacArthur found that legibility and spelling were greatly improved by the use of word prediction and speech synthesis. Even though in the first part of his later study (1999), there were no differences among conditions (handwriting, the use of a word processor, and the use of a word processor with word prediction and speech synthesis) on spelling and overall readability of the text, in the second part of his study he found improvements in both legibility and spelling for two of the three participants. The use of technology in Zhang’s (2000) study, along with prompting from research assistants encouraged some of the students to put more effort into revision and editing. This is not surprising, as MacArthur et al. (2001) stated that one of the benefits of using a word processor was that students put more effort into revisions and editing because of the attractiveness, neatness, and legibility of the text. The students benefited

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the most from the audio feedback feature of the software included in this study. The author noted that while students did benefit from the use of technology, the classroom teacher and preservice teachers were not familiar with the program and there was not a continuation of use of Robo-Writer after the completion of the study. Bahr et al. (1996) found that with the use of the graphics-based writing software, many of the students spent a lot of time creating and arranging their graphic scenes. This did take away some of the time spent on actually writing their story. This conform to the findings of MacArthur et al. (2001), that although the graphics may enhance students’ motivation, these may be distracting and students may spend less time writing and revising. Students with LDs often lack psychological motivation due to previous failures, and technology is one way that the psychological barriers can be overcome (Zhang, 2000). Technology can propel students in writing who are otherwise unwilling and hesitant. It can be a spur to help motivate hesitant, struggling students to write (Bahr et al., 1996). However, Bahr et al. cautioned teachers to not assume that students will learn best or produce high quality work just because they are interested in and motivated by a particular software program.

ImPLIcAtIons This review yields several implications for general and special education teachers. These studies indicate that word processing software with and without graphics can serve to motivate students to participate more in all steps of the writing process. As students are able to produce legible text, they are encouraged to share with others and take pride in their work. This means that technology should always be considered an option for those with LDs. The use of speech synthesis with word processing provides audio feedback that is beneficial to students. This supports students in that they are

able to self-monitor their spelling and grammar. Having adults or peers to actively communicate with students is also beneficial in that they are able to think out loud and generate new ideas. However, it is not sufficient to only have the technology, but teachers must be active in engaging the students and facilitating them in the writing process. Teacher training is needed for full integration of technology in the general education classroom. This training must be extensive and thorough (Zhang, 2000). Funding will be necessary for future training of teachers at both the school district and university level (Zhang, 2000). General education teachers must be trained alongside special education teachers, as most students with LDs spend much of the day in the general education classroom.

currIcuLum For PreservIce teAcHer trAInIng In the previous sections we examined the AT needs of students with disabilities, as well as the needs of students and families from CLD populations. We have found that teachers need more training in the use of technology for students in general and special education classrooms. The purpose of this section is to address what teachers need to know about AT to be able to use AT devices in their classrooms, with the help of related service providers. At the University of Texas at Austin, the College of Education’s AT Lab orientation serves as an example of teacher training for these purposes. The orientation introduces undergraduates to some of the technology they will use in the public school setting, AT across the lifetime, and how decisions are made regarding the selection of AT devices. This section describes the curriculum structure and how hands-on activities are used to ensure active participation. The AT lab works in collaboration with faculty to ensure a cohesive and integrated orientation curriculum. The lab operates as a service to all of

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the College of Education, and most of the students complete the orientation as a course requirement related to an introductory course in special education. In this introductory course, students learn about different disabilities, assessment and identification, and the Individual Education Program process and team decision-making. The orientation presents students with information about AT throughout the lifespan of the individual, addressing different disability types and how to make proper decisions regarding the selection of AT for the individual. The lab staff takes the students through a series of settings, beginning in the home and moving to the classroom, workplace, early childhood and communication areas. The items discussed in this section can be found at the College of Education’s AT Lab website (http:// www.edb.utexas.edu/ATLab). The orientation begins in the home setting, with the students gathered around a table with adapted utensils and plates. After getting to know each other the staff facilitate an informal conversation about everyone’s knowledge of AT. The purpose is to informally assess the students’ previous knowledge about AT and the special education process. Some of the questions the staff asks are: What do you think AT is? Do you have any experience with AT? Have you ever met anyone who uses AT? Who has older relatives or neighbors that use equipment that they may not have needed when they were younger? What devices did you see on the way into the building as you came here today? What constitutes AT? What is the federal definition? How are devices chosen? It is important after this discussion to explain the definition of AT and discuss the differences between no-tech, low-tech, and high-tech options. The staff talks them through a process of choosing AT devices based on the student’s needs, using Bryant and Bryant’s (2003) framework for selecting AT devices. The home setting, where this conversation takes place, includes a simulation of a kitchen with dining room, a den, a bathroom, and an

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indoor recreational area. As the students have been sitting at the table during this conversation, they have seen adapted appliances, utensils and electronic equipment. After giving the students some background information, the staff encourages the students to use and explore the aids for daily living in the four areas of the home. In the kitchen area, the students try to use the adapted materials they find on the table. The staff will ask questions such as: What was hard and what was easy? How did it feel using this? Who might this be helpful for? The students take turns trying some of the utensils in the kitchen section, such as the grabber/reacher, jar opener, talking scale, and tab grabber. Many of these devices are helpful in the home and not just for people with disabilities. Some of the students have commented that their mother or their grandparents regularly use some of these items. After the kitchen area, the students move to the living room and bathroom simulation to try using the adapted equipment, such as back scrubbers and combs with adapted handles, and office items such as the talking clock, the talking calculator, and the Braille money marker. The goal for the home section is that students will know more about different AT devices used in the kitchen, living room, bathroom, and den. They will learn about the requisite skills needed to use the devices, and their benefits. The staff gives them opportunities to use the tools so that they can become familiar with how to manipulate them. After familiarizing students with the assistive devices in the home, the students move to the classroom area, which contains instructional software currently used in schools. The classroom simulation also has devices for students with cognitive disabilities, sensory impairment, and physical disabilities. The classroom module begins with a demonstration of how to use Braille. The staff show the students technology used to produce Braille such as portable and electronic note-takers such as the Braille ‘n Speak and the pocket slate. Each

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student is given a Braille math flash card which has a line of Braille at the top, and a cut corner. The staff asks them to close their eyes and tell what they notice about the card. There is a line of Braille at the top of the card along with a cut corner to help the student know how to hold the card. Each student is then given a different Braille book. Some are for emergent readers and some are high school textbooks and yearbooks. The staff asks them how these books are different from the books the students usually read and then answer any other questions they have about the books. After learning about Braille, the staff leads the students through a hands-on activity with instructional devices. The students each choose one of the following: Quicktionary Pen, Alpha Smart, Leap Pad, Turbo Twists (Math, Spelling, and Brain Quest). Then they are given an instruction card with how to use their device and what to look for. The staff gives them approximately five minutes to explore their device, and then they ask the students to come back together as a group. Each person tells the group about their device, how it works, and for whom it would be helpful. After that, students go in pairs to use different instructional software programs. Lexia, CoWriter, Math Blaster, Show me Math, and Inspiration are some examples of the software in the classroom area. Again, there is a simple instruction card at their computer and they have five minutes to explore their program as a small group. After using the software for about five minutes, everyone comes back as a large group to discuss the software. They share what they did, telling each other how the software worked, who the software was useful for, and whether or not they would like to use this in their classroom as a future teacher. The goals for the classroom area are for students to become familiar with different devices to facilitate instruction for students with a variety of disabilities. It is important that they know how those devices can help individuals function more independently, as well as how to use the devices and software.

After the classroom, the students go to the workplace, which is a simulation of an office setting. The tools and software programs in this area are used to help individuals with physical disabilities and visual impairments to work independently. The students have a chance to try the alternative keyboards, FM system, automatic page turners, and software used for individuals with visual impairments. Some of the software includes Kurzweil, Jaws, Dragon Naturally Speaking, Magic Screen Magnification, and Duxbury Braille translation. The goals for the students in the workplace area are to learn about different devices that individuals with primarily physical and visual impairments can use in a workplace setting. The students need to know about the skills required for individuals to be able to use these devices, and the benefits of using the devices. Students will also learn how to use the devices themselves. The workplace is located next to the early childhood area, which is the next section that the students visit. They sit around a large play mat that has many adapted toys, communication devices, and equipment for positioning and mobility. The students explore the toys and devices on their own for a few minutes, and then the staff facilitate a discussion about the devices. They ask the students to name the features that make a toy appropriate for a child with a sensory deficit, such as blindness or deafness, and then to find another toy that would not be suitable for that same child. The staff asks them to think about the skills required to use a certain toy, and which toys would be effective to increase socialization opportunities for children with and without disabilities. The early childhood setting allows students to manipulate adapted toys and hardware that are generally used by service providers (OT/PT and speech pathologists) and teachers who work with children who have sensory or physical impairments, and language or cognitive delays. One of the goals for the students in this area are to understand developmental domains (cognitive,

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motor, communication, and social) of children and how AT can be incorporated into their daily environment to promote the development of these domains. Another goal is to understand how toys from standard retail outlets can be made accessible to children with developmental delays, and how AT devices can increase children’s independence and daily living skills. After the early childhood center, students move to the AAC center where they get hands-on experience using different levels of communication devices. In this area students experience both “low-tech” and “high-tech” communication devices to help individuals who have expressive communication difficulties. Here, students learn the concepts of communication systems and how to manipulate each communication tool. They learn how communication devices can help increase the independence of individuals with disabilities and also how these devices help individuals interact with others in their daily lives. The first device the staff shows the students is an eye-gaze display board as an example of a no-tech communication device. The students take turns using the device to communicate what they want to eat, for example. After that, there are some one-button devices such as the Big Mac, and students record their own speech and learn how to operate the devices. There are also a few high-tech complex communication devices such as the Vanguard and Dynavox systems and the staff will demonstrate these for the students. A major goal for the students in the communication area is to become knowledgeable about the different choices available for communication devices. They also learn how to manipulate these devices. When the orientation is complete, the students have a chance to give immediate feedback. They use computers in the AT lab to complete an online survey of their experience. The comments and feedback from students are very helpful for improving the lab each semester. The majority of students (96%) completing the survey reported that the content of the orientation related to what

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they were learning in their introduction to special education course, and 94% expressed that this experience was “good” or “wonderful.” By working with faculty to integrate the AT lab orientation into their curriculum, the lab staff are able to give preservice teachers a meaningful experience using some of the technology that will likely be available in the schools. Future research should be conducted to follow-up with those students who become teachers, and ask how their experience prepared them to work with students using AT in school.

concLusIon Teacher educators need to develop a curriculum and training program for preservice teachers to learn to use AT with diverse learners. It is evident preservice teachers need more comprehensive training in AT to meet the needs of diverse learners. One of the ways to train preservice teachers in the use of AT is to first find funding for AT laboratories and then provide preservice teachers with hands-on experiences with this technology through curriculum development. There is such a variety of AT devices that it is important preservice teachers be made aware of low-tech and high-tech equipment that are available to assist students. Preservice teachers should also have the knowledge base so that AT can seamlessly be incorporated into the home and school environment. This way parents, family, peers and other staff will be able participate and become comfortable assisting the child in the use of their AT. This is necessary because as the teacher interacts and has a greater rapport with the student, family, and other staff, they will be able to serve as a liaison when needs may arise regarding the technology.

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reFerences Achieving the Goals. (1996). U.S. Department of Education. Retrieved April 25, 2008, from http:// www.ed.gov/pubs/AchGoal4/mission.html Bahr, C., Nelson, N., & Van Meter, A. (1996). The effects of text-based and graphics-based software tools on planning and organizing of stories. Journal of Learning Disabilities, 29(4), 355–370. doi:10.1177/002221949602900404 Bausch, M. E., & Hasselbring, T. S. (2004). Assistive technology: Are the necessary skills and knowledge being developed at the preset-vice and in service levels? Teacher Education and Special Education, 27, 97–104. doi:10.1177/088840640402700202 Binger, C., & Light, J. (2006). Demographics of preschoolers who require AAC. Language, Speech, and Hearing Services in Schools, 37(3), 200–208. doi:10.1044/0161-1461(2006/022) Bryant, D., & Bryant, B. (1998). Using assistive technology adaptations to include students with learning disabilities in cooperative learning activities. Journal of Learning Disabilities, 31(1), 41–54. doi:10.1177/002221949803100105 Bryant, D., & Bryant, B. (2003). Assistive technology for people with disabilities. Boston: Allyn and Bacon. Building a Legacy: IDEA 2004. (2004). U.S. Department of Education, Office of Special Education Programs. Retrieved November 25, 2007, from http://idea.ed.gov Duquette, C. (2007). Students at risk: Solutions to classroom challenges. Ontario: Pembroke Publishers. Graham, S., & Harris, K. (2003). Students with learning disabilities and the process of writing: A meta-analysis of SRSD studies. In Swanson, H. L., Harris, K. R., & Graham, S. (Eds.), Handbook of learning disabilities (pp. 323–344). New York: Guilford Press.

Hasselbring, T., & Bausch, M. (2006). Assistive technologies for reading. Educational Leadership, 63(4), 72–75. Huer, M. B., Parette, H. P., & Saenz, T. I. (2001). Conversations with Mexican Americans regarding children with disabilities and augmentative and alternative communication. Communication Disorders Quarterly, 22(4), 197–206. doi:10.1177/152574010102200405 Lee, Y., & Vega, L. (2005). Perceived knowledge, attitudes, and challenges of AT use in special education. Journal of Special Education Technology, 20(2), 60–63. Lerner, J. (2003). Learning disabilities: Theories, diagnoses, and teaching strategies (9th ed.). Boston: Houghton Mifflin. MacArthur, C. (1998). Word processing with speech synthesis and word prediction: Effects on the dialogue journal writing of students with learning disabilities. Learning Disability Quarterly, 21(2), 151–166. doi:10.2307/1511342 MacArthur, C. (1999). Word prediction for students with severe spelling problems. Learning Disability Quarterly, 22(3), 158–172. doi:10.2307/1511283 MacArthur, C., Ferretti, P., Okolo, C., & Cavalier, A. R. (2001). Technology applications for students with literacy problems: A critical review. The Elementary School Journal, 3(101), 273–301. doi:10.1086/499669 McCord, S., & Soto, G. (2004). Perceptions of AAC: An ethnographic investigation of Mexican-American families. Augmentative and Alternative Communication, 20(4), 209–227. doi:10.1080/07434610400005648 Parette, H. P., Brotherson, M. J., & Huer, M. B. (2000). Giving families a voice in augmentative and alternative communication decision-making. Education and Training in Mental Retardation and Developmental Disabilities, 35(2), 177–190.

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Stuart, S., & Parette, H. P. (2002). Native Americans and augmentative and alternative communication issues. Multiple Voices, 5(1), 38–53. Technology-Related Assistance for Individuals with Disabilities Act of 1988. (Tech Act). (1988). Public Law 100-407 Utley, C. A., Delquadri, J. C., Obiakor, F. E., & Mims, V. A. (2000). General and special educators’ perceptions of teaching strategies for multicultural students. Teacher Education and Special Education, 23, 34–50. doi:10.1177/088840640002300107 Woodward, J., & Rieth, H. (1997). A historical review of technology research in special education. Review of Educational Research, 67(4), 503–536. Zhang, Y. (2000). Technology and the writing skills of students with learning disabilities. Journal of Research on Computing in Education, 32(4), 467–478.

key terms And deFInItIons Augmentative and Alternative Communication (AAC): Any system that increases or improves communication of individuals with receptive or expressive communication impairments. The system can include speech, gestures, sign language, symbols, synthesized speech, dedi-

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cated communication devices, microcomputers, and other communication systems. (see FCTD Assistive Technology Glossary: http://www.fctd. info/resources/glossary.php) Assistive Technology (AT) Device: Any item, piece of equipment, or product system that is used to increase, maintain, or improve functioning of individuals with disabilities (Assistive Technology Act of 1998). Bicultural: Being or relating to two different cultures in one nation or geographic area. Culturally and Linguistically Diverse (CLD): in the context of this paper and US public schools and universities, we are using this to mean of non-White ethnicity or in a home where English is not the native language. Communication Board: Communication boards are both AAC devices. That means that they are used to supplement or replace spoken language as a means of communication, specifically non-verbal communication. Low Incidence Disabilities: Disabilities that do not occur frequently in the population but can have a major impact on a student’s functioning; includes autism, Asperger’s disorder, Tourette syndrome, fetal alcohol syndrome, and physical disabilities (Duquette, 2007). Universal Design: A broad-spectrum solution that produces buildings, products and environments that are usable and effective for everyone, not just people with disabilities.

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Chapter 24

Supporting Early Childhood Outcomes through Assistive Technology Diane Plunkett University of Kansas, USA Rashida Banerjee University of Northern Colorado, USA Eva Horn University of Kansas, USA

AbstrAct Assistive technology (AT) makes it possible for young children with disabilities to learn, play, and build relationships. By improving their mobility, communication, and access to their environment, AT allows children with disabilities more freedom and independence. The purpose of this chapter is to guide early childhood professionals with examples and recommendations for the integration of AT in natural environments to meet early childhood outcomes for children up to the age of five. This chapter is organized in three sections. Section 1 briefly discusses the legal background in early childhood services as it applies to AT. Section 2 describes the framework for meeting young children’s needs for AT within the context of early childhood outcomes. Section 3 presents the application of AT in meeting recommended family outcomes. The Additional Readings section to this chapter offers relevant articles and research reports in the area of early childhood and AT.

IntroductIon Assistive technology is a universal avenue for assisting all children to engage with their environment and meet developmental milestones. However, this requires early childhood professionals to reflect DOI: 10.4018/978-1-61520-817-3.ch024

on their practices, approaches, and perspectives to support all children to achieve their outcomes, and for the families to support their children’s development and learning. Historically, guides to the utilization of AT have addressed specific developmental domains. For example, if a child had a delay in the area of social-communication performance the solutions focused on that particular

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domain. Similarly, if a child experienced a delay in mobility, then a mobility device was provided as the answer. Once early childhood professionals embrace assistive technology (AT), allowing a child with disabilities to meet comprehensive developmental outcomes, as opposed to isolated areas of development domains, the field can move towards recognizing the beneficial aspects of AT in meeting early childhood outcomes. Assistive technology allows children full participation with family, friends, and community. Upon completion of this chapter readers should be able to: •

• •

•

Summarize key legislation impacting AT for young children with disabilities and their families. Describe federally mandated early childhood outcomes as they relate to AT. Identify evidence-based and promising AT solutions for children with disabilities and their families to meet early childhood outcomes. Identify evidence-based and promising AT solutions for families of children with disabilities to meet family outcomes.

bAckground “maria” Maria, the youngest in a family of three children, is an 8 month-old girl with Down syndrome. Maria has difficulty feeding, and she has to have frequent hospital visits for a related heart condition. Maria’s parents live on a remote rural ranch and travel up to three hours to the nearest clinic for their daughter’s special health needs. With the help of the clinic, Maria’s family has been in contact with an early interventionist and an occupational therapist who visits weekly to assist Maria and her family with Maria’s disability. In an ideal world, children and families have resources to meet challenges inherent to all per-

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sons, such as information, resources, and support. If all things were equal, every child would have the opportunity to reach developmental milestones ensuring their success and leading to a productive and fulfilling adulthood. For children such as Maria, developmental challenges are significant. However, a provision for early intervention services under the federal laws ensures that she and her family receive the assistance needed to help her in reaching developmental milestones. These services begin at birth and may well extend into a child’s school years. According to the Individuals with Disabilities Education Act (IDEA), all children who are eligible to receive special education or early intervention services are also eligible to receive AT at no cost to the family, if it is included as part of their Individualized Family Service Plan (IFSP) (34CFR§ 303.344[d]) or Individualized Education Plan (IEP) (34CFR§ 300.105). The following section explains the federal mandates that may guide the provision of AT for children with disabilities, such as Maria.

Federal mandates governing At In 1988, federal initiatives developed definitions for devices and services outlining support for persons with disabilities in the form of AT (Tech Act, 1988). What emerged from the original initiatives is now embodied in the Individuals with Disabilities Education Improvement Act of 2004 (IDEA, 2004). IDEA is the federal education program that assists states in developing and implementing systems of comprehensive services for all eligible individuals with disabilities, birth through 21 years of age. Part C of IDEA supports young children with disabilities from birth to 3 years of, and Part B of IDEA supports children 3 through 5 years of age. Part C and Part B stipulate that these children receive these services in inclusive and natural settings (NECTAC, 2009). IDEA also requires AT be considered and provided for a child if it is determined the child needs such

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technology to access and participate in everyday activities in assisting with the child’s learning (Judge & Parrette, 1998). IDEA defines AT as: Any item, piece of equipment, or product system, whether acquired commercially modified or customized, that is used to increase, maintain, or improve the functional capacities of a child with a disability. The term does not include a medical device that is surgically implanted, or the replacement of such device [34CFR§300.5]. Assistive technology service means any service that directly assists a child with a disability in the selection, acquisition, or use of an AT device. The term includes: (a) The evaluation of the needs of a child with a disability, including a functional evaluation in the child’s customary environment; (b) Purchasing, leasing, or otherwise providing for the acquisition of AT devices by children with disabilities; (c) Selecting, designing, fitting, customizing, adapting, applying, maintaining, repairing, or replacing AT devices; (d) Coordinating and using other therapies, interventions, or services with AT devices, such as those associated with existing education and rehabilitation plans and programs; (e) Training or technical assistance for a child with a disability or, if appropriate, that child’s family; and (f) Training or technical assistance for professionals (including individuals providing education or rehabilitation services), employers, or other individuals who provide services to, employ, or are otherwise substantially involved in the major life functions of that child [34CFR§300.6]. According to IDEA, all children who are eligible to receive special education or early intervention services are also eligible to receive AT services at no cost to the family, if it is included as part of their Individualized Family Service Plan (IFSP) or Individualized Education Plan (IEP).

IDEA requires the intervention team routinely consider AT as part of the early intervention and preschool evaluation. AT services include any service that directly assists a child with a disability in the selection, acquisition, and use of an AT device. Services may also include training and coordinating with other service providers and family members. However, if AT has not been considered at the time of the IFSP or IEP meetings, the family or a team member may request an AT evaluation at any time. Even though IDEA guarantees consideration and implementation of AT services, underutilization of AT services persists for young children with disabilities and their families (Lesar, 1998; Mistrett, 2001). The exception of AT services that should be noted from IDEA 2004 is the explicit definition of medical devices and related services. This addition to IDEA makes clear the roles and responsibilities of local education authorities in medical device and services as it is related to AT. (b) Exception; services that apply to children with surgically implanted devices, including cochlear implants. (1) Related services do not include a medical device that is surgically implanted, the optimization of that device’s functioning (e.g., mapping), maintenance of that device, or the replacement of that device. (2) Nothing in paragraph (b)(1) of this section—(i) Limits the right of a child with a surgically implanted device (e.g., cochlear implant) to receive related services (as listed in paragraph (a) of this section) that are determined by the IEP Team to be necessary for the child to receive FAPE. (ii) Limits the responsibility of a public agency to appropriately monitor and maintain medical devices that are needed to maintain the health and safety of the child, including breathing, nutrition, or operation of other bodily functions, while the child is transported to and from school or is at school; or (iii) Prevents the routine checking of an external component of a surgically-implanted device to

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Figure 1. Legislation relevant to AT at early childhood

make sure it is functioning properly, as required in Sec. 300.113(b).

mAndAted eArLy cHILdHood outcomes

Even children with disabilities who are not eligible for special education under IDEA may also be entitled to the provision of AT under Section 504 of the Rehabilitation Act or under the Americans with Disabilities Act (ADA) (National Early Childhood Technical Assistance Center, NECTAC, 2009). The Figure 1 summarizes additional legislation that influences AT services and their relevance to early childhood.

Substantial progress has been made for young children with disabilities and their use of and access to AT. In 2005, the Office of Special Education Programs (OSEP) mandated for each state receiving federal dollars to fund early intervention (Part C) and special education preschool programs (Part B) must report on child and family outcomes (ECO, 2009). The OSEP uses resulting data to support program planning, research, and

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early intervention services (ECO, 2009). For the purpose of accountability, states must report on the percentage of infants and toddlers with Individualized Family Service Plans (IFSPs) and on preschool children with Individualized Education Plans (IEPs) who demonstrate improved: (a) positive social-emotional skills (including social relationships), (b) acquisition and use of knowledge and skills (including early language/ communication and early literacy), and (c) appropriate behaviors to meet their needs. The ultimate goal is “to enable young children to be active and successful participants during the early childhood years and in the future in a variety of settings…” (ECO, 2009). States are also required to report the family outcomes to OSEP. For family outcomes, early intervention programs are required to report the percentage of families who are participating in Part C and report early intervention services helping them to: (a) know their rights, (b) effectively communicate their children’s needs, and (c) help their children develop and learn. Additionally, state 619 preschool (Part B) programs must report the percentage of parents with a child receiving special education services who report that schools facilitated parent involvement as a means of improving services and results for children with disabilities.

early childhood child outcomes Each of the following sections discuss one of the three early childhood child outcomes mandated by the OSEP by explaining and responding to the following question: “So what do these outcomes look like for a child in the home and classroom?” The following section will also illustrate these behaviors and outcomes by discussing specific cases of children with disabilities and the possible solutions that AT would provide. We conclude each outcome with evidence-based and promising AT methods. Evidence-based practice is inherent in quality service provision to young children with disabilities and their families. Therefore, the

evidence-based and promising AT methods and practices chosen in the case study examples are guided by the review of evidence for teaching young children to use AT provided by Campbell, Milbourne, Dugan and Wilcox (2006) and Mistrett et al. (2001).

Early Childhood Child Outcome 1: Positive Social-emotional Skills Research indicates positive social and emotional skill attainment in early childhood has an enormous impact on the children’s success later in life. Children’s development of positive skills is shaped by successful interpersonal relationships. Positive attachment to parents or a primary caregiver facilitates successful interpersonal relationship and the development of positive emotional, social, and academic skills. Attachment in infancy is facilitated by rudimentary behaviors of smiling, prolonged eye contact, and separation. After the age of 18 months, a child demonstrates more sophisticated interactions with peers and parents by cooperating in social games, enjoying being the center of attention and solitary play (Allen & Marotz, 2007). As a child prepares to enter preschool, rule-related skills are observed in peer play with materials, active engagement, and self-regulating behaviors (Allen & Marotz, 2007). Rule-related skills include taking turns with simple board games, waiting to be served a snack, and being able to transition from one activity to the next. The following section discusses early childhood child outcome one and illustrates ways of selecting AT for an infant with disabilities and potential AT solutions as the child ages. “Charles”. Charles is a 6-month-old boy, the second of two children in the family, who was born by cesarean section at 27 weeks gestation and weighing 2 pounds, 1 ounce. Shortly after birth, Charles experienced a grade 3 brain bleed on the left hemisphere, and the placement of a shunt was necessary. The extent of his disability remains uncertain, but his doctors anticipate Charles may

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have mild to moderate mental retardation, cerebral palsy, vision impairment, and hydrocephaly. Charles’ parents are worried if he will grow up, and if he does live, what quality of life he will have. His 8 year-old brother is embarrassed, as Charles looks different than other babies and cries often. His brother has asked if they can leave Charles at home instead of taking him to the church nursery as other children are making fun of him. Charles’ parent’s immediate concern is their inability to comfort Charles. Extended hospital stays and his disabilities are causing him to exhibit symptoms of anxiety which prevents him from successfully interacting with his parents, brother, and grandparents. Charles takes a number of medications to deal with seizures and muscle spasticity. Charles’ physicians and family are unwilling to add any more medications to address anxiety. Coming home from the hospital, a Part C early interventionist met with the family to provide support and suggest resources available to them. An IFSP was developed and with the help of the occupational therapist, techniques were introduced to provide brief periods of relaxation for Charles. However, the family would like to see Charles have more consistent and longer periods of relaxation. Prematurity, or birth before the gestational age of 37 weeks, can result in numerous medical problems affecting different body systems. Most commonly associated with prematurity are developmental disabilities, seizure, cerebral palsy, retinopathy of prematurity (blindness/low vision), and breathing problems (Centers for Disease Control and Prevention, 2009). Extended hospital stays are common and may make the transition to home stressful for all the family members. However, AT can assist children who were born prematurely with resulting delays or disabling conditions and their families in a number of ways. As Charles’ example illustrates, the use of off-the-shelf baby equipment might improve a prematurely born child’s experience by allowing positive interactions among family members. Charles’ family discovered through trial and er-

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ror that placing Charles in the swing and turning on the vibrator element allowed him the longest period of sustained contentment. With this medium-tech device, Charles was able to tolerate his family members holding his hand, talking to him, and stroking his face. Charles might also benefit from additional physical supports such as a Boppy pillow, wedge pillows, or a vibrating pillow to support him physically and encourage sitting during typical routines such as lap reading with his grandparents. Assistive technology may also encourage others to interact with Charles. Between the ages of 2 and 3, medium-tech assistive devices, such as switch-activated sound and vibrating toys will be useful to encourage Charles to interact with his environment. Adapting popular toys, such as “My first RC Car” with a switch to encouraging others to play with him would help ease Charles’ social interactions at church functions and give his brother a positive role as well. The early intervention team may also suggest seating and positioning devices for Charles to support him during typical family routines. When Charles begins attending preschool, AT can help facilitate peer interactions. The use of electronic storybooks on the computer or specifically designed activity boards that encourage peer contact have been demonstrated to be effective moderators for peer interaction (Spiegel-McGill, Zippiroli, & Mistrett, 1989). Evidence-based and promising AT solutions. For Charles and other children like him, AT provides solutions to promoting interpersonal relationships. Studies have demonstrated AT as an effective means for facilitating the development of social emotional skills between the child and their caregiver and the child and his peers (Sullivan & Lewis, 2000; Whaley, 1990). Typically, AT solutions for social and interpersonal relationships are built around communication. Numerous research studies have confirmed the social benefits of communication (Schepis, Reid, Behrmann, & Sutton, 1998). Schepis and col-

Supporting Early Childhood Outcomes through Assistive Technology

leagues reported positive peer interactions during typical classroom routines and activities. Butler also reported positive psychosocial gains from parental perspectives and offered the benefit of self-initiated behaviors with powered mobility for children as young as 23 months -old (1986). Additionally, social facilitation utilizing computer games resulted in positive gains for children with significant social interaction deficits and speech and language impairments (McCormick, 1987; Spiegel-McGill, 1989).

Early Childhood Child Outcome 2: Acquisition and Use of Knowledge and Skills (Including Early Language/ Communication and Early Literacy) Children understand the physical and social world through activity and exploration, which involves thinking, reasoning, remembering, solving problem, as well as using symbols and language (Dunst & Shue, 2005). These interactions involve exploration of early concepts, symbols, pictures, numbers, classification, spatial relationships, imitation, expressive language, and early literacy. For children with disabilities, this process of exploring the world is often interrupted by their inability to demonstrate an understanding through questioning and inquiry. Their language may be impaired or ineffective unless they are given alternate means of communication and expression. Children are typically expected to move through stages of language development and communication which are interlinked with later literacy skills (NIFL, 2009). AT can provide solutions to children who are unable to move to the next level of communicative intent. The following section discusses early childhood child outcome two and illustrates ways of selecting AT for a toddler with disabilities and potential AT solutions. “Haley”. Haley is a 26-month-old girl and an only child. Haley has moebius syndrome, which is marked by the paralysis of facial muscles that control speech, jaw, eye movement, and facial

features. As a result, Haley has difficulty swallowing, hearing, and verbally communicating effectively. Haley is unable to articulate clearly, drools frequently, and her facial expressions do not reflect her feelings. The syndrome has resulted in delays in Haley’s speech and social skills. Additionally, Haley is experiencing gross motor delays due to mild cerebral palsy. She recently started crawling and pulling herself to standing and uses a wheelchair for most outings. Since she is their only child, Haley’s parents have enough time and energy to anticipate her needs and are quick to do things for her, but they can rarely understand what she is trying to say and are concerned about their ability to care for her. As a result of her parents’ inability to understand her, Haley has begun exhibiting tantrums. Haley’s parents are reluctant to take her to public places such as restaurants and the grocery store. After witnessing children removing their toys from her reach and moving away from her, Haley’s parents are concerned that children will not want to play with Haley. Living in a rural area, Haley’s parents have had limited access to, and success with, early intervention, but they visit a large medical center and have received suggestions for simple AT to facilitate and improve Haley’s language and communication with parents and peers. For any child, including Haley, communication development in infancy is necessary for acquiring information. Before developing formal speech, infants use a number of facial expressions, body language, and gestures to demonstrate emotion and participate in interactions. Parents read their infant’s facial expressions and react to them, thus providing their children with learning opportunities and access to information. The expressions of the eyes and mouth reveal when a child understands and is at ease with solving problems. If a child senses wonder, utterances of “oh” emerge, which the adult can reinforce with more information or questions. For children like Haley, however, the natural give-and-take of exchanging information through a look of confusion or awe is not possible

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because they do not express thinking, reasoning, and remembering in a typical fashion. Expressive and receptive demonstrations of language are a hallmark for the development of children between the ages of 2 and 3. Disability or delays, however, impede the crucial exchange of information that commonly scaffolds development in multiple areas. Unfortunately, children with moebius syndrome cannot make themselves understood as their speech clarity is poor. Haley, for example, is unable to clearly state her choice of clothes for the day, which limits her expressions to pointing out objects with her fingers or hands. When her mother asks, “Haley would you like the blue or pink sweater today?” for instance, Haley can respond only by pointing to the sweater she prefers. Her opportunity to expand on what she understands remains unexplored because pointing does not indicate she recognizes the color she is choosing; only that she is making a choice. However, a medium-tech solution, such as digital recordings in a picture frame, could help with Haley’s expressive and receptive communication. Multiple picture frames or modified greeting card recorders of Haley wearing the outfit of her choice can provide the means for Haley to voice her choice of items from her closet. Each morning, the picture frames can be laid out for Haley to choose from. As she gets older, Haley will learn to make more choices by responding to an increasing number of frames. Moreover, Haley’s need to engage in social communication with peers and exchange information with unfamiliar adults will grow as soon as she begins to transition to preschool. Digital recording mechanisms, which are now financially feasible and can be attached to a key chain, can help children like Haley to communicate. For instance, if Haley were to ride the school bus home and wished to address the bus driver, she could activate a key chain recording saying: “Hi Mrs. Timmer.” This digital recording device would help in a communication exchange typical for preschool aged children with adult models.

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More sophisticated voice recording technology, such as assistive augmentative communication devices, will also help children like Haley meet their communicative needs in the future. Such devices include a portable Tango (a speech generating device which contains a broad array of communication methods, a built-in camera, voice morphing and highly robust scanning options with multiple symbols) or a Springboard Lite (a small, light-weight and portable speech generating device designed for just beginning AAC communicators with 4, 8, 15, and 36 display options). Evidence-based and promising AT solutions. Augmentative and alternative communication (AAC) systems enable children to communicate expressively. Early provision of AAC systems promotes cognitive development and social competence and thereby allows young children with expressive communication delays to participate in a variety of activities that are otherwise impossible. Through these activities, children acquire skills they will need to succeed in school and their social life (Schepis et al., 1998). In addition, researchers have demonstrated the effectiveness of supporting early literacy skills through AT by reducing physical barriers and enhancing participation (Farmer, Klein, & Bryson, 1992; Pierce & McWilliam, 1993; Steelman, Pierce, & Koppenhaver, 1993). The findings are consistent with Soto, Belfiore, Schlosser, and Haynes (1993), who conducted research with a child who had severe disabilities; found that the child demonstrated a clear preference for using one device over another. These researchers also found that the child’s overall performance was better with the preferred device than with a device assigned to the child. Even though children have more success with devices when their preferences are respected, professionals do not usually take the children’s preferences into account during assessments. In a survey of state practices regarding the assessment procedures used to prescribe communication devices for young children, Parrette and Hourcade (1997) found that child preferences were

Supporting Early Childhood Outcomes through Assistive Technology

only considered 39% of the time in assessments. Early childhood professionals should, therefore, consider child preference as a prerequisite for any AT solutions.

Early Childhood Outcome 3: Appropriate Behaviors to Meet Their Needs As children integrate motor skills into completing tasks and develop self-help skills (toileting, feeding, grooming) they are acting on the world to get what they want and need. Children integrate various skills to complete tasks, gross motor and fine motor, working in tandem to take care of their basic needs (e.g., choosing what to wear, walking to a door, responding to a request). Children contribute to their health by following rules, assisting with hand washing, avoiding inedible objects, mobilizing from place to place, and using tools (e.g., forks, pencils). This outcome includes the function of multiple behaviors working simultaneously. Children gain the emotional maturity to plan, execute, and meet a variety of competing needs. For example, their need to satisfy thirst requires recognition of being thirsty, being able to mobilize or ask for something to drink and then actually drinking a beverage. The following section discusses early childhood child outcome 3 and illustrates ways of selecting AT for an infant with disabilities and potential AT solutions as he ages. Zander. Zander, the youngest of three children in the family, is a 16-month-old boy with significant delays in speech and motor development. Zander has been identified with fetal alcohol syndrome (FAS). FAS may result in poor motor control, distractibility, poor fine and gross motor control and problems with concrete thinking (NOFAS, 2009). Zander has not had the opportunity to develop along typical lines as he spent his first 16 months confined in his car seat and playpen. Zander appears to be alert, but is having difficulty holding up his head and raising his arms. Zander

and his older sisters were recently placed with his grandmother after being relocated by state social services. His grandmother is concerned Zander still drinks from a bottle and she would like him to begin eating table food. Social services contacted the local education agency (LEA) to initiate early intervention services for Zander and his family. The early intervention team has referred Zander’s grandmother to local resources in addition to developing an Individualized Family Service Plan (IFSP). Zander has entered early intervention services with a number of significant needs. Not only does Zander have to face significant physical challenges, but his living environment has also multiplied his difficulties for typical development. Children with a history of prenatal exposure to drugs are more likely to have environmental risks than those without exposure (Carta, Atwater, Greenwood, McConnell, McEvoy, & Williams, 2001). Tasks for Zander include acquiring the strength and muscle control to begin acting upon his environment. Providing Zander with opportunities to reach, grab and pull can be achieved through assistive, off-the-shelf technology. Activity gyms that encourage ‘cause and effect’ require Zander to manipulate the item. Zanders’ grandmother’s concern about his self-feeding is a valid concern. Developmentally Zander is of an age to be exploring self-feeding. As he should begin eating table foods, assisting him from bottle-feeding will require incremental changes. Weaning from his current feeding bottle and trained to use more typical cup forms will necessitate Zander to grip with two-fist formations. This in turn will allow him to transition more easily to other utensils and also generalize to grabbing items such as toys and smaller food pieces. Between the ages of 2-3, the OT and early interventionist could suggest low-tech AT that will allow Zander to gain strength and mobility, and to roam safely in his home. Push-walking toys can be modified to increase the surface friction between the wheels and floor and allow Zander to gain

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strength as he mobilizes around his environment. Exploring his environment safely will also require an element of internal regulation on Zander’s part. Children prenatally exposed to alcohol and drugs have a higher incidence of impaired adaptive behaviors (Whaley, 2001). These behaviors may include communication, socialization, self-help skills, and distractibility. Zander may benefit from the use of picture schedules to guide his adaptive behavior with sensitivity to his age and developmentally appropriate expectations. Upon entering preschool, children experience multiple opportunities for meeting their developmental needs. Putting on a jacket and washing and drying hands for snack time are all typical activities within a classroom routine. Simple lowtech solutions are available with creative input. Attaching a small key ring toy to the zipper pull would allow Zander to pull the zipper closed while encouraging independence. Additionally, placing a strip picture prompt sequence at eye level above the hand washing sink will assist Zander in planning his movements during hand washing. Evidence-based and promising AT solutions. The majority of the research studies in AT has centered on mobility devices enabling children access to their world. Researchers have established the withholding of mobility for developing infant’s increases a pattern of apathy, learned helplessness, and an unwillingness to venture and explore (Butler, 1986; Beckwith, 1971; Harter, 1978). However, AT devices such as robotic armature, infant mobility devices, wheelchairs, and prosthetic limbs all encourage exploration. Therefore, a child mobilizing autonomously in a self-realizing manner is beginning to operate from a view of self-determination. This is a beginning foundation for acts of self-determination which continue through the life span (Erwin & Brown, 2003; Wehmeyer & Palmer, 2000). Using case studies, we have offered a variety of potential AT solutions for Charles, Haley, and Zander.

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While each of these children has unique needs, they do share one aspect in common—each child’s family is part of a team. In the following section, we will examine how the OSEP early childhood family outcomes may be positioned with respect to AT devices and services in early intervention.

early childhood Family outcomes A family outcome is defined as “a benefit experienced by families as a result of services received… A family outcome is not the receipt of services, but what happens as a consequence of providing services or supports” (Bailey, Bruder, Hebbeler, Carter, Defosset, & Greenwood, 2006, p.228). Family outcomes have received less attention from researchers than child outcomes due to the lack of focus on and clear definition of family outcomes (Bailey & Bruder, 2005). The OSEP has recommended three family outcomes to address accountability issues in early childhood special education; families must: (a) know their rights, (b) effectively communicate their children’s needs, and (c) help their children develop and learn. Additionally, state 619 preschool programs must report the percentage of parents with children who receive special education services and report that schools facilitated their involvement as a means of improving services and results for children with disabilities (OSEP, 2006). Recently, the delivery of early childhood intervention services has shifted from professional, clinical models to a family-centered model in all areas of service delivery, including AT (Bailey, McWilliam, & Winton, 1992; Judge, 2002; Keilty & Galvin, 2006). Due to the increased importance of the family in the provision of early intervention and early childhood services for children up to five years of age, it’s critical to include family outcomes in the overall child outcomes required by OSEP. Further, Part C of IDEA clearly states the benefit of services should be provided to families, and Part B states that services should support family

Supporting Early Childhood Outcomes through Assistive Technology

participation to meet the developmental needs of the children. In fact, AT can help families support their children’s development and learning, and promote their participation in daily activities and routines at home and in community settings (Campbell et al., 2004). In a study examining the factors in families’ daily lives increasing or impeding AT use, Hider (1999) found that parents were the largest determinant of whether AT was used or not used. Thus, inclusion of the family is crucial for understanding and reporting outcomes of children using AT because children’s uses of AT are intertwined within their homes, schools, and community contexts. The following sections discuss each of the three family outcomes mandated by OSEP for children and families receiving services under Part C. The section begins with the description of the early childhood family outcome, then discusses a specific case demonstrating how the outcomes may be achieved through the use of AT.

Early Childhood Family Outcome 1: Families Know Their Rights IDEA 2004 outlines the rights for parents of children with disabilities. This set of rights enables parents to participate actively in decisions regarding the design and delivery of services. Families must have knowledge of their rights and responsibilities under the law, and have access to information empowering them to advocate effectively on behalf of their children. Parents’ opinions and suggestions are critical in understanding the child’s needs and preferences for AT. With the help of families, the Individualized Family Service Plan (IFSP) team or the Individualized Education Plan (IEP) team may be able to determine the appropriate AT, such as special seating or an adaptive switch that has been useful for the child in different settings-both at home and school. Let’s revisit 8-month-old Maria and allow her family’s needs to guide us through family outcome one.

Maria, who lives with her family on a remote rural ranch, has Down syndrome with a related heart condition and has special feeding needs. In order to access and provide support for Maria, her parents must understand their rights. Maria’s parents play an important part in the decision-making process. Under IDEA 2004, Maria’s parents have: (a) the right to have an evaluation, assessment, IFSP development, service coordination and procedural safeguards at no cost. They may be charged for other early intervention services on a sliding fee schedule; (b) the right, if eligible under Part C, to appropriate early intervention services for Maria and her family as addressed in an Individualized Family Service Plan (IFSP); (c) the right to be invited to and participate in all meetings in which a decision is expected to be made regarding a proposal to change the placement for Maria or the provision of services to Maria or her family; (d) the right to request a change in service coordinators; (e) the right to choose or not to use their health insurance to pay for early intervention or AT services for Maria; (f) the right to receive timely written notice (Prior Notice) before a change is proposed or refused in the identification, evaluation, or placement of Maria, or in the provision of services to Maria or her family; (g) the right to receive services in the natural environment, to the maximum extent appropriate for Maria; (h) the right to have all personally identifiable information treated as confidential; and (i) the right to an impartial hearing to resolve parent/provider disagreements. The family also has a right to refuse evaluations, assessments, and services. If Maria’s parents are not satisfied with the evaluation by the agency, they have the right to seek an independent evaluation. To better support families in the partnership, it is imperative that the professionals are aware of the family’s rights and support families in advocating for these rights. Professionals must provide a copy of the procedural safeguards listing parental rights at the time of the beginning of services under

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IDEA, and thereafter at least once a year. Maria’s parents may also request the document any other time. However, providing a copy of rights is not enough. Professionals must allow families time to reflect on these rights, and return to ask more questions if required.

Early Childhood Family Outcome 2: Families Communicate Their Child’s Needs One of the critical components of IDEA (particularly in Part C) is the inclusion of families as equal partners in the design and delivery of intervention for their children. As the main decision makers for their children, parents must have opportunities to participate in the eligibility determination, goals to be addressed, and the specific services to be provided to their children. In order to support families to act as equal partners, professionals must encourage questions, comments, and requests for clarifications, and provide families with tools and resources to support their children to grow to their highest expectations. Most families need to have access to, and participate in, a “wide range of community resources, services, programs, and activities…[However], families of children with disabilities often experience challenges in accessing community resources, especially those that seem responsive to their needs and those of their children” (Bailey et al., 2006, p. 5). For instance, a family’s need for inclusive services and resources is often guided by their child’s age and needs, the family’s culture, religion, and priorities and its desire to participate in these activities. Additionally, families of children with a delay or a disability need formal and informal supports which can help attenuate the stress and loneliness these families may already feel. Formal supports may include support from professionals, parent groups, and agencies. Informal supports may include extended family, friends, or neighborhood communities, participation in church or other

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institutions of social, spiritual, or religious nature. For the families of children who use AT, formal and informal supports may include persons such as, technology experts, technicians, and product customer service representatives. Turnbull, Summers, Turnbull, Brotherson, Winton, and Roberts (2007) argue that the early childhood field has not sufficiently addressed the specific needs of families to enhance the outcomes for families themselves and for their children in terms of the types of services offered on the individual family service plans (IFSPs). The authors state that while the child-focused services, such as occupational therapy, speech therapy and physical therapy increased, the family-centered services such as family training, social work services, and respite care service decreased between 1994 and 2001. Further, most families do not have access to information from other families on evidencebased strategies that have been helpful to their children in the short and long-term. For families to better understand and communicate their children’s needs to professionals, they must understand the stages of typical development and be aware of the difference in developmental patterns among children (ECO Center, 2005). Knowledge of the special risk factors to their children’s development and learning and the recommended interventions and practices related to these risk factors allow families to communicate and meet their children’s needs more effectively. However, understanding the development of children using AT poses a unique challenge as young children grow, mature, and develop quickly. As children grow and develop, their needs for AT devices and services change. They may either outgrow their devices or surpass the capability of their devices (Isabelle, Bessey, Dragas, Blease, Shepherd, & Lane, 2002). Using the previous vignette for 6-month-old Charles, let’s see how his family’s needs are met through early childhood family outcome two. Due to Charles’ premature birth and post-natal complications, he has significant sensory, physical,

Supporting Early Childhood Outcomes through Assistive Technology

and cognitive needs. His visual disability, poor cognitive functioning, and heightened anxiety are affecting his daily living. Further, the significant caring needs for 6-month-old Charles are impacting the family’s quality of life. Charles’ IFSP team not only needs to identify AT for Charles, but also his family’s needs for support and services. His family will also need training in teaching Charles within the natural routines to utilize his other senses of touch, smell, hearing, and taste to benefit from his environment. For all AT devices, Charles family should be a part of the assessment of the device and planning in how best to use the device within Charles’ natural environment and routines. Parents may recognize opportunities to use the devices such that it brings him and his brother emotionally closer. Amongst the varied AT devices for sitting and positioning the early intervention team suggests Charles’ family should be encouraged to voice their preferences. As the family lives in a small two bedroom condominium, a bulky wheelchair or large positioning devices will not be feasible. The team will have to research smaller positioning devices that can be folded and made portable. As Charles grows older, the early intervention team, which includes his parents, may consider introducing Braille for him. Throughout the decision-making process, the family must be placed in a pivotal position and their needs respectfully listened to and their suggestions adhered to. If a device is not working for the parents, if the technology is too difficult for them to understand, or if there is a problem with the device use at home, parents should be encouraged to communicate these challenges and their needs to professionals.

Early Childhood Family Outcome 3: Families Help Their Children Develop and Learn A safe, nurturing, and stimulating home environment is critical to the healthy development

of the child. Families must have the knowledge and understanding of effective ways to enhance their child’s learning within the daily routines and activities in natural environment (Dunst, Hamby, Trivett, Raab, & Bruder, 2000). For children who need special adaptive equipment, families must know how to use the special equipment to benefit their child in the home environment, the primary learning environment for young children. Researchers agree for the successful implementation of AT, it is imperative families are involved in the assessment and implementation. When AT is selected by the family it is more likely to be incorporated in use throughout the child’s daily routine (Judge & Parette, 1998). Further, training the family in the use of AT is critical to successful implementation of AT (Judge, 2002). Parents may need minimal training or no training in order to incorporate simple adaptations and low-tech devices such as special spoons, single switches, and Velcro in their child’s daily routines. However, families will require planned instruction in the effective use of high-tech devices such as powered wheelchairs, alternative and augmentative communication devices, and highly specialized switch interfaces that are not readily available (Long, Huang, Woodbridge, Woolverton, & Minkel, 2003; Mistrett, 2004). Despite the importance cited in research concerning parent training and the call for embedding instruction within the natural environments and daily routines and activities, Campbell, Milbourne, Dugan, and Wilcox et al. (2006) found that professionals did not train families using AT to embed high-tech and low-tech devices in their daily routines and activities. Instead, families were “provided separate training sessions that parents carried out at home” (p. 9). Only one in 23 studies reported teaching children to use voice output communication aids within the context of routines in special education preschool classrooms. Additionally, no studies reported routines-based instructions in a typical home environment. In their study of parent perception, Wilcox et al. (2006), found parents begin using AT with their

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child as early as 6 months of age. Parents reported a high use of low-tech, high-tech, and positioning devices with their infants and toddlers irrespective of the severity of their disability. Numerous challenges were cited in the study for low success rate in the use of the device, and thereby, increased probability of abandonment and underutilization of the AT. The findings suggest that families are often unaware of available resources supporting the use of AT. In addition, families received little support from service providers for locating or using these devices. A number of factors are responsible for children receiving appropriate AT services they need: financial resources (of both family and program, which includes health insurance) and access to the service delivery system (educational and medical). Contrary to popular belief, receiving early special education services does not guarantee that children’s AT needs will be met. In the United States, children primarily access AT services through the health care and public education systems. Carlson and Ehrlich (2006) revealed that the most common source of funding for AT is personal and family funds. Wilcox et al. (2006) also found that families identify, use, and pay for their preschool children’s AT. As in the previous two outcomes, we will now revisit another vignette and allow Zander and his family to guide us through early childhood family outcome three. Exposure to alcohol with additional environmental challenges of being confined to car seat and play pen has resulted in speech and motor delays for Zander. Once 16-month-old Zander was identified as having a developmental delay, he and his family began to receive services under IDEA. IDEA mandates that AT be considered when developing goals for the Individualized Family Service Plan (IFSP; or the Individual Education Plan, IEP). If Zander’s IFSP team, which includes his grandmother (who is Zander’s guardian and is legally responsible for Zander’s welfare), decide that AT is required for Zander to meet the IFSP goals, the needed AT must be

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provided by the agency. Occupational, physical, or speech therapists are typically responsible for assessment, acquisition, training, and follow-up processes required for providing the AT services in medical and educational settings (Benedict & Baumgardner, 2009). Due to Zander’s feeding problems the OT may suggest using special spoons or feeding bottles with a larger opening. The OT may also suggest special positioning and seating system for Zander to better support his body during play and daily living skills. Further, the speech therapist may provide Zander with adapted or off-the-shelf toys to help exercise his mouth muscles and practice inhaling and exhaling, which will further his feeding and speech development. As Zander grows older he may need low-tech augmentative communication devices such as picture cards or high-tech devices such as voice output devices to support his socialcommunication needs. Zander’s grandmother will need to be trained in the use of new high-tech or low-tech devices until she feels competent to use the AT by herself. However, throughout this process, the professionals will need to consult with the family during the Zander’s assessment, goal development, and choice of AT to best support his needs in the natural environment. They may also provide the family with a list of stores where they can purchase the AT and if needed, the professionals may suggest other no-cost options such as toy libraries or tech resource centers. In addition, professionals will help Zander’s family to identify the source of funding for the AT.

Early Childhood Family Outcome for Part B: Section 619 Preschool Programs Turnbull et al. (2005) suggest that family functions are affected when families proceed through a sequence of developmental stages, non-developmental stages and transitions throughout a child’s life. One of the important transitions for children with disabilities is the transition from the

Supporting Early Childhood Outcomes through Assistive Technology

family-focused service in early intervention (Part C) to child-centered education programs (Part B) on the child’s third birthday. IDEA requires a minimum of six months transition period from Part C to Part B services. Let us revisit Haley’s vignette and allow her and her family to guide us through this family outcome. The early intervention team has informed 26-month-old Haley’s parents about the upcoming transition. This period has been filled with the evaluations and meetings required by the law. Haley’s parents have met with her preschool teacher and have visited her new preschool. Despite the preparation, Haley’s family feels rushed to make decisions. They frequently feel the need for additional conversations to answer questions about Haley’s potential services. They wonder who will provide the services for Haley. Would the professionals be familiar with her Tango? Can she continue to use the Tango that her early intervention agency loaned her? What if she cannot? Would she have any AT to help her communicate? If a new device is provided, who will teach them how to use it? It took them and Haley almost six months to learn to use the Tango, thanks to the patient training with the early interventionist. What about the wheelchair Haley used? Would the new classroom have enough space for the wheelchair to maneuver? To support Haley’s family through the transition process, professionals from the local Part B agency receiving Haley, need to facilitate the family’s involvement as a means of improving services and results for Haley. They need to meet with her family prior to the transition meeting and take the time to listen to the questions and concerns that Haley’s family has. Since the sources of funding are different for the two agencies, the Part B team, along with the early intervention team, need to clearly plan the transition of the AT equipment when Haley moves to Part B. Early intervention agency may continue to loan the Tango to Haley until the Part B agency can make alternate ar-

rangements. Arrangements will also need to be made within the preschool classroom for Haley’s wheelchair and provide her easy access and maneuvering capabilities. Haley’s teacher may need to reconsider the layout of the classroom. The school administrator may consider an alternative classroom to accommodate the wheelchair if the classroom is too small. Additionally, administrators may reassign staff as Haley’s need for paraprofessional support in active participation in the classroom becomes evident. When Haley begins to receive services through Part B, the school will continue to facilitate parent involvement in all aspects of Haley’s education, through assessment, goal development, program planning, and decisions on the use of AT If any new technology is introduced, Haley’s family will need to be equal partners in decision-making and may need to be provided training with the technology.

Future reseArcH dIrectIons Our primary intent in this chapter is to present an outcome based framework for meeting early childhood outcomes for children with disabilities utilizing AT. As such, we are reluctant to offer too many conclusions about AT in early intervention. Clearly, we are able to identify a handful of “evidence-based” AT practices in early intervention according to criteria set forth by Campbell, Milbourne, Dugan, & Wilcox et al. (2006) and Mistrett et al. (2001). Despite the findings, gaps continue to be reported in AT research with infants and young children. Whether the reasons for these gaps are due to AT underutilization or abandonment, it is an area that bears further scrutiny. Additionally, one of our primary concerns is the misunderstanding of professionals and families about the power of AT in a young child’s life to meet developmental outcomes. The solution to meeting early childhood outcomes through AT has little merit if we, as professionals, are unable

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to overcome professional misunderstanding and discomfiture in the use of AT with very young children.

concLusIon This chapter focused on the application of AT to meet OSEP early childhood outcomes with attention given to evidence-based strategies and practices in the use of AT. As early childhood professionals reflect upon their experience, they begin to recognize the benefit AT has in meeting child developmental outcomes. By presenting a firm understanding for AT consideration the early childhood professional can assist children with disabilities and their families in meeting early childhood outcomes. Supported by legislative directives, young children with disabilities and their families are fundamentally entitled to AT that supports the knowledge, skills and experiences that contribute to positive lifelong goal attainment, it is hoped that these recommendations help to ensure the successful application of AT for young children with disabilities and their families for meeting childhood outcomes.

reFerences Allen, K. E., & Marotz, L. (2007). Developmental profiles: Pre-birth-twelve (5th ed.). Clifton Park: Delmar/International Thomson Publishers. Bailey, D. B., & Bruder, H. B. (2005). Family outcomes of early intervention and early childhood special education: Issues and considerations. Early Childhood Outcomes Center. Retrieved on August, 14, 2009, from http://olms.noinc.com/ olms/data/resource/1811/FamilyOutcomesIssues%20Bruder 20bailey05.pdf

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Bailey, D. B., Bruder, M. B., Hebbeler, K., Carta, J., Defosset, M., & Greenwood, G. (2006). Recommended outcomes for families of young children with disabilities. Journal of Early Intervention, 28, 227–251. doi:10.1177/105381510602800401 Bailey, D. B., McWilliam, P. J., & Winton, P. (1992). Building family-centered practices in early intervention: A team-based model for change. Infants and Young Children, 5, 73–82. Beckwith, L. (1971). Relations between attributes of mothers and their infants’ I.Q. scores. Child Development, 42, 1083–1097. doi:10.2307/1127794 Benedict, R. E., & Baumgardner, A. M. (2009). A population approach to understanding children’s access to assistive technology. Disability and Rehabilitation, 31, 582–592. doi:10.1080/09638280802239573 Butler, C. (1986). Effects of powered mobility on self-initiated behaviors of very young children with locomotor disability. Developmental Medicine and Child Neurology, 28, 325–332. Campbell, P. H., Milbourne, S., Dugan, L. M., & Wilcox, M. J. (2006). A review of the evidence on practices for teaching young children to use assistive technology devices. Topics in Early Childhood Special Education, 26, 3–13. doi:10. 1177/02711214060260010101 Carlson, D., & Ehrlich, N. (2006). Sources of payment for assistive technology: Findings from a national survey of persons with disabilities. Assistive Technology, 18, 77–86. Carta, J. J., Atwater, J. B., Greenwood, C. R., McConnell, S. R., McEvoy, M. A., & Williams, R. (2001). Effects of cumulative prenatal substance exposures and environmental risks on children’s developmental trajectories. Clinical and Child Adolescent Psychology, 30, 327–337. doi:10.1207/S15374424JCCP3003_5

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Centers for Disease Control and Prevention (CDC). (2009). Maternal and Infant Health Research: Preterm Birth. Retrieved August 14, 2009, from http://www.cdc.gov/reproductivehealth/ MaternalInfant Health/PBP.htm Dunst, C. J., Hamby, D., Trivette, C. M., Raab, M., & Bruder, M. B. (2000). Everyday family and community lives and children’s natural occurring learning opportunities. Journal of Early Intervention, 23, 151–154. doi:10.1177/105381 51000230030501 Dunst, C. J., & Shue, P. (2005). Creating literacy rich natural learning environments for infants, toddlers, and preschoolers. In Horn, E. M., & Jones, H. (Eds.), Supporting early literacy development. Young Exceptional Children (pp. 15–30). Longmont, CO: Sopris West. Early Childhood Outcomes Center (ECO). (2005). Family and child outcomes for early intervention and early childhood special education. Retrieved August 14, 2009, from http://www.fpg.unc. edu /~eco/assets/ pdfs/ECO_New%20requirement%20OSEP_9-7-06.pdf Early Childhood Outcomes Center (ECO). (2009). Retrieved August 14, 2009, from http://www.fpg. unc. edu/~eco/pages/fed_req.cfm Erwin, E. J., & Brown, F. (2003). From theory to practice. A contextual framework for understanding self-determination in early childhood environments. Infants and Young Children, 16(1), 77–87. Farmer, M. E., Klein, R., & Bryson, S. E. (1992). Computer-assisted reading: Effects of whole word feedback on fluency and comprehension in readers with severe disabilities. Remedial and Special Education, 13, 50–60. doi:10.1177/074193259201300208 Harter, S. (1978). Effectance motivation reconsidered: Toward a developmental model. Annual Human Resources Development Report, 21, 36–64.

Individuals with Disabilities Education Improvement Act, 118 Stat 2647. (2004). Isabelle, S., Bessey, S. F., Dragas, K. L., Blease, P., Shepherd, J. T., & Lane, S. J. (2002). Assistive technology for children with disabilities. Occupational Therapy in Health Care, 16, 29–51. doi:10.1300/ J003v16n04_03 Judge, S. (2002). Family-centered assistive technology assessment and intervention practices for early intervention. Infants and Young Children, 15, 60–68. Judge, S. L., & Parette, H. L. (1998). Family centered assistive technology decision making. Infant-Toddler Intervention, 8, 185–206. Keilty, B., & Gavin, K. M. (2006). Physical and social adaptations of families to promote learning in everyday experiences. Topics in Early Childhood Special Education, 26, 219–233. doi:10.1177/027 11214060260040301 Lesar, S. (1998). Use of assistive technology with young children with disabilities: Current status and training needs. Journal of Early Intervention, 21, 146–159. doi:10.1177/105381519802100207 Long, T., Huang, L., Woodbridge, M., Woolverton, M., & Minkel, J. (2003). Integrating assistive technology into an outcome driven model of service delivery. Infants and Young Children, 19, 272–283. McCormick, L. (1987). Comparison of the effects of a microcomputer activity and toy play on social and communication behaviors of young children. Journal of the Division for Early Childhood, 11, 195–205. Mistrett, S. (2004). Assistive technology helps young children with disabilities participate in daily activities. Technology in Action, 1(4), 1–8. Mistrett, S. G., Hale, M. M., Gruner, A., Sunshine, C., & McInerney, M. (2001). Synthesis on the use of assistive technology with infants and toddlers with disabilities (birth–two). Washington, DC: American Institutes of Research.

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National Early Childhood Technical Assistance Center (NECTAC). (2009). Retrieved August 14, 2009, from http://www.nectac.org/idea/idea.asp National Institute for Literacy (NIFL). (2009). Developing early literacy. Report of the early literacy panel. Retrieved August 14, 2009, from http://www.nifl.gov/publications/pdf/NELPReport09.pdf National Organization on Fetal Alcohol Syndrome. (n.d.). Retrieved August 14, 2009, from http://www.nofas.org. Parrette, H. P., & Hourcade, J. J. (1997). Family issues and assistive technology needs: A sampling of state practices. Journal of Special Education Technology, 13, 27–43. Pierce, R. L., & McWilliam, P. J. (1993). Emergent literacy and children with severe speech and physical impairments (SSPI): Issues and possible intervention strategies. Topics in Language Disorders, 13, 1–11. Schepis, M., Reid, D., Behrmann, M., & Sutton, K. (1998). Increasing communicative interactions of young children with autism using a voice output communication aid and naturalistic teaching. Journal of Applied Behavior Analysis, 31, 561–578. doi:10.1901/jaba.1998.31-561 Soto, G., Belfiore, P. J., Schlosser, R. W., & Haynes, C. (1993). Teaching specific requests: A comparative analysis on skill acquisition and preference using two augmentative and alternative communication aids. Education and Training in Mental Retardation, 28, 169–178. Spiegel-McGill, P., Zippiroli, S., & Mistrett, S. (1989). Microcomputers as social facilitators in integrated preschools. Journal of Early Intervention, 13, 249–260. doi:10.1177/105381518901300306

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Steelman, J. D., Pierce, P. L., & Koppenhaver, D. A. (1993). Emerging literacy and children with severe speech and physical impairments (SSPI): Issues and possible interventions. Topics in Language Disorders, 13, 47–57. Sullivan, M. W., & Lewis, M. (2000). Assistive technology for the very young: Creating responsive environments. Infants and Young Children, 12, 34–52. Technical-Related Assistance for Individuals with Disabilities Act of 1988 (Tech Act). (1998). Catalogue No. 850.(Senate Report 100-438). Washington, DC: US Government Printing Office. Turnbull, A. P., Summers, J., Turnbull, R., Brotherson, M. J., Winton, P., & Roberts, R. (2007). Family supports and services in early intervention. A bold vision. Journal of Early Intervention, 29, 187–206. doi:10.1177/105381510702900301 U.S. Department of Education Office of Special Education Programs (OSEP). (2006). Office of special education and rehabilitation services. Retrieved August 14, 2009, from http://www. ed.gov/about/ offices/list/osers/osep/index. html?src=mr Wehmeyer, M., & Palmer, S. B. (2000). Promoting the acquisition and development of selfdetermination in young children with disabilities. Early Education and Development, 11, 465–481. doi:10.1207/s15566935eed1104_6 Whaley, K. K. (1990). The emergence of social play in infancy: A proposed developmental sequence of infant-adult social play. Early Childhood Research Quarterly, 5, 347–358. doi:10.1016/0885-2006(90)90026-W Wilcox, J. M., Dugan, L. M., Campbell, P. H., & Guimond, A. (2006). Recommended practices and parent perspectives regarding AT use in early intervention. Journal of Special Education Technology, 21, 7–16.

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AddItIonAL reAdIng Beck, J. (2002). Emerging literacy through assistive technology. Teaching Exceptional Children, 35, 44–49.

Lieber, J., Horn, E., Palmer, S., & Fleming, K. (2008). Access to the general education curriculum for preschoolers with disabilities. Children’s school success. Exceptional Children, 16, 18–32. doi:10.1080/09362830701796776

Campbell, P. H., Milbourne, S., Dugan, L. M., & Wilcox, M. J. (2006). A review of the evidence on practices for teaching young children to use assistive technology devices. Topics in Early Childhood Special Education, 26, 3–13. doi:10. 1177/02711214060260010101

Light, J., & Drager, K. (2007). AAC technologies for young children with complex communication needs: State of the science and future research directions. Augmentative and Alternative Communication, 23, 204–216. doi:10.1080/07434610701553635

Clements, D. H., & Sarama, J. (2003). Young children and technology: What does the research say? Young Children, 58, 34–41.

Lund, S. K., & Light, J. (2006). Long-term outcomes for individuals who use AAC: Part I – What is a “good” outcome? Augmentative and Alternative Communication, 22, 284–299. doi:10.1080/07434610600718693

DeVore, S., & Bowers, B. (2006). Childcare for children with disabilities: Families search for specialized care and cooperative childcare partnerships. Infants and Young Children, 19, 203–212. DeVore, S., & Russel, K. (2007). Early childhood education and care for children with disabilities: Facilitating inclusive practice. Early Childhood Education Journal, 35, 189–198. doi:10.1007/ s10643-006-0145-4 Erwin, E. J., & Brown, F. (2003). From theory to practice. A contextual framework for understanding self-determination in early childhood environments. Infants and Young Children, 16, 77–87. Horn, E., Lieber, J., Sandall, S., Schwartz, I., & Wolery, M. (2002). Classroom models of instruction. In Odom, S. (Ed.), Widening the circle: Including children with disabilities in preschool programs (pp. 46–60). New York: Teachers College Press. Judge, S. (2002). Family-centered assistive technology assessment and intervention practices for early intervention. Infants and Young Children, 15, 60–68.

Lund, S. K., & Light, J. (2007). Long-term outcomes for individuals who use AAC: Part II – Expressive Communication. Augmentative and Alternative Communication, 23, 1–15. doi:10.1080/07434610600720442 Lund, S. K., & Light, J. (2007). Long-term outcomes for individuals who use augmentative and alternative communication: Part III - contributing factors. Augmentative and Alternative Communication, 23, 323–335. doi:10.1080/02656730701189123 Parette, H. P., Wojcik, B. W., Stoner, J. B., & Watts, E. H. (2007). Emergent writing literacy outcomes in preschool settings using AT toolkits. Paper presented at the Assistive Technology Industry Association (ATIA) Annual Meeting, Orlando, FL. Parrette, H. P., Blum, C., Boeckmann, N. M., & Watts, E. H. (2009). Teaching word recognition to young children who are at risk using Microsoft PowerPoint coupled with direct instruction. Early Childhood Education Journal, 36, 393–401. doi:10.1007/s10643-008-0300-1

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Peterson-Karlan, G. R., & Parette, H. P. (2008). Integrating technology into the curriculum. In Parette, H. P., & Peterson-Karlan, G. R. (Eds.), Research-based practices in developmental disabilities (2nd ed., pp. 183–214). Austin, TX: Pro-Ed. Turnbull, A. P., Summers, J., Turnbull, R., Brotherson, M. J., Winton, P., & Roberts, R. (2007). Family supports and services in early intervention. A bold vision. Journal of Early Intervention, 29, 187–206. doi:10.1177/105381510702900301

key terms And deFInItIons Boppy Pillow: An ergonomically correct positioning pillow reducing stress to the body. The Boppy pillow makes positioning during feeding, lying, playing supported.

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Down Syndrome: A chromosome disorder due to an extra chromosome number 21 (trisomy 21). Down syndrome causes mental retardation, and multiple facial and physical malformations. High-tech: Technology device with electronic or motor functions such as computers, mobility devices, and communication aids. Individualized Education Plan (IEP): A written document for each eligible child ages 3-21 with a disability that is developed, reviewed, and implemented by education team. Individualized family service plan (IFSP): Process and a document intended to assist families and professionals in a combined effort to meet the developmental needs of a child from age birth to three with a disability or developmental delay. Low-tech: A technology device with simple, passive, lacking or limited moving parts.

Section 6

Past, Present, and Future

It has often been stated that we learn from past experiences. While that is true in the context of developing assistive devices, we also find that the landscape is in such a state of change that it is difficult to predict the future based on what we know today about learners with diverse needs. The presence of learners with diverse needs, caused by disabilities, is changing. Technologies are advancing. The costs of computer technology are becoming more affordable. Social networking is changing communications and greater investments are being made in technologies that benefit all learners. Freeware and shareware are gaining in popularity in the market place with the pooling of talent. And, we are seeing younger people with a life time of exposure to technology, becoming the entrepreneurs of the future. This is not to suggest that the past holds no value as one looks to the future of assistive technologies. However, it does suggest that the changing conditions of the present may have greater impact on the future than what has occurred in the past. Just as obsolescence in computer technology occurs at a rapid rate, so may those ideas that were driven by the past for the creation of assistive technology become obsolete? As odd as that sounds, it is not uncommon in research and development units, where students are employed, to have significant ideas shared by students, naive in the focus of the research, but tuned into technologies that have a positive influence on the learning of young adults. If there is an area in which programmatic research applies, it may well be in the area of assistive technologies. In programmatic research, there is a focus of work committed to the long term, often carried through from conceptualization to development, research and implementation. It is formative in nature in that participants are always open to new ideas and to changes in their consumer needs and the contributions of the many disciplines that impact their work. While outputs emerge, there is always new work evolving. Nothing seems to be the consummate solution. Offering a list of needs for the future would be presumptuous; however, with some risk, it may be appropriate to share a couple of ideas for readers of this section. Those engaged in the development and research on assistive technologies, are creative people committed to visions of what needs to be done with technology to benefit diverse learners. Thus, areas of emerging work being done today that benefits all diverse learners will be reinforced. The first example is the work being done that integrates cognitive science with technology that is delivered by interactive student tutorials. Of particular importance is the reduction of cognitive load. For example, the teaching of mathematics via online tutorials is often complicated by the level of reading required by the learner to benefit from the learning experience in mathematics. Through the use of animation and interactivity, combined with scaffolding and feedback, students have a greater opportunity to demonstrate what they are learning in the targeted area of instruction. Their rate of learning and retention may also improve. A second area that is evolving with great potential for the future includes the integration of the Computer Adaptive Testing (CAT) model into elearning instructional models that result in instructional decision-making as a systemic element of the elearning experience. While teachers are adept at evidenced-based instruction decision-making, the frequency and level of instructional decision-making could be altered through change in elearning models allowing teachers to devote more time to the challenges presented by diverse learners. This could also result in instructional time becoming more powerful.

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Chapter 25

Assistive Technology’s Past, Present and Future Barbara J. Kouba California State University, San Bernardino, USA Brian Newberry California State University, San Bernardino, USA

AbstrAct Even though the term is relatively new, assistive technologies of various types have helped people overcome, achieve, and perform for many years and come in many forms. In fact, many familiar technologies, some that might even be considered mainstream, were in fact initially conceived as assistive devices. Recently, assistive technology has become the subject of legislation including the Rehabilitation Act and the Americans with Disabilities Act and much more legislation regarding access to and funding for assistive technology is expected. Currently, much attention in the area of assistive technology focuses on the computer, and communications technology, including portable devices, which help individuals use powerful tools for accessing information and communicating with others. The future of assistive technology certainly will continue these areas of development but will also likely begin to adopt newer methods for interfacing various assistive technologies directly with the human sensory system. As has happened in the past, it is expected that many technologies initially created as assistive will be adopted by non-disabled individuals.

IntroductIon In 1967, the Fab Four harmonized their lyrical insights: “I get by with a little help from my friends,” and, “I’m gonna try with a little help from my DOI: 10.4018/978-1-61520-817-3.ch025

friends” (Lennon & McCartney). Increasingly, the Beatle’s perceptive words are true for everyone, and they have an even greater importance for people living with special needs. In order to communicate, function, and participate in this society, people with disabilities need extra help and rely on some form of assistive technology (AT).

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Assistive Technology’s Past, Present and Future

bAckground Anyone can become a person with disabilities. Former President Ronald Reagan, credited with tearing down the Berlin Wall, and Hollywood superhero, Christopher Reeve, both became individuals with disabilities. It is not an exclusive club. Young and old, rich and poor, famous and obscure, powerful and weak, males and females can all belong. No exceptions are made for race, creed, nationality, sexual preference, or socioeconomic status. Helen Keller, one of the most admired persons in 20th century America, was both deaf and blind. In her 1957 book, Ms. Keller said, “All about me may be silence and darkness, yet within me, in the spirit, is music and brightness, and color flashes through all my thoughts” (Keller, 1957). Educator Annie Sullivan helped to break through the silence and darkness to release this inner light. As Helen Keller learned to communicate, her genius emerged. Throughout history, people with disabilities were often relegated to lead frustrated, isolated, and dehumanized existences. Some even trace the origins of the word “handicap” to describe people with disabilities as beggars who went “cap in hand” (Barnes, 1992). Twenty-first century technology can complement basic education by delivering a voice to the voiceless, sound to the deaf, sight to the sightless, movement to the incapacitated, and independence to the dependant. Marcia J. Scherer, Ph.D. referred to these people as “lives nearly lost forever” and spoke of the assistive technology revolution by comparing the past and present opportunities for users: The choices available today for communication— from gestures to wordboards to computerized devices that speak for the person—are nothing short of a major revolution. Today, the mind of a child born with cerebral palsy who cannot speak is not apt to be a mind “nearly lost forever.” That

child will go to school and will be a visible member of the adult community (2005, p. 34). Without the ability to communicate, whether naturally or through artificial devices, learning, self-improvement, and social inclusion are impossible. Stephen Hawking, Ph.D. is one of the most recognized users of AT. Without the use of AT, Professor Hawking would have been unable to share his scientific genius with the rest of the world. This brilliant mathematician and theoretical physicist discovered that when one fused the ideas of quantum mechanics with those of general relativity, it was no longer true that black holes were completely black. Throughout most of his adult life, Dr. Hawking has had Amyotrophic Lateral Sclerosis (ALS), a motor neuron disease. Through the use of augmentive communication devices, the professor continues sharing his teachings, lectures, and written works. In the 1970s, Dr. Hawking’s speech became so slurred that very few people could understand him. By 1985, after undergoing a tracheotomy to help him breathe easier, he lost all remaining abilities to speak. For several years, the only way he could communicate was to spell out words letter by letter, by raising his eyebrows when someone pointed to the correct corresponding letter on a spelling card. It was laborious for this genius to carry on a simple conversation, let alone write a scientific paper. David Mason, of Cambridge Adaptive Communication, fitted a small portable computer and a speech synthesizer to his wheelchair. This system allowed the professor to communicate much better. He was able to manage up to 15 words a minute which he could either speak or save to disk. Once in a digitized format, his thoughts could be printed out or disseminated using a variety of methods, including email. Using this system, he began to write books and scientific papers and has also given many scientific and popular talks.

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In the June 20, 2001 edition of Business Week Online, John Williams (2001) described the impact of AT on the life of Professor Hawking: Had Stephen Hawking lived a century ago, many of his thoughts on the universe would never have been recorded, and the world would have lost tremendous input from a truly original and great mind. Here’s a model example of how assistive technology is contributing mightily to the intellectual capital of the world. “While I have lost the ability to speak, I have not lost my ability to think. These products were designed specifically for people, like me, who can’t speak,” says Hawking. Now, the world can hear him loud and clear, as he unlocks the mysteries of the universe thanks to intelligence, perseverance, software, and hardware. Clearly, AT has impacted the life of Professor Hawking as it has the lives of countless others in the past, continues to do so today, and will continue on into the future. The past, present and future of AT is one of breaking down barriers, overcoming obstacles, and adding capacity to perform.

dentures, prosthesis devices, drinking tubes, the talking telegraph, and optical technologies. Interestingly, many technologies that were developed initially for people with disabilities became mainstream in time. Within the past 200 years, technology was developed for people with disabilities that became embraced by the entire society because of its benefit for all members. Many of these devices are so essential they are not even considered AT. Some of these technologies include: •

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•

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History of Assistive technology Thomas W. King, in his book, “Assistive Technology Essential Human Factors,” explained the perception that AT being a recent human development is inaccurate. He described people in many cultures throughout history (and prehistory) who have been brilliantly creative in adapting, developing, and using special tools and devices to help others in their societies with special needs (King, 1999). Indeed, the phrase assistive technology may have been recently coined, but the concept of AT seems to be as old as human ability to innovate. Many have described various simple strategies that heralded the development of more complex solutions. Some important technologies include

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• •

•

•

•

Typewriter: developed in 1808 by Pellegrino Turri so his blind friend, Countess Carolina Fantoni da Fivizzono, could write legibly. Telephone: developed by Alexander Graham Bell in 1876 as a device to help people with hearing loss. Hearing Aid and Headset: developed in 1916 by Harvey Fletcher working at the Research Division of Bell Labs. Recorded music: developed in 1934, the Readphone reproduced literature and music on long-playing discs to be used by the blind. Later, these discs became 33-1/3 RPM records, the precursor to CDs and eventually digitized music. Audio Books: used by the American Foundation for the Blind in 1935. Speech synthesis: developed in 1936 by H.W. Dudley at Bell Labs to help deaf or hard-of-hearing people learn to speak intelligibly. Tape recorder: commissioned by National Bureau of Standards in 1948 for a lowcost reliable talking-book machine for the blind. Speech recognition: developed at Bell Labs in 1952 as an off-shoot of Alexander Graham Bell’s work to ease the isolation of the deaf. Captioning: developed in 1960 by Pilgrim Imaging for the Captioned Films for the

Assistive Technology’s Past, Present and Future

•

•

•

•

•

•

Deaf Program, under the Department of Health, Education and Welfare. Chat Rooms: developed in 1964 by two deaf California scientists who attached a teletype machine to a telephone system so long-distance phone communication could take place between deaf people. Text Messaging: developed in 1972 by Vinton Cerf, one of the pioneers in the development of the ARPANET, precursor of the Internet. Cerf was hard-of-hearing and wanted a way to communicate electronically with his wife and other deaf friends. Optical Character Recognition Technology: developed in 1975 by Ray Kurzweil as a way for blind users to have access to type-written text. Picture-based keyboards: developed in 1988 to enable people who could not speak. This technology is now used mostly in fast food restaurant point-of-sale machines. Online newspapers: used by the National Federation of the Blind in 1994 as a dial-up, synthetic-speech, talking daily newspaper available for blind or low vision people. Loopset: released by Nokia in 1998 allowing hearing aid users to talk on digital mobile phones. Ushered in hands-free operation of telephone.

Assistive technology Legislation and mandates Even though life-altering AT has been developed, it does not necessarily mean that it is immediately available for the people who need it. Invisible barriers, such as prohibitive cost and lack of access, serve as tangible obstacles. In the past few decades, landmark laws and mandates have been enacted to help overcome these obstacles to help improve the lives of people with disabilities. Many of these were inspired by the successful civil rights legislation of the 1960’s, and the disability rights movement in the United States has motivated

federal and state legislatures to legislatively improve the lives of people with disabilities. These laws and mandated standards regulate business, government, and architectural practices resulting in equal employment, housing, and educational opportunities (Wattenberg, 2004; First & Hart, 2002; Frieden, 2003; Levy, 2001).

sections 504 and 508 of the rehabilitation Act In the history of the disability rights movement, Section 504 of the Vocational Rehabilitation Amendments of 1973 represented a significant coming together of the disability community (Lathrop, 1997). The Act’s passage began legal protections for students at elementary schools, colleges, and universities from discrimination based on physical, mental, or learning disabilities. These rights included many types of reasonable accommodations in the physical facilities, programs, and specialized services that enable students with disabilities the same opportunities as those students without disabilities. Under Sections 504 and 508, the Rehabilitation Act attempts to prevent discrimination in employment and education in any facility receiving federal monies. In 1998, amendments to Section 508 expanded these guarantees to electronic and information technologies (Wattenberg, 2004).

Americans With disabilities Act (AdA) Millions of Americans heralded the enactment of the Americans With Disabilities Act (ADA) of 1990 as the landmark victory that awarded longdenied civil rights for people with disabilities. It was expected that this historical legislation would usher in major social change, impacting every level of government, business, and education. This has in fact been the case. In addition, after 18 years, the United States Congress amended the Americans with Disability Act. Effective January 1, 2009,

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major changes have been enacted affecting the way the definition of disability is interpreted. One purpose of this Act is to carry out the ADA’s objectives of providing “a clear and comprehensive national mandate for the elimination of discrimination” and “clear, strong, consistent, enforceable standards addressing discrimination” by reinstating a broad scope of protection to be available under the ADA.” (The ADA Amendments Act of 2008, Section 2 (b) (1)). In other words, the purpose of the original ADA was to eliminate discrimination. However, if hardly anyone was covered, then hardly anyone was actually being protected from discrimination. So, in the Amendments Act, Congress fixed the definition of disability to cover more people and as a result, prevent more discrimination. That means that once the Act goes into effect, the question of who has a disability will no longer be the main focus; instead, the focus will be on whether discrimination has occurred.

technology related Assistance for Individuals with disabilities Act (tech Act) The United States Congress recognized the importance of technology in the lives of people with disabilities and passed the Technology Related Assistance for Individuals with Disabilities Act (Tech Act) of 1988. It was replaced with the Assistive Technology Act of 1998. This legislation established projects in each state to implement changes in laws and policies, develop information resources, and provide legal advocacy services.

section 255 of the telecommunications Act Section 255 of the Telecommunications Act of 1996 required telecommunications products and services, including the Internet, to be accessible to people with disabilities. Section 255 has sig-

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nificantly increased the availability of accessible telecommunications products and services to people with disabilities both in the workplace and at home (Moulton, Huyler, Hertz, & Levenson, 2002).

Web Accessibility Initiative The Web Content Accessibility Guidelines 1.0 have been adopted by the World Wide Web Consortium (W3C) as the Web Accessibility Initiative. Guidelines provide comprehensive methodology and production standards for Web development to ensure accessibility.

comprehensive Individuals with disabilities Act (IdeA) The makeup of traditional classrooms has changed due to disability rights legislation concerning inclusion and students with special needs. Under the Comprehensive Individuals with Disabilities Act (IDEA), each child, regardless of disability, is entitled to a “free, appropriate public education (FAPE) in the least restrictive environment appropriate to his/her individual needs.” Moreover, IDEA amendments require that the Individualized Education Program (IEP) teams consider whether a student requires AT and services. If such a determination is made, federal law mandates that all AT devices and services be provided free of charge by the local school district. This legislation marked a significant shift in how AT is viewed. Prior to the 1997 reauthorization of the IDEA, AT had been viewed almost exclusively within a rehabilitative or remediative context. Within the context of planning individualized education plans, technology was now considered a viable tool for expanding access to the general education curriculum. With the growing acceptance of AT, much work needs to be done to ensure that IEP teams consider the maximum benefits of technology.

Assistive Technology’s Past, Present and Future

current AssIstIve tecHnoLogy The thirty-second President of the United States used canes, eyeglasses, braces, automobile hand controls, and wheelchairs to help him guide the American people out of the Great Depression and through World War II. But even Franklin Delano Roosevelt would be amazed at the evolution of the very items that sustained him throughout his four terms in office. In fact, especially since the advent of microchips and personal computers in the 1980s, the AT field has exploded. Screen reading, screen magnification, speech recognition, optical character recognition, augmentative and electronic communication, microprocessor augmented prosthetics, GPS technology, and universal design have opened educational and vocational doors of opportunity for millions of people. If these trends continue, an exciting future awaits AT users. Current technology will be improved, new technology will be developed, and as-yet inconceivable hybrid technology will emerge. Despite this and although most people consider AT to involve specialized microprocessor-based computer equipment, it can be as commonplace as adapted eating utensils, lowered drinking fountains, curb cuts, bendable straws or eyeglasses. King (1999) described the most commonly prescribed AT relied on by well over half of the population of North America is optical – glasses and contact lenses. Consider how vision augmentation has moved beyond eyeglasses. We now have contact lenses, implantable lenses and various surgeries all designed to reshape the eye in order to improve vision. Over the past two centuries, Western society has embraced assistive, enabling optical technologies to the point they are now an invisible AT. This universal acceptance comes with little or no social penalty or stigma, regardless of age group. In reality, all technology can be considered assistive in that it augments users’ capabilities

to perform a given task. In understanding AT, it is important that society becomes aware of this view and appreciate how enabling technology has become a seamless part of everyone’s life. AT is not necessarily some esoteric technology used only by a small segment of population; instead, many mainstreamed tools are readily used by people with and without disabilities. Four common examples of this phenomenon are computer accessibility applications, literacy tools, way-finding devices, and speech recognition technology.

current comPuter AccessIbILIty APPLIcAtIons Most people find it easy to turn on a computer, click a mouse, tap a keyboard, use a software application, and surf the Web. Twenty-first century technology has transformed the way society learns, works, plays, and communicates. Regrettably, this same technology is not always user friendly for people with disabilities, who comprise nearly 18.7% of the American population (Brault; U.S. Census Bureau, 2008). Assistive Technology exists to maintain, increase, or improve functional capabilities of children and adults with disabilities and bridges this digital divide by utilizing innovative accessibility equipment. The inherent design of a computer requires use of vision and motor skills. King (1999) noted, “If you have visual difficulties that preclude you from seeing the keyboard and/or monitor screen, or if you have motoric difficulties that interfere with or preclude your ability to press the keys on a standard computer keyboard, you will be effectively locked out of use of the personal computer” (p. 18). To help overcome some of the challenges that blind computer users experience, various software applications have been developed. Screen reading software converts visual text to other more accessible formats. In a drive to incorporate more Universal Design, Windows and Macintosh

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operating systems are designed with basic screen readers included. Speech synthesizers allow users to listen to material. For computer users who process information in a tactile way, the screen reading programs can send it to refreshable Braille displays. Optical Character Recognition (OCR) technology is used in conjunction with a computer and a flatbed scanner. Type-written text (not handwritten documents) can be scanned, recognized, translated, and read aloud to the user. Computer users with limited vision rely on magnification software to enlarge the screen content. Magnification levels range from 1x – 36 x. The greater the magnification, the smaller the proportion of the original screen content that can be viewed; that is why users tend to use the lowest magnification level they can manage. Other features also provided include color inversion, smoothing, pointer cursor and color enhancements, and screen reading capabilities. Alternative data entry devices can include software, hardware, and non-technical technologies. A plethora of software exists to augment keyboards and mice or to bypass them entirely. Morse Code Software involves a system of dots and dashes used to represent the characters on a keyboard. It is available as freeware, but is often bundled with switch input devices. Voice recognition applications convert spoken words into screen text. After a successful training period when the software learns to recognize the user’s voice, every keystroke or mouse click that would otherwise be entered with a keyboard or mouse can be entered through voice command. Accessibility features built directly into Windows and Macintosh Operating Systems include Sticky keys and an On-screen keyboard. Sticky keys provides a modifier key, such as Shift, Ctrl, or Alt that can be pressed and remains active until another key is depressed. This alleviates the need to use two fingers simultaneously for those computer users who can use only one hand, one finger, or for those using mouthsticks. People with arthritis, tremors, or spasms can also benefit from

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these readily available tools. On-Screen Keyboards display virtual keyboards onto computer screens. Users can enter data by using a mouse or an alternative input device to select the screen contents without having to rely on a standard keyboard or mouse. Hardware alternative input devices vary greatly. Some are developed for use with hands or feet, others with breath or mouth. Some track eye or head movements and the newest genre are designed to interact cerebrally with a person’s thoughts. Alternative and ergonomic keyboards have been miniaturized, expanded, and even re-designed into one-handed styles. Switches, touch screens, pen systems, scanners, alternative mice, touchpads, joysticks, and trackballs are also available. Typical non-technical pointing devices can range from modular mouth sticks to inexpensive unsharpened pencils with eraser tips. A mouth stick is a plastic stick designed to be placed in the mouth and has a rubber tip at the end. This tip gives a user with no use of hand usage the ability to press keyboard keys, activate mouse or trackball buttons, and turn pages.

current Literacy tools Spell checkers are comprised of programming routines that scan text and compare it with a list of correctly spelled words. Any words not in the algorithms are flagged and the user can accept the suggested form or choose from a list of other suggested words or phrases. Originally developed in the late 1970s for mainframe computers, spell checkers have moved to more ubiquitously used applications such as word processors, web browsers, and email clients. In the past 30 years, software developers have built on the widespread acceptance of spell checkers. Even more sophisticated programs have evolved that assist users with grammar, homophone usage, and word meaning. All these tools help users navigate the sometimes murky waters of

Assistive Technology’s Past, Present and Future

complicated language structures. Although some language arts professionals criticize literacy tools as a form of laziness and an inability to learn the nuances of language, most users welcome the assistance and consider it an essential aid to improve writing, research, and communication skills. This criticism is oftentimes refuted as being unfounded and compare literacy tools to other emerging technologies that society once decried. One often-cited comparison is with the criticism by early Greek philosophers of the print culture. Even Socrates complained about writing, feeling it forced one to follow an argument rather than participate in it, and he disliked both its alienation and its persistence. He was unsettled by the idea that a manuscript travelled without the author, with whom no argument was possible. Worse, the author could die and never be talked away from the position taken in the writing (Kay, 1991). Over the centuries, printed material evolved to benefit the masses; but, at the dawn of the 21st century, electronic material has quickly replacing printed text as the preferred form of communication. For this nascent technology, specialized tools are emerging to improve accessibility to all users. To benefit people with cognitive processing disabilities, spell checkers and other literacy tools provide added functionality. Built-in spell checkers, grammar programs, and dictionaries are the most common form of AT for people with language processing difficulties. Having the immediate ability for software to flag incorrectly spelled words or improper grammar usage alerts the user and provides multiple modalities to process the complexities of language successfully. People with mobility limitations often struggle with standard means of inputting data through a keyboard. Having literacy tools such as word prediction help limit the amount of keyboarding required. Furthermore, built in synonym and dictionary tools provide an all-in-one environment that limits the amount of extra movements required.

Computer users with vision limitations also benefit from language tools. Because blind users are unable to see the actual words on a screen, screen reading technology provides an auditory means to navigate through applications. Literacy tools such as spell checkers will automatically flag misspelled words so the user is able to ascertain whether or not the word in question is spelled correctly. However, this is not always effective with words that sound alike but have vastly different meanings. Homophone tools provide an added benefit so people with vision limitations can choose the correct usage of words that are pronounced identically. Early software tools were unable to point out the correct contextual use of words but newer programs are addressing this important facet of language. A project funded by the National Institute on Disability and Rehabilitation Research of the U.S. Department of Education, reported that the study was conducted to evaluate the effectiveness of four AT tools on literacy. These were speech synthesis, spell checkers, a homophone tool and an electronic dictionary (Lange, McPhillips, Mulhern, & Wylie. 2006). A total of 93 secondary-level students with reading disabilities participated in the study which found that these technologies have a positive effect on literacy among students with reading disabilities.

current Way-Finding devices On June 26, 1993, the United States Air Force launched the 24th Navstar satellite into orbit, completing a network of 24 satellites known as the Global Positioning System, or GPS. Like the Internet, this technology was originally developed for military applications but was soon embraced by the civilian sector. A popular way-finding device used in the first decade of the 21st century is a small GPS receiver costing less than a few hundred dollars. It gives immediate feedback about the user’s location on

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the planet in terms of latitude, longitude, and even altitude. Some GPS receivers have the ability to store attribute information in addition to position information. Examples of attribute information are street signs, names of roads, or the condition of a fire hydrant. Position and attribute information can be stored in a Geographic Information System (GIS) to help users manage their assets more efficiently. Within the past decade, this technology has become so commonplace that it is built into ground transportation, automobiles, boats, golf carts, and airplanes. It is used in such diverse fields as weather forecasting, space exploration, mining, telecommunications, and tourism/recreation. Through voice guidance, drivers can receive turn-by-turn voice and video directions to their destination by announcing lane guidance, street names, and directions. Real time traffic reports are also able to be relayed and users can be directed around traffic bottlenecks. Traveling without benefit of being able to see signs and other way-finding cues places extreme demands on travelers with visual impairments and can severely limit peoples’ horizons resulting in exclusion rather than inclusion. It can also force individuals to become overly dependent on others, thus creating a life of dependence. In a worst case scenario, people with vision limitations can be thrust into dangerous or even life-threatening situations. Accurate to within a few feet, GPS receivers, maps, and points of interest databases can provide spoken and/or Braille access to location information in any outdoor environment. GPS technology provides compact accessibility that allows users critical navigational information so the traveler can make informed decisions about route, path of travel, direction and destination. It can provide essential location information including street names, approximate addresses, and selected points of interest so a blind user can explore unknown areas, find businesses and community services, access public transportation, and follow a route to a selected destination. Having access to this

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range of choices dramatically increases the ease, efficiency and safety of the travel experience. In the spring of 2006, a project examined the impact of GPS technology on the orientation and mobility of 12 secondary students with visual impairments (Special Education Technology). The project, known as Trekker, used an accessible PDA-based GPS device to help the participants learn how to navigate their environment better. Surveys and interviews were completed by both students who applied to participate in the GPS project and their orientation and mobility instructors. In addition, interviews with instructors were conducted after three months to record the short term feedback on impact of GPS technology in orientation and mobility instruction. Informal responses from students were also invited at the three month mark. Data from three-month followup interviews indicated that GPS technology: • • • •

Helped the students become more confident to explore their community. Increased sense of safety, lessened fear of being lost, and provided a safety net. Lessened cognitive load for order of streets on route to destination. Helped students to feel more connected to their community, providing information on community services and places.

current speech recognition technology Speech recognition refers to the ability of a machine or software to understand spoken words for the purpose of receiving data input from a speaker. When these words are converted, specific commands or actions are completed. In 1966, American science fiction fans were introduced to speech recognition technology in the Star Trek fictional universe created by Gene Roddenberry. “Computer On” became a familiar command enticing viewers with the ease with which the 23rd century Starship Enterprise crew

Assistive Technology’s Past, Present and Future

was able to communicate with their powerful mainframe-like centralized computers. Within a few decades, speech recognition jumped from the realm of imaginative television scripts to 20th century reality. Its use is becoming increasingly more widespread as its multifaceted capabilities are being realized. One of the earliest domains for the commercial application of speech recognition in the United States was health care; in particular, the field of medical transcription. The impact has also been felt in the fields of law, military, air traffic control, and business document completion. In the early 21st century smart phones, speech is commonly used as an integral user interface. For those with disabilities, the benefits of speech recognition technology are manifold. A wide range of physical disabilities can prevent people from using a keyboard—from arthritis and amputation, to repetitive stress injuries and paralysis. An alternative for many people is to use their voices for data input. After a brief training period, they can operate a computer or telephone by voice commands. Individuals with learning disabilities can also benefit from speech recognition technology and is an important alternative for people who have difficulties transferring their thoughts to written communication. The humane implementation of technology to assist those with disabilities ensures all members will be able to play an active role in society. For anyone needing more pragmatic rather than purely legalistic or altruistic reasons, Sara Basson, Ph.D., Director of Accessibility Services for IBM Global Services, said, “It’s just good business.” (Franklin, Wilson, & Ebel, 2004). It’s good business probably because it is potentially so profitable. The disabled population of the United States, almost 20 percent of the country’s adult population, has a potential disposable income to rival that of the coveted teenager market. With advances in medical and rehabilitation services and the teeming number of Baby Boomers entering their retirement years, the number

of people with disabilities continues to grow. Although humans will live longer and healthier lives than at any time in history, everyone, at one time or another, will be in need of some form of AT.

Future oF AssIstIve tecHnoLogy Imagine a day without technologies such as a spell checker, a GPS in-vehicle navigation system, eye glasses or contacts and then understand that all technology is assistive. Technology permits individuals to do things they couldn’t otherwise accomplish or to do things better or faster than would be possible without the technology. This broad definition of AT is not accepted by everyone. For example, Cook and Hussey (2007) note that the term AT does not normally include devices that are used by the non-disabled. However, with the advent of Universal Design, the idea that measures taken, or technologies created to make anything more user friendly has been done so merely for those who are labeled disabled is outdated (Rose & Meyer, 2002). Universal Design is good design and good design helps everyone. The future of AT is bright, and it seems that increasingly the definition of AT will continue to blur as the same technologies that some use to play games will be used by others to access email and communicate on the job. Recent developments in AT have largely involved, or have been driven by, advancement in communications technologies, especially those related to computer assisted technologies. Future AT may well become possible because of developments in human-machine interfaces that effectively create a direct connection between the human nervous system and machines. The categorization of existing AT into several groups can provide a glimpse into AT’s future. Mobility aids, such as wheelchairs, scooters, leg braces, crutches, etc. are examples of one category

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of existing technology. Recent advancements in prosthetics led to a challenge that almost kept double amputee sprinter, Oscar Pistorius, from being able to try out for the Bejing Olympics because his carbon fiber prosthetics were thought by some to give him an advantage over competitors with two normal legs (Longman, 2007). Although no advantage was proven in the case of Pistorius, the trend suggests that at some point some prosthetics may indeed prove to be, in some ways, superior to the limbs they replace. In the nearer future, mobility devices that do not rely on joystick or mouthstick directions might be available. Instead, a network of brainwave detectors may be arranged to receive the user’s thoughts that will then be interpreted into direction and speed commands for the device. Related developments will no doubt continue the many recent advances made in computer controlled prosthetic devices which also network directly with the nervous system. Aside from mobility improvements via canes, crutches and chairs, some of the earliest ATs were aimed at augmentation of senses to enhance abilities, such as in the case of eyeglasses and hearing aides. Technology continues to improve the effectiveness of these aides and to develop alternatives to some. For example, various surgeries have been developed to address various visual impairments and in some cases can result in better than normal eyesight for some patients. Functioning artificial eyes have been developed and cochlear implants help thousands to once again hear sound. The trend-line suggests that such developments will continue to improve. There has been an explosion of technologies that build on the availability of Global Positioning Systems (GPS) technologies to provide wayfinding assistance. These devices range from the simple hand-held GPS systems that assist people so they know where they are, to advanced systems that provide turn-by-turn directions from point-topoint. Current mobile phone technology integrates this capability to provide the user’s whereabouts through the phone’s location. Additionally one

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can now get a phone that uses GPS and various databases to allow the user to locate nearby businesses or places of interest. These capabilities will be embedded in more and more devices and perhaps even one day into clothing, eyeglasses or sunglasses. With the advent of neural interfaces, these capabilities will be available as direct sensory input. These could be combined to provide clothing that directs individuals towards their expected or desired destinations or to help them remember where they are supposed to go or be. Information access and storage has been a large area of development for ATs. The range of technologies, both hardware and software, that are designed to assist individuals with disabilities to use computers, access information on the Internet and to communicate with others has grown exponentially. This is another area that in the future promises to be enhanced greatly by emerging technologies that connect the human nervous system with machines. A demonstration of this technique allowed an individual to move a mouse cursor on a computer screen with thoughts alone (Pollack, 2006). Another initiative has demonstrated an electrode studded cap that can be worn by a user who can then control a cursor on a screen (BBC, 2004). Interfaces like these, and those that may be implanted, have the potential to allow individuals to do much more than control a cursor. For example, a researcher had an array of sensors implanted in his arm and through this neural interface he was able to control a robotic hand and an electric wheelchair (Warwick, Gasson, Hutt, Goodhew, Kyberd, Andrews, Teddy, & Shad, 2003). Others have demonstrated that cap-mounted neural interfaces can be used by individuals with disabilities to navigate the virtual environment Second Life (Science Daily, 2008). These and other devices will permit individuals with various challenges to access electronic information as effortlessly as thinking. These devices will no doubt be combined with new categories of software to augment the

Assistive Technology’s Past, Present and Future

individual memory. This might include facial recognition abilities that prompt the user with the name of people they know but have forgotten. Another useful tool would be social behavior prompts to help users speak and act appropriately in whatever circumstances they find themselves. Additionally such devices could augment users’ memories by allowing them to access memories and information stored in machines rather than in their own brains. There has been a generalized communication revolution underway, in part attributable to the widespread adoption of the Internet as well as cell phone and other portable devices. This has resulted in increased modes of communication as well as an increased acceptance of forms of communication that make use of various technologies. Many of the technologies, now taken for granted, such as spell and grammar checkers, are in a very real way assistive in that they help improve communication attempts by making them conform to higher standards of production. Many of these forms of communication are asynchronous, meaning that there is an acceptable and even expected time between communication events. This time lag allows more time to more carefully craft messages and, in the case of individuals who have difficulty using available interfaces, this time lag provides them the opportunity to communicate at a speed that is most effective for them while removing any stigma that difficulty in participating in other forms of communication can bring. The future promises more developments in AT to improve everyone’s communication abilities. It is not difficult to foresee the development of communication improvement tools that not only help with spelling and grammar, but with production and presentation of communication as well. In other words, software will no doubt be developed that will examine communication and suggest better ways of phrasing or structuring

that communication. In addition, improvements in speech recognition software can be anticipated to better apprehend meaning from non-standard vocal, or even direct from brain thoughts via neural transponders, utterances. This software could even be extended to help the user shape the message in multiple ways. The future promises tools that will serve as real time translators from one language to another allowing those with the disability of knowing only one language to better communicate with the world. Additionally, these real time tools, which will no doubt first be text-based, but which could mature to work in an auditory mode through generated speech, might even be able to perform grammatical corrections on the fly to improve not only the tone of communication, but also its quality. The future of AT will be characterized by advances in human/machine interfaces that remove or circumvent barriers to individuals’ ability to interact with their environment, move confidently in the world, access information and communicate with others. These new ATs will be so useful that they will become technologies used by many in society which will further blur the lines between what is considered AT and technologies for the masses. This blurring will herald needed attention to legislation dealing with AT. Areas that may need examination or review include funding requirements and the use of devices that result in better than “normal” abilities. As more ATs are adapted by mainstream society, the stigma associated with using such devices will no doubt be diminished. In addition, with larger markets, such ATs can be expected to be available to all at much more attractive prices than if the technologies were only able to serve a smaller more specialized population. Ultimately, all technology is assistive and as Universal Design has shown, good design, and good technologies work well for all.

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reFerences Barnes, C. (1992). Disabling imagery and the media: An exploration of the principles for media representations of disabled people. Derby: The British Council of Disabled People. Brault, M. (2008). Current population reports. Household economic studies. Americans With Disabilities: 2005. U.S. Census Bureau. Retrieved from http://www.census.gov/prod/2008pubs/ p70-117.pdf Business Week Online. (2001, June 20). Retrieved from http://www.businessweek.com/bwdaily/ dnflash/jun2001/nf20010620_067.htm Cook, A. M., & Hussey, S. (2007). Assistive technologies: Principles and practice (2nd ed.). St. Louis, MO: Mosby. First, P., & Hart, Y. (2002, October). Access to cyberspace: The new issue in educational justice. Journal of Law & Education, 31(4), 385–411. Franklin, C. Jr., Wilson, T., & Ebel, M. (2004). Preparing for the Americans with Disabilities Act. Frieden, L. (2003). When the Americans with Disabilities Act goes online: Application of the ADA to the Internet and the worldwide web (1st ed.). Washington, DC: National Council on Disability. Kay, A. (1991). Computer, networks and education. Scientific American. September. Keller, H. (1957). The open door. Garden City, NY: Doubleday & Company. King, T. W. (1999). Assistive technology essential human factors. Boston: Allyn & Bacon. Lange, A., McPhillips, M., Mulhern, G., & Wylie, J. (2006). Assistive software tools for secondarylevel students with literacy difficulties. Journal of Special Education Technology, 21(3), 13–22.

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Lathrop, D. (1997, April). Remember 504. Mainstream, 32-34. Lennon, J., & McCartney, P. (1967). With a little help from my friends [Recorded by The Beatles]. On Sgt. Pepper’s Lonely Hearts Club Band [CD]. London, UK: EMI Records Ltd. Levy, T. (2001). Legal obligations and workplace implications for institutions of higher education accommodating learning disabled students. Journal of Law & Education, 30(1), 85–121. Longman, J. (2007, May 15). An amputee sprinter: Is he disabled or too-abled? The New York Times. Retrieved from http://www.nytimes. com/2007/05/15/sports/othersports/15runner. html?pagewanted=1 Moulton, G., Huyler, L., Hertz, J., & Levenson, M. (2002). Accessible technology in today’s business. Microsoft Press. Network Computing. Retrieved from http://www. networkcomputing.com/gswelcome/showArticle. jhtml?articleID=26806213 News, B. B. C. (2004). ‘Brainwave’ cap controls computer. Retrieved December 7, 2004, from http://news.bbc.co.uk/1/hi/technology/4074869. stm Pollack, A. (2006). Paralyzed man uses thoughts to move a cursor. Retrieved July 13, 2006, from http://www.nytimes.com/2006/07/13/ science/13brain.html Rose, D., & Meyer, A. (2002). Teaching every student in the digital age: Universal design for learning. Alexandria, VA: Association for Supervision and Curriculum Development. Scherer, M. (2005). Living in the state of stuck: How assistive technology impacts the lives of people with disabilities (4th ed.). Cambridge, MA: Brookline Books.

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Science Daily. (2008). Using brainwaves to chat and stroll through Second Life: World’s first. Retrieved from http://www.sciencedaily.com/ releases/2008/06/080613163213.htm Special Education Technology. (n.d.). The GPS project. Retrieved from http://www.setbc.org/ news/docs/gpsproject.html The ADA Amendments Act of 2008. (2008). Section 2 (b) (1). Retrieved from http://www.access-board. gov/about/laws/ada-amendments.htm U.S. Equal Employment Opportunity Commission Notice Concerning The Americans With Disabilities. Act (ADA) Amendments Act Of2008. (n.d.). Retrieved from http://www.eeoc.gov/ada/ amendments_notice.html Warwick, D., Gasson, M., Hutt, B., Goodhew, I., Kyberd, P., & Andrews, B. (2003). The application of implant technology for cybernetic systems. Archives of Neurology, 60(10). doi:10.1001/ archneur.60.10.1369 Wattenberg, T. (2004). Beyond legal compliance: Communities of advocacy that support accessible online learning. The Internet and Higher Education, 7, 123–139. doi:10.1016/j. iheduc.2004.03.002

key terms And deFInItIons Americans with Disabilities Act (ADA): American legislation that specifies many rights for individuals with disabilities. Assistive Technology (AT): Technologies designed to augment individuals with disabilities capacity to receive sensory information, access information, communicate, orient themselves and navigate. Global Positioning System (GPS): A combination of a satellite network and various devices that provide real time data about location, altitude and speed. These are often integrated in a way that allows the user to use on-screen maps and in some cases synthesize voice systems that provide turn by turn navigation assistance. Optical Character Recognition (OCR): Computer software/hardware that transforms printed text to machine readable formats. Web Accessibility: Specifications and guidelines that help ensure that individuals with disabilities are able to access and use resources available via the Internet.

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Chapter 26

Digital Inequity:

Understanding the Divide as it Relates to Culture and Disability Monica R. Brown New Mexico State University, USA Michael Fitzpatrick New Mexico State University, USA

AbstrAct A major challenge in education is to ensure that ALL students are prepared for the technological advances of the 21st century and beyond. This means that ALL students must have access and use of information/educational technologies (I/ET), including assistive technologies for students with disabilities, in their schools. Unfortunately, there is evidence that indicates that I/ET is not equitably distributed in schools and across all types of students (i.e., students with disabilities and students from culturally and linguistically diverse (CLD) backgrounds) (Brown, 2004; Brown, Higgins, & Hartley, 2001; Fitzpatrick & Brown, 2008). This chapter will: (a) discuss what access and use looks like for certain at-risk populations (i.e., students with disabilities and CLD students), (b) discuss some of the factors that account for the inequitable access and use of I/ET for those groups, and (c) offer solutions for increasing I/ET access and use for students with disabilities and CLD students.

IntroductIon As we move further into the 21st century, it is evident that technology (instructional/educational and assistive) will continue to play an integral part in the lives of children and adults. And, as it becomes increasingly prevalent, there will continue to be concern regarding the “digital divide” between those children and adolescents who are benefitting DOI: 10.4018/978-1-61520-817-3.ch026

and those who are potentially being left behind (i.e., students with disabilities and students from CLD backgrounds) (Brown, 2004; Brown, Higgins, & Hartley, 2001; Fairlie, 2005; Fitzpatrick & Brown, 2008; Mossberger & Tolbert, 2003; U.S. Department of Commerce, 2002). The most recent data from the Computer and Internet Use Supplement to the Current Population Survey (CPS) of 2003 detailed information on computer and Internet access. The report indicated that there is a large and substantial digital divide that

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Digital Inequity

currently exists in the United States. This divide may have serious economic consequences for disadvantaged (i.e., CLD students and students with disabilities) groups as I/ET skills are becoming increasingly more important in the labor market, and the Internet is expected to become a primary medium for communication, commerce, education, and entertainment in the 21st century (U.S. General Accounting Office, 2001). Advancements (e.g., economic, educational, and political) for these groups may hinge on access to and effective use of computers, the Internet, and other technologies (Fairlie, 2005). There is a need for greater understanding of ways in which culture and other forms of diversity affect information/educational technology (I/ ET) access and use. There is a noticeable digital divide with regard to computer and Internet access and use by certain groups (i.e., students with disabilities and students from CLD backgrounds) of individuals and this topic has been discussed in the literature (Brown, 2004; DeBell & Chapman, 2003; Fairlie, 2005; U.S. Department of Commerce, 2002). In order to gain a better understanding of the issues associated with I/ET access and use for students with disabilities and students from CLD backgrounds, we will examine digital equity in education by combining several datasets in order to present a picture of I/ET access and use for the aforementioned groups. We will show that I/ET are, in fact, distributed and used differentially across student demographics (disability status and race/ethnicity). Therefore, this chapter will: (a) discuss what access to and use of I/ET looks like for students with disabilities and CLD students, (b) discuss some of the factors that account for the inequitable access and use of I/ET for those groups, and (c) offer solutions for increasing I/ ET access and use for students with disabilities and CLD students. Additionally, we will offer topics for future research regarding technology access and use for students with disabilities and CLD students.

bAckground Prior to delving into this issue, it is important to make a distinction between I/ET and assistive technology (AT) as it is used in this chapter. The literature is replete with definitions of I/ET and AT. Typically, AT was considered only for students with developmental disabilities because it was thought that these devices (e.g., communication wallets, electronic communication devices, wheelchairs, prone standers, adapted eating utensils, large print or books on tape, Braille watches, closed-circuit television units, hearing aids, etc.) were necessary for their “compensatory” function and helpful in compensating for the students’ deficits that are barriers to their achievement. There is a clear relationship between the function lost or impaired and the function AT replaces or enhances (Blackhurst, 2005). Sadly, Warger (2005) noted that there is still misunderstanding regarding the “compensatory” nature of AT despite the widespread availability of resources containing descriptions of devices and services available to educators. It was once believed that AT were devices provided only to persons with sensory, physical, and communication disabilities (Parette & Peterson-Karlan, 2007). Their visible disabilities were perceived as something that required AT to help compensate for some deficit (e.g., deafness, blindness) exhibited by the children. However, there has recently been a convergence of student achievement-related factors emphasizing not just physical access, but also the role of AT in facilitating access to educational experiences as a means to achieving important curricular outcomes (for example, in the general education environment). Assistive technology can now be used for educational functions associated with academic deficits and learning disabilities (Edyburn, 2000). There is a range of technology that can support students with their reading, writing, math, information acquisition, organization, and cognitive processes. But, there is oftentimes a blurring of

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the distinctions between I/ET and AT. Instructional/educational technology is defined as the application of “scientific knowledge about human learning to the practical tasks of teaching and learning” (Newby, Stepich, Lehman, & Russell, 2000, p. 10). It typically addresses three desired learning outcomes of instruction, including: (a) instructional effectiveness (results in the students learning a better way than without the I/ET experience), (b) instructional efficiency [results in the same amount (or more) learning in a shorter amount of time], and (c) instructional appeal (enhances the possibility that students will devote time and energy to the learning task) (Parette & Peterson-Karlan, 2007). Instructional/educational technology in the classroom is used to teach new skills, supplement or expand the curriculum, or remediate skill deficits (Parette & Peterson-Karlan, 2007). They are helpful, but not essential to learning. However, when students with disabilities require continued use of the I/ET tool after its use in typical “learning situations” is done for the student without disabilities, the tool becomes “compensatory” and is then AT (i.e., individually matched to and uniquely required for a student to make educational progress or participate in the curriculum and/or classroom (Rose, Hasselbring, Stahl, & Zabala, 2004). As Peterson-Karlan and Parette (2005) pointed out, AT allows the student to: (a) access the classroom materials, media and instructional activities; (b) enhance their productivity; (c) increase the amount, frequency, rate, and duration of communication; and (d) improve his or her work output while decreasing cognitive or physical time and effort. Ultimately the goal of AT is to augment and develop student capacity to increase the quality of their communication skill sets, social interactions, and academic outcomes.

digital divide/equity defined There have been numerous attempts over the years to define the digital divide. Mossberger and Tolbert

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(2003) used it to describe patterns of unequal and inequitable access to I/ET based on factors such as income, race/ethnicity, gender, age, disability status, and residence in urban and rural areas. Becker (2006) considered I/ET to be “a set of learning resources distributed differentially across student and school characteristics” (p. 3). In 2003, Soloman, Allen, and Rester described differential access to I/ET in education as digital equity. To address the digital divide/equity, schools must provide full access for special populations of students (i.e., students with disabilities and CLD students) to the Internet, as distance learning and multimedia materials (Mason & Dodd, 2005). The following sections will address the demographic factors, specifically the inequity that exists for students based on race/ethnicity (e.g., African American, Asian/Pacific Islander, Latino/a, and Native American) and disability status.

Issues, controversy, And ProbLems As schools become more and more challenged by a technologically-savvy student population, they have been forced to incorporate the use of computers and the Internet into the curricula. Unfortunately, not all students (i.e., students with disabilities and CLD students) are afforded the same access to it, and this inability to keep pace has created a digital divide that is continuing to widen (Mason & Dodd, 2005). There is no shortage of research confirming the existence of a digital divide along racial/ethnic and disability lines (Brown, 2004; Fitzpatrick & Brown, 2008; Kalyanpur & Kirmani, 2005; Mellander, 2007; U.S. Department of Commerce, 2000; U.S. Department of Commerce, 2002). This divide particularly affects students who are African American, Latino/a, Native American, are poor and/or have a disability (Bohlin & Bohlin, 2002; Mellander, 2007). These groups are less likely to have computers or Internet connections at home

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than their Caucasian or Asian peers (Fairlie, 2005). Therefore, schools become the primary source of computer and Internet access and are oftentimes the only place they can go online. Additionally, many students with disabilities cannot use the computers to participate in online activities because the equipment in their schools is not compatible with their learning and/or physical needs (Mason & Dodd, 2005). Next we take a closer look at how the digital divide affects each of those aforementioned populations.

I/et and African-American students Statistics indicated that as of 2001 about threequarters of the children between 5 and 7 use computers at school and 56 percent use computers at home (DeBell & Chapman, 2003). Despite this increase in access and use at home and at school, other research has indicated a somewhat polarized picture of technology access and use in U.S. schools (Dividing Lines, 2001). Schools serving Latino/a, African-American, and low socioeconomic status (SES) students tended to have the least access, and the most remedial usages of new technology (Brown, 2004; Dividing Lines, 2001). In addition, there is a significant gap in home computer ownership and Internet access between African-American and Caucasian households (Brown, 2004; DeBell & Chapman, 2003). The No Child Left Behind Act of 2002 (NCLB, P.L. 107-110) and its subset Enhancing Education Through Technology (ED Tech) program was enacted to improve the academic achievement of elementary and secondary schools through technology use, and help students become technically literate by grade 8, and to ensure that teachers were in fact integrating technology into the curriculum to improve student achievement (Judge, 2005). Numerous studies have found that, on average, African-American children arrive at kindergarten or 1st grade with lower levels of school readiness than their Caucasian counterparts (Farkas, 2003; Lee & Burkham, 2002). Additionally, we know

these things regarding African-American children and computer and Internet use: (a) AfricanAmerican children are much less likely to have access to computers in the home than Caucasian, non-Latinos (50.6% to 74.6%) (Fairlie, 2005); (b) African-American children are less likely to have Internet access at home (40.5% to 67.3) (Fairlie, 2005); and (c) One out of 7 African-American children has broadband at home compared to 26.1% of Caucasian, non-Latinos (Fairlie, 2005). However, African-American students are aware that the digital divide is not solely about computer and Internet access. It involves access to the social networks that ease the path to success in high-tech careers (Payton, 2003).

I/et and Latino students According to Bohlin and Bohlin (2002), Latinos were the most highly underrepresented ethnic group in the United States in terms of computer usage and computer science participation. And, despite the fact that ethnic groups have made progress in computer usage and Internet access, the gap between Latinos and Caucasian non-Latinos was still considerable and had increased during the second half of the last decade (Bohlin & Bohlin, 2002). Additionally, Fairlie (2005) reported that: (a) all Latino groups were less likely to own a computer or have Internet access at home than are Caucasian, non-Latinos; (b) one out of 8 Latino children had broadband at home compared to 26.1% of Caucasian, non-Latinos; and (c) Latino home computer and Internet access rates were lower than Caucasian, non-Latino rates (51.6 and 40.9% respectively). Likewise, DeBell and Chapman (2006) reported that for students living in households that speak only Spanish, the rate of computer use was 11 percentage points lower than those in households where other languages (usually English) are spoken. And, that Internet use by students in Spanish-speaking monolingual households was less than half of students in other households.

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Many reasons have been posited regarding why the divide is increasing for this population, both economic and affective. In fact, Badagliacco (1990) found that Latino students had the least favorable attitudes toward computers, Bohlin and Crozier (1996) found that 4th grade Latino students had more negative attitudes toward computers than African-American and Caucasian students, and Bohlin and Bohlin (1998) found that Latinos students believed learning about computers to be important, but did not see that they would be personally important to their future. Factors affecting the usage of technology for CLD students includes not only differences in cultural values, as pointed out by Guice and McCoy (2001), or communication styles (Janey Wang, 2001), but also language barriers (National Education Association, 1997). For Latino students, Cullen (2001) pointed out that “the use of English as the lingua franca of the Internet is far more inhibiting than English speakers realize” (p. 9). For students for whom English is a second language (ESL), there is: (a) a dearth of high-quality software and websites in languages other than English (Gorski, 2005); (b) when there are software programs and websites available, the content is often based on stereotypical assumptions of interests (Gorski, 2005); (c) ESL programs tend to be poorly funded and often lack basic computer equipment, thus restricting ESL students’ access when they are included in typical academic classrooms (Zehr, 2001); and (d) directions in drop-down menus are often in English, making it more difficult for older students with limited English proficiency (LEP) to acquire the skills to manipulate software programs (Kalyanpur & Kirmani, 2005). Despite the information gap between Latino students and their peers, there is hope for closing the gap between this traditionally marginalized group and their peers. The National Education Association (1997) found that when traditionally marginalized ESL students are introduced to technology towards creating multimedia presentations

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of their homelands and cultural heritages, that they feel empowered and less isolated from their peers because they are the technology experts, or at least are perceived as such. It is obvious that there are barriers to decreasing the technology divide that exists between Latino students and their peers. But, before this can be achieved, we must find ways to change the attitudes that these children have towards the potential benefits of technology to their current and future lives.

I/et and native American students In 2001, Davis and Trebian (2001) illustrated the dismal picture of Native Americans and their access to the nation’s infrastructure. They reported that: (a) 76.4% of rural Native American households had access to telephones, far below the national average of 94.1%; (b) 26.8% of rural Native American households had access to computers, again below the national average of 42.1%; and (c) only 18.9% of Native American households had access to the Internet, compared to the 26.2% national average. Additionally, the Benton Foundation (1999) reported, in their study of Native networking in Indian country, that: (a) of 185 schools supported by the Bureau of Indian Affairs on Reservations, only 76 (41.1%) were connect to the Department of Interior’s Internet service T1 lines; (b) classroom cable drops were present in 104 schools; (c) more than 80% of some homes on reservations (i.e., some in New Mexico, Arizona, and Utah) lacked telephone services; and (d) as of 1998, TribalWeb, showed that only 100 of 550 (18.2%) tribes had official websites accessible to the public. A cursory check of TribalWeb (see http://www.doi.gov/bia/ia_tribal_directory. html) indicated that there are now 180 tribal sites available, up from the 100 in 1998. Although this is nearly double the sites from 1998, it still only represents 32.7% of all 550 tribes. In 2002, Twist asked where Native Americans were regarding online/Internet access and use. In February of 2002, the U.S. Department

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of Commerce’s National Telecommunication Information Administration (NTIA) released A Nation Online. As with Falling Through the Net (U.S. Department of Commerce, 2000), the NTIA report served as a reference point for those interested in developments with the digital divide. Unfortunately, as with Falling Through the Net, there was no data relating to Native Americans included in the report by the U.S. Department of Commerce (2002). Consequently, there was no current measurement of progress of information technology efforts with Native American populations. The concern with this exclusion was that critical issues regarding Indian Country’s digital divide were being excluded from the radar screen of federal decision makers. To illustrate this divide between Native American and other populations, researchers reported that: (a) one out of 8 Native American children has broadband at home compared to 26.1% of Caucasian, non-Latinos (Fairlie, 2005); (b) 26.8% of rural Native American households have computer access, compared to the national average of 42.1% (OMB Watch, 2002); (c) 18.9% of Native Americans reported having Internet access, compared to the national average of 26.2% (OMB Watch, 2002); (d) 39% of rural households in Native communities have telephones, compared with 94% for non-Native rural communities (OMB Watch, 2002), (e) 9% of rural Native households have personal computers and, of those, 8% have Internet access (OMB Watch, 2002); and (f) 90% of Native schools and libraries have basic computer and Internet access, yet lack access to high-speed Internet connections (OMB Watch, 2002). Access to technology is a requirement for having any part to play in the future of society as education, politics, and economic functions are progressively being digitized (Sherson, 2000). Although this is true, there is still a segment of society that is clearly not connected and therefore ends up on the “unconnected” side of the divide. Native Americans are one such group. Because of a complex set of geographic, economic, and

social factors a lack of connection has occurred. To illustrate the lack of connectedness between Native American populations and technology, Guice and McCoy (2001) reported what they observed at two tribal schools. They found that the most important issue affecting technology use in the two tribal schools they visited involved the tribe’s attitudes towards education. The authors concluded that differences in cultural values, and not lack of funds and materials, were the real cause of the digital divide for these two schools. As is evident from the wealth of research available extolling the benefits (i.e., social, financial, educational, etc.) of access to technology, Native American are still not connected to the extent they should be. The research suggests many barriers (i.e., lack of infrastructure, cultural and identity, weak economic base, lack of education and training, lack of information, and/or exclusion from federal discourse) (Sherson, 2000; Twist, 2002) to closing that divide and one can see how each could be an impediment to Native communities’ closing the technology gap. However, until both sides find ways to mitigate these barriers, Native American children will not be able to bridge the digital divide, and consequently they remain disconnected from information and miss out on the educational, social, and affective benefits of technology.

I/et and students with disabilities As with the aforementioned marginalized groups, the spread of the Internet and other technologies has the potential to enhance the lives of people with disabilities (PWD) (Dobransky & Hargittai, 2006). But, one would be hard pressed to identify existing research to suggest that PWD are actively participating in these new technologies. In fact, there are numerous studies in the United States and elsewhere that have found that PWD lag behind those without disabilities in access to computers and the Internet (Kaye, 2000; U.S. Department of Commerce, 2000, 2002).

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Soloman (2000) suggested that not only is there a digital divide but possibly a “disability divide” as well. To support this assertion, in 2000 the U.S. Department of Commerce reported their major findings, including: (a) people with disabilities were half as likely to have Internet access and computer use than their peers without disabilities and (b) More people with disabilities had never used a computer compared to their peers without disabilities (60% and 25%, respectively). Additionally, Kaye (2000) reported that people with physical disabilities were less than half as likely to have computer access at home as people without physical disabilities (23.9% and 51.7%, respectively).

soLutIons And recommendAtIons Novice and veteran educators will continue to encounter complex problems within the classroom and school setting which were not addressed in their teacher preparation programs. For example, Turner (2007) claimed that “preparing prospective teachers to work effectively with culturally diverse students remains an ongoing challenge” (p. 12) and Smith (2000) suggested that educators are entering the classroom ill prepared to effectively use or implement technology. Each of these factors often leaves educators wrestling with issues of how to implement technology (Bauer & Kenton, 2005) and differentiate curriculum and instructional strategies (Carson & Johnston, 2000). The following suggestion focuses on teacher preparation and advocates for technology integration and culturally responsive curriculum. Although Higgins, Belland, Conceicao-Runlee, Santos, and Rothenberg (2000) and Lombardi, Bauer, Peters, and O’Keefe (1992) focused on the use of technology in SPED teacher preparation programs; Smith (2000) advocated for greater technology-rich teacher preparation programs

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because the impact of technology integration has on educators within these programs is one area that needs more research (Pollard & Pollard, 2004/2005; Roblyer & Knezek, 2003). Moreover, the dearth of literature and research related to how teacher preparation programs address the unique educational needs of CLD students with disabilities continues to pose difficulties for educators when implementing AT and I/ET devices and services. One factor is related to special educator’s confidence when matching the needs of students with appropriate AT and IT devices and services. According to Michaels and Mcdermott (2003) effectively implementing AT helps students with disabilities participate in the general education curriculum. Based on the issues outlined above, teacher preparation programs need to focus on technology integration (Brown, Higgins, & Hartley, 2001; Edyburn, 2000; Kovalik, 2003) and technology awareness (Anderson & PetchHogan, 2001). Aside from technology integration and awareness, teacher preparation programs need to address culturally responsive curriculums (Ajayi, 2005; Costa, McPhail, Smith, Brisk, 2005) and characteristic traits. Below are five characteristics that Grant and Gillette (2006) suggested that every educator should possess: (a) have the ability to build a community of learners and connect with the students’ families, (b) vary instruction to meet the unique needs of CLD students, (c) recognize that CLD students have a wealth of knowledge and skills and use these in teaching, and (d) be introspective about themselves and their teaching and monitor actions for bias. Finally, in addition to these five character traits, Valentin (2006) suggested that a holistic approach needs to be used to look at diversity throughout all teacher education programs in order to determine an accurate understanding if the programs are adequately preparing preservice educators for diverse classrooms.

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Future reseArcH dIrectIons Unfortunately, despite the research presented in this chapter, CLD students with disabilities continue to receive inadequate support with regards to AT and I/ET. Therefore, in an effort to promote the integration of AT and I/ET and increase access to the general education curriculum for CLD students with disabilities, this section provides suggestions for future research directions. The following recommendation is based on the belief that integrating AT and I/ET will enhance the academic and social outcomes for CLD students with disabilities. Accordingly, the authors hope that each recommendation will stimulate action on the part of practicing professionals working with CLD students with disabilities. Theoretically general and special educators born after the 1980s are considered “digital natives” (see Tapscott, 1997). Conversely Prensky (2001) suggested that individuals born prior to the 1980s are considered “digital immigrants” and are often resistant to interacting with technology. Sadly, beyond what has been presented in this chapter, we know very little about how educators who have been in the field for more than ten years incorporate technology (Fitzpatrick & Knowlton, 2009) especially for CLD students with disabilities (Fitzpatrick & Brown, 2008). Regardless if an educator is an “immigrant” or “native” they must come to school equipped to use technology pedagogically (Fitzpatrick & Knowlton, 2009). According to Becker (2001), educators with constructivistic mindsets typically employ computer-based and computer-assisted instruction in sophisticated ways. Additionally Wozney, Venkatesh, and Abrami (2006) suggested that educators who are comfortable with using technology in their personal lives are more likely to incorporate technology into their classroom. Therefore it is recommended that educators learn how to generalize their ability to use technology in their personal lives and apply their knowledge of technology to transform their classrooms.

Finally, evidence suggests that learners born during the outset of the digital age and after are different thinkers than their elders (Fitzpatrick & Knowlton, 2009). However, as noted earlier, the key is that both digital “immigrant” and “native” educators must come to their classroom equipped to employ technology and to engage in life-long learning as trackers of the advances in AT and I/ ET applications for ALL students including CLD students with disabilities.

concLusIon Compared to the last 200 years, recent technological advances have had the greatest impact on civilization (McDonald & Hannafin, 2003) and as discussed in previous chapters innovative highand low-tech AT and I/ET devices and services enhance the learning outcomes of students with disabilities (Raskind & Higgins, 1998). However, despite current and past legal mandates (e.g. IDEA, 2004) educators often have difficulties implementing technology into their curriculums for CLD students with disabilities. As discussed throughout this chapter, these difficulties have exasperated the digital divide and created a sense of digital inequity among CLD students with disabilities within k-12 educational settings. Although African Americans and Asian/ Pacific Islander’s have experienced major issues regarding technology integration, Latinos and Native Americans are the two most underserved CLD groups when attempting to access and use AT and I/ET. As noted above, the increasing digital divide with regard to computer and Internet access and use by CLD students with disabilities has been discussed in the literature (Brown, 2004; DeBell & Chapman, 2004; Fairlie, 2005; U.S. Department of Commerce, 2002). Regrettably, despite the slowly emerging literature base regarding CLD students with disabilities, it is difficult to employ AT and I/ ET for this student population because of factors ranging from archaic equipment to systems that

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do not meet the unique individual needs of the student population. To address these issues, this chapter outlined a variety of issues, trends, and specific strategies preservice and inservice educators can use to employ AT and I/ET when working with CLD students and students with disabilities. Therefore, to ensure optimal learning outcomes occur, educators must systematically introduce I/ET and/or AT into their daily routines (Luft, 2008), make sure all barriers are removed, and be cognizant of how the technology is being used.

reFerences Administration, Economics and Statistics Administration (NTIA). (n.d.). Retrieved August 1, 2009, from www.ntia.doc.gov/ntiahome/fttn00/ Falling.htm Ajayi, L. J. (2005). A sociocultural perspective: Language arts framework, vocabulary activities and English language learners in a second grade mixed classroom [Electronic version]. Journal of Instructional Psychology, 32, 180–195. Anderson, C. L., & Petch-Hogan, B. (2001). The impact of technology use in special education field experience on preservice teachers’ perceived technology expertise. Journal of Special Education Technology, 16(3), 27–44. Badagliacco, J. M. (1990). Gender and race differences in computing attitudes and experience. Social Science Computer Review, 8(1), 42–43. doi:10.1177/089443939000800105 Bauer, J., & Kenton, J. (2005). Toward technology integration in the schools: Why it isn’t happening [Electronic version]. Journal of Technology and Teacher Education, 13(4), 519–546.

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Becker, H. J. (2001, April). How are teachers using computers in instruction? Paper presented at the annual meeting of the American Educational Research Association. Retrieved July 9, 2007, from http://www.crito.uci.edu/tlc/findings/ conferences-pdf/how_are_teachers_using.pdf Becker, J. D. (2006). Digital equity in education: A multilevel examination of differences in and relationship between computer access, computer use and state-level technology policies. Education Policy Analysis Archives, 15(3). Retrieved May 13, 2009, from http://epaa.asu.edu/epaa/v15n3/ Benton Foundation. (1999). Native networking: Telecommunications and information technology in Indian Country. Retrieved August 14, 2009, from http://www.benton.org/publibrary/native/ indexnew.html Blackhurst, A. E. (2005). Historical perspective about technology applications for people with disabilities. In Edyburn, D., Higgins, K., & Boone, R. (Eds.), Handbook of special education technology research and practice (pp. 3–29). Whitefish Bay, WI: Knowledge by Design. Bohlin, R. M., & Bohlin, C. F. (1998, March). Educational implications for limited English proficient students’use of computers. Paper presented at the American Educational Research Association Annual Conference, San Diego, CA. Bohlin, R. M., & Bohlin, C. F. (2002). Computerrelated effects among Latino students: Educational implications. TechTrends, 46(2), 29–31. doi:10.1007/BF02772072 Bohlin, R. M., & Crozier, K. (1996, April). A comparison of the computer anxiety, confidence, and attitudes of African-American, Latino, and South-east Asian middle grade students. Paper presented at the American Educational Research Association Annual Conference, New York.

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Brown, M. R. (2004). Access granted: Achieving technological equity in the 21st century. In Edyburn, D., Higgins, K., & Boone, R. (Eds.), Handbook of special education technology research and practice (pp. 105–118). Whitefish Bay, WI: Knowledge by Design, Inc. Brown, M. R., Higgins, K., & Hartley, K. (2001). Teachers and technology equity [Electronic version]. Teaching Exceptional Children, 33(4), 32–39. Carson, T., & Johnston, I. (2000). The difficulty with difference in teacher education: Toward a pedagogy of compassion [Electronic version]. The Alberta Journal of Educational Research, 46(1), 75–83. Costa, J., McPhail, G., Smith, J., & Brisk, M. E. (2005). Faculty first: The challenge of infusing the teacher education curriculum with scholarship on English language learners [Electronic version]. Journal of Teacher Education, 56(2), 104–118. doi:10.1177/0022487104274119 Cullen, R. (2001). Addressing the digital divide. Online Information Review, 25(5), 311–320. doi:10.1108/14684520110410517 Davis, T., & Trebian, M. (2001). Shaping the destiny of Native American people by ending the digital divide: The nation’s tribal colleges and universities. EDUCAUSE Review, 38–46. DeBell, M., & Chapman, C. (2003). Computers and Internet use by children and adolescents in 2001 (NCES 2004-014). Washington, DC: National Center for Education Statistics, U.S. Department of Education. DeBell, M., & Chapman, C. (2006). Computer and Internet use by students in 2003 (NCES 2006-065). U.S. Department of Education. Washington, DC: National Center for Education Statistics.

Dobransky, K., & Hargittai, E. (2006). The disability divide in Internet access and use. Information Communication and Society, 9(3), 313–334. doi:10.1080/13691180600751298 Edyburn, D. L. (2000). Assistive technology and students with mild disabilities [Electronic version]. Focus on Exceptional Children, 32(9), 1–24. Fairlie, R. W. (2005). Are we really a nation online? Ethnic and racial disparities in access to technology and their consequences. Retrieved May 12, 2009, from http://www.civilrights.org/ publications/nation-online/ Farkas, G. (2003). Racial disparities and discrimination in education. What do we know, how do we know it, and what do we need to know? Teachers College Record, 105, 1119–1146. doi:10.1111/1467-9620.00279 Fitzpatrick, M., & Brown, M. R. (2008). Assistive technology access and use: Considerations for culturally and linguistically diverse students and their families. Journal of Special Education Technology, 23(4), 47–52. Fitzpatrick, M., & Knowlton, E. (2009). Bringing evidence-based self-directed intervention practices to the trenches for students with emotional and behavioral disorders [Electronic version]. Preventing School Failure, 53(4), 253–266. doi:10.3200/PSFL.53.4.253-266 Gorski, P. C. (2005). Multicultural education and the Internet: Intersections and integrations (2nd ed.). Boston: McGraw Hill. Grant, C. A., & Gillette, M. (2006). A candid talk to teacher educators about effectively preparing teachers who can teach everyone’s children [Electronic version]. Journal of Teacher Education, 57, 292–299. doi:10.1177/0022487105285894

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Guice, A. A., & McCoy, L. P. (2001). The digital divide in Native American tribal schools: Two case studies. Paper Presented at the Annual Meeting of the American Educational Research Association, Seattle, WA, April 10-14, 2001.

Luft, P. (2008). Examining educators of the Deaf as “highly qualified” teachers: Roles and responsibilities under IDEA and NCLB [Electronic version]. American Annals of the Deaf, 152(5), 429–440. doi:10.1353/aad.2008.0014

Higgins, A. H., Belland, J., Conceicao-Runlee, S., & Santos, R., M., & Rothenberg, D. (2000). Instructional technology and personnel preparation. Topics in Early Childhood Special Education, 20, 132–144. doi:10.1177/027112140002000302

Mason, C. Y., & Dodd, R. (2005). Bridge the digital divide for educational equity. Education Digest, 70(9), 25–27.

Janey Wang, C. Y. (2001, November). Handshakes in cyberspace: Bridging the cultural differences through effective intercultural communication and collaboration. Paper presented at National Convention of the Association for Educational Communications and Technology, Atlanta, GA. Retrieved August 1, 2009, from http://www.eric. ed.gov/ERICDocs/data/ericdocs2sql/content_ storage_01/0000019b/80/1a/87/e7.pdf Judge, S. (2005). The impact of computer technology on academic achievement of young African American children. Journal of Research in Childhood Education, 20(2), 91–101. Kalyanpur, M., & Kirmani, M. H. (2005). Diversity and technology: Classroom implications of the digital divide. Journal of Special Education Technology, 20(4), 9–18. Kaye, H. S. (2000). Computer and Internet use among people with disabilities. San Francisco: National Institute on Disability and Rehabilitation Research. Lee, V. E., & Burkham, D. T. (2002). Inequality at the starting gate: Social background differences in achievement as children begin school. Washington, DC: Economic Policy Institute. Lines, D. (2001, May 10)... Education Week, 20, 12–13. Lombardi, T., Bauer, D., Peters, C., & O’Keefe, S. (1992). Satellite distance learning: Collaboration meets demands of special education teachers. T.H.E. Journal, 19(11), 59–62.

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McDonald, K. K., & Hannafin, R. D. (2003). Using web-based computer games to meet the demands of today’s high-stakes testing: A mixed method inquiry [Electronic version]. Journal of Research on Technology in Education, 35(4), 459–472. Mellander, G. A. (2007). High-tech: Help or hindrance to Hispanics in college? Education Digest, 72(9), 19–23. Michaels, C. A., & Mcdermott, J. (2003). Assistive technology integration in special education teacher preparation: Program coordinators’ perceptions of current attainment and importance. Journal of Special Education Technology, 18(3), 29–41. Mossberger, K., & Tolbert, C. J. (2003). Race, place, and information technology. Urban Affairs Review, 41(5), 583–620. doi:10.1177/1078087405283511 National Education Association. (1997). Technology for diverse learners. West Haven, CT: National Education Association Library. Newby, T. J., Stepich, D. A., Lehman, J. D., & Russell, J. D. (2000). Instructional technology for teaching and learning: Designing instruction, integrating computers, and using media (2nd ed.). Englewood Cliffs, NJ: Prentice-Hall. No Child Left Behind. (NCLB, P.L. 107-110). (2002). The facts: 21st century technology. Retrieved March 3, 2009, from http://www.ed.gov/ nclb/methods/whatworks/21centtech.html

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P. L. 108-446. (2004). The Individuals with Disabilities Education Improvement Act. Retrieved July 5, 2009, from http://www.ed.gov/policy/ speced/guid/idea/idea2004.html Parette, P., & Peterson-Karlan, G. R. (2007). Facilitating student achievement with assistive technology. Education and Training in Developmental Disabilities, 42(4), 387–397. Payton, F. C. (2003). Rethinking the digital divide. Communications of the ACM, 46(6), 89–91. doi:10.1145/777313.777318 Peterson-Karlan, G. R., & Parette, P. (2005). Millennial students with mild disabilities and emerging assistive technology trends. Journal of Special Education Technology, 20(4), 27–38. Pollard, C., & Pollard, R. (2004/2005). Research priorities in educational technology: A Delphi study [Electronic version]. Journal of Research on Technology in Education, 37(2), 145–160. Prensky, M. (2001). Digital game-based learning. New York: McGraw Hill. Raskind, M. H., & Higgins, E. L. (1998). Assistive technology for postsecondary students with learning disabilities: An overview [Electronic version]. Journal of Learning Disabilities, 31, 27–40. doi:10.1177/002221949803100104 Roblyer, M. D., & Knezek, G. A. (2003). New millennium research for educational technology: A call for a national research agenda [Electronic version]. Journal of Research on Technology in Education, 36(1), 60–76. Rose, D. H., Hasselbring, T. S., Stahl, S., & Zabala, J. (2004). Assistive technology and universal design for learning: Two sides of the same coin. In Edyburn, D., Higgins, K., & Boone, R. (Eds.), Handbook of special education technology research and practice (pp. 507–518). Whitefish Bay, WI: Knowledge by Design, Inc.

Sherson, G. W. (2000). Closing the gap: The digital divide and Native Americans. Submitted in partial fulfillment of the requirement for the degree of Master of Communications, Victoria University in Wellington. Retrieved June 10, 2009, from www.ucol.ac.nz/~g.sherson/papers/ Closing_the_Gaps.pdf Smith, S. (2000). Teacher education—Associate editor’s column [Electronic version]. Journal of Special Education Technology, 15(1), 59–62. Soloman, K. (2000). Disability divide. The Industry Standard. Retrieved August 1, 2009, from http:// www.thestandard.com/article/0,1902,16236,00. html Solomon, G., Allen, N. J., & Resta, P. (Eds.). (2003). Toward digital equity: Bridging the divide in education. Boston: Allyn and Bacon. Tapscott, D. (1997). Growing up digital: The rise of the net generation. New York: McGraw Hill. Turner, J. D. (2007). Beyond cultural awareness: Prospective teachers’ visions of culturally responsive literacy teaching [Electronic version]. Action in Teacher Education, 29(3), 12–24. Twist, K. (2002). A nation online, but where are the Native Americans? Retrieved August 17, 2009, from http://www.digitaldivide.net/articles/view. php?ArticleID=153 U.S. Department of Commerce. (2000). Falling through the net: Toward digital inclusion: A report on Americans’ access to technology tools. Washington, DC: National Telecommunications and Information. U.S. Department of Commerce. (2002). A nation online: How Americans are expanding their use of the Internet. Washington, DC: National Telecommunications and Information Administration, Economics and Statistics Administration (NTIA). Retrieved August 1, 2009, from www.ntia.doc. gov/ntiahome/dn/nationonline_020502.htm

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U.S. Department of Education, National Center for Education Statistics. (2003). Computer and Internet use by children and adolescents in 2001. NCES 2004–014. Retrieved June 2, 2009, from http://nces.ed.gov/pubs2004/2004014.pdf U.S. General Accounting Office. (2001). Telecommunications: Characteristics and choices of Internet users. Washington, DC: USGPO. Valentin, S. (2006). Addressing diversity in teacher education programs [Electronic version]. Education, 127, 196–202. Warger, C. L. (Ed.). (2005). Technology and media for accessing the curriculum. Instructional support for students with disabilities. Columbia, MD: Center for Technology in Education and Technology and Media Division. Watch, O. M. B. (2002). Closing the digital divide: Community technology centers. Retrieved August 17, 2009, from http://www.ombwatch. org/node/352 Wozney, L., Venketesh, V., & Abrami, P. (2006). Implementing computer technologies: Teachers’ perceptions and practices [Electronic version]. Journal of Technology and Teacher Education, 14(1), 173–207. Zehr, M. A. (2001). Language barriers. Education Week, 20(35), 28–30.

AddItIonAL reAdIng Allen, N., Resta, P. E., & Christal, M. (2002). Technology and tradition: The role of technology in Native American schools. TechTrends, 46(2), 50–55. doi:10.1007/BF02772078 Beglau, M. M. (2005). Can technology narrow the black-white achievement gap? T.H.E. Journal, 32(12), 13–14, 17.

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Beyerbach, B., Walsh, C., & Vannatta, R. (2001). From teaching technology to using technology to enhance student learning: Preservice teachers changing perception of technology infusion [Electronic version]. Journal of Technology and Teacher Education, 9, 105–127. Butler, M. B., Lee, S. Y., & Tippins, D. J. (2006). Case-based methodology as an instructional strategy for understanding diversity: Preservice teachers’ perceptions [Electronic version]. Multicultural Education, 13(3), 20. Cartledge, G., & Kourea, L. (2008). Culturally responsive classrooms for culturally diverse students with and at risk for disabilities [Electronic version]. Exceptional Children, 74(3), 351–371. Chamberlain, S. P. (2005). Recognizing and responding to cultural differences in the education of culturally and linguistically diverse learners [Electronic version]. Intervention in School and Clinic, 40(4), 195–211. doi:10.1177/105345120 50400040101 Garcia, S. B., & Guerra, P. L. (2004). Deconstructing deficit thinking: Working with educators to create more equitable learning environments [Electronic version]. Education and Urban Society, 36(2), 150–168. doi:10.1177/0013124503261322 Harris-Murri, N., King, K., & Rostenberg, D. (2006). Reducing disproportionate minority representation in special education programs for students with emotional disturbances: Toward a culturally responsive response to intervention. Education & Treatment of Children, 29(4), 779–800. Hourcade, J. J., & Parette, P. (2001). Providing assistive technology information to professionals and families of children with MRDD: Interactive CD-ROM technology. Education and Training in Mental Retardation and Developmental Disabilities, 36(3), 272–279.

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James, K. (2006). Identity, cultural values, and American Indians’ perceptions of science and technology. American Indian Culture and Research Journal, 30(3), 45–58. Kaye, H. S. (2000). Computer and Internet use among people with disabilities. Disability Statistics Report (13). Washington, DC: U.S. Department of Education, National Institute on Disability and Rehabilitation Research. Kovalik, C. (2003). Reflections on a technology integration project [Electronic version]. Journal of Technology and Teacher Education, 11(1), 73–90. Leonard, J., Davis, J. E., & Sidler, J. L. (2005). Cultural relevance and computer-assisted instruction. Journal of Research on Technology in Education, 37(3), 263–284. Lovingfoss, D., Molloy, D. E., Harris, K. R., & Graham, S. (2001). Preparation, practice, and program reform: Crafting the University of Maryland’s five-year, multicategorical undergraduate program in special education [Electronic version]. The Journal of Special Education, 35, 105–114. doi:10.1177/002246690103500206 Maccini, P., Gagnon, J. C., & Hughes, C. A. (2002). Technology-based practices for secondary students with learning disabilities [Electronic version]. Learning Disability Quarterly, 25(4), 247–261. doi:10.2307/1511356 Okolo, C. M., & Bouck, E. C. (2007). Research about assistive technology: 2000-2006. What have we learned? Journal of Special Education Technology, 22(3), 19–33.

key terms And deFInItIons Assistive Technology (AT): Any item, piece of equipment, or product system, whether acquired commercially off the shelf, modified, or customized that is used to increase, maintain, or improve the functional capabilities of a child with a disabilities (20 U.S.C. § 1401(1), 1997, 2004). Culturally and Linguistically Diverse: A non-pejorative term referring to individuals who come from racial and ethnic groups other than the European American culture (e.g., African American, Asian American, Latino/a, Native American) and/or who may speak languages other than English as their first language. Digital Divide: Digital divide is based on the apparent gap between individuals who can effectively access digital and information technology versus individuals who have limited or no access at all. Digital Equity: Ensuring equitable access to instructional and educational technology despite factors such as income, race/ethnicity, gender, age, disability status, and residence in urban and rural areas. Equity: Ensuring equitable access despite factors such as income, race/ethnicity, gender, age, disability status, and residence in urban and rural areas. Instructional/Educational Technology: Application of scientific knowledge about human learning to the practical tasks of teaching and learning (Newby, Stepich, Lehman, & Russell, 2000).

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Chapter 27

Cognition and Learning Blessing Nma Okrigwe Rivers State College of Education, Nigeria

AbstrAct Because of the failure of the behaviorist tradition in developing the full potential of the individual, there is a shift to a cognitive paradigm which emphasizes the process of learning as against methods of teaching. Each of us has the potential to excel if we have the right opportunities at the right time of our development and backed up with a stimulating environment in the process of learning. The effectiveness of any teaching learning process is measured by the extent to which it has met the individual’s needs and expectations. The cognitive view of learning refers to individual’s mode of thinking, remembering or problem-solving, because learners learn in different ways of absorbing information and demonstrating their knowledge. Individualized instruction is a personalized learning which meaningfully involves only the learner working on his own and at his own pace. On a practical level, a personalized learning environment entails flexibility to enable learners to interact with resources when it is most appropriate for them. There is awareness that many learners today are already creating personalized learning environments using digital resources. Without digital technology, meeting individual learner needs will be practically impossible. The implications of the introduction of technologies in homes and schools have created the problem of reinforcing the existing inequalities in the education system of the developed and developing countries. To arrest this situation, there is the need to ensure that access to digital resources is universal. Without a commitment to this goal, the learning landscape will be easily navigable only by those with the relevant economic and cultural resources. The present evolutionary trend in education technology has enhanced mass education making learning to be more individualized. Innovations in teaching and learning have thus been dominated by computer and the Internet. DOI: 10.4018/978-1-61520-817-3.ch027

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IntroductIon The past three or four decades have witnessed tremendous growth in the body of research on teaching and learning. The invention of the microprocessor in the late sixties brought in the personal computer and electronic media which has necessitated this growth. Furthermore the advent of the World Wide Web brought instant dissemination of information enhancing research activities. This has resulted in a striking variety of approaches to study how people learn because the greatest challenge to educators in this era of information technology is how to make all learners with a variety of social and intellectual backgrounds benefit maximally from school. Thus, the search for different ways, means and techniques of identifying, developing and utilizing learners’potentials has pre-occupied educators and psychologists for many years. Researchers have also come to the realization that group research does provide valuable information about group characteristics, but has not taken cognizance of a particular child with a particular need. It is therefore not advisable to take a single study as a defining word. Efforts are converging from cognitive psychology, developmental psychology, social psychology, anthropology and neuroscience. In this chapter, a theoretical literature review on cognitive theory will be adopted with emphasis on the three important cognitive theories - Piaget’s cognitive development theory, Vygotsky’s sociocultural cognitive theory, and the theory behind the information processing approach. They have the most complete descriptions of children’s cognitive development (Santrock, 2003). These cognitive theories, especially Piaget’s and Vygotsky’s, emphasize the individual’s active construction of understanding, but did not give adequate attention to individual variations in cognitive development. The information processing approach, on the other hand, offers a detailed description of cognitive processes, thus complementing the missing link in understanding

the extreme complex structure of mental abilities. The study of individual functioning will require new and different approaches to learning. This chapter will identify appropriate cognitive and instructional strategies that will enhance learning and increase the individual’s performance, thus making him an able learner and not a disabled learner.

bAckground cognitive Psychology Cognitive psychology developed around the late 1950s when technology was developing computers capable of manipulating large amounts of data very rapidly. Over the last two decades cognitive psychology has been widely embraced because of the insights the theories have demonstrated in describing and explaining cognitive processes such as thinking and problem-solving. Cognitive theories deal with intrinsic motivation. Motivation serves to create intentions and goal seeking acts. Cognitive views of learning refer to an individual’s mode of thinking, remembering, or problem-solving (Santrock, 2003). There is a tendency to behave in a certain manner known as mental models. Mental models are representations of reality that people use to understand specific phenomena. These models provide prediction and explanatory power for understanding the interaction. Cognitive psychology studies mental processes underlying behavior. It uses information processing as a framework for understanding the mind. Furthermore, cognitive psychology also makes and attempt at understanding the nature of mental representation that underline perception since most of the relationships that we establish with the environment are carried out through perception. Cognitive psychology is, therefore, the science that studies mental activities in terms of information processing (reasoning),

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concept formation, recognition, imagination, and problem-solving. Cognitive psychologists focus on the way human’s process information. They apply a homothetic approach where cognitive changes are said to be common to children across cultures to discover human cognitive processes. They also have adopted idiographic techniques through using case studies. They argue that those who emphasize the homothetic approach may often see more orderliness than actually exists (Gray, 1990). This chapter attempts to adopt the case study approach in recommending the intervention strategies which are highly dependent upon the nature of the task and differences across learners.

the three cognitive Approaches (Piaget, vygotsky, and the Information Processing Approach) Piaget’s Theory Piaget revealed how cognitive change is likely to occur if the context is structured to allow gradual movement to the next higher level and that a concept does not emerge suddenly, but rather through a series of partial accomplishments that lead to increasingly comprehensive understanding (Haiti & Benson, 1998). Piaget proposed a cognitive developmental theory where children go though cognitive stages that are largely independent of instruction from the teacher. They just need to be nurtured through their own stages of self-discovery instead of being taught according to any particular schedule. He called his theoretical framework “genetic epistemology” because he was primarily interested in how knowledge developed in human organisms. Cognitive development involves constant effort to adapt to the environment in terms of assimilation and accommodation. The stages of cognitive development as proposed by Piaget are as follows:

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Sensory motor stage (0-2 years), where intelligence takes the form of motor actions. Pre-operation stage (3-7 years), where intelligence is intuitive in nature. Concrete stage (8-11 years), where intelligence is logical, but depends upon concrete referents. Formal operation stage (12-15 years), where intelligence involves abstraction.

The stages of cognitive development, as proposed by Piaget, vary for every individual child. Furthermore, each stage has many detailed structural forms. Take for instance the concrete operational stage; it has more than forty distinct structures covering: classification and relations, spatial relationships, time, movement, number, conservation and measurement (Brainerd, 1978). He further added that culture and education exert strong influence on child development. For example, the age at which children acquire conservation skills is related to the extent to which their culture provides relevant practice. The main points spelled out in his theory include the following principles: •

•

Children will provide different explanations of reality at different stages of cognitive development. As a result, learning materials and activities should involve appropriate levels of mental operations for a child of given age. In other words, a teacher should consider the cognitive level of the children he is teaching, and then choose material and teaching methods that are appropriate to the child’s reasoning capacity. Cognitive development is facilitated by providing activities or situations that engage learners and present challenge. For example, teachers of infants should try to provide ample objects to play with while primary school teachers (concrete operation) should involve problems of

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classification, ordering, location, and conservation, using concrete objects (Bybee & Sand, 1992). Activity methods, especially at the primary level, lays stress on the importance of children manipulating objects with widely differing properties of texture, color, and shape. This together with discovery, collection, classification, construction, and analysis of materials are essential for the natural development of cognitive skills such as perceptions, conception, memory, language reasoning and creativity. These cognitive skills underline all academic learning. Absence of these skills predisposes the child to academic failure.

Vygotsky’s Theory Vygotsky’s theory consists of three basic claims about cognitive development. The major theme of this theory is that social interaction plays a fundamental role in the development of cognition. His first claim is that cognitive skills need to be interpreted developmentally. Like Piaget, Vygotsky claimed that infants are born with the basic abilities for intellectual development. While Piaget focuses on motor reflexes and sensory abilities, Vygotsky refers to elementary mental functions as attention, sensation, perception, and memory. Through interaction with the social environment, these are developed into more sophisticated effective mental processes and strategies, which he refers to as higher mental functions. For example, having noted that the memory of a child is limited by biological factors, its subsequent development determines the type of memory strategy we develop. A second aspect of Vygotsky’s theory is the idea that the potential for cognition depends upon what he calls “zone of proximal development (ZPD)” as the area where the most sensitive instruction or guidance should be given. It is the stage at which the child finds the task difficult to master, but which can be learned with the guidance and

assistance of adults and more skilled children. His ‘ZPD’ is, therefore, the distance between the level of actual development and the more advanced level of potential development that comes into existence in interaction between the more and less capable participant. Normally, intelligent quotient (IQ) is a measure of learning potential just as the zone of proximal development is also a measure of learning potential. The difference is that IQ emphasizes that intelligence is a property of the child, while ZPD emphasizes that learning is interpersonal. It is inappropriate to say that the child has a ZPD; rather a child shares a ZPD with a more skilled individual. Vygotsky did not believe that formal standardized tests are the best way to assess children’s learning. Rather, he argued that assessment should focus on determining the child’s ZPD. Hence, he claimed that the range of skill that can be developed with adult guidance or peer collaboration exceeds what can be attained alone (Discovery Learning - Piaget). Vygotsky’s third claim is that cognitive skills are mediated by language. He believed that language plays a key role in guiding cognition. He said language and thought initially developed independently, but then children internalize their egocentric speech in the form of inner speech which becomes their thoughts. This transition occurs at about 3 to 7 years of age. He went further to say that language plays two critical roles in cognitive development. The first one is that it is the means by which adults transmit information to children. While the second role is that language itself becomes a very powerful tool of intellectual adaptation (Santrock, 2003).

Contrasting Piaget and Vygotsky In comparing Piaget and Vygotsky’s theories, both emphasize the individual’s active construction of understanding; while Vygotsky’s theory is social constructivists, Piaget’s is cognitive constructivist. They both acknowledge the importance of examining developmental changes in children’s

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thinking—that of Vygotsky is determined by the social and cultural context, while that of Piaget is determined by biological changes. They both view the teacher as a guide and a facilitator rather than a director. Vygotsky gives the more skilled individual a stronger teaching role than Piaget. In the area of language, Vygotsky argues that children internalize their egocentric speech in the form of inner speech, which becomes their thoughts. This view contrasts with Piaget’s view that young children’s inner speech is egocentric and immature. Neo-Piagetians believed that children’s cognition needs to be studied in more specific ways than the stages of cognitive development that young children go through as outlined by Piaget. They, therefore, presented an information processing model.

hardware, cognition as its software. Working memory is where information is temporarily processed. Long-term memory (LTM) is where information is stored indefinitely as knowledge. Working memory is, therefore, equivalent to a computer’s central processing unit (CPU), where the data is processed; and LTM is equivalent to a computer’s hard disk, external disk, or magnetic media, where data is stored persistently. The processed information is displayed on the screen or as a hardcopy. The human equivalent is talking, walking—simply put-action. According to this view there are three kinds of memory: •

•

The Information Processing Approach According to Bjorkland and Rosenbaum (2000) and Chen and Siegle (2000), the information processing approach emphasizes that individuals manipulate information, monitor it, and strategize about it. Individuals develop a gradual increasing capacity for processing information, which allows them to acquire increasingly complex knowledge and skills. The study of human information processing is based upon systems analysis and an understanding of internal stages of response to external stimuli. The approach views the person as an active and adaptive part of the environment. Information theory tells us that behavior depends upon all the stimuli that might have occurred and not only upon the particular stimuli that did occur. People are capable of processing the same information in several different ways. The information processing perspective is compared to computer processing. Like a computer, where information (data) is entered through a keyboard, scanner, or another input device, the human mind takes information through the senses. The physical brain is described as the computer’s

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Sensory registers: The part of the memory that receives all the information a person senses. Short-term memory: Also known as working memory—the part of memory where new information is held temporarily until it is either lost or placed into LTM. Long-term memory: The part of memory which has an unlimited capacity and can hold information indefinitely (Roblyer & Edwards, 2000).

Information gets selected when people pay attention. The new information will only be transferred to LTM when it is linked in some way to prior knowledge already in LTM. Information is translated into some meaningful form (encoded) and retrieved through a process of identification and recall for a particular purpose. Learning now becomes the result of individuals successfully encoding new information or recording existing information in a new way. This knowledge can then be recalled from memory and used. The key factors for effective encoding of information include ensuring that the material is meaningful and that activation of prior knowledge occurs. Information processing theory is highly acknowledged by educationists because it deals with intellectual performance which covers the following areas:

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Attention-directing mental efforts towards important aspects. Memory strategies Highlighting key points and making summaries. Concept mapping Problem-solving Metacognition Pattern recognition Elaboration

From the information processing view point, people are active learners who can control and manipulate information and devise strategies to deal with particular situations.

Paradigm shift in Learning The tremendous growth of the body of research on teaching and learning has demonstrated that below average children could become functionally gifted when given proper development. This does not negate the physical reality that people are born with different aptitudes. It simply states that the margins of differences in our natural aptitudes are most often less significant than the differences in our environmental and developmental opportunities. The case of Maria Montessori is a glaring example. She was able to teach a number of children with cognitive disabilities, who were residing in an asylum, both to read and write so well that she was able to present them at a public school for examination together with children without disabilities where her students passed successfully. Furthermore a number of gifted children have dropped out of school under the supervision of uninformed teachers. For example, Albert Einstein, whose theory of relativity has challenged the best minds in the world, was expelled from school because it was said that his presence had a disruptive effect on the class and other children. Bill Gates, one of the founders of Microsoft, not to mention one of the richest men in the world, also dropped out of school. Woodrow Wilson, one of

the most well known of the American Presidents, was described as dull and backward because he could not say his ABCs until he was nine and could only read and write at age eleven. Teaching during that period was based on the assumption that effective learning is a matter of conditioned response or “conditioning” and failure to respond correctly is punished, whereas successful responses are rewarded. Motivation for learning is derived from the need to gain rewards for success and avoid punishment for failure. Conditioned learning is passive learning. Consequently, emphasis is placed on the mechanics of teaching or “teaching methods”, which define the teacher’s function in terms of their ability to meet given learning requirements or “learning outcomes.” Students are taught how to meet teacher’s expectations. The knowledge acquired is evaluated and measured in terms of a standardized system of evaluation, i.e., grades. Emphasis on grades creates a dependency on extrinsic motivation, the likely cause for educational crisis. Teachers are too quick to label children with the slightest learning problem as having a learning disability, instead of recognizing that the problem may rest in their ineffective teaching. Many children are being diagnosed without understanding extensive professional evaluation based on input from multiple sources. From research findings it is very obvious that learners learn in different ways of absorbing information and of demonstrating their knowledge. By implication, there has to be a reversal on the standardized evaluation system, by moderating the authority of the teacher. People need not accept information because somebody in authority said so. They accept the information if it makes sense to them, if they know about it, if it makes their thinking clear, or if it makes things better for them. The effectiveness of any teaching learning process is measured by the extent to which it has met individual’s need and expectation. In the last two decades, printed instruction constituted one of the most widely utilized forms of instructional materials. This is being replaced

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by technology media since it is being realized that only 10% of what is read can be recalled (Alcorn, Kinder, & Shunert, 1979). Today, there are many kinds of innovative learning systems through which information is given to the learners through some media other than the teacher. Such modern media includes programmed instructional materials (books), motion pictures, photographic prints and television and video tapes, audiotapes, microfilms, and computers. The present evolutionary trend in educational technology, where instructional materials made available at scale has enhanced mass education. This means students received education via few teachers and instead, learning is being made more individualized which collaborates with the cognitive psychologists’ theory. Many interventions on learning disabilities have focused on improving the child’s reading ability, like using individual reading materials, individual viewing and listening equipment, language laboratory, and programmed printed material (Cable & Ralph, 1965).

data. It is one of obtaining new understanding and better ways to do things. In this situation, teachers help students to construct knowledge rather than to reproduce a series of facts. The teachers’ effort is thus aimed at developing students’ competencies and talents. This approach has implication for individualize learning. By individualized learning, learners can learn at their own pace, and can also work independently. It thus encourages the individualization of instruction in accord with students’ characteristics and aptitudes. The following characteristics can be identified of individualized instruction: •

•

Issues and controversies The traditional behavioral paradigm with its emphasis on methods of teaching is being replaced by the cognitive paradigm which emphasizes the process of learning. The cognitive paradigm is concerned with teaching as the facilitation of natural learning and learner empowerment. In this process, knowledge is discovered as the learner constructs and adapts to the new challenges. What cognitive psychologists have in common is getting the learners involved with the whole tasks or problems as contrasted with the traditional approach where students are passive learners. The belief is that getting students involved with realistic whole situations will help them for appropriate schema and mental models. These internal representations are believed to facilitate their later application of their newly acquired knowledge and skill. The process of learning is not just piling data on top of more

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Criterion-Reference Testing: With criteria-reference testing, students’ performance is assessed against specific determined criteria and not against grades relative to peer performance. This is done to encourage each learner to achieve mastery of the learning experience or topic. Self-Pacing: The students are allowed to move at their pace. They are allowed sufficient time needed to accomplish the task, thus reducing the frustration that will occur if they followed the fixed time table. Flexible scheduling of time tables encourages individualization of instruction as each learner may learn in accord with his own pace, or rate of understanding. This is what Ferguson (1968) called promoting responsible learning freedom. Presentation Mode Selection: Where it is practicable, learners can select the presentation modes that best suit them instead of using a pre-specified media. They might decide to choose computer assisted instruction or the Internet. Learning Criteria: Behavior change is recognized as the index of learning. This is why repeated tests are used to allow for mastery of learning where the student is experiencing learning difficulty.

Cognition and Learning

ProbLems Creating instructional opportunities that can be adapted to diverse learners require the use of variety of instructional strategies which will demand flexible and responsible environments. This laudable ambition unfortunately will not be realized in the existing institution. On a practical level, personalized learning environments should be sufficiently flexible to enable learners to interact with resources when it is most appropriate for them. Digital technology—like the Internet can make flexibility possible. There is awareness that many learners today are already creating personalized learning environments for themselves, out of school, using digital resources. For most young people, technology is part of their daily life. In spite of the innumerable positive attributes of personalized learning, the Nigerian educational system is still very slow to catch up. This is a result of the numerous constraints. For example, many teachers in Nigerian schools are still not computer literate and this is compounded by low level awareness of the benefits of the potentials of digital technology. Such complications have led many researchers, students and teachers to still depend heavily on the traditional method of teaching, such as searching for information in libraries. Most information technology materials and equipment are not within the reach of the poor. Where these facilities are available, their high cost of installation and maintenance pose much resistance since the technology is not indigenous. It is very obvious that without digital technology we are unlikely to be able to meet the needs of learners. And unfortunately, digital technology in Nigerian educational system is still at the basic level.

soLutIons And recommendAtIons The aim of this chapter is to understand how human beings learn from the perspective of the cognitive theorist approach. It is very obvious that we cannot directly control internal conditions. However, Gagne’s theory has led to a set of strategies for providing external support for learners as they attempt to achieve a goal. These strategies differ depending on the domain of learning. The following strategies below will help to decide on effective strategies for each domain as we create our instructional strategy (adapted from Essentials of Learning for Instruction by R.M. Gagne and M.P. Driscoll, 1988).

verbal Information • • • • • •

•

•

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Provide a meaningful context for effective encoding of information. Draw attention to distinctive features by variations in print or speech. Use terms or definitions in a sentence. Present information so that it can be made into chunks. Relate the information (term or definition) to preexisting knowledge. Present all terms clearly using the fewest number of words to convey the meaning. If more than five terms or units of information are to be presented in one lesson, group related terms or units into five or fewer clearly defined categories. Use a variety of concrete (observable) examples when possible, emphasizing the clear and well defined features that relate directly to the information. Explain clearly how learners will be expected to recall the information while it is initially presented. Make information readily accessible to learners, and provide opportunities for

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• •

them to explore “nice-to-know” information associated with the knowledge. Practice with immediate feedback! Provide cues for effective recall and generalization of information.

Intellectual skills •

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• •

•

• •

•

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Encourage learners to recall previously learned information or examples that illustrate concepts or rules being presented. Clearly communicate the definition of defined concepts, using the fewest number of words. Call attention to distinctive features. Stay within the limits of working memory. Present verbal cues to the ordering or combination of component skills. Break down the process of performing or applying rules into steps, and clearly communicate these steps to the students. Demonstrate an application of the rule for the students. Present varied examples or instances of concepts and rule applications, calling attention to the distinctive features of examples, definitions, and procedures. Present non-examples or non-instances of the concept if they will help to clarify the concept. Schedule occasions for practice and spaced review. Provide learners with opportunities to “play” with concepts and rules within simulated or “real” environments, identifying and selecting their own examples and nonexamples of concepts and rule applications if possible. Present a variety of contexts or experiences that allow the students to practice applying the rules or identifying/describing concepts (transfer), providing guidance throughout early stages of practice.

cognitive strategies • • • •

Recall relevant rules and concepts. Describe or demonstrate the strategy. Provide a variety of occasions for practice using the strategy. Provide information feedback as to the creativity or originality of the strategy or outcome.

Attitudes • • •

•

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Establish an expectancy of success associated with the desired attitude. Assure student identification with an admired human model. Make students aware of the personal benefits gained by making choices based on attitudes (preferably by someone the students admire). Clearly identify examples of choices made by people who possess the desired attitude (credible and attractive-similarity, familiarity, appearance). Clearly identify instances in the students’ lives in which making choices are based on the attitude being presented. Allow students the opportunity to practice making choices associated with the desired attitude (role-playing, group discussion, etc.) and give them feedback. Arrange for communication or demonstration of choice of personal action. Positive feedback for successful performance, or allow observation of feedback in the human model.

motor skills • • • •

Verbally guide learners through routine. Visually present example of routine execution. Encourage the use of mental practice. Arrange repeated practice.

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•

Furnish immediate feedback as to the accuracy of performance.

The use of cognitive strategies such as—rehearsals, elaboration, transformation, imagery, mnemonics, chunking and organization—can increase the efficiency and confidence with which the learner approaches a learning task, as well as his ability to develop a product, retain essential information, or perform a skill. While teaching these strategies, it requires a high degree of commitment from both the teacher and learner, the results are very encouraging. The key to education now is helping students learn a rich repertoire of strategies.

Future reseArcH dIrectIons Innovations in teaching and learning have been dominated by the computer and the Internet. In response to these innovations, schools in the developed regions of the world have made moves to ensure that children have computers and Internet access to use both in school and at home. In the United States, as far back as 2001, the average ratio of child to computer was three to one. While in Nigeria, one of the Sub-Sahara African countries classified as a developing country cannot boast of a single computer in most of their schools. There is now a digital divide between developed areas of the world; and also a digital divide between the rich and the poor in the developing countries due to the lack of basic infrastructure and electricity. Consequently, we call out the following questions of importance:

research Question 1 How can we reduce the digital divide between those in the developed and developing regions of the world, with a view of providing equal opportunities to every school age child in any country? Bear in mind that introducing the new

technology in developing nations would require developing new infrastructure rather than taking advantage of infrastructure already existing. This calls for government intervention.

research Question 2 What kind of policies should be put in place to overhaul the system? The new technology, which encourages individual constructivism and in so doing deprives the teacher of his autonomous control, will be seriously resisted by the traditional educational establishments characterized by rigidity, bureaucracy, and conformity.

research Question 3 How will the innovation be introduced to such a closed system to adopt such an explosive change?

concLusIon Cognitive psychologists view learning as an active process, and for learners to benefit from such a learning experience, they must be actively involved. In order for instruction to bring about effective learning, it must be made to influence the internal processes of learning. A cognitive strategy serves to support the learner as he develops internal procedures that enable him to perform tasks that are complex. According to the cognitive information processing theory, most new learning depends on connections made to prior learning. This will, therefore, take into account prior knowledge, motivation, attitude, the importance of metacognition and the need for knowledge to be available in an integrated form. The traditional paradigm with its emphasis on methods of teaching is being replaced by the new holistic paradigm, which emphasizes the process of learning and individualized approach. The teacher

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in this setting plays the role of a facilitator and not as the provider of information/knowledge. As the Internet continues to unfold, it will make individualized instruction very possible. And there is no nation today where the Internet does not exist. We acknowledge that a digital divide between developed and developing countries exists, and consequently call for immediate government intervention.

reFerences Alcorn, D. M., Kinder, J. S., & Shunert, J. R. (1979). Better teaching in secondary education. New York: Holt Rinehart & Winston. Atkinson, R. L., Atkinson, R. C., Smith, E. E., & Hilgard, E. K. (1987). Introduction to psychology (9th ed.). San Diego, CA: Harcourt Brace Jovanovich. Bjorkhund, D. F., & Rosenbaum, K. (2000). Middle childhood cognitive development. In Kazdin, A. (Ed.), Encyclopedia of psychology. New York: American Psychological Association and Oxford University Press. doi:10.1037/10520-103 Brainerd, C. (1978). Piaget’s theory of intelligence. Englewood Cliffs, NJ: Prentice-Hall. Bybee, R. W., & Sand, R. D. (1992). Piaget for educators (2nd ed.). Columbus, OH: Charles Merrill. Cable, R. (1965). Audio-visual handbook. London: University of London Press Ltd. Chen, Z., & Siegler, R. S. (2000). Intellectual development in childhood. In Sternberg, R. J. (Ed.), Handbook of intelligent. New York. Cambridge. Drever, J. (1952). A dictionary of psychology. London: Penguin Reference Books. Ferguson, H. (1968). Modular scheduling and social atmosphere. Clearing House (Menasha, Wis.), 42(9).

398

Gagne, R. M., & Driscolt, M. P. (1988). Essentials of learning for instruction. Retrieved August 10, 2009, from http://www.brighthub.com Gray, W. M. (1990). Formal operational thought. In Overton, W. F. (Ed.), Reasoning necessity and logic: Developmental perspective (pp. 76–79). Hillsdale, NJ: Erlbaum. Haith, M. M., & Benson, J. B. (1998). Infant cognition. In Damond, W. (Ed.), Handbook of child psychology (5th ed., Vol. 2). New York: John Wiley & Sons. Roblyer, M. D., & Edward, J. (2000). Assistive technology: Meeting the needs of learners with disabilities. Retrieved August 10, 2009, from http:// www.questia.com Santrock, J. W. (2003). Children (7th ed.). Boston: Mc Graw Hill. Sprinthal, N. A., Sprinthal, R. C., & Oja, S. N. (1994). Educational psychology: A developmental approach (6th ed.). Boston: McGraw Hill, Inc.

AddItIonAL reAdIng Ebbinghans, H. (1964). Memory (Roger, H. A., & Bussenirs, C. E., Trans.). New York: Dover. Fergusen, J. (2006). Global shadows: Africa in the neo-liberal world order. Durham, NC: Duke University Press. Festinger, L. (1957). A theory of cognitive dissonance. New York: Harper and Row. Gulliford, R. (1971). Special educational needs. London: Routledge and Kegan Paul. Hooker, M. (2008). 1.1 Technologies/computing in the developing world: Challenging the digital divide. Retrieved July 30, 2008, from http://www. gesci.org

Cognition and Learning

International Institute for Educational Planning. (n.d.). New partnership for EFA: Building an experience. Retrieved November 21, 2008, from http://unesco.org/iiep Kirk, S. A. (1971). Educating exceptional children. Boston: Houghton Mifflin. Papert, S. (1980). Mindstroms: Children, computers and powerful ideas. New York: Basic Books. Papert, S. (1993). The children’s machine: Rethinking schools in the age of the computer. New York: Basic Books. Piaget, J. (1952). 1953). The origins of intelligence in children. New York: International Universities Press. London: Routledge and Kegan Paul. Piaget, J. (1954). 1955). The construction of reality in the child. New York: Basic Books. London: Routledge and Kegan Paul. doi:10.1037/11168000 Restle, F. (1957). Discrimination of cues in mazes: A resolution of the “place-vs-response” question. Psychological Review, 64, 217–228. doi:10.1037/ h0040678 Rogers, C. (1969). Freedom to learn. Columbia: Charles Merril Books, Columbia University Press. Sperling, G. (1963). A model for visual memory tasks. Human Factors, 5, 19–30. Stahl, L. (2007). What if every child had a laptop? Retrieved July 30, 2008, from http://www. cbsnews.com/stories/2007-05-20/60 minutes/ main 2830058 UNESCO. (n.d.). Education for all. Retrieved July 30, 2008, from http://www.unesco.org Watson, D. L. (1988). Self-directed behavior: Self modification for personal adjustment. Monterey, CA: Brooks/Cole.

Zang, J., Scardamalia, M., Lamon, M., Messina, R., & Reeve, R. (2007). Socio-cognitive dynamics of knowledge building in the work of 9 and 10 year olds. Educational Technology Research and Development (ETR&D), 55(2).

cHAPters In journALs Alexander, R. (2000). Culture and pedagogy. International comparisons in primary education. Oxford, UK: Blackwell. Blasco, M. (2004). Teachers should be like “second parents”: Affectivity, schooling and poverty in Mexico. Compare, 34, 371–393. doi:10.1080/0305792042000294797 Brophy, J. E., & Good, T. L. (1970). Teachers communication of differential expectations for children’s classroom performance: Some behavioral data. Journal of Educational Psychology, 365–374. doi:10.1037/h0029908 Carney, S. (2009). Negotiating policy in an age of globalization: Exploring educational “policyscapes” in Denmark, Nepal, and China. CER 53(1). The University of Chicago Press. Davidson, H. H., & Lang, G. (1960). Children’s perceptions of their teachers’ feelings towards them related to self-perception, school achievement and behavior. Journal of Educational Psychological, 44(2). Feud, H. (1985). Determinants of school achievement levels: How important are the teachers? Education, (32): 31–49. Katz, D. (1968). Academic motivation and equal educational opportunity. Harvard Educational Review, 38. Klahr, D., & Nigam, M. (2004). The equivalence of learning paths in early science instruction: Effect of direct instruction and discovery learning. Psychological Science, 15(10), 661–667. doi:10.1111/j.0956-7976.2004.00737.x 399

Cognition and Learning

Pask, G. (1976). Styles and strategies of learning. The British Journal of Educational Psychology, 46(2).

key terms And deFInItIons Programmed Learning: A teaching method which places emphasis on teacher’s written communication. It is a method whereby the learner teaches himself by working though a series of steps all leading to carefully defined goals or objectives. He cannot go on to the next step until he has mastered the preceding one, based on the feedback received through the answers to the questions. The information to be taught is presented in a form known as a “Program.” Programs can be presented either in book form or through machines. Perception: Is the foundation of learning. It is the process whereby an individual becomes aware of his environment. It is a selective process and an individual style of perception is unique to such individual’s previous experience, attitude, knowledge and interest. Metacognition: Is an internal awareness of cognitive abilities, including self-awareness of both learning and retrieval strategies (Sprinthal, Sprinthal, & Oja, 1994). Whereas cognition helps us to learn, metacognition helps us to monitor and structure our learning strategies. Thinking about thinking and deciding how best to manage mental processes. Mnemonic Device: A system for enhancing memory work. It involves a set of symbols that can substitute for the material to be remembered. The common example, “Every Good Boy Deserves Favour”, used for the notes on a music staff.

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Concepts: This is our means of dividing the world into Manageable units (Atkinson, Atkinson, Smith, & Hilgard, 1987). To have a concept is to know the properties common to all. Concepts are categorization of objects, events, people or animals that share common characteristics. Such categorization enables us to organize complex information into simpler, easily manageable cognitive categories. Concept Mapping: E.g., setting out the relationship between key ideas in a topic in diagram form. Chunking: This is the grouping together of several separate items in order to aid in their retrieval. Short term memory can encode only about seven separate items (plus or minus two) and can hold them for only limited time (e.g., the 11 digits phone number—08066734720—can be chunked like 08066-734-720). Each chunk is counted as an item. Cognition: A general term covering all the various modes of knowing – perceiving, remembering, imagining, conceiving, judging, and reasoning. The cognitive function, as an ultimate mode or aspect of the conscious life is, contrasted with the affective and cognitive-feeling and willing (Drever, 1952). Cue: Signal to do something. Scaffolding: In cognitive development, Vygotsky used this term to describe the changing support over the course of a teaching session, with the more skilled person adjusting guidance to fit the child’s current performance level. Schema: In Piaget’s theory, this is a cognitive structure that helps individuals organizes and understands their experiences.

401

Compilation of References

Abell, M. M., Bauder, D. K., & Simmons, T. J. (2005). Access to the general curriculum: A curriculum and instruction perspective for educators. Intervention in School and Clinic, 41, 82–86. doi:10.1177/1053451205 0410020801

Ackerman, P. L. (1988). Determinants of individual differences during skill acquisition: Cognitive abilities and information processing. Journal of Experimental Psychology. General, 117(3), 288–318. doi:10.1037/00963445.117.3.288

ABLEDATA. (2009). [On-line database of assistive technology and rehabilitation equipment]. Retrieved February 3, 2009, from http://www.abledata.com

Ackerman, P. L. (1992). Predicting individual differences in complex skill acquisition: Dynamics of ability determinants. The Journal of Applied Psychology, 77(5), 598–614. doi:10.1037/0021-9010.77.5.598

Abner, G. H., & Lahm, E. A. (2002). Implementation of assistive technology with students who are visually impaired: teachers’ readiness. Journal of Visual Impairment & Blindness, 92, 98–105. Abraham, W., Epstein, S., Thráinsson, H., & Zwart, C. (Eds.). (1996). Minimal ideas: Syntactic studies in the minimalist framework. Amsterdam: John Benjamins Publishing Co. Accelerated Reader. (2006). Renaissance Learning, Inc. Retrieved from http//www.renlearn.com/ar.com/ default/htm.

Adams, M. J. (1990). Beginning to read: Thinking and learning about print. Cambridge, MA: The MIT Press. Adger, D. (2003). Core syntax: A minimalist approach. New York: Oxford University Press. Administration, Economics and Statistics Administration (NTIA). (n.d.). Retrieved August 1, 2009, from www.ntia. doc.gov/ntiahome/fttn00/Falling.htm

Achieving the Goals. (1996). U.S. Department of Education. Retrieved April 25, 2008, from http://www.ed.gov/ pubs/AchGoal4/mission.html

Agran, M., Blanchard, C., & Wehmeyer, M. L. (2000). Promoting transition goals and self-determination through student-directed learning: The self-determined learning model of instruction. Education and Training in Mental Retardation and Developmental Disabilities, 35, 351–364.

Ackerman, P. L. (1986). Individual differences in information processing: An investigation of intellectual abilities and task performance during practice. Intelligence, 10(2), 101–139. doi:10.1016/0160-2896(86)90010-3

Ahuja, J. S., & Webster, J. (2001). Perceived disorientation: An examination of a new measure to assess web design effectiveness. Interacting with Computers, 14(1), 15–29. doi:10.1016/S0953-5438(01)00048-0

Ackerman, P. L. (1987). Individual differences in skill learning: An integration of psychometric and information processing perspectives. Psychological Bulletin, 101(1), 3–27. doi:10.1037/0033-2909.102.1.3

Ajayi, L. J. (2005). A sociocultural perspective: Language arts framework, vocabulary activities and English language learners in a second grade mixed classroom [Electronic version]. Journal of Instructional Psychology, 32, 180–195.

Copyright © 2010, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Compilation of References

Akamatsu, C. T., Mayer, C., & Farrelly, S. (2005). An investigation of two-way text messaging use with deaf students at the secondary level. Journal of Deaf Studies and Deaf Education, 11(1), 120–131. doi:10.1093/ deafed/enj013 Alcorn, D. M., Kinder, J. S., & Shunert, J. R. (1979). Better teaching in secondary education. New York: Holt Rinehart & Winston. Alexander, J. M., Carr, M., & Schwanenflugel, P. J. (1995). Development of metacognition in gifted children: Directions for future research. Developmental Review, 15(1), 1–37. doi:10.1006/drev.1995.1001 Allen, K. E., & Marotz, L. (2007). Developmental profiles: Pre-birth-twelve (5th ed.). Clifton Park: Delmar/ International Thomson Publishers. Alliance for Technology Access. ATA, (2000). Current laws and legislation. In alliance for technology access (Eds). Computer and web resources for people with disabilities: A guide to exploring today’s Assistive Technology. Alameda, CA: Hunter House. Alper, S., & Raharinirina, S. (2006). Assistive technology for individuals with disabilities: A review and synthesis of the literature. Journal of Special Education Technology, 21(2), 47–64. American Educational Research Association, American Psychological Association, National Council on Measurement in Education. (1999). Standards for educational and psychological testing. Washington, DC: American educational Research Association. Americans with Disabilities Act of 1990. (2004). Pub. L. No. 101-336, 42 U.S.C. Sec. 12101 et seq. Anderson, C. L., & Petch-Hogan, B. (2001). The impact of technology use in special education field experience on preservice teachers’ perceived technology expertise. Journal of Special Education Technology, 16(3), 27–44. Anderson, J. R. (1980). Cognitive psychology and its implications. San Francisco: Freeman.

402

Anderson, J. R. (1983). The architecture of cognition. Cambridge, MA: Harvard University Press. Anderson, J. R. (1996). ACT: A simple theory of complex cognition. The American Psychologist, 51, 355–365. doi:10.1037/0003-066X.51.4.355 Anderson, J. R. (2004). Cognitive psychology and its implications (6th ed.). New York: Worth Publishers. Anderson, S. (1997, Fall). Understanding teacher change: Revisiting the concerns based adoption model: Curriculum Inquiry. Retrieved December 18, 2008, from Professional Development Collection database. Anderson-Inman, L., Knox-Quinn, C., & Szymanski, M. (1999). Computer supported studying: Stories of successful transition to postsecondary education. Career Development for Exceptional Individuals, 22(2), 185–212. doi:10.1177/088572889902200204 Andre, T., & Phye, G. D. (1986). Cognition, learning, and education. In Phye, G. D., & Andre, T. (Eds.), Cogntivie classroom learning: Understanding, thinking, and problem solving. Orlando, FL: Academic Press. Ansburg, P. I., & Shields, L. (2003). Training overcomes reasoning schema effects and promotes transfer. The Psychological Record, 53(2), 231–242. Aretz, A. J., & Wickens, C. D. (1992). The mental rotation of map displays. Human Performance, 5(4), 303. Retrieved July 26, 2008, from http://search.ebscohost. com/login.aspx?direct=true&db=afh&AN=7310604& site=ehost-live Arter, A. J., & Spandel, V. (1992). Using portfolios of student work in instruction and assessment. Education Measurement: Issues and Practices, Spring, 36-44. Atkinson, M. (1992) Children’s syntax: An introduction to principles and parameters theory. Oxford, UK. Atkinson, R. C., & Shiffrin, R. M. (1968). Human memory: A proposed system and its control processes. In Spence, K. W., & Spence, J. T. (Eds.), The Psychology of learning and motivation: Advances in research and theory (Vol. 2, pp. 89–195). Oxford, UK: Academic Press. doi:10.1016/S0079-7421(08)60422-3

Compilation of References

Atkinson, R. L., Atkinson, R. C., Smith, E. E., & Hilgard, E. K. (1987). Introduction to psychology (9th ed.). San Diego, CA: Harcourt Brace Jovanovich. Augcomm, U. W. (n.d.). Augmentative and alternative communication at the University of Washington, Seattle. Retrieved October 5, 2009, from http://depts.washington. edu/augcomm/00_general/glossary.htm Ausburn, F. B., Ausburn, L. J., Cooper, J., Kroutter, P., & Sammons, G. (2007). Virtual reality technology: Current status, applications, and directions for education research. OATE Journal: Oklahoma Association of Teacher Educators, 11, 7–14. Ausburn, F. B., Ausburn, L. J., Cooper, J., Kroutter, P., & Sammons, G. (2007). Virtual reality in surgical technology education: A study in instructional theory and design. In Proceedings of the 2007 CTE Research and Professional Development Conference, Las Vegas, NV (pp. 218-233). Ausburn, L. J., & Ausburn, F. B. (2004). Desktop virtual reality: A powerful new technology for teaching and research in industrial teacher education. Journal of Industrial Teacher Education, 41(4), 33–58. Ausburn, L. J., & Ausburn, F. B. (2008). Effects of desktop virtual reality on learner performance and confidence in environment mastery: Opening a line of inquiry. Journal of Industrial Teacher Education, 45(1), 54–87. Ayres, A. J. (1985). Sensory integration and the child. Los Angeles, CA: Western Psychological Services. Ayres, A. J., & Maillous, Z. (1981). Influence of sensory integration procedures on language development. The American Journal of Occupational Therapy., 35(6), 383–390. Ayres, P., & Sweller, J. (2005). The split-attention principle in multimedia learning. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning (pp. 135–146). New York: Cambridge University Press. Badagliacco, J. M. (1990). Gender and race differences in computing attitudes and experience. Social Science Computer Review, 8(1), 42– 43. doi:10.1177/089443939000800105

Baddeley, A. D. (1986). Working memory. New York: Oxford University Press. Baddeley, A. D. (1998). Human memory: Theory and practice. Boston, MA: Allyn and Bacon. Baddeley, A. D. (2002). Is working memory still working? European Psychologist, 7(2), 85–97. doi:10.1027//10169040.7.2.85 Bahr, C., Nelson, N., & Van Meter, A. (1996). The effects of text-based and graphics-based software tools on planning and organizing of stories. Journal of Learning Disabilities, 29(4), 355–370. doi:10.1177/002221949602900404 Bailey, D. B., & Bruder, H. B. (2005). Family outcomes of early intervention and early childhood special education: Issues and considerations. Early Childhood Outcomes Center. Retrieved on August, 14, 2009, from http://olms. noinc.com/olms/data/resource/1811/FamilyOutcomesIssues%20Bruder 20bailey05.pdf Bailey, D. B., Bruder, M. B., Hebbeler, K., Carta, J., Defosset, M., & Greenwood, G. (2006). Recommended outcomes for families of young children with disabilities. Journal of Early Intervention, 28, 227–251. doi:10.1177/105381510602800401 Bailey, D. B., McWilliam, P. J., & Winton, P. (1992). Building family-centered practices in early intervention: A team-based model for change. Infants and Young Children, 5, 73–82. Bain, K., Basson, S., & Faisman, A. (2005). Accessibility, transcription, and access everywhere [Electronic version]. IBM Systems Journal, 44(3), 589–603. doi:10.1147/ sj.443.0589 Baker, M. C. (2001). The atoms of language. New York: Basic Books. Baker, M. C. (2003). Lexical categories: Verbs, nouns, and adjectives. Cambridge, UK: Cambridge University Press. doi:10.1017/CBO9780511615047 Balajthy, E. (2005, January/February). Text-to-speech software for helping struggling readers. Reading Online, 8(4). Retrieved from http://www.readingonline.org/ articles/artindex.asp?HRE=balajthy2/index.html.

403

Compilation of References

Bargh, J. A., & Chartrand, T. L. (1999). The unbearable automaticity of being. The American Psychologist, 54(7), 462–479. doi:10.1037/0003-066X.54.7.462

ciation. Retrieved July 9, 2007, from http://www.crito. uci.edu/tlc/findings/conferences-pdf/how_are_teachers_using.pdf

Barnes, C. (1992). Disabling imagery and the media: An exploration of the principles for media representations of disabled people. Derby: The British Council of Disabled People.

Becker, J. D. (2006). Digital equity in education: A multilevel examination of differences in and relationship between computer access, computer use and state-level technology policies. Education Policy Analysis Archives, 15(3). Retrieved May 13, 2009, from http://epaa.asu.edu/ epaa/v15n3/

Bauer, J., & Kenton, J. (2005). Toward technology integration in the schools: Why it isn’t happening [Electronic version]. Journal of Technology and Teacher Education, 13(4), 519–546. Bausch, M. E., & Ault, M. J. (2008). Assistive technology implementation plan: A tool for improving outcomes. Teaching Exceptional Children, 41(1), 6–14. Bausch, M. E., & Hasselbring, T. S. (2004). Assistive technology: Are the necessary skills and knowledge being developed at the preservice and inservice levels? Teacher Education and Special Education: The Journal of the Teacher Education Division of the Council for Exceptional Children, 27(2), 97–104. doi:10.1177/088840640402700202

Beckwith, L. (1971). Relations between attributes of mothers and their infants’ I.Q. scores. Child Development, 42, 1083–1097. doi:10.2307/1127794 Bedore, L., & Leonard, L. (1998). Specific language impairment and grammatical morphology: A discriminate function analysis. Journal of Speech and Hearing Research, 41, 1185–1192. Behrmann, M. (1998). Assistive technology for young children in special education. Yearbook (Association for Supervision and Curriculum Development), 73-93. Wilson Web Database.

Bausch, M. E., & Jones-Ault, M. (2008). Assistive Technology Implementation Plan: A tool for improving outcomes. Teaching Exceptional Children, 41(1), 6–14.

Beiter, L. J. (2000). Cochlear implants. In Alpiner, J., & Mcarthy, P. (Eds.), Rehabilitative audiology: Children and adults (3rd ed., pp. 473–496). Baltimore: Lippincott Williams & Wilkins.

Bausch, M. E., Ault, M. J., Evmenova, A. S., & Behrmann, M. M. (2008). Going beyond AT devices: Are AT services being considered? Journal of Special Education Technology, 23, 1–16.

Benedict, R. E., & Baumgardner, A. M. (2009). A population approach to understanding children’s access to assistive technology. Disability and Rehabilitation, 31, 582–592. doi:10.1080/09638280802239573

Baylor, A. L. (2001). Incidental learning and perceived disorientation in a web-based environment: Internal and external factors. Journal of Educational Multimedia and Hypermedia, 10(3), 227–251.

Benton Foundation. (1999). Native networking: Telecommunications and information technology in Indian Country. Retrieved August 14, 2009, from http://www. benton.org/publibrary/native/indexnew.html

Beasley, R., & Waugh, M. (1995). Cognitive mapping architectures and hypermedia disorientation: An empirical study. Journal of Educational Multimedia and Hypermedia, 4(2/3), 239–255.

Berninger, V., & Winn, W. (2006). Implications of advancements in brain research and technology for writing development, writing instruction, and educational evolution. In MacArthur, C., Graham, S., & Fitzgerald, J. (Eds.), The handbook of writing research (pp. 96–114). New York: Guilford.

Becker, H. J. (2001, April). How are teachers using computers in instruction? Paper presented at the annual meeting of the American Educational Research Asso-

404

Betrancourt, M. (2005). The animation and interactivity principles of multimedia learning. In Mayer, R. E. (Ed.),

Compilation of References

The Cambridge handbook of multimedia learning (pp. 287–296). New York: Cambridge University Press. Beukelman, D. R., & Mirenda, P. (1992). Augmentative and alternative communication: Management of severe communication disorders in children and adults. Baltimore, MD: Paul H. Brookes Publishing Co., Inc. Binger, C., & Light, J. (2006). Demographics of preschoolers who require AAC. Language, Speech, and Hearing Services in Schools, 37(3), 200–208. doi:10.1044/01611461(2006/022) Bishop, S. J., Jenkins, R., & Lawrence, A. D. (2007). Neural processing of fearful faces: Effects of anxiety are gated by perceptual capacity limitations. Cerebral Cortex, 17(7), 1595–1603. doi:10.1093/cercor/bhl070 Bjorkhund, D. F., & Rosenbaum, K. (2000). Middle childhood cognitive development. In Kazdin, A. (Ed.), Encyclopedia of psychology. New York: American Psychological Association and Oxford University Press. doi:10.1037/10520-103 Blackhurst, A. (2004). Handbook of special education technology research and practice. Whitefish Bay, WI: Knowledge by Design, Inc. Blackhurst, A. E. (2005). Historical perspective about technology applications for people with disabilities. In Edyburn, D., Higgins, K., & Boone, R. (Eds.), Handbook of special education technology research and practice (pp. 3–29). Whitefish Bay, WI: Knowledge by Design. Blackhurst, A. E., Lahm, E. A., Harrison, E. M., & Chandler, W. G. (1999). A framework for aligning technology with transition competencies. Career Development for Exceptional Individuals, 22(2), 153–183. doi:10.1177/088572889902200203 Blackhurst, E. A., & MacArthur, C. (1986). Microcomputer use in special education personnel preparation programs. Teacher Education and Special Education, 7(3), 27–36. doi:10.1177/088840648600900104 Blair, C., & Scott, K. (2002). Proportion of LD placements associated with low socioeconomic status: Evidence for a gradient. The Journal of Special Education, 36(1), 14–22. doi:10.1177/00224669020360010201

Bliss, J. P., Tidwell, P. D., & Guest, M. A. (1997). The effectiveness of virtual reality for administering spatial navigation training to firefighters. Presence (Cambridge, Mass.), 6, 73–86. Boeckx, C., & Piattelli-Palmarini, M. (2005). Language as a natural object – linguistics as a natural science. Linguistic Review, 22, 447–466. doi:10.1515/ tlir.2005.22.2-4.447 Bohlin, R. M., & Bohlin, C. F. (1998, March). Educational implications for limited English proficient students’ use of computers. Paper presented at the American Educational Research Association Annual Conference, San Diego, CA. Bohlin, R. M., & Bohlin, C. F. (2002). Computer-related effects among Latino students: Educational implications. TechTrends, 46(2), 29–31. doi:10.1007/BF02772072 Bohlin, R. M., & Crozier, K. (1996, April). A comparison of the computer anxiety, confidence, and attitudes of African-American, Latino, and South-east Asian middle grade students. Paper presented at the American Educational Research Association Annual Conference, New York. Bohnacker, U. (1997). Determiner phrases and the debate on functional categories in early child language. Language Acquisition, 6(1), 49–90. doi:10.1207/ s15327817la0601_3 Booker, B. W. (1995). An evaluation of the [CoWriter:SOLO] Program & its implementation. The University of Western Ontario, London, Ontario. A directed research project submitted in partial fulfillment of the requirements for the degree of Master of Education, Faculty of Graduate Studies, University of Western Ontario, London, Ontario, Canada. Retrieved July 22, 2009, from http://www.donjohnston.com/pdf/cowriter/CoWriter_Research.pdf Bowe, F. G. (2002). Deaf and hard-of-hearing Americans’ IM and e-mail use: A national survey. American Annals of the Deaf, 147, 6–10. Boys Town National Research Hospital. (2009). About hearing aids—FM systems for the classroom. Retrieved February 5, 2009, from http://boystwonhospital.org/ Hearing/hearingaids/fmsystems.asp 405

Compilation of References

Bracy, O. L., Oakes, A. L., Cooper, R. S., Watkins, D., Watkins, M., Brown, D. E., & Jewell, C. (1999). The effects of cognitive rehabilitation therapy techniques for enhancing the cognitive/intellectual functioning of seventh and eighth grade children. Cognitive Technology, 4(1), 19-27. Retrieved February 7, 2009, from http:// www.challenging-our-minds.com/tour/CognitiveTechnology.pdf Bradley, R. (1993). Children’s home environments, health, behavior, and intervention efforts: A review using the HOME inventory as a marker measure. Genetic, Social, and General Psychology Monographs, 119, 439–490. Bradley, R., Caldwell, B., Rock, S., Barnard, K., Gray, C., & Hammond, M. (1989). Home environment and cognitive development in the first 3 years of life: A collaborative study involving six sites and three ethnic groups in North America. Developmental Psychology, 25, 217–235. doi:10.1037/0012-1649.25.2.217 Brainerd, C. (1978). Piaget’s theory of intelligence. Englewood Cliffs, NJ: Prentice-Hall. Brandt, R. S. (Ed.). (2000). Education in a new era. Alexandria, VA: Association for Supervision & Curriculum Development. Bransford, J. D., Brown, A. L., & Cocking, R. R. (Eds.). (2000). How people learn: Brain, mind, experience, and school: Expanded edition. Washington, DC: National Academies Press. Brault, M. (2008). Current population reports. Household economic studies. Americans With Disabilities: 2005. U.S. Census Bureau. Retrieved from http://www.census. gov/prod/2008pubs/p70-117.pdf Bronfenbrenner, U. (1979). The ecology of human development: Experiments by nature and design. Cambridge, MA: Harvard University Press. Brotherson, M. J., & Berdine, W. H. (1993). Transition to adult services: Support for ongoing parent participation. Remedial and Special Education, 14(4), 44–52. doi:10.1177/074193259301400409

406

Brown, A. L. (1987). Metacognition, executive control, self-regulation, and other more mysterious mechanisms. In Weinert, F. E., & Kluwe, R. H. (Eds.), Metacognition, motivation, and understanding (pp. 65–116). Hillsdale, NJ: Lawrence Erlbaum Associates. Brown, M. R. (2004). Access granted: Achieving technological equity in the 21st century. In Edyburn, D., Higgins, K., & Boone, R. (Eds.), Handbook of special education technology research and practice (pp. 105–118). Whitefish Bay, WI: Knowledge by Design, Inc. Brown, M. R., Higgins, K., & Hartley, K. (2001). Teachers and technology equity [Electronic version]. Teaching Exceptional Children, 33(4), 32–39. Brown, R. (1973). A First Language: The early stages. Cambridge, MA: Harvard University Press. Brownstein, A. (2007). ED touts IDEA set-aside as funding stream for Title I. Retrieved July 24, 2009, from http://www.thompson.com/public/newsbrief. jsp?id=1626&cat=EDUCATION Brunken, R., Plass, J. L., & Leutner, D. (2003). Direct measurement of cognitive load in multimedia learning. Educational Psychologist, 38(1), 53–61. doi:10.1207/ S15326985EP3801_7 Brunning, R. H., & Schraw, G. J., Norby, M. M., & Ronning, R. R. (2004). Cognitive psychology and instruction. Upper Saddle River, NJ: Pearson/Merrill/ Prentice Hall. Bryant, D. P., & Bryant, B. R. (2003). Assistive technology for people with disabilities. New York: Allyn and Bacon. Bryant, D., & Bryant, B. (1998). Using assistive technology adaptations to include students with learning disabilities in cooperative learning activities. Journal of Learning Disabilities, 31(1), 41–54. doi:10.1177/002221949803100105 Building a Legacy: IDEA 2004. (2004). U.S. Department of Education, Office of Special Education Programs. Retrieved November 25, 2007, from http://idea.ed.gov

Compilation of References

Bull, R., Johnston, R. S., & Roy, J. A. (1999). Exploring the roles of the visual-spatial sketch pad and central executive in children’s arithmetical skills: Views from cognition and developmental neuropsychology. Developmental Neuropsychology, 15, 421–442. doi:10.1080/87565649909540759 Burgstahler, S. (2003). The role of technology in preparing youth with disabilities for postsecondary education and employment [Electronic version]. Journal of Special Education Technology, 18(4), 7–19. Burton, R., Brown, J. S., & Fischer, G. (1984). Skiing as a model of instruction. In Rogoff, B., & Lave, J. (Eds.), Everyday cognition: Its development in social context (pp. 139–150). Cambridge, MA: Harvard University Press. Bush, V. (1945) As we may think. Atlantic Monthly. Retrieved September 9, 2008, from http://www.theatlantic. com/doc/194507/bush Business Week Online. (2001, June 20). Retrieved from http://www.businessweek.com/bwdaily/dnflash/ jun2001/nf20010620_067.htm Butler, C. (1986). Effects of powered mobility on selfinitiated behaviors of very young children with locomotor disability. Developmental Medicine and Child Neurology, 28, 325–332. Bybee, R. W., & Sand, R. D. (1992). Piaget for educators (2nd ed.). Columbus, OH: Charles Merrill. Cable, R. (1965). Audio-visual handbook. London: University of London Press Ltd. Calabrese, E. J., & Baldwin, L. A. (1993). Performing ecological risk assessments. Chelsea, MI: Lewis Publishers. Calderon, R., & Greenberg, M. (2003). Social and emotional development of deaf children: Family, school, and program effects. In Marschark, M., & Spenser, P. E. (Eds.), Oxford handbook of deaf studies, language and education (pp. 177–189). New York: Oxford University Press. Campbell, J. (1996). Electronic portfolios: A five-year history. Computers and Composition, 13, 185–194. doi:10.1016/S8755-4615(96)90008-0

Campbell, P. H., Milbourne, S., Dugan, L. M., & Wilcox, M. J. (2006). A review of the evidence on practices for teaching young children to use assistive technology devices. Topics in Early Childhood Special Education, 26, 3–13. doi:10.1177/02711214060260010101 Caramazza, A., & Shapiro, K. (2004). The representation of grammatical knowledge in the brain. In Jenkins, L. (Ed.), Variation and universals in biolinguistics (pp. 147–167). Amsterdam: Elsevier B.V. Carlson, D., & Ehrlich, N. (2006). Sources of payment for assistive technology: Findings from a national survey of persons with disabilities. Assistive Technology, 18, 77–86. Carraher, D., & Schliemann, A. (2002). The transfer dilemma. Journal of the Learning Sciences, 11, 1–24. doi:10.1207/S15327809JLS1101_1 Carrow-Woolfolk, E. (1999). CASL: Comprehensive assessment of spoken language. Circle Pines, MN: American Guidance Service. Carson, T., & Johnston, I. (2000). The difficulty with difference in teacher education: Toward a pedagogy of compassion [Electronic version]. The Alberta Journal of Educational Research, 46(1), 75–83. Carta, J. J., Atwater, J. B., Greenwood, C. R., McConnell, S. R., McEvoy, M. A., & Williams, R. (2001). Effects of cumulative prenatal substance exposures and environmental risks on children’s developmental trajectories. Clinical and Child Adolescent Psychology, 30, 327–337. doi:10.1207/S15374424JCCP3003_5 Caudhill, M., & Butler, C. (1990). Naturally intelligent systems. Cambridge, MA: MIT Press. Centers for Disease Control and Prevention (CDC). (2009). Maternal and Infant Health Research: Preterm Birth. Retrieved August 14, 2009, from http://www. cdc.gov/reproductivehealth/MaternalInfant Health/ PBP.htm Chandler, P., & Sweller, J. (1991). Cognitive load theory and the format of instruction. Cognition and Instruction, 8(4), 293–332. doi:10.1207/s1532690xci0804_2

407

Compilation of References

Chandler, P., & Sweller, J. (1996). Cognitive load while learning to use a computer program. Applied Cognitive Psychology, 10, 151–170. doi:10.1002/(SICI)10990720(199604)10:2<151::AID-ACP380>3.0.CO;2-U Chandler, P., & Sweller, J. (1992). The split-attention effect as a factor in the design of instruction. The British Journal of Educational Psychology, 62, 233–246. Chen, S. Y. (2002). A cognitive model for non-linear learning in hypermedia programs. British Journal of Educational Technology, 33(4), 449–460. doi:10.1111/14678535.00281 Chen, Z., & Siegler, R. S. (2000). Intellectual development in childhood. In Sternberg, R. J. (Ed.), Handbook of intelligent. New York. Cambridge. Chomsky, N. (1955). The logical structure of linguistic theory. Cambridge, MA: Mimeographed Monograph, MIT Library. Chomsky, N. (1957). Syntactic structures. The Hague: Mouton & Co. Chomsky, N. (1981). Lectures on government and binding. Dordrecht, The Netherlands: Foris. Chomsky, N. (1995). The minimalist program. Cambridge, MA: MIT Press. Chomsky, N. (2002). An interview on minimalism. In Chomsky, N. (Ed.), On nature and language (pp. 92–161). Cambridge, UK: Cambridge University Press. doi:10.1017/CBO9780511613876.005 Chomsky, N. (2004). Language and mind: Current thoughts on ancient problems. In Jenkins, L. (Ed.), Variation and universals in biolinguistics (pp. 379–405). Cambridge, MA: Elsevier. Chomsky, N. (2009). Introduction. In Piattelli-Palmarini, M., Uriagereka, J., & Salaburu, P. (Eds.), Of minds & language: A dialogue with Noam Chomsky in the Basque Country (pp. 13–43). Oxford: Oxford University Press. Christensen, C. M., Horn, M. B., & Johnson, C. W. (2008). Disrupting class: How disruptive innovation will change

408

the way the world learns. New York: McGraw-Hill. Clare, L., & Woods, R. T. (2004). Cognitive training and cognitive rehabilitation for people with early-stage Alzheimer’s disease: A review. Neuropsychological Rehabilitation, 14(4), 385– 401. doi:10.1080/09602010443000074 Clark, J. M., & Paivio, A. (1991). Dual coding theory and education. Educational Psychology Review, 3(3), 149–210. doi:10.1007/BF01320076 Clark, R. (2003). Building Expertise: Cognitive Methods for Training and Performance Improvement (2nd ed.). Washington, DC: International Society for Performance Improvement. Clark, R. C. (2003). Authorware, multimedia, and instructional methods. Retrieved December 3, 2008, from http://www.macromedia.com/support/authorware/ basics/instruct/index.html Clark, R., Nguyen, F., & Sweller, J. (2006). Efficiency in learning: Evidence-based guidelines to manage cognitive load. San Francisco, CA: Pfeiffer. Clay, M. (1993). Reading Recovery: A guidebook for teachers in training. Portsmouth, NH: Heinemann. Cloud, D. J., & Rainer, L. B. (1998). Applied modeling and simulation: An integrated approach to development and operation. New York: McGraw Hill. Cobanoglu, C., Warde, B., & Moreo, P. J. (2001). A comparison of mail, fax, and web-based survey methods. International Journal of Market Research, 43(4), 441–452. Cobb, S., & Fraser, D. S. (2005). Multimedia learning in virtual reality. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning. New York: Cambridge University Press. Cobb, S., Beardon, L., Eastgate, R., Glover, T., Kerr, S., & Neale, H. (2002). Applied virtual environments to support learning of social interaction skills in users with Asperger’s Syndrome. Digital Creativity, 13(1), 11–22. doi:10.1076/digc.13.1.11.3208

Compilation of References

Collins, A., Brown, J. S., & Newman, S. E. (1989). Cognitive apprenticeship: Teaching the crafts of reading, writing, and mathematics. In Resnick, L. B. (Ed.), Knowing, learning, and instruction: Essays in honor of Robert Glasser (pp. 453–494). Hillsdale, NJ: Lawrence Erlbaum & Associates, Inc.

Cuddihy, A., Fisher, B., Gordon, R., & Schumaker, E. (1994). C-note: A computerized notetaking system for hearing-impaired students in mainstream secondary education [Electronic version]. Information and Technology for the Disabled, 1(2), 45–52.

Conklin, J. (1987, September 20). Hypertext-an introduction and survey. IEEE Computer, 17-41.

Cullen, R. (2001). Addressing the digital divide. Online Information Review, 25(5), 311–320. doi:10.1108/14684520110410517

Cook, A. M., & Hussey, S. (2007). Assistive technologies: Principles and practice (2nd ed.). St. Louis, MO: Mosby.

DaCosta, B. (2009). The effect of cognitive aging on multimedia learning: An investigation of the cognitive aging principle. Germany: VDM Verlag Dr. Muller.

Correll, J., Park, B., Judd, C. M., Wittenbrink, B., Sadler, M. S., & Keesee, T. (2007). Across the thin blue line: Police officers and racial bias in the decision to shoot. Journal of Personality and Social Psychology, 92(6), 1006–1023. doi:10.1037/0022-3514.92.6.1006

Daniels, H. L. (1996). Interaction of cognitive style and learner control of presentation mode in a hypermedia environment. Unpublished Doctoral dissertation, Virginia Polytechnic Institute and State University, Blacksburg, VA.

Corver, N., & van Riemsdijk, H. (Eds.). (2001). Semilexical categories (Studies in Generative Grammar 59). Berlin: Mouton de Gruyter.

Daniels, H. L., & Moore, D. M. (2000). Interaction of cognitive style and learner control in a hypermedia environment. International Journal of Instructional Media, 27(4), 369–383.

Costa, J., McPhail, G., Smith, J., & Brisk, M. E. (2005). Faculty first: The challenge of infusing the teacher education curriculum with scholarship on English language learners [Electronic version]. Journal of Teacher Education, 56(2), 104–118. doi:10.1177/0022487104274119 Courtright, J., & Courtright, I. (1976). Imitative modeling as a theoretical base for instructing language-disordered children. Journal of Speech and Hearing Research, 19, 655–663. Courtright, J., & Courtright, I. (1979). Imitative modeling as a language intervention strategy: The effects of two mediating variables. Journal of Speech and Hearing Research, 22, 389–402. Crain, S. (1991). Language acquisition in the absence of experience. The Behavioral and Brain Sciences, 14, 597–650. Cuban, L. (1986). Teachers and machines: The classroom use of technology since 1920. New York: Teachers College Press.

Darwin, C. J., Turkey, M. T., & Crowder, R. G. (1972). An auditory analogue of the Sperling Partial Report Procedure: Evidence for brief auditory storage. Cognitive Psychology, 3, 255–267. doi:10.1016/00100285(72)90007-2 Davis, T., & Trebian, M. (2001). Shaping the destiny of Native American people by ending the digital divide: The nation’s tribal colleges and universities. EDUCAUSE Review, 38–46. de Jong, P. F. (1998). Working memory deficits of reading disabled children. Journal of Experimental Child Psychology, 70(2), 75–96. doi:10.1006/jecp.1998.2451 DeBell, M., & Chapman, C. (2003). Computers and Internet use by children and adolescents in 2001 (NCES 2004-014). Washington, DC: National Center for Education Statistics, U.S. Department of Education. DeBell, M., & Chapman, C. (2006). Computer and Internet use by students in 2003 (NCES 2006-065). U.S. Department of Education. Washington, DC: National Center for Education Statistics.

409

Compilation of References

Demchak, M., & Greenfield, R. (2000). A transition portfolio for Jeff, a student with multiple disabilities. Teaching Exceptional Children, 32(6), 44–49. Denard-Goldman, K., & Jahn-Scmalz, K. (2007). “As you Likert it”: Conducting gap-based needs assessments. Health Promotion Practice, 8(3), 225–228. doi:10.1177/1524839907303608

Dickey, M. (2005). Brave new (interactive) worlds: A review of the design affordances and constraints of two 3D virtual worlds as interactive learning environments. Interactive Learning Environments, 13(1-2), 121–137. doi:10.1080/10494820500173714 Dillion, H. (2001). Hearing aids. Turramurra, Australia: Boomerang Press.

Deno, S. L. (2003). Curriculum-based measures: Development and perspectives. Assessment for Effective Intervention, 28(3-4), 3–12. doi:10.1177/073724770302800302

Dimmitt, S., Hodapp, J., Judas, C., Munn, C., & Rachow, C. (2006). Iowa Text Reader Project impacts on student achievement. Closing the Gap, 24(6), 12–13.

Deno, S. L. (2003). Developments in curriculum-based measurement. The Journal of Special Education, 37(3), 184–192. doi:10.1177/00224669030370030801

Dix, A. D., Finlay, E. J., Abowd, D. G., & Beale, R. (1998). Human-computer interaction. London: Prentice Hall Europe.

Dept, U. S. of Education, National Center for Education Statistics. (2006). Internet access in public schools and classrooms. 1994-2005 (NCES 2007-020). Retrieved January 31, 2008, from http://nces.ed.gov/ pubs2007/2007020.pdf

Dobransky, K., & Hargittai, E. (2006). The disability divide in Internet access and use. Information Communication and Society, 9(3), 313–334. doi:10.1080/13691180600751298

DeRuyter, F. (1994). Assistive technology usage outcomes: A preliminary report. RESNA Annual Conference. Washington, DC: RESNA. DeRuyter, F. (1997). The importance of outcome measures for assistive technology service delivery systems. Technology and Disability, 6, 89–104. doi:10.1016/ S1055-4181(96)00197-5 Desouza, E. R., & Sivewright, D. (1993). An ecological approach to evaluating a special education program. Adolescence, 28, 517–525. Desse, J. (2001). The state of education and the double transfer of learning paradox. In Haskell, R. E. (Ed.), Transfer of learning: Cognition, instruction, and reasoning (pp. 3–21). San Diego: Academic Press. Dewey, J. (1938). Experience in education. New York: Collier Books. Dias, P., & Sousa, A. P. (1997). Understanding navigation and disorientation in hypermedia learning environments. Journal of Educational Multimedia and Hypermedia, 6(2), 173–185.

410

DoD Modeling and Simulation (M&S) Glossary. (1998). Under Secretary of Defense for Acquisition Technology. Don Johnston Developmental Equipment, Inc. (1992). CoWriter:SOLO [Writing-assistance software]. Wauconda, IL: Author. Donne, V., & Zigmond, N. (2008). Engagement during reading instruction for students who are deaf or hard of hearing in public schools [Electronic version]. American Annals of the Deaf, 153(3), 294–303. doi:10.1353/ aad.0.0044 Drever, J. (1952). A dictionary of psychology. London: Penguin Reference Books. Dunkel, P., & Davy, S. (1989). The heuristic of lecture note taking: Perceptions of American and international students regarding the value & practice of note taking [Electronic version]. English for Specific Purposes, 8, 33–50. doi:10.1016/0889-4906(89)90005-7 Dunst, C. J., & Shue, P. (2005). Creating literacy rich natural learning environments for infants, toddlers, and preschoolers. In Horn, E. M., & Jones, H. (Eds.), Supporting early literacy development. Young Exceptional Children (pp. 15–30). Longmont, CO: Sopris West.

Compilation of References

Dunst, C. J., Hamby, D., Trivette, C. M., Raab, M., & Bruder, M. B. (2000). Everyday family and community lives and children’s natural occurring learning opportunities. Journal of Early Intervention, 23, 151–154. do i:10.1177/10538151000230030501 Duquette, C. (2007). Students at risk: Solutions to classroom challenges. Ontario: Pembroke Publishers. Early Childhood Outcomes Center (ECO). (2005). Family and child outcomes for early intervention and early childhood special education. Retrieved August 14, 2009, from http://www.fpg.unc.edu /~eco/assets/ pdfs/ ECO_New%20requirement%20OSEP_9-7-06.pdf Early Childhood Outcomes Center (ECO). (2009). Retrieved August 14, 2009, from http://www.fpg.unc. edu/~eco/pages/fed_req.cfm Easterbrooks, S. (2001). Veteran teachers of children who are deaf/hard of hearing describe language instructional practices: Implications for teacher preparation [Electronic version]. Teacher Education and Special Education, 24, 116–127. doi:10.1177/088840640102400206 Education for All Handicapped Children Act of 1975. (1975). Public Law 94-142. Edvinsson, L., & Malone, M. S. (1997). Intellecutal Captial: Realizing your Company’s True Value by Finding its Hdden Brainpower. New York: Harper Business. Edyburn, D. (2003). Assistive technology and evidencedbased practice. ConnSENCE Bulletin. Retrieved January 20, 2009, from http://www.connsensebulletin.com/ edyatevidence.html Edyburn, D. L. (2000). 1999 in review: A synthesis of the special education technology literature. Journal of Special Education Technology, 15(1), 7–18. Edyburn, D. L. (2000). Assistive technology and students with mild disabilities [Electronic version]. Focus on Exceptional Children, 32(9), 1–24. Edyburn, D. L. (2003). Measuring assistive technology outcomes: Key concepts. Journal of Special Education Technology, 18(1), 53–55.

Edyburn, D. L. (2005). Technology enhanced performance. Special Education Technology Practice, 72(2), 16–25. Edyburn, D. L. (2007). 2006 year in review: What have we learned lately? Paper presented at the 25th Annual Closing the Gap Conference, October 18, Minneapolis, MN. Edyburn, D. L. (2007). Technology-enhanced reading performance: Defining a research agenda. Reading Research, 42(1), 146–152. doi:10.1598/RRQ.42.1.7 Edyburn, D. L. (2008). Measuring outcomes in Assistive Technology. Special Education Technology Practice, 10(4), 16–21. Edyburn, D. L., Fennema-Jansen, S., Harihan, P., & Smith, R. (2005). Assistive Technology outcomes: Implementation strategies for collecting data in schools. Assistive Technology Benefits and Outcomes. Retrieved from http://www/atia.org/atob/ATOBWeb/ATOBV2N1/ Documents/[email protected] Elbro, C., Rasmussen, I., & Spelling, B. (1996). Teaching reading to disabled readers with language disorders: A controlled evaluation of synthetic speech feedback. Scandinavian Journal of Psychology, 37, 140–155. doi:10.1111/j.1467-9450.1996.tb00647.x Elementary and Secondary Education Act, 1965. (n.d.). Retrieved on January 2, 2009, from http://nces.ed.gov Eleweke, C. J., & Rodda, M. (2000). Factors contributing to parents’ selection of a communication mode to use with their deaf children [Electronic version]. American Annals of the Deaf, 145(4), 375–383. Elkind, J., Cohen, K., & Murray, C. (1993). Using computer-based readers to improve reading comprehension with students with Dyslexia. Annals of Dyslexia, 42, 238–259. doi:10.1007/BF02928184 Elliot, L., Foster, S., & Stinson, M. (2002). Student study habits using notes from a speech-to-text support service [Electronic version]. Exceptional Children, 69(1), 25–40.

411

Compilation of References

Elm, W., & Woods, D. (1985). Getting lost: A case study in interface design. In Proceedings of the human factors society 29th Annual Meeting (pp. 927-931). Emmelkamp, P. M., Krijn, M., Hulsbosch, A. M., de Vries, S., Schuemie, M. J., & van der Mast, C. A. (2002). Virtual reality treatment versus exposure in vivo: A comparative evaluation in acrophobia. Behaviour Research and Therapy, 40(5), 509–516. doi:10.1016/ S0005-7967(01)00023-7 Engelbart, D. (1962). Augmenting Human Intellect: A conceptual framework, summary report. SRI International. On Contract AF, 49(638), 1024. Engle, C. (1978). A Single Subject Study of Multimorpheme Structures in Early Language Development. Unpublished Master of Science Thesis, University of Vermont. Ertmer, D. J. (2002). Technological innovations and intervention practices for children with cochlear implants [Electronic version]. Language, Speech, and Hearing Services in Schools, 33(3), 218–221. doi:10.1044/01611461(2002/019) Ertmer, D. J., & Mellon, J. A. (2001). Beginning to talk at 20 months: Early vocal development in a young cochlear implant recipient. Journal of Speech, Language, and Hearing Research: JSLHR, 44(1), 192–206. doi:10.1044/1092-4388(2001/017) Erwin, E. J., & Brown, F. (2003). From theory to practice. A contextual framework for understanding selfdetermination in early childhood environments. Infants and Young Children, 16(1), 77–87. Estrada-Hernandez, N., Wadsworth, J. S., Nietupski, J., Warth, J., & Winslow, A. (2008). Employment or economic success? Experiences of youth with disabilities in transition from school to work. Journal of Employment Counseling, 45(1), 14–24. Eveland, W. P. Jr, & Dunwoody, S. (2001). User control and structural isomorphism or disorientation and cognitive load? Learning from the web versus print. Communication Research, 28(1), 48–78. doi:10.1177/009365001028001002

412

Fairlie, R. W. (2005). Are we really a nation online? Ethnic and racial disparities in access to technology and their consequences. Retrieved May 12, 2009, from http://www. civilrights.org/publications/nation-online/ FAPE. (2001). 1997 Individuals with disabilities education act amendments increase access to technology for students. Families and Advocates Partnership for Education (FAPE) Retrieved August 1, 2009, from http://www. fape.org/pubs/FAPE-13.pdf Farkas, G. (2003). Racial disparities and discrimination in education. What do we know, how do we know it, and what do we need to know? Teachers College Record, 105, 1119–1146. doi:10.1111/1467-9620.00279 Farmer, M. E., Klein, R., & Bryson, S. E. (1992). Computer-assisted reading: Effects of whole word feedback on fluency and comprehension in readers with severe disabilities. Remedial and Special Education, 13, 50–60. doi:10.1177/074193259201300208 Ferguson, C. J. (2000). Free will: An automatic response. The American Psychologist, 55(7), 762–763. doi:10.1037/0003-066X.55.7.762 Ferguson, H. (1968). Modular scheduling and social atmosphere. Clearing House (Menasha, Wis.), 42(9). Field, S., Martin, J., Miller, R., Ward, M., & Wehmeyer, M. (1998). A practical guide to teaching self-determination. Reston, VA: Council for Exceptional Children. Figueras, B., Edwards, L., & Langdon, D. (2008). Executive function and language in deaf children [Electronic version]. Journal of Deaf Studies and Deaf Education, 13(3), 362–377. doi:10.1093/deafed/enm067 Finn, D., Futernick, A., & MacEachern, S. (2005). Efficacy of language intervention software in preschool classrooms. Paper presented at the annual meeting of the American Speech-Language-Hearing Association, San Diego, November, 2005. First, P., & Hart, Y. (2002, October). Access to cyberspace: The new issue in educational justice. Journal of Law & Education, 31(4), 385–411.

Compilation of References

Fishbein, M. (Ed.). (1967). Attitude and the Prediction of Behaviour. New York: Wiley. Fitzpatrick, M., & Brown, M. R. (2008). Assistive technology access and use: Considerations for culturally and linguistically diverse students and their families. Journal of Special Education Technology, 23(4), 47–52. Fitzpatrick, M., & Knowlton, E. (2009). Bringing evidence-based self-directed intervention practices to the trenches for students with emotional and behavioral disorders [Electronic version]. Preventing School Failure, 53(4), 253–266. doi:10.3200/PSFL.53.4.253-266 Flavell, J. H. (1979). Metacognition and cognitive monitoring: A new area of cognitive-developmental inquiry. The American Psychologist, 34, 906–911. doi:10.1037/0003-066X.34.10.906 Flecher, J. D., & Tobias, S. (2005). The multimedia principle. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning (pp. 117–133). New York: Cambridge University Press. Fleishman, E. A. (1972). On the relation between abilities, learning and human performance. The American Psychologist, 27(11), 1017–1032. doi:10.1037/h0033881 Fleishman, E. A., & Quaintance, M. K. (1984). Taxonomies of human performance. Orlando, FL: Academic Press. Fletcher, J. M., Lyon, G. R., Fuchs, L. S., & Barnes, M. A. (2006). Learning disabilities: From identification to intervention. New York: The Guilford Press. Fletcher, J., Francis, D., Rourke, B., Shaywitz, S., & Shaywitz, B. (1992). The validity of discrepancy-based definitions of reading disabilities. Journal of Learning Disabilities, 25, 555–561. doi:10.1177/002221949202500903 Fodor, J. D. (2009). Syntax Acquisition: An evaluation measure after all? In Piattelli-Palmarini, M., Uriagereka, J., & Salaburu, P. (Eds.), Of minds & language: A dialogue with Noam Chomsky in the Basque Country (pp. 256–277). Oxford, UK: Oxford University Press. Foltz, P. W. (1996). Comprehension, coherence and strategies in hypertext and linear text. In Rouet, J. F.,

Levonen, J. J., Dillon, A. P., & Spiro, R. J. (Eds.), Hypertext and cognition. Hillsdale, NJ: Lawrence Erlbaum Associates. Forbes, T. L., & Forbes, T. L. (1994). Ecotoxicology in theory and practice. London: Chapman & Hall. Foss, C. (1989). Tools for reading and browsing hypertext. Information processing management. In S. McDonald & R. J. Stevenson (1996). Disorientation in hypertext: The effects of three text structures on navigation performance. Applied Ergonomics, 27(1), 61–68. Frank, A. R., & Sitlington, P. L. (2000). Young adults with mental disabilities: Does transition planning make a difference? Education and Training in Mental Retardation and Developmental Disabilities, 35(2), 119–134. Franklin, C. Jr., Wilson, T., & Ebel, M. (2004). Preparing for the Americans with Disabilities Act. Frick, R. W. (1984). Using both an auditory and a visual short-term store to increase digit span. Memory & Cognition, 12(5), 507–514. Frieden, L. (2003). When the Americans with Disabilities Act goes online: Application of the ADA to the Internet and the worldwide web (1st ed.). Washington, DC: National Council on Disability. Friedman, A., Polson, M. C., & Dafoe, C. G. (1988). Dividing attention between the hands and the head: Performance trade-offs between rapid finger tapping and verbal memory. Journal of Experimental Psychology. Human Perception and Performance, 14, 60–68. doi:10.1037/0096-1523.14.1.60 Froud, K. (2001). Prepositions and the lexical/functional divide: Aphasic evidence. Lingua, 111, 1–28. doi:10.1016/ S0024-3841(00)00026-7 Fuchs, D., & Kearns, D. M. (2008, February 29). Cognitive assessment in an RTI framework. Presentation at the Learning Disabilities Association of America Conference, Chicago, Illinois. Fuchs, D., Mock, D., Morgan, P., & Young, C. (2003). Responsiveness-to-instruction: Definitions, evidence, and implications for learning disabilities construct.

413

Compilation of References

Learning Disabilities Research & Practice, 18(3), 157–171. doi:10.1111/1540-5826.00072 Fuchs, L. S., & Fuchs, D. (1986). Effects of systematic formative evaluation: A meta-analysis. Exceptional Children, 53(3), 199–208. Fuchs, L. S., & Fuchs, D. (2007). A model for implementing responsiveness to intervention. Teaching Exceptional Children, 39(5), 14–20. Fuchs, L., Fuchs, D., Hamlett, C. L., Walz, L., & Germann, G. (1993). Formative evaluation of academic progress: How much growth can we expect? School Psychology Review, 22, 1–30. Furst, M. (1993). Building self-esteem. Academic Therapy, 19(1), 11–15. Gagne, R. (1962). The acquisition of knowledge. Psychological Review, 69(4), 355–365. doi:10.1037/h0042650 Gagne, R. M., & Driscolt, M. P. (1988). Essentials of learning for instruction. Retrieved August 10, 2009, from http://www.brighthub.com Gale, M., Crofford, J., & Gillam, R. (1999). Fast ForWord vs. Laureate Learning Systems: Comparative outcomes. Paper presented at the annual meeting of the American Speech-Language-Hearing Association, San Francisco, November, 1999. Gamble, D., & Satcher, J. (2002). Rehabilitation outcomes, expenditures, and the provision of assistive technology for persons with traumatic brain injury. Journal of Applied Rehabilitation Counseling, 33(3), 41–44. Garcia-Palacios, A., Hoffman, H., Carlin, A., Furness, T. A., & Botella, C. (2002). Virtual reality in the treatment of spider phobia: A controlled study. Behaviour Research and Therapy, 40(9), 983–993. doi:10.1016/ S0005-7967(01)00068-7 Gardner, M. F. (1990). Expressive One-Word Picture Vocabulary Test-Revised. Novato, CA: Academic Therapy Publications. Gelfer, J., & Perkins, P. (1998). Portfolios: Focus on young children. Teaching Exceptional Children, 31(2), 44–47.

414

Gerber, M. M. (2005). Teachers are still the test: Limitations of response to instruction strategies for identifying children with learning disabilities. Journal of Learning Disabilities, 38(6), 516–524. doi:10.1177/00222194050 380060701 Gersten, R., & Edyburn, D. L. (2007). Enhancing the evidence base of special education technology research: Defining special education research quality indicators. Journal of Special Education Technology, 22(3), 3–18. Gersten, R., Baker, B., & Lloyd, J. W. (2000). Designing high-quality research in special education. The Journal of Special Education, 34(1), 2–18. doi:10.1177/002246690003400101 Geurts, H. M., & Embrechts, M. (2008). Language profiles in ASD, SLI, and ADHD. Journal of Autism and Developmental Disorders, 38, 1931–1943. doi:10.1007/ s10803-008-0587-1 Gillam, R. B., Loeb, D. F., Hoffman, L. M., Bohman, T., Champlin, C., & Thibodeau, L. (2008). The Efficacy of Fast ForWord-Language Intervention in School-Age Children with Language Impairment: A Randomized Clinical Trial. Journal of Speech-Language-Hearing Research, 51, 97–119. doi:10.1044/1092-4388(2008/007) Gillam, R., & Loeb, D. (2005). A comparison of language intervention programs. Paper presented at the American Speech-Language-Hearing Association Schools Conference, Indianapolis, July 2005. Gillam, R., Crofford, J., Gale, M., & Hoffman, L. (2001). Language change following computer-assisted language instruction with Fast ForWord or Laureate Learning Systems software. American Journal of SpeechLanguage Pathology, 10, 231–247. doi:10.1044/10580360(2001/021) Gilman, A. (1969). Comparison of several feedback methods for correcting errors by computer-assisted instruction. Journal of Educational Psychology, 60, 503–508. doi:10.1037/h0028501 Goodman, G., & Williams, C. M. (2007). Interventions for increasing the academic engagement of students with autism spectrum disorders in inclusive classrooms. Teaching Exceptional Children, 39, 53–61.

Compilation of References

Goodman, K. (1967). Reading: A psychologlinguistic guessing game. The Journal of the Reading Specialist, 4, 126–135. Gorski, P. C. (2005). Multicultural education and the Internet: Intersections and integrations (2nd ed.). Boston: McGraw Hill. Graham, S., & Harris, K. (2003). Students with learning disabilities and the process of writing: A meta-analysis of SRSD studies. In Swanson, H. L., Harris, K. R., & Graham, S. (Eds.), Handbook of learning disabilities (pp. 323–344). New York: Guilford Press. Graham, S., & Harris, K. R. (2005). Writing better: Effective strategies for teaching students with learning difficulties. Baltimore: Paul H. Brookes Publishing Co. Grant, C. A., & Gillette, M. (2006). A candid talk to teacher educators about effectively preparing teachers who can teach everyone’s children [Electronic version]. Journal of Teacher Education, 57, 292–299. doi:10.1177/0022487105285894 Gray, W. M. (1990). Formal operational thought. In Overton, W. F. (Ed.), Reasoning necessity and logic: Developmental perspective (pp. 76–79). Hillsdale, NJ: Erlbaum. Greenberg, M. T., & Kusche, C. A. (1993). Promoting social and emotional development in deaf children: The PATHS Project. Seattle, WA: University of Washington Press. Greene, R. L. (1992). Human memory: Paradigms and paradoxes. Hillsdale, NJ: Lawrence Erlbaum. Greeno, J. G. (1998). The situativity of knowing, learning, and research. The American Psychologist, 53(1), 5–26. doi:10.1037/0003-066X.53.1.5 Greenwood, C. R., & Carta, J. J. (1987). An ecobehavioral analysis of instruction within special education. Focus on Exceptional Children, 19, 1–12. Gresham, F. (2002). Responsiveness to intervention: An alternative approach to the identification of learning disabilities. In Bradley, R., Danielson, L., & Hallahan, D.

(Eds.), Identification of learning disabilities: Response to treatment (pp. 467–519). Mahwah, NJ: Erlbaum. Gresham, F. M. (1989). Assessment of treatment integrity in school consultation and prereferral intervention. School Psychology Review, 18, 37–50. Grodzinsky, Y. (2004). Variation in Broca’s Region: Preliminary cross-methodological comparisons. In Jenkins, L. (Ed.), Variation and universals in biolinguistics (pp. 172–189). Oxford: Elsevier B.V. Grodzinsky, Y. (2006). A blueprint for a brain map of syntax. In Grodzinsky, Y., & Amunts, K. (Eds.), Broca’s Region (pp. 83–107). New York: Oxford University Press. doi:10.1093/acprof:oso/9780195177640.003.0006 Guice, A. A., & McCoy, L. P. (2001). The digital divide in Native American tribal schools: Two case studies. Paper Presented at the Annual Meeting of the American Educational Research Association, Seattle, WA, April 10-14, 2001. Gupta, M., & Gramopadhye, A. K. (1995). An evaluation of different navigational tools in using hypertext. Computers & Industrial Engineering, 29(1-4), 437–441. doi:10.1016/0360-8352(95)00113-F Haager, D., Klingner, J., & Vaughn, S. (2007). Evidencebased practices for response to intervention. Baltimore, MD: Paul H. Brookes Publishing Co. Haith, M. M., & Benson, J. B. (1998). Infant cognition. In Damond, W. (Ed.), Handbook of child psychology (5th ed., Vol. 2). New York: John Wiley & Sons. Halff, H. M., Hollan, J. D., & Hutchins, E. L. (1986). Cognitive science and military training. The American Psychologist, 41(10), 1131–1139. doi:10.1037/0003066X.41.10.1131 Hall, G., & Hord, S. (1987). Change in schools: Facilitating the process. New York: State University Press. Hall, G., & Louks, S. F. (1997). A developmental model for determining whether the treatment is actually implemented. American Educational Research Journal, 14(3), 263–273.

415

Compilation of References

Hammill, D. (2004). What we know about correlates of reading. Exceptional Children, 70(4), 453–468. Hammill, D. D., & Bryant, B. R. (1998). Learning disabilities diagnostic inventory. Austin, TX: Pro-ed. Hammond, N. (1993). Learning with hypertext: Problems, principles and prospects. In McKnight, C., Dillon, A., & Richardson, J. (Eds.), Hypertext: A psychological perspective (pp. 51–69). London: Ellis Horwood. Hanson, M., Horn, E., Sandall, S., Beckman, P., Morgan, M., & Marquaart, J. (2001). After preschool inclusion: children’s educational pathways over the early school years. Exceptional Children, 68, 65–83. Harp, S. F., & Mayer, R. E. (1997). The role of interest in learning from scientific text and illustrations: On the distinction between emotional interest and cognitive interest. Journal of Educational Psychology, 89(1), 92–102. doi:10.1037/0022-0663.89.1.92 Harp, S. F., & Mayer, R. E. (1998). How seductive details do their damage: A theory of cognitive interest in science learning. Journal of Educational Psychology, 90(3), 414–434. doi:10.1037/0022-0663.90.3.414 Harrington, M. L., & Powers, A. R. (2004). Preparing teachers to meet the needs of children who have cochlear implants [Electronic version]. Teacher Education and Special Education, 27(4), 360–372. doi:10.1177/088840640402700404 Harter, S. (1978). Effectance motivation reconsidered: Toward a developmental model. Annual Human Resources Development Report, 21, 36–64. Harty, S. C., Miller, C. J., Newcorn, J. H., & Halperin, J. M. (2008). Adolescents with childhood ADHD and disruptive behavior disorders: Aggression, anger, and hostility. Child Psychiatry and Human Development, (40): 85–97. Hasselbring, T. S., & Bausch, M. E. (2005). Assistive technologies for reading. Educational Leadership, 63(4), 72–75. Hasselbring, T. S., & Glaser, C. H. (2000). Use of computer technology to help students with special needs. The Future of Children, 10(2), 102–122. doi:10.2307/1602691 416

Hasselbring, T., & Bausch, M. (2006). Assistive technologies for reading. Educational Leadership, 63(4), 72–75. Hatton, C. (1998). Pragmatic language skills in people with intellectual disabilities: A review. Journal of Intellectual & Developmental Disability, 23(1), 79–100. doi:10.1080/13668259800033601 Hauser, M. D., Chomsky, N., & Fitch, W. T. (2002). The faculty of language: What is it, who has it, and how did it evolve? Science, 298, 1569–1579. doi:10.1126/science.298.5598.1569 Healy, A., F., & McNamara, D., S. (1996). Verbal learning and memory: Does the modal model still work? Annual Review of Psychology, 47, 143–172. doi:10.1146/annurev. psych.47.1.143 Henry, M. K., & Redding, N. C. (2002). Patterns for success in reading and spelling: A multisensory approach to teaching phonics and word analysis. Austin, TX: Pro-Ed. Heppner, P. P., Kivlighan, D. M. Jr, & Wampold, B. E. (1999). Validity issues in research design. In Heppner, P. P., Kivlighan, D. M. Jr, & Wampold, B. E. (Eds.), Research design in counseling (2nd ed., pp. 56–78). Belmont, CA: Wadsworth. Herczeg, M. (2004). Experience design for computerbased learning systems: Learning with engagement and emotions. Paper presented at the ED-MEDIA 2004 World Conference on Educational Multimedia, Hypermedia and Telecommunications. Hermans, D., Knoors, H., Ormel, E., & Verhoeven, L. (2008). The relationship between the reading and signing skills of deaf children in bilingual education programs [Electronic version]. Journal of Deaf Studies and Deaf Education, 13(4), 518–530. doi:10.1093/deafed/enn009 Hetzroni, O., & Schrieber, B. (2004). Word processing as an assistive technology tool for enhancing academic outcomes of students with writing disabilities in the general classroom. Journal of Learning Disabilities, 37(2), 143–154. doi:10.1177/00222194040370020501

Compilation of References

Higgins, A. H., Belland, J., Conceicao-Runlee, S., & Santos, R., M., & Rothenberg, D. (2000). Instructional technology and personnel preparation. Topics in Early Childhood Special Education, 20, 132–144. doi:10.1177/027112140002000302 Hinds, P. J., Patterson, M., & Pfeffer, J. (2001). Bothered by abstraction: The effect of expertise on knowledge transfer and subsequent novice performance. The Journal of Applied Psychology, 86(6), 1232–1243. doi:10.1037/00219010.86.6.1232 Hintermair, M. (2006). Parental resources, parental stress, and socioemotional development of deaf and hard of hearing children [Electronic version]. Journal of Deaf Studies and Deaf Education, 11(4), 493–513. doi:10.1093/deafed/enl005 Hirose, M., Taniguchi, M., Nakagaki, Y., & Nihei, K. (1994). Virtual playground and communication environments for children. IEICE Transactions on Information & Systems. E (Norwalk, Conn.), 77D(12), 1330–1334. Hirsh-Pasek, K., & Golinkoff, R. M. (1996). The origins of grammar: Evidence from early language comprehension. Cambridge, MA: The MIT Press. Hirsh-Pasek, K., Golinkoff, R., Fletcher, P., DeGaspeBeaubien, F., & Cauley, K. (1985). In the beginning: One-word speakers comprehend word order. Paper presented at the Boston Child Language Conference, Boston, October 1985. Hitch, G. J., & McLean, J. F. (1991). Working memory in children with specific arithmetical learning difficulties. The British Journal of Psychology, 82, 375–386. Hitchcock, C., Meyer, A., Rose, D., & Jackson, R. (2007). Technical brief: Access, participation, and progress in the general curriculum. Retrieved April 19, 2008, from http:// www.cast.org/publications/ncac/ncac_techbrief.html Hmelo-Silver, C. E. (2006). Design principles for scaffolding technology based inquiry. In O’Donnell, A. M., Hmelo-Silver, C. E., & Erkens, G. (Eds.), Collaborative reasoning, learning and technology (pp. 147–170). Mahwah, NJ: Erlbaum.

Hockey, G. R., Healey, A., Crawshaw, M., Wastell, D. G., & Sauer, J. (2003). Cognitive demands of collision avoidance in simulated ship control. Human Factors, 45(2), 252–265. doi:10.1518/hfes.45.2.252.27240 Hodapp, J., Judas, C., Rachow, C., Munn, C., & Dimmitt, S. (2007). Iowa Text Reader Project Year 3: Longitudinal results. Paper presented at the 25th Annual Closing the Gap Conference, October 20, Minneapolis, MN. Hodgedon, L. Q. (1995). Solving social-behavioral problems through the use of visually supported communication. In Quill, K. A. (Ed.), Teaching children with Autism: Strategies to enhance communication and socialization (pp. 265–286). New York: Delmar. Hoffman, B., Hartley, K., & Boone, R. (2005). Reaching accessibility: Guidelines for creating and refining digital learning materials. Intervention in School and Clinic, 40, 171–176. doi:10.1177/10534512050400030601 Holland, J., & Skinner, B. F. (1961). The analysis of behavior. New York: McGraw-Hill. Hong, F. T. (1998). Picture-Based vs. Rule-Based Learning. Department of Physiology, Wayne State University. Hord, S., Rutherford, W. L., Austin, L., & Hall, G. E. (1987). Taking charge of change. Alexandria, VA: Association of Supervision and Curriculum Development. Hornstein, N., Nunes, J., & Grohmann, K. (2005). Understanding minimalism. New York: Cambridge University Press. Hotz, G. A., Castelblanco, A., Lara, I. M., Weiss, A. D., Duncan, R., & Kuluz, J. W. (2006). Snoezelen: A controlled multi-sensory stimulation therapy for children recovering from severe brain injury. Brain Injury : [BI], 20(8), 879–888. doi:10.1080/02699050600832635 Howard, R. (1986). Microcomputer applications in speech pathology. In Northern, J. (Ed.), The personal computer for speech, language, and hearing professionals (pp. 101–112). Boston: Little, Brown & Company. Huer, M. B., Parette, H. P., & Saenz, T. I. (2001). Conversations with Mexican Americans regarding children

417

Compilation of References

with disabilities and augmentative and alternative communication. Communication Disorders Quarterly, 22(4), 197–206. doi:10.1177/152574010102200405 Huitt, W. (2003). The information processing approach to cognition. Valdosta State University. Retrieved July 14, 2007, from http://chiron.valdosta.edu/whuitt/col/ cogsys/infoproc.html Hume, D., & Shepard, R. N. (2001). Introduction. In Haskell, R. E. (Ed.), Transfer of learning: Cognition, instruction, and reasoning (pp. xiii–xx). San Diego: Academic Press. Humphries, T., & Allen, B. M. (2008). Reorganizing teacher preparation in deaf education [Electronic version]. Sign Language Studies, 8(2), 160–180. doi:10.1353/ sls.2008.0000 Hunt, E., & Waller, D. (1999). Orientation and wayfinding: A review. Seattle, WA: University of Washington. Retrieved March 3, 2008, from http://www.cs.umu.se/ kurser/TDBD12/HT01/papers/hunt99orientation.pdf Hyams, N. (1986). Language acquisition and the theory of parameters. Cambridge, MA: The MIT Press. Iglesia, J., Buceta, M., & Campos, A. (2005). Prose learning in children and adults with Down syndrome: The use of visual and mental image strategies to improve recall. Journal of Intellectual & Developmental Disability, 30(4), 199–206. doi:10.1080/13668250500349391 Individuals with Disabilities Education Improvement Act of 2004. (2004). Pub. L. No. 108-446, 118 Stat. 2647 Individuals with Disabilities Education Improvement Act, 118 Stat 2647. (2004).

IT Accessibility & Workforce Division. (2006). 508 Law. Washington, DC: Author. Retrieved September 3, 2008, from http://www.section508.gov/index. cfm?FuseAction=Content&ID=3 Jacobs, J. E., & Paris, S. G. (1987). Children’s metacognition about reading: Issues in definition, measurement, and instruction. Educational Psychologist, 22(3), 255–278. doi:10.1207/s15326985ep2203&4_4 James, V., & Hammersley, M. (1993). Notebook computers as notetakers for handicapped students [Electronic version]. British Journal of Educational Technology, 24, 63–66. doi:10.1111/j.1467-8535.1993.tb00642.x Jamestown Reading Fluency. (1996). Glencoe Publishing. Retrieved from http://www.glencoe.com/gln/jamestown/ reading_rate/reading_fluency.php Janey Wang, C. Y. (2001, November). Handshakes in cyberspace: Bridging the cultural differences through effective intercultural communication and collaboration. Paper presented at National Convention of the Association for Educational Communications and Technology, Atlanta, GA. Retrieved August 1, 2009, from http:// www.eric.ed.gov/ERICDocs/data/ericdocs2sql/content_storage_01/0000019b/80/1a/87/e7.pdf Jenkins, L. (Ed.). (2004). Variation and universals in biolinguistics. Amsterdam: Elsevier B.V. Jensema, C. J., Danturthi, R. S., & Burch, R. (2000). Time spent viewing captions on television programs [Electronic version]. American Annals of the Deaf, 145(5), 464–468.

Iowa Department of Education. (1997). Iowa IDEA 97 Implementation Plan. Des Moines, IA: Author.

Jensema, C. J., Sharkawy, S. E., Danturthi, R. S., Burch, R., & Hsu, D. (2000). Eye movement patterns of captioned television viewers [Electronic version]. American Annals of the Deaf, 145(3), 275–285.

Iowa Department of Education. (2001). Iowa’s Quality Indicators for Assistive Technology (QIAT). Des Moines, IA: Author.

Jeung, H. J., & Chandler, P. (1997). The role of visual indicators in dual sensory mode instruction. Educational Psychology, 17(3), 329. doi:10.1080/0144341970170307

Isabelle, S., Bessey, S. F., Dragas, K. L., Blease, P., Shepherd, J. T., & Lane, S. J. (2002). Assistive technology for children with disabilities. Occupational Therapy in Health Care, 16, 29–51. doi:10.1300/J003v16n04_03

Jibaja-Weiss, M. L., & Volk, R. J. (2007). Utilizing computerized entertainment education in the development of decision aids for lower literate and naïve computer

418

Compilation of References

users. Journal of Health Communication, 12(7), 681–697. doi:10.1080/10810730701624356 Jiménez-Glez, J. E., & Rodrigo-López, M. R. (1994). Is it true that differences in reading performance between students with and without ID cannot be explained by IQ? Journal of Learning Disabilities, 27, 155–163. doi:10.1177/002221949402700304 Jimerson, S. R., Burns, M. K., & Van Der Heyden, A. M. (2007). Handbook of response to intervention: The science and practice of assessment and intervention. New York: Springer.

Judge, S. (2005). The impact of computer technology on academic achievement of young African American children. Journal of Research in Childhood Education, 20(2), 91–101. Judge, S. L. (2001). Computer applications for young children with disabilities: current status and future directions. Journal of Special Education Technology, 16(1), 29–40. Judge, S. L., & Parette, H. L. (1998). Family centered assistive technology decision making. Infant-Toddler Intervention, 8, 185–206.

Johnson, R. S., Mims-Cox, J. S., & Doyle-Nichols, A. (2006). Developing portfolios in education: A guide to reflection, inquiry, and assessment. Thousand Oaks, CA: Sage.

Judge, S., Floyd, K., & Jeffs, T. (2008). Using an assistive technology toolkit to promote inclusion. Early Childhood Education Journal, 36(2), 121–126. doi:10.1007/ s10643-008-0257-0

Jonassen, D. (1989). Hypertext/Hypermedia. Englewood Cliffs, NJ: Educational Technology Publications.

Juel, C. (1988). Learning to Read and Write: A Longitudinal Study of 54 Children from First through Fourth Grades. Journal of Educational Psychology, 80(4), 437–447. doi:10.1037/0022-0663.80.4.437

Jonassen, D. H., & Land, S. (Eds.). (2000). Theoretical foundations of learning environments. Mahwah, NJ: Lawrence Erlbaum. Jonassen, D. H., Lee, C. B., Yang, C.-C., & Laffey, J. (2005). The collaboration principle in multimedia learning. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning (pp. 247–270). New York: Cambridge University Press. Jonassen, D. H., Louise, B., & Grabowski, H. (1993). Handbook of individual differences, learning, and instruction. Mahwah, NJ: Lawrence Erlbaum. Jong, T. d. (2005). The guided discovery principle in multimedia learning. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning (pp. 215–228). New York: Cambridge University Press. Jorna, R. (2001). Knowledge types and organizational forms in knowledge managment. ISMICK. Judge, S. (2002). Family-centered assistive technology assessment and intervention practices for early intervention. Infants and Young Children, 15, 60–68.

Justice, L., Chow, S., Capellini, C., Flanigan, K., & Colton, S. (2003). Emergent literacy intervention for vulnerable preschoolers: relative effects of two approaches. American Journal of Speech-Language Pathology, 12, 320–332. doi:10.1044/1058-0360(2003/078) Kalisch, R., Wiech, K., Critchley, H. D., & Dolan, R. J. (2006). Levels of appraisal: A medial prefrontal role in high-level appraisal of emotional material. NeuroImage, 30(4), 1458–1466. doi:10.1016/j.neuroimage.2005.11.011 Kalyanpur, M., & Kirmani, M. H. (2005). Diversity and technology: Classroom implications of the digital divide. Journal of Special Education Technology, 20(4), 9–18. Kalyuga, S. (2005). Prior knowledge principle in multimedia learning. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning (pp. 325–338). New York: Cambridge University Press. Kalyuga, S., Chandler, P., & Sweller, J. (1998). Levels of expertise and instructional design. Human Factors, 40(1), 1–17. doi:10.1518/001872098779480587

419

Compilation of References

Kalyuga, S., Chandler, P., & Sweller, J. (1999). Managing split-attention and redundancy in multimedia instruction. Applied Cognitive Psychology, 13, 351–371. doi:10.1002/(SICI)1099-0720(199908)13:4<351::AIDACP589>3.0.CO;2-6 Kalyuga, S., Chandler, P., Tuovinen, J., & Sweller, J. (2001). When problem solving is superior to studying worked examples. Journal of Educational Psychology, 93(3), 579–588. doi:10.1037/0022-0663.93.3.579 Kangas, K. (2002). Seating for task performance. Rehab Management Journal. Retrieved January 14, 2009, from http://www.rehabpub.com/features/672002/8.asp Kaplan, H., Clopton, M., Kaplan, M., Messbauer, L., & McPherson, K. (2006). Snoezelen multi-sensory environments: Task engagement and generalization. Research in Developmental Disabilities, 27, 443–455. doi:10.1016/j. ridd.2005.05.007 Kay, A. (1991). Computer, networks and education. Scientific American. September. Kaye, H. S. (2000). Computer and Internet use among people with disabilities. San Francisco: National Institute on Disability and Rehabilitation Research. Keeler, M. L., & Swanson, H. L. (2001). Does strategy knowledge influence working memory in children with mathematical disabilities? Journal of Learning Disabilities, 34(5), 418–434. doi:10.1177/002221940103400504 Keilty, B., & Gavin, K. M. (2006). Physical and social adaptations of families to promote learning in everyday experiences. Topics in Early Childhood Special Education, 26, 219–233. doi:10.1177/02711214060260040301 Kelker, K. A. (1997). Family guide to assistive technology. Parents, Let’s Unite for Kids (PLUK). Retrieved December 1, 2008, from http://www.pluk.org/AT1.html Keller, H. (1957). The open door. Garden City, NY: Doubleday & Company. Kentucky Department of Education. (2006-2007). Kentucky Alternate Assessment Program. Retrieved February 8, 2009, from http://www.education.ky.gov/KDE/ Administrative+Resources/Testing+and+Reporting+/

420

District+Support/Kentucky+Alternate+Assessment+ Program/ Kiewra, K. A. (1985). Investigating notetaking and review: A depth of processing alternative [Electronic version]. Educational Psychologist, 20(1), 23–32. doi:10.1207/s15326985ep2001_4 Kim, K. (2000). Effects of cognitive style on web search and navigation. World Conference on Educational Multimedia, Hypermedia and Telecommunications (EMEDIA), 2000(1), 531-536. King, T. W. (1999). Assistive technology essential human factors. Boston: Allyn & Bacon. Kirk, S. A., Gallagher, J. J., & Anastasiow, N. J. Coleman, M. R. (2006). Educating exceptional children (11th Ed.). Boston: Houghton Mifflin. Kirschner, P. A. (2002). Cognitive load theory: Implications of cognitive load theory on the design of learning. Learning and Instruction, 12(1), 1–10. doi:10.1016/ S0959-4752(01)00014-7 Klein, D. H., & Parker, E. W. (2002). Spoken communication for students who are deaf or hard of hearing: A multidisciplinary approach. Hillsboro, OR: Butte Publications. Klein, L. R. (1992). Self-concept enhancement, computer education, and remediation: A study of the relationship between a multifaceted intervention program and academic achievement. Unpublished doctoral dissertation, University of Pennsylvania, Philadelphia, PA. Koester Performance Research. (2007). Compass assessment software: Spectronics. Ventura, CA: Inclusive Learning Technologies. Korsten, J., Foss, T., & Berry, T. L. (1993). Every move counts, clicks & chat. Overland Park, KS: CDS Printing. Koul, R., Schlosser, R., & Sancibrian, S. (2001). Effects of symbol, referent, and instructional variables on the acquisition of aided and unaided symbols by individuals with autism spectrum disorders. Focus on Autism and Other Developmental Disabilities, 16(3), 162–169. doi:10.1177/108835760101600304

Compilation of References

Kratcoski, A. (1998, January). Guidelines for using portfolios in assessment and evaluation. Language, Speech, and Hearing Services in Schools, 29, 3–10. Kritzenberger, H., Winkler, T., & Herczeg, M. (2002). Mixed reality environments as collaborative and constructive learning spaces for elementary school children. Paper presented at the ED-Media 2002 World Conference on Educational Multimedia, Hypermedia and Telecommunications, Denver, Colorado. Kruger, R., Kruger, J., Hugo, R., & Campbell, N. (2001). Relationship patterns between central auditory processing disorders and language disorders, learning disabilities, and sensory integration dysfunction. Communication Disorders Quarterly, 22(Winter), 87–98. doi:10.1177/152574010102200205 Kuhn, D., Black, J., Keselman, A., & Kaplan, D. (2000). The development of cognitive skills to support inquiry learning. Cognition and Instruction, 18(4), 495–523. doi:10.1207/S1532690XCI1804_3 Laffey, J. (1995). Dynamism in performance support systems. Performance Improvement Quarterly, 8(1), 31–46. Laffey, J., Schmidt, M., Stichter, J., Schmidt, C., & Goggins, S. (2009). iSocial: A 3D VLE for Youth with Autism. Proceedings of CSCL 2009, Rhodes, Greece. Laffey, J., Schmidt, M., Stichter, J., Schmidt, C., Oprean, D., Herzog, M., & Babiuch, R. (in press). Designing for social interaction and social competence in a 3D-VLE. In Russell, D. (Ed.), Cases on collaboration in virtual learning environments: Processes and interactions. Hershey, PA: Information Science Reference. Laka, I. (2009). What is there in Universal Grammar? On innate and specific aspects of language. In PiattelliPalmarini, M., Uriagereka, J., & Salaburu, P. (Eds.), Of minds & language: A dialogue with Noam Chomsky in the Basque Country (pp. 329–343). Oxford: Oxford University Press. Lance, A. A., McPhillips, M., Mulhern, G., & Wylie, J. (2006). Assistive software tools for secondary-level students with literacy difficulties. Journal of Special Education Technology, 21(3), 13–22.

Lange, A., McPhillips, M., Mulhern, G., & Wylie, J. (2006). Assistive software tools for secondary- level students with literacy difficulties. Journal of Special Education Technology, 21(3), 13–22. Langton, A. J., & Ramseur, H. (2001). Enhancing employment outcomes through job accommodation and assistive technology resources and services. Journal of Vocational Rehabilitation, 16(1), 27–37. Lankes, A. (1995September). Electronic portfolios: A new idea in assessment. ERIC Digest, 3-4. Lathrop, D. (1997, April). Remember 504. Mainstream, 32-34. Lavie, N. (1995). Perceptual load as a necessary condition for selective attention. Journal of Experimental Psychology. Human Perception and Performance, 21(3), 451–468. doi:10.1037/0096-1523.21.3.451 Lavie, N. (2000). Selective attention and cognitive control: Dissociating attentional functions through different types of load. In Monsell, S., & Driver, J. (Eds.), Control of cognitive processes: Attention & performance XVIII (pp. 175–194). Cambridge, MA: MIT Press. Lavie, N. (2001). The role of capacity limits in selective attention: Behavioural evidence and implications for neural activity. In Braun, J., & Koch, C. (Eds.), Visual attention and cortical circuits (pp. 49–68). Cambridge, MA: MIT Press. Lavie, N., & Cox, S. (1997). On the efficiency of visual selective attention: Efficient visual search leads to inefficient distractor rejection. Psychological Science, 8(5), 395–398. doi:10.1111/j.1467-9280.1997.tb00432.x Lavie, N., & Tsal. (1994). Perceptual load as a major determinant of the locus of selection in visual attention. Perception & Psychophysics, 56(2), 183–197. Lavie, N., Hirst, A., Fockert, J. W. D., & Viding, E. (2004). Load theory of selective attention and cognitive control. Journal of Experimental Psychology. General, 133(3), 339–354. doi:10.1037/0096-3445.133.3.339 Lawson, Q., Humphrey, L., Wood-Garnett, S., Fearn, K., Welch, C., Greene-Bryant, B., & Avoké, S. (2002).

421

Compilation of References

Addressing over-representation of African-American students in special education. Washington, DC: Council for Exceptional Children.

Lerner, J. (2003). Learning disabilities: Theories, diagnoses, and teaching strategies (9th ed.). Boston: Houghton Mifflin.

Leahy, W., Chandler, P., & Sweller, J. (2003). When auditory presentations should and should not be a component of multimedia instruction. Applied Cognitive Psychology, 17, 401–418. doi:10.1002/acp.877

Lesar, S. (1998). Use of assistive technology with young children with disabilities: Current status and training needs. Journal of Early Intervention, 21, 146–159. doi:10.1177/105381519802100207

Leberman, S., McDonald, L., & Doyle, S. (2006). The transfer of learning: Participants’ perspectives of adult education and training. Burlington, VT: Gower.

Levy, T. (2001). Legal obligations and workplace implications for institutions of higher education accommodating learning disabled students. Journal of Law & Education, 30(1), 85–121.

LeDoux, J. E. (1995). Emotion: clues from the brain. Annual Review of Psychology, 46, 209–235. doi:10.1146/ annurev.ps.46.020195.001233 Lee, V. E., & Burkham, D. T. (2002). Inequality at the starting gate: Social background differences in achievement as children begin school. Washington, DC: Economic Policy Institute. Lee, Y., & Vega, L. (2005). Perceived knowledge, attitudes, and challenges of AT use in special education. Journal of Special Education Technology, 20(2), 60–63. Lennon, J., & McCartney, P. (1967). With a little help from my friends [Recorded by The Beatles]. On Sgt. Pepper’s Lonely Hearts Club Band [CD]. London, UK: EMI Records Ltd. Leonard, L. (1995). Functional categories in the grammars of children with specific language impairments. Journal of Speech and Hearing Research, 38, 1270–1283. Leonard, L. (1998). Children with specific language impairment. Cambridge, MA: MIT Press. Leonard, L., & Loeb, D. (1988). Government-binding theory and some of its applications: a tutorial. Journal of Speech and Hearing Research, 31, 515–524. Leonard, L., Camarata, S., Pawtowska, M., Brown, B., & Camarata, M. (2006). Tense and agreement morphemes in the speech of children with specific language impairment during intervention: Phase 2. Journal of Speech and Hearing Research, 49, 749–770. doi:10.1044/10924388(2006/054)

422

Lewis, M. S., & Jackson, D. W. (2001). Televison literacy: Comprehension of program content using closed captions for the deaf. Journal of Deaf Studies and Deaf Education, 6(1), 43–53. doi:10.1093/deafed/6.1.43 Lewis, R. B. (1998). Assistive technology and learning disabilities: Today’s realities and tomorrow’s promises. Journal of Learning Disabilities, 31(1), 16–26, 54. doi:10.1177/002221949803100103 Lightfoot, D. (1991). How to set parameters: Arguments from language change. Cambridge, MA: MIT Press. Lin, F. (Ed.). (2004). Designing distributed learning environments with intelligent software agents. Hershey, PA: Information Science Publishing. Littlefield, H. (2005). Lexical and Functional Prepositions in Acquisition: Evidence for a Hybrid Category. Boston University Conference on Language Development 29, Online Proceedings Supplement. Littlefield, H. (2006). Syntax and acquisition in the prepositional domain: Evidence from English for fine-grained syntactic categories. Dissertation, Boston University. Liu, C.-C., Chou, C.-C., & Liu, B.-J. (2006). Improving mathematics teaching and learning experiences for hard of hearing students with wireless technology-enhanced classrooms [Electronic version]. American Annals of the Deaf, 151(3), 345–355. doi:10.1353/aad.2006.0035 Liu, M. (1994). Hypermedia-assisted-instruction and second language learning: A semantic-network-based approach. Computers in the Schools, 10(3/4), 293–312.

Compilation of References

Lombardi, T., Bauer, D., Peters, C., & O’Keefe, S. (1992). Satellite distance learning: Collaboration meets demands of special education teachers. T.H.E. Journal, 19(11), 59–62. Long, T., Huang, L., Woodbridge, M., Woolverton, M., & Minkel, J. (2003). Integrating assistive technology into an outcome driven model of service delivery. Infants and Young Children, 19, 272–283. Longman, J. (2007, May 15). An amputee sprinter: Is he disabled or too-abled? The New York Times. Retrieved from http://www.nytimes.com/2007/05/15/sports/ othersports/15runner.html?pagewanted=1 Lotan, M., & Shaprio, M. (2005). Management of young children with Rett Disorder in the controlled multisensory (Snoezelen) environment. Brain & Development, 27, 88–94. doi:10.1016/j.braindev.2005.03.021 Love, N. (2002). Using data/getting results: A practical guide for school improvement in mathematics and science. Norwood, MA: Christorpher-Gordon Publishers. Low, R., & Sweller, J. (2005). The modality principle in multimedia learning. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning (pp. 147–158). New York: Cambridge University Press. Lowe, D., & Hall, W. (1999). Hypermedia and the Web: An engineering approach. London: Wiley. Lowe, M. A. (2005). The Development of electronic portfolios for individuals who use augmentative and alternative communication. Unpublished doctoral dissertation, Nova Southeastern University, Fort Lauderdale, Florida. Luft, P. (2008). Examining educators of the Deaf as “highly qualified” teachers: Roles and responsibilities under IDEA and NCLB [Electronic version]. American Annals of the Deaf, 152(5), 429–440. doi:10.1353/ aad.2008.0014 Lunzer, E. (1986). Cognitive development: Learning and the mechanisms of change. In Phye, G. D., & Andre, T. (Eds.), Cogntivie classroom learning: Understanding, thinking, and problem solving. Orlando, FL: Academic Press.

Lynch, P. J. (1994). Visual design for the user interface: Design fundamentals. The Journal of Biocommunication, 21(1), 22–30. MacArthur, C. (1998). Word processing with speech synthesis and word prediction: Effects on the dialogue journal writing of students with learning disabilities. Learning Disability Quarterly, 21(2), 151–166. doi:10.2307/1511342 MacArthur, C. (1999). Word prediction for students with severe spelling problems. Learning Disability Quarterly, 22(3), 158–172. doi:10.2307/1511283 MacArthur, C., Ferretti, P., Okolo, C., & Cavalier, A. R. (2001). Technology applications for students with literacy problems: A critical review. The Elementary School Journal, 3(101), 273–301. doi:10.1086/499669 MacDonald, M. C., & Christiansen, M. H. (2002). Reassessing working memory: Comment on Just and Carpenter (1992) and Waters and Caplan (1996). Psychological Review, 109(1), 35–54. doi:10.1037/0033-295X.109.1.35 Malouf, D. B., & Hauser, J. (2005). A federal program to support innovation and implementation of technology in special education. In Edyburn, D. L., Higgins, K., & Boone, R. (Eds.), Handbook of special education technology research and practice (pp. 47–59). Whitefish Bay, WI: Knowledge by Design. Mansell, W., Harvey, A., Watkins, E. R., & Shafran, R. (2008). Cognitive behavioral processes across psychological disorders: A review of the utility and validity of the transdiagnostic approach. International Journal of Cognitive Therapy, 1(3), 181–191. doi:10.1521/ ijct.2008.1.3.181 Marchionini, G. (1988). Hypermedia and learning. Freedom and chaos. Educational Technology, 28(11), 8–12. Marcus, N., Cooper, M., & Sweller, J. (1996). Understanding instructions. Journal of Educational Psychology, 88(1), 49–63. doi:10.1037/0022-0663.88.1.49 Marschark, M., Lang, H., & Albertini, J. (2002). Educating deaf students: From research to practice. New York: Oxford University Press.

423

Compilation of References

Marshall, H. H. (1996). Recent and emerging theoretical frameworks for research on classroom learning: Contributions and limitations (Vol. 31). Mahwah, NJ: Educational Psychologist. Marzano, R. (2000). A new era of school reform: Going where the research takes us. Aurora, CO: Mid-continent Research for Education and Learning. Mason, C. Y., & Dodd, R. (2005). Bridge the digital divide for educational equity. Education Digest, 70(9), 25–27. Mathews, A., & Machintosh, B. (1998). Cognitive model of selective processing in anxiety. Cognitive Therapy and Research, 22(6), 539–560. doi:10.1023/A:1018738019346 Maurice, C., Green, G., & Luce, S. (Eds.). (1996). Behavioral intervention for young children with Autism. Austin, TX: Pro-ed. Mautone, P. D., & Mayer, R. E. (2001). Signaling as a cognitive guide in multimedia learning. Journal of Educational Psychology, 93(2), 377–389. doi:10.1037/00220663.93.2.377 Max, M. L., & Burke, J. C. (1997). Virtual reality for autism communication and education, with lessons for medical training simulators. In Morgan, K. S., Hoffman, H. M., Stredney, D., & Weghorst, S. J. (Eds.), Studies in health technologies and informatics, 39. Burke, VA: IOS Press. Mayer, R. E. (1989). Systematic thinking fostered by illustrations in scientific text. Journal of Educational Psychology, 81(2), 240–246. doi:10.1037/0022-0663.81.2.240 Mayer, R. E. (2001). Multimedia learning. New York: Cambridge University Press. Mayer, R. E. (2002). Rote versus meaningful learning. Theory into Practice, 41(4), 226–232. doi:10.1207/ s15430421tip4104_4 Mayer, R. E. (2003). Elements of science in E-learning. Journal of Educational Computing Research, 29(3), 297–313. doi:10.2190/YJLG-09F9-XKAX-753D Mayer, R. E. (2005). Cognitive theory of multimedia learning. In Mayer, R. E. (Ed.), The Cambridge hand-

424

book of multimedia learning (pp. 31–48). New York: Cambridge University Press. Mayer, R. E. (2005). Introduction to multimedia learning. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning (pp. 1–16). New York: Cambridge University Press. Mayer, R. E. (2005). Principles for managing essential processing in multimedia learning: Segmenting, pretraining, and modality principles. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning (pp. 169–182). New York: Cambridge University Press. Mayer, R. E. (2005). Principles for reducing extraneous processing in multimedia learning: Coherence, signaling, redundancy, spatial contiguity, and temporal contiguity principles. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning (pp. 183–200). New York: Cambridge University Press. Mayer, R. E. (2005). Principles of multimedia learning based on social cues: Personalization, voice, and image principles. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning (pp. 201–212). New York: Cambridge University Press. Mayer, R. E., & Anderson, R. B. (1991). Animations need narrations: An experimental test of a dual-coding hypothesis. Journal of Educational Psychology, 83(4), 484–490. doi:10.1037/0022-0663.83.4.484 Mayer, R. E., & Anderson, R. B. (1992). The instructive animation: Helping students build connections between words and pictures in multimedia learning. Journal of Educational Psychology, 84(4), 444–452. doi:10.1037/0022-0663.84.4.444 Mayer, R. E., & Chandler, P. (2001). When learning is just a click away: Does simple user interaction foster deeper understanding of multimedia messages? Journal of Educational Psychology, 93(2), 390–397. doi:10.1037/00220663.93.2.390 Mayer, R. E., & Gallini, J. K. (1990). When is an illustration worth ten thousand words? Journal of Educational Psychology, 82(4), 715–726. doi:10.1037/00220663.82.4.715

Compilation of References

Mayer, R. E., & Moreno, R. (1998). A split-attention effect in multimedia learning: Evidence for dual processing systems in working memory. Journal of Educational Psychology, 90(2), 312–320. doi:10.1037/00220663.90.2.312

Mayer, R. E., Moreno, R., Boire, M., & Vagge, S. (1999). Maximizing constructivist learning from multimedia communications by minimizing cognitive load. Journal of Educational Psychology, 91(4), 638–643. doi:10.1037/0022-0663.91.4.638

Mayer, R. E., & Moreno, R. (2003). Nine ways to reduce cognitive load in multimedia learning. Educational Psychologist, 38, 43–52. doi:10.1207/S15326985EP3801_6

Mayer, R. E., Steinhoff, K., Bower, G., & Mars, R. (1995). A generative theory of textbook design: Using annotated illustrations to foster meaningful learning of science text. Educational Technology Research and Development, 43(1), 31–43. doi:10.1007/BF02300480

Mayer, R. E., & Moreno, R. (2003). Nine ways to reduce cognitive load in multimedia learning. Educational Psychologist, 38(1), 43–52. doi:10.1207/ S15326985EP3801_6 Mayer, R. E., & Sims, V. K. (1994). For whom is a picture worth a thousand words? Extensions of a dualcoding theory of multimedia learning. Journal of Educational Psychology, 86(3), 389–401. doi:10.1037/00220663.86.3.389 Mayer, R. E., Bove, W., Bryman, A., Mars, R., & Tapangco, L. (1996). When less is more: Meaningful learning from visual and verbal summaries of science textbook lessons. Journal of Educational Psychology, 88(1), 64–73. doi:10.1037/0022-0663.88.1.64 Mayer, R. E., Dow, G. T., & Mayer, S. (2003). Multimedia learning in an interactive self-explaining environment: What works in the design of agent-based microworlds? Journal of Educational Psychology, 95(4), 806–812. doi:10.1037/0022-0663.95.4.806 Mayer, R. E., Heiser, J., & Lonn, S. (2001). Cognitive constraints on multimedia learning: When presenting more material results in less understanding. Journal of Educational Psychology, 93(1), 187–198. doi:10.1037/00220663.93.1.187 Mayer, R. E., Mathias, A., & Wetzell, K. (2002). Fostering understanding of multimedia messages through pre-training: Evidence for a two-stage theory of mental model construction. Journal of Experimental Psychology. Applied, 8(3), 147–154. doi:10.1037/1076-898X.8.3.147 Mayer, R. E., Mautone, P., & Prothero, W. (2002). Pictorial aids for learning by doing in a multimedia geology simulation game. Journal of Educational Psychology, 94(1), 171–185. doi:10.1037/0022-0663.94.1.171

Mayer, R., Heiser, J., & Lonn, S. (2001). Cognitive constraints on multimedia learning: When presenting more material results in less understanding. Journal of Educational Psychology, 93, 187–198. doi:10.1037/00220663.93.1.187 Maylor, E. A., & Lavie, N. (1998). The influence of perceptual load on age differences in selective attention. Psychology and Aging, 13(4), 563–573. doi:10.1037/08827974.13.4.563 McCord, S., & Soto, G. (2004). Perceptions of AAC: An ethnographic investigation of Mexican-American families. Augmentative and Alternative Communication, 20(4), 209–227. doi:10.1080/07434610400005648 McCormick, L. (1987). Comparison of the effects of a microcomputer activity and toy play on social and communication behaviors of young children. Journal of the Division for Early Childhood, 11, 195–205. McCormick, L., Won, M., & Yogi, L. (2003). Individualization in the inclusive preschool: A planning process. Childhood Education, 79, 212–217. McDonald, K. K., & Hannafin, R. D. (2003). Using webbased computer games to meet the demands of today’s high-stakes testing: A mixed method inquiry [Electronic version]. Journal of Research on Technology in Education, 35(4), 459–472. McDonald, S., & Stevenson, R. J. (1996). Disorientation in hypertext: The effects of three text structures on navigation performance. Applied Ergonomics, 27(1), 61–68. doi:10.1016/0003-6870(95)00073-9

425

Compilation of References

McDonald, S., & Stevenson, R. J. (1998). The effects of text structure and prior knowledge on navigation in hypertext. Human Factors, 40(1), 18–27. doi:10.1518/001872098779480541

Messbauer, L. (2008). What is a multi-sensory or Snoezelen room? American Association of Multi Sensory Environments. Retrieved from http://www.aamse.us/ faq.php

McGregor, G., & Pachuski, P. (1996). Assistive technology in schools: Are teachers ready, able, and supported? Journal of Special Education Technology, 13, 4–15.

Michaels, C. A., & Mcdermott, J. (2003). Assistive technology integration in special education teacher preparation: Program coordinators’ perceptions of current attainment and importance. Journal of Special Education Technology, 18(3), 29–41.

McKeachie, W. (2001). Transfer of learning: What it is and why it’s important. In Haskell, R. E. (Ed.), Transfer of learning: Cognition, instruction, and reasoning (pp. 23–39). San Diego: Academic Press. McLean, J. F., & Hitch, G. J. (1999). Working memory impairments in children with specific arithmetic learning difficulties. Journal of Experimental Child Psychology, 74(3), 240–260. doi:10.1006/jecp.1999.2516 McLellan, D. L. (1991). Functional recovery and the principles of disability medicine. In Swash, M., & Oxbury, J. (Eds.), Clinical Neurology (Vol. 1, pp. 768–790). London: Churchill Livingstone. McLoughlin, J. A., & Lewis, R. B. (2005). Assessing students with special needs (6th ed.). Upper Saddle River, NJ: Merrill. McLoughlin, J., & Lewis, R. (1994). Assessing special students (4th ed.). Columbus, OH: Merrill. Meinke, D. K., & Dice, N. (2007). Comparison of audiometric screening criteria for the identification of noise-induced hearing loss in adolescents [Electronic version]. American Journal of Audiology, 16(2), S190– S202. doi:10.1044/1059-0889(2007/023) Mellander, G. A. (2007). High-tech: Help or hindrance to Hispanics in college? Education Digest, 72(9), 19–23. Merchant, G., de Villiers, J., & Smith, S. (2008). Optimized intervention software benefits grammar skills in young oral deaf children. Paper presented at the Council for Exceptional Children Convention and Expo, Boston, MA, April 2008. Messbauer, L. (2005). The art and science of multisensory environments. Presentation at workshop in Queens, NY.

426

Michigan Department of Education. (2008). Public agency placement of students with disabilities in private schools. Retrieved on March 1, 2009, from http://www. michigan.gov Miller, G., A. (1956). The magical number seven, plus or minus two: Some limits on our capacity for processing information. Psychological Review, 63, 81–97. doi:10.1037/h0043158 Miller, J. (1993). The effectiveness of computer-assisted instruction in language intervention. Ph.D. dissertation, Department of Education, University of Kentucky, Lexington, KY. Milone, M. N. Jr. (1995). Electronic portfolios: Who’s doing them and how? Technology & Learning, 16(2), 28–36. Mirenda, P. (2001). Autism, augmentative communication, and assistive technology: What do we really know? Focus on Autism and Other Developmental Disabilities, 16(3), 141–151. doi:10.1177/108835760101600302 Mirenda, P. (2009). Introduction to AAC for individuals with Autism Spectrum Disorders. In Mirenda, P., & Iacono, T. (Eds.), AAC for individuals with Autism Spectrum Disorders (pp. 247–278). Baltimore, MD: Paul H. Brookes Publishing Co. Mistrett, S. (2004). Assistive technology helps young children with disabilities participate in daily activities. Technology in Action, 1(4), 1–8. Mistrett, S. G., Hale, M. M., Gruner, A., Sunshine, C., & McInerney, M. (2001). Synthesis on the use of assistive technology with infants and toddlers with disabilities

Compilation of References

(birth–two). Washington, DC: American Institutes of Research.

and media. Journal of Educational Psychology, 94(3), 598–610. doi:10.1037/0022-0663.94.3.598

Mitchell, P., Parsons, S., & Leonard, A. (2007). Using virtual environments for teaching social understanding to 6 adolescents with autistic spectrum disorders. Journal of Autism and Developmental Disorders, 37(3), 589–600. doi:10.1007/s10803-006-0189-8

Moreno, R., Mayer, R. E., Spires, H. A., & Lester, J. C. (2001). The case for social agency in computer-based teaching: Do students learn more deeply when they interact with animated pedagogical agents? Cognition and Instruction, 19(2), 177–213. doi:10.1207/S1532690XCI1902_02

Moeller, M. P. (2000). Early intervention and language development in children who are deaf and hard of hearing [Electronic version]. Pediatrics, 106, E43. doi:10.1542/ peds.106.3.e43 Molfese, V., DiLalla, L., & Lovelace, L. (1995). Prenatal, home environment, and infant measures as successful predictors of preschool cognitive and verbal abilities. International Journal of Behavioral Development, 18, 1–19. Moore, M., & Calvert, S. (2000). Vocabulary acquisition for children with autism: Teacher or computer instruction. Journal of Autism and Developmental Disorders, 30, 359–362. doi:10.1023/A:1005535602064 Moreno, R. (2005). Multimedia learning with animated pedagogical agents. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning (pp. 507–523). New York: Cambridge University Press. Moreno, R., & Mayer, R. E. (1999). Cognitive principles of multimedia learning: The role of modality and contiguity. Journal of Educational Psychology, 91(2), 358–368. doi:10.1037/0022-0663.91.2.358 Moreno, R., & Mayer, R. E. (2000). A coherence effect in multimedia learning: The case for minimizing irrelevant sounds in the design of multimedia instructional messages. Journal of Educational Psychology, 92(1), 117–125. doi:10.1037/0022-0663.92.1.117 Moreno, R., & Mayer, R. E. (2000). Engaging students in active learning: The case for personalized multimedia messages. Journal of Educational Psychology, 92(4), 724–733. doi:10.1037/0022-0663.92.4.724 Moreno, R., & Mayer, R. E. (2002). Learning science in virtual reality multimedia environments: Role of methods

Morey, C. C., & Cowan, N. (2004). When visual and verbal memories compete: Evidence of cross-domain limits in working memory. Psychonomic Bulletin & Review, 11(2), 296–301. Moro, A. (2008). The boundaries of babel. Cambridge, MA: MIT Press. Morrison, R. (1999). Picture this! Using portfolios to facilitate the inclusion of children in preschool settings. Early Childhood Education Journal, 27(1), 45–48. doi:10.1023/A:1026023608023 Mossberger, K., & Tolbert, C. J. (2003). Race, place, and information technology. Urban Affairs Review, 41(5), 583–620. doi:10.1177/1078087405283511 Moulton, G., Huyler, L., Hertz, J., & Levenson, M. (2002). Accessible technology in today’s business. Microsoft Press. Mousavi, S. Y., Low, R., & Sweller, J. (1995). Reducing cognitive load by mixing auditory and visual presentation modes. Journal of Educational Psychology, 87(2), 319–334. doi:10.1037/0022-0663.87.2.319 Mull, C. A., & Sitlington, P. L. (2003). The role of technology in the transition to postsecondary education of students with learning disabilities. The Journal of Special Education, 7(1), 26–32. doi:10.1177/0022466 9030370010301 Munro-Ludders, B., Simpatico, T., & Zvetina, D. (2004). Making public mental-health services accessible to deaf consumers: Illinois deaf services 2000 [Electronic version]. American Annals of the Deaf, 148(5), 396–402. doi:10.1353/aad.2004.0008

427

Compilation of References

Murray, T. (2001). Characteristics and affordances of adaptive hyperbooks. Proceedings of WebNet 2001, Orlando, FL. Musselman, C. (2000). How do children who can’t hear learn to read an alphabetic script? A review of the literature on reading and deafness [Electronic version]. Journal of Deaf Studies and Deaf Education, 5(1), 9–31. doi:10.1093/deafed/5.1.9 National Association of the Deaf. (2008). Assistive technology. Retrieved December 14, 2008, from http://www. nad.org/site/pp.asp?c=folINKQMBF&b=180305 National Center for Education Statistics. (2008). Participation in education: Indicator 3, past and projected public school enrollments. Retrieved on January 2, 2009, from http://nces.ed.gov/programs/coe/2008/section1/ indicator 03.asp National Center for Education Statistics. (2008). Participation in education: Indicator 8, children and youth with disabilities in public schools. Retrieved on January 2, 2009, from http://nces.ed.gov/programs/coe/2008/ section1/indicator 08.asp National Early Childhood Technical Assistance Center (NECTAC). (2009). Retrieved August 14, 2009, from http://www.nectac.org/idea/idea.asp National Education Association. (1997). Technology for diverse learners. West Haven, CT: National Education Association Library. National Institute for Literacy (NIFL). (2009). Developing early literacy. Report of the early literacy panel. Retrieved August 14, 2009, from http://www.nifl.gov/ publications/pdf/NELPReport09.pdf National Institute of Child Development. (2005). Mental retardation and developmental disabilities (MRDD) branch. NICHD Report to the NACHHD Council: National Institute of Child Health and Human Development. NICHD. National Joint Committee on Learning Disabilities. (1991). Learning disabilities: Issues on definition [Electronic Version]. Asha, 33, 18–20. Retrieved April 29,

428

2009, from www.ldonline.org/?module=uploads&func =download&fileId=514 National Organization on Fetal Alcohol Syndrome. (n.d.). Retrieved August 14, 2009, from http://www. nofas.org. Neel, R. (2006). Consider the opportunities: A response to no child left behind. Education & Treatment of Children, 29(4), 533–548. Neilsen, J. (1990). The art of navigating through hypertext. Communications of the ACM, 33(3), 298–310. Neilsen, J. (1995). Multimedia and hypertext: The Internet and beyond. Cambridge, MA: AP Professional. Netherton, D., & Deal, W. (2006). Assistive technology in the classroom. Technology Teacher, 66(1), 10–15. Newby, T. J., Stepich, D. A., Lehman, J. D., & Russell, J. D. (2000). Instructional technology for teaching and learning: Designing instruction, integrating computers, and using media (2nd ed.). Englewood Cliffs, NJ: Prentice-Hall. News, B. B. C. (2004). ‘Brainwave’ cap controls computer. Retrieved December 7, 2004, from http://news. bbc.co.uk/1/hi/technology/4074869.stm Niaz, M., & Logie, R. H. (1993). Working memory, mental capacity and science education: Towards an understanding of the ‘working memory overload hypothesis’. Oxford Review of Education, 19(4), 511–525. doi:10.1080/0305498930190407 Niaz, M., & Logie, R. H. (1993). Working memory, mental capacity and science education: Towards an understanding of the ‘working memory overload hypothesis’. Oxford Review of Education, 19(4), 511–525. doi:10.1080/0305498930190407 Niguidula, D. (1997, November). Picturing performance with digital portfolios. Educational Leadership, 26–29. No Child Left Behind. (NCLB, P.L. 107-110). (2002). The facts: 21st century technology. Retrieved March 3, 2009, from http://www.ed.gov/nclb/methods/ whatworks/21centtech.html

Compilation of References

Norman, D. (1994). Things that make us smart. Reading, MA: Addison-Wesley Publishing Co.

applications in coastal habitats (pp. 3–16). San Diego, CA: Academic Press.

Norman, D. A. (1983). Some observations on Mental Models. In Gentner, D., & Stevens, A. L. (Eds.), Mental models (pp. 7–14). Mahwah, NJ: Lawrence Erlbaum Associates Inc.

Overton, T. (2009). Assessing learners with special needs. Upper Saddle River, NJ: Merrill.

Northern Grid for Learning. (2001). SENSwitcher. Gateshead, UK: Northern Grid for Learning. Retrieved January 21, 2009, from http://www.northerngrid.org/ ngflwebsite/sen/intro.htm Novick, L. R. (1988). Analogical transfer, problem similarity, and expertise. Journal of Experimental Psychology. Learning, Memory, and Cognition, 14(3), 510–520. doi:10.1037/0278-7393.14.3.510 Nunes, J. M., & Fowell, S. P. (1996). Hypermedia as an experiential learning tool: A theoretical model. Information Research, 2(1). O’shaughnessy, T. E., & Swanson, H. L. (2007). A comparison of two reading interventions for children with reading disabilities. Journal of Learning Disabilities, 33(3), 257–277. doi:10.1177/002221940003300304 Odom, S. L., Brantlinger, E., Gersten, R., Horner, R. H., Thompson, B., & Harris, K. R. (2005). Research in special education: Scientific methods and evidence-based practices. Exceptional Children, 71(2), 137–148. Olson, R. K., & Wise, B. (1992). Reading on the computer with orthographic and speech feedback. Reading and Writing: An Interdisciplinary Journal, 4, 107–144. doi:10.1007/BF01027488 Olson, R. K., Wise, B., Ring, J., & Johnson, M. (1997). Computer-based remedial training in phoneme awareness and phonological decoding: Effects on the post-training development of word recognition. Scientific Studies of Reading, 1, 235–253. doi:10.1207/s1532799xssr0103_4 Orton, S. T.(1925). ‘Word-blindness’ in school children. Archives of Neurology and Psychiatry, 14, 285–516. Osenberg, C. W., & Schmitt, R. J. (1996). Detecting ecological impacts caused by human activities. In Osenberg, C. W., & Schmitt, R. J. (Eds.), Concepts and

P. L. 107-110. (2002). The No Child Left Behind Act of 2001. Retrieved June 14, 2004, from http://www.ed.gov/ policy/elsec/leg/esea02/index.html P. L. 108-446. (2004). The Individuals with Disabilities Education Improvement Act. Retrieved July 5, 2005, from http://www.ed.gov/policy/speced/guid/idea/idea2004. html Paas, F. G. W. C. (1992). Training strategies for attaining transfer of problem-solving skill in statistics: A cognitiveload approach. Journal of Educational Psychology, 84(4), 429–434. doi:10.1037/0022-0663.84.4.429 Paas, F., Renkl, A., & Sweller, J. (2003). Cognitive load theory and instructional design: Recent developments. Educational Psychologist, 38(1), 1–4. doi:10.1207/ S15326985EP3801_1 Paas, F., Van Gerven, P. W. M., & Tabbers, H. K. (2005). The cognitive aging principle in multimedia learning. In R. E. Mayer (Ed.), The Cambridge handbook of multimedia learning (pp. 339-354). New York: Cambridge University Press. Paas, R., Renkel, A., & Sweller, J. (2003). Cognitive load theory and instructional design: Recent developments. Educational Psychologist, 38(1), 1–3. doi:10.1207/ S15326985EP3801_1 Paivio, A. (1971). Imagery and verbal processes. New York: Holt, Rinehart and Winston. Paivio, A. (1990). Mental representations: A dual coding approach. New York: Oxford University Press. Palmer, S. B., & Wehmeyer, M., L., Gibson, K., & Agran, M. (2004). Promoting access to the general curriculum by teaching self-determination skills. Exceptional Children, 70, 427–439. Parette, H. P., & Stoner, J. B. (2008). Benefits of assistive technology user groups for early childhood education

429

Compilation of References

professionals. Early Childhood Education Journal, 35, 313–319. doi:10.1007/s10643-007-0211-6

Pecorino, P. A. (2000). Chapter 5: Epistemology. Types of knowledge. In.

Parette, H. P., Brotherson, M. J., & Huer, M. B. (2000). Giving families a voice in augmentative and alternative communication decision-making. Education and Training in Mental Retardation and Developmental Disabilities, 35(2), 177–190.

Pena, E., & Quinn, R. (2003). Developing effective collaboration teams in speech-language pathology: A case study. Communication Disorders Quarterly, 24(2), 53–63. doi:10.1177/15257401030240020201

Parette, H., Peterson-Karlan, G., Wojcik, B., & Bardi, N. (2007, September). Monitor that progress! [from Academic Search Elite database.]. Teaching Exceptional Children, 40(1), 22–29. Retrieved January 3, 2009. Parette, P., & Peterson-Karlan, G. R. (2007). Facilitating student achievement with assistive technology. Education and Training in Developmental Disabilities, 42(4), 387–397. Park, C., Jang, G., & Young, C. (2006). Development of a virtual reality training system for live-line workers. International Journal of Human-Computer Interaction, 20(3), 285–303. doi:10.1207/s15327590ijhc2003_7 Parsons, S., Leonard, A., & Mitchell, P. (2006). Virtual environments for social skills training: Comments form two adolescents with autistic spectrum disorder. Computers & Education, 47, 186–206. doi:10.1016/j. compedu.2004.10.003 Pashler, H. E. (1998). The psychology of attention. Cambridge, MA: The MIT Press. Passolunghi, M. C., & Siegel, L. S. (2004). Working memory and access to numerical information in children with disability in mathematics. Journal of Experimental Child Psychology, 88(4), 348–367. doi:10.1016/j. jecp.2004.04.002 Paul, P. V., & Quigley, S. P. (1990). Education and deafness. White Plains, NY: Longman. Paulson, L., Paulson, P. R., & Meyer, C. (1990). What makes a portfolio a portfolio?Portland, OR: Multnomah. Payton, F. C. (2003). Rethinking the digital divide. Communications of the ACM, 46(6), 89–91. doi:10.1145/777313.777318

430

Penney, C. G. (1989). Modality effects and the structure of short-term verbal memory. Memory & Cognition, 17, 398–422. Pennington, B. F., Peterson, R. L., & McGrath, L. M. (2009). Dyslexia. In Pennington, B. F. (Ed.), Diagnosing learning disorders: A neuropsychological framework (pp. 45–82). New York: The Guilford Press. Perkins, B. (1995). Integrating hypermedia and assistive technology: An overview of possibilities. Information Technology and Disabilities, 2(2). Retrieved December 20, 2008, from http://www.isc.rit.edu/~easi/itd/itdv02n2/ perkins.html Perkins, R. (1991). Using HyperStudio to create lessons that use alternative input devices. In D. Carey, R. Carey, D. A. Willis, & J. Willis (Eds.), Technology and teacher education. Annual 1991: Proceedings of the Annual Conference of the Society for Teacher Education (pp. 80-83). ERIC Document Reproduction Service No. ED 343 562. Perkins, R. (1993). Integrating alternative input devices and hypermedia for use by exceptional individuals. Computers in the Schools, 10(1-4). Peterson, L., & Peterson, M. J. (1959). Short-term retention of individual verbal items. Journal of Experimental Psychology, 58(3), 193–198. doi:10.1037/h0049234 Peterson-Karlan, G. R., & Parette, P. (2005). Millennial students with mild disabilities and emerging assistive technology trends. Journal of Special Education Technology, 20(4), 27–38. Pew Internet & American Life project. (2009). Retrieved September 30, 2009, from http://www.pewinternet.org Phillips, B., & Zhao, H. (1993). Predictors of assistive technology abandonment. Assistive Technology, 5(1), 36–45.

Compilation of References

Phye, G. D. (1986). Practice and skilled classroom performance. In Phye, G. D., & Andre, T. (Eds.), Cognitive classroom learning: Understanding, thinking, and problem solving (pp. 141–168). Orlando, FL: Academic Press. Picciano, A. G., & Seaman, J. (2008). K-12 online learning: A 2008 follow-up of the survey of U.S. school district administrators. The Sloan Consortium. Pierangelo, R., & Giuliani, G. (2008). The educator’s step-by-step guide to classroom management techniques for students with autism. Thousand Oaks, CA: Corwin Press. Pierce, R. L., & McWilliam, P. J. (1993). Emergent literacy and children with severe speech and physical impairments (SSPI): Issues and possible intervention strategies. Topics in Language Disorders, 13, 1–11. Pilling, D., & Barrett, P. (2008). Text communication preferences of deaf people in the United Kingdom. Journal of Deaf Studies and Deaf Education, 13(1), 92–103. doi:10.1093/deafed/enm034 Pinker, S. (1994). The language instinct. New York: William Morrow. Pollack, A. (2006). Paralyzed man uses thoughts to move a cursor. Retrieved July 13, 2006, from http://www. nytimes.com/2006/07/13/science/13brain.html Pollard, C., & Pollard, R. (2004/2005). Research priorities in educational technology: A Delphi study [Electronic version]. Journal of Research on Technology in Education, 37(2), 145–160. Pollock, E., Chandler, P., & Sweller, J. (2002). Assimilating complex information. Learning and Instruction, 12, 61–86. doi:10.1016/S0959-4752(01)00016-0 Polloway, E. A., Patton, J. R., & Serna, L. (2005). Strategies for teaching learners with special needs. Upper Saddle River, NJ: Pearson. Power, M. R., Power, D., & Horstmanshof, L. (2007). Deaf people communicating via SMS, TTY, relay service, fax, and computers in Australia. Journal of Deaf Studies and Deaf Education, 12(1), 80–92. doi:10.1093/ deafed/enl016

Power, M., & Dalegleish, T. (1997). Cognition and emotion: From order to disorder. London: The Psychology Press. Preminger, J., & Leavit, H. (1997). Computer-assisted remote transcription: A tool to aid people who are deaf or hard of hearing in the workplace [Electronic version]. The Volta Review, 99, 219–230. Prensky, M. (2001). Digital game-based learning. New York: McGraw Hill. Price, E. A., & Driscoll, M. P. (1997). An inquiry into the spontaneous transfer of problem-solving skill. Contemporary Educational Psychology, 22(4), 472–494. doi:10.1006/ceps.1997.0948 Prigatano, G. P. (1999). Principles of neuropsychological rehabilitation. New York: Oxford University Press. Public Law 100-407 (1988). Technology-Related Assistance for Individuals with Disabilities Act of 1988. Retrieved October, 12, 2009, from http://www.ok.gov/ abletech/documents/Tech%20Act-Individuals%20 with%20Disabilities.pdf Pugliese, M. (2000). Stages. Bedford, MA: Cambium Learning Technologies. Quill, K. (1997). Instructional considerations for young children with autism: The rationale for visually cued instructions. Journal of Autism and Developmental Disorders, 27, 697–714. doi:10.1023/A:1025806900162 Quintana, C., Reiser, B. J., Davis, E. A., Krajcik, J., Fretz, E., & Duncan, R. G. (2004). A scaffolding design framework for software to support science inquiry. Journal of the Learning Sciences, 13, 337–386. doi:10.1207/ s15327809jls1303_4 Quirk, R., Greenbaum, S., Leech, G., & Svartvik, J. (1985). A comprehensive grammar of the English language. New York: Longman, Inc. Rachow, C., & Hodapp, J. (2008, October). Measure it, monitor it: Teacher tools for increasing access to print through use of text-to-speech software. Paper presented at 27th Annual Closing the Gap Conference, Minneapolis, MN.

431

Compilation of References

Radford, A. (1990). Syntactic theory and the acquisition of English syntax. Oxford, UK: Basil Blackwell Ltd. Radford, A. (2004). Minimalist syntax: Exploring the structure of English. Cambridge, UK: Cambridge University Press. Radford, A. (2009). Analyzing English sentences: A minimalist approach. Cambridge, UK: Cambridge University Press. Rapp, W. H. (2005). Using assistive technology with students with exceptional learning needs: When does an aid become a crutch? Reading & Writing Quarterly, 21(2), 193–196. doi:10.1080/10573560590915996 Raskind, M. H., & Higgins, E. L. (1998). Assistive technology for postsecondary students with learning disabilities: An overview [Electronic version]. Journal of Learning Disabilities, 31, 27–40. doi:10.1177/002221949803100104 Raskind, M., & Bryant, B. R. (2002). Functional evaluation of assistive technology (FEAT). Austin, TX: PsychoEducational Services. Rasmussen, J. (1986). Information processing and human-machine interaction: An approach to cognitive engineering. New York: Elsevier. Read Naturally. (2009). Retrieved July 24, 2009, from http://www.readnaturally.com/products/improvereading.htm Reed, P. (2009). Wisconsin Assistive Technology. Initiative Created through WI DPI IDEA. Grant number 990623, Assessing Students’ Needs for Assistive Technology (ASNAT) (5th ed.). Milton, WI: WATI. Reed, P., Bowser, G., & Korsten, J. (2002). How do you know it? How do you show it? Wisconsin Assistive Technology Initiative. Created through WI DPI IDEA. Grant number 9906-23. Milton, WI: WATI. Reed, S. K. (2006). Cognitive architectures for multimedia learning. Educational Psychologist, 41(2), 87–98. doi:10.1207/s15326985ep4102_2

432

Reid, R., & Lienemann, T. O. (2006). Strategy instruction for students with learning disabilities. New York: The Guilford Press. Renaissance Learning. (2009). NEO Alphasmarts. Wisconsin Rapids, WI: Renaissance Learning. Renkl, A. (2005). The worked-out examples principle in multimedia learning. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning (pp. 229–245). New York: Cambridge University Press. Renkl, A., & Atkinson, R. K. (2003). Structuring the transition from example study to problem solving in cognitive skill acquisition: A cognitive load perspective. Educational Psychologist, 30(1), 15–22. doi:10.1207/ S15326985EP3801_3 Reschly, D. (2002, February 22). Disproportional representation in special education. Presentation to the President’s Commission on Excellence in Special Education. Revenaugh, M. (2006). K-8 virtual schools: A glimpse into the future. Educational Leadership, 63(4), 60–64. Rice, M. (1998). In search of a grammatical marker of language impairment in children. Language Learning and Education (ASHA Special Interest Division 1), 5(1), 3-7. Rice, M., Wexler, K., & Cleave, P. (1995). Specific language impairment as a period of extended optional infinitive. Journal of Speech and Hearing Research, 38, 850–863. Rice, M., Wexler, K., & Hershberger, S. (1998). Tense over time: the longitudinal course of tense acquisition in children with specific language impairment. Journal of Speech and Hearing Research, 41, 1412–1431. Rieber, L. P. (2005). Multimedia learning in games, simulations, and microworlds. In R. E. Mayer (Ed.), The Cambridge handbook of multimedia learning (pp. 549567). New York: Cambridge University Press. Riva, G. (2005). Virtual reality in psychotherapy [Review]. Cyberpsychology & Behavior, 8(3), 220–230. doi:10.1089/cpb.2005.8.220

Compilation of References

Riva, G., Bacchetta, M., Baru, M., Rinaldi, S., & Molinari, E. (1999). Virtual reality based experiential cognitive treatment of anorexia nervosa. Journal of Behavior Therapy and Experimental Psychiatry, 30(3), 221–230. doi:10.1016/S0005-7916(99)00018-X Roberson, L. (2001). Integration of computers and related technologies into deaf education teacher preparation programs [Electronic version]. American Annals of the Deaf, 146(1), 60–66. Robins, B., Dautenhahn, K., te Boekhorst, R., & Billard, A. (2004). Robots as assistive technology - Does appearance matter? Proceedings of the 2004 IEEE International Workshop on Robot and Human Interactive Communication Kurashiki, Okayama Japan. Roblyer, M. D., & Edward, J. (2000). Assistive technology: Meeting the needs of learners with disabilities. Retrieved August 10, 2009, from http:// www.questia.com Roblyer, M. D., & Knezek, G. A. (2003). New millennium research for educational technology: A call for a national research agenda [Electronic version]. Journal of Research on Technology in Education, 36(1), 60–76. Rodda, M., & Eleweke, C. J. (2000). Literacy development in limited English proficiency deaf people: A review [Electronic version]. Deafness & Education International, 2(2), 101–113. doi:10.1002/dei.77 Roeper, T. (2007). The prism of grammar. Cambridge, MA: MIT Press. Roeper, T., & Seymour, H. (1994). The place of linguistic theory in the theory of language acquisition and language impairment. In Levy, Y. (Ed.), Other children, other languages (pp. 305–330). Hillsdale, NJ: Lawrence Erlbaum. Roeper, T., & Williams, E. (Eds.). (1987). Parameter setting. Dordrecht, The Netherlands: D. Reidel. Rogers, F. K. (1979). Parenting the difficult child. Radnor, PA: Chilton Book Co. Rogers, S., Muir, K., & Evenson, C. R. (2003). Signs of resilience: Assets that support deaf adults’ success in bridging the deaf and hearing worlds [Electronic ver-

sion]. American Annals of the Deaf, 148(3), 222–232. doi:10.1353/aad.2003.0023 Rogers-Dulan, J. (1998). The power of portfolios in inclusive classrooms. Adventist Education, Summer, 24-28. Rose, D. H., Hasselbring, T. S., Stahl, S., & Zabala, J. (2004). Assistive technology and universal design for learning: Two sides of the same coin. In Edyburn, D., Higgins, K., & Boone, R. (Eds.), Handbook of special education technology research and practice (pp. 507–518). Whitefish Bay, WI: Knowledge by Design, Inc. Rose, D., & Meyer, A. (2002). Teaching every student in the digital age: Universal design for learning. Alexandria, VA: Association for Supervision and Curriculum Development. Rose, F. D., Attree, E. A., & Johnson, D. A. (1996). Virtual reality: An assistive technology in neurological rehabilitation. Current Opinion in Neurology, 9(6), 461–467. Rosen, J. (2007). Calling for consumer directed and inclusively designed technology [Electronic version]. Policy and Practice of Public Human Services, 65(3), 14–17. Rossi, P., Freeman, H., & Lipsey, M. (1998). Evaluation: A systematic approach (6th ed.). Newbury Park, CA: Sage. Rothbaum, B. O., Hodges, L., Smith, S., Lee, J. H., & Price, L. (2000). A controlled study of virtual reality exposure therapy for the fear of flying. Journal of Consulting and Clinical Psychology, 68(6), 1020–1026. doi:10.1037/0022-006X.68.6.1020 Rouet, J.-F., & Potelle, H. (2005). Navigational Principles in Multimedia Learning. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning (pp. 297–312). New York: Cambridge University Press. Roy, M., & Chi, M. T. H. (2005). The self-explanation principle in multimedia learning. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning (pp. 271–286). New York: Cambridge University Press. Roy, S., Légeron, P., Klinger, E., Chemin, I., Lauer, F., & Nugues, P. (2003). Definition of a VR−based protocol for

433

Compilation of References

the treatment of social phobia. Cyberpsychology & Behavior, 6(4), 411–420. doi:10.1089/109493103322278808 Royer, J. M. (1986). Designing instruction to produce understanding: An approach based on cognitive theory. In Phye, G. D., & Andre, T. (Eds.), Cognitive classroom learning: Understanding, thinking, and problem solving. Orlando, FL: Academic Press. Rutter, M., & Yule, W. (1975). The concept of specific reading retardation. Journal of Child Psychology and Psychiatry, and Allied Disciplines, 16, 181–197. doi:10.1111/j.1469-7610.1975.tb01269.x Sáenz, L. M., Fuchs, L. S., & Fuchs, D. (2005). PeerAssisted Learning Strategies for English language learners with learning disabilities. Exceptional Children, 71(3), 231–247. Safer, N., & Fleischman, S. (2005). Research matters: How progress monitoring improves instruction. Educational Leadership, 62(5), 81–83. Salend, S. (1998). Using portfolios to assess student performance. TEACHING Exception Children, 31(2), 36–43. Salomon, G., & Perkins, D. N. (1989). Rocky roads to transfer: Rethinking mechanisms of a neglected phenomenon. Educational Psychologist, 24(2), 113–142. doi:10.1207/s15326985ep2402_1 Saltillo. (2008-2009). Point-and-Chat. Retrieved September 30, 2009, from http://www.saltillo.com/shop/catalog/ product_info.php?cPath=24&products_id=137 Santrock, J. W. (2003). Children (7th ed.). Boston: Mc Graw Hill. Schaimberg, L., & Lee, C. (1991, April). Predictors of verbal intelligence and behavioral problems among 4-year-old children. Paper presented at the biennial meeting of the Society for Research in Child Development, Seattle, WA. Schepis, M., Reid, D., Behrmann, M., & Sutton, K. (1998). Increasing communicative interactions of young children with autism using a voice output communication aid and naturalistic teaching. Journal of Applied Behavior

434

Analysis, 31, 561–578. doi:10.1901/jaba.1998.31-561 Scherer, M. (2005). Living in the state of stuck: How assistive technology impacts the lives of people with disabilities (4th ed.). Cambridge, MA: Brookline Books. Schery, T., & O’Connor, L. (1995). Computers as a context for language intervention. In Fey, M., Windsor, J., & Warren, S. (Eds.), Language intervention: Preschool through the elementary years (pp. 275–314). Baltimore: Brookes Publishing. Schmidt, M., Laffey, J., Stichter, J., Goggins, S., & Schmidt, C. (2008). The design of iSocial: A threedimensional, multiuser, virtual learning environment for individuals with autism spectrum disorder to learn social skills. The International Journal of Technology. Knowledge and Society, 2(4), 29–38. Schmidt, R. A., Young, D. E., Cormier, S. M., & Hagman, J. D. (1987). Transfer of movement control in motor skill learning. In Transfer of learning: Contemporary research and applications (pp. 47–79). San Diego, CA: Academic Press. Schoenfeld, A. H. (1987). Confessions of an accidental theorist. For the Learning of Mathematics--An International Journal of Mathematics Education, 7(1), 30. Schow, R. L., & Nerbonne, M. A. (1996). Introduction to audiologic rehabilitation. Needham Heights, MA: Allyn & Bacon. Schultheis, M. T., & Rizzo, A. A. (2001). The application of virtual reality technology in rehabilitation. Rehabilitation Psychology, 46(3), 296–311. doi:10.1037/00905550.46.3.296 Science Daily. (2008). Using brainwaves to chat and stroll through Second Life: World’s first. Retrieved from http:// www.sciencedaily.com/releases/2008/06/080613163213. htm Scott, C. (2009). A case for the sentence in reading comprehension. Language, Speech, and Hearing Services in Schools, 40, 184–191. doi:10.1044/0161-1461(2008/080042)

Compilation of References

Seth, A., & Smith, S. (2004). PC-based virtual reality for CAD model viewing. The Journal of Technology Studies, 30(4), 32–37.

Silverman, M. K., Stratman, K. F., & Smith, R. O. (2000). Measuring assistive technology outcomes in schools using functional assessment. Diagnostique, 25(4), 307–327.

Seymour, H., Roeper, T., & de Villiers, J. (2003). Diagnostic evaluation of language variation. San Antonio: The Psychological Corporation.

Simms, B. (2003). Assistive technology for early childhood. [from Wilson Web Database.]. Exceptional Parent, 33(8), 72–73. Retrieved on July 14, 2004.

Shapiro, A. M. (2005). The site map principle in multimedia learning. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning (pp. 313–324). New York: Cambridge University Press.

Simons, P. R. J. (1999). Transfer of learning: Paradoxes for learners. International Journal of Educational Research, 31, 577–589. doi:10.1016/S0883-0355(99)00025-7

Sherson, G. W. (2000). Closing the gap: The digital divide and Native Americans. Submitted in partial fulfillment of the requirement for the degree of Master of Communications, Victoria University in Wellington. Retrieved June 10, 2009, from www.ucol.ac.nz/~g.sherson/papers/ Closing_the_Gaps.pdf Shiffrin, R. M., & Atkinson, R. C. (1969). Storage and retrieval processes in long-term memory. Psychological Review, 76(2), 179–193. doi:10.1037/h0027277 Shim, K., Kim, H., Kim, J., Park, J., Park, Y., & Ryu, H. (2003). Application of virtual reality technology in biology education. Journal of Biological Education, 37(2), 71–73. Shneiderman, B. (Ed.). (1993). Encyclopedia of virtual environments (EVE). Human Interface Technology Lab, University of Washington. Retrieved February 8, 2004, from http://www.hitl.washington.edu/scivw/EVE Siegel, L. (1999). Issues in the definition and diagnosis of learning disabilities: A perspective on Guckenberger v. Boston University. Journal of Learning Disabilities, 32(4), 304–319. doi:10.1177/002221949903200405 Siegel, L. S. (1998). The discrepancy formula: Its use and abuse. In Shapiro, B., Accardo, P., & Capute, A. (Eds.), Specific reading disability: A view of the spectrum (pp. 123–135). Timonium, MD: York Press. Siegel, S., & Gaylord-Ross, R. (2001). Factors associated with employment success among youth with disabilities. Journal of Learning Disabilities, 24(1), 40–47. doi:10.1177/002221949102400108

Singh, N., Lancioni, G. E., Winton, A. S. W., Molina, E., Sage, M., Brown, S., & Groeneweg, J. (2004). Effects of Snoezelen room, activities of daily living skills training, and vocational skills training on aggression and self-injury by adults with mental retardation and mental illness. Research in Developmental Disabilities, 25, 285–293. doi:10.1016/j.ridd.2003.08.003 Singleton, J. L., Morgan, D., DiGello, E., Wiles, J., & Rivers, R. (2004). Vocabulary use by low, moderate, and high ASL-proficient writers compared to hearing ESL and monolingual speakers [Electronic version]. Journal of Deaf Studies and Deaf Education, 9(1), 86–103. doi:10.1093/deafed/enh011 Skinner, B. F. (1974). About behaviorism. New York: Random House, Inc. Slotznick, B., Hershberger, D., & Higginbotham, J. (2009). Point-and-Chat: Instant messaging software for augmentative/alternative communications users. National Center for Technology Innovation, AIR SubGrant No. 0037802411.002, AIR prime grant No. H327Z060003. Retrieved February 6, 2009, from http://www.nationaltechcenter. org/documents/point_and_chat_final_report.pdf Smedley, T., & Higgins, K. (2005). Virtual technology: Bringing the world into the special education classroom. Intervention in School and Clinic, 41(2), 114–119. doi:10 .1177/10534512050410020201 Smith, D. W., & Kelley, P. (2007). A survey of assistive technology and teacher preparation programs for individuals with visual impairments. Journal of Visual Impairment & Blindness, 101(7), 429–433.

435

Compilation of References

Smith, R. O. (2000). Measuring assistive technology outcomes in education. Diagnostique, 25, 273–290.

Spear, N. E., & Riccio, D. C. (1994). Memory: Phenomena and principles. Boston, MA: Allyn & Bacon.

Smith, S. (2000). Teacher education—Associate editor’s column [Electronic version]. Journal of Special Education Technology, 15(1), 59–62.

Special Education Technology. (n.d.). The GPS project. Retrieved from http://www.setbc.org/news/docs/ gpsproject.html

Smith, S. J., & Jones, E. P. (1999). Technology infusion: Preparing teachers through web-based cases [Electronic version]. Career Development for Exceptional Individuals, 22, 251–266. doi:10.1177/088572889902200207

Sperling, G. (1960). The information available in brief visual presentations. Psychological Monographs: General and Applied, 74(11), 1–29.

Smith, T. M., Desimone, L. M., & Ueno, K. (2005). Highly qualified to do what? The relationship between NCLB teacher quality mandates and the use of reform-oriented instruction in middle school mathematics [Electronic version]. Educational Evaluation and Policy Analysis, 27(1), 75–109. doi:10.3102/01623737027001075 Smurall, W. J., & Curry, K. (2006). Teaching for transferal. Science Scope, 14(17). Soloman, K. (2000). Disability divide. The Industry Standard. Retrieved August 1, 2009, from http://www. thestandard.com/article/0,1902,16236,00.html Solomon, G., Allen, N. J., & Resta, P. (Eds.). (2003). Toward digital equity: Bridging the divide in education. Boston: Allyn and Bacon. Solso, R. L. (2001). Cognitive psychology (Vol. 6). Needham Heights, MA: Allyn & Bacon. Sorrell, C. A., Bell, S. M., & McCallum, R. S. (2007). Reading rate and comprehension as a function of computerized versus traditional presentation mode: A preliminary study. Journal of Special Education Technology, 22(1), 1–12. Soto, G., Belfiore, P. J., Schlosser, R. W., & Haynes, C. (1993). Teaching specific requests: A comparative analysis on skill acquisition and preference using two augmentative and alternative communication aids. Education and Training in Mental Retardation, 28, 169–178. Spaulding, K. (1980). Multimorpheme structures in emerging grammar: A single subject study. Unpublished Master of Science Thesis, University of Vermont.

436

Spiegel-McGill, P., Zippiroli, S., & Mistrett, S. (1989). Microcomputers as social facilitators in integrated preschools. Journal of Early Intervention, 13, 249–260. doi:10.1177/105381518901300306 Sprinthal, N. A., Sprinthal, R. C., & Oja, S. N. (1994). Educational psychology: A developmental approach (6th ed.). Boston: McGraw Hill, Inc. Squire, L. R. (2008). Memory and brain. New York: Oxford University Press. Staal, J. A., Sacks, A., Matheis, R., Calia, T., Hanif, H., Collier, L., & Kofman, E. (2005, July). The effects of Snoezelen (Multi-Sensory Behavior Therapy) and psychiatric care on agitation, apathy, and activities of daily living in dementia patients on a short term geriatric psychiatric inpatient unit. Poster session presented at the Alzheimer’s Association International Conference, Washington, DC. Stanovich, K. E., & Siegel, L. S. (1994). The phenotypic performance profile of reading-disabled children: A regression-based test of the phonological-core variabledifference model. Journal of Educational Psychology, 86, 24–53. doi:10.1037/0022-0663.86.1.24 Stanovick, K. E. (1986). Matthew effects in reading: Some consequences of individual differences in the acquisition of literacy. Reading Research Quarterly, 21, 360–407. doi:10.1598/RRQ.21.4.1 Steelman, J. D., Pierce, P. L., & Koppenhaver, D. A. (1993). Emerging literacy and children with severe speech and physical impairments (SSPI): Issues and possible interventions. Topics in Language Disorders, 13, 47–57.

Compilation of References

Steiner, S., & Larson, V. (1991). Integrating microcomputers into language intervention with children. Topics in Language Disorders, 11, 18–30. Stemach, G., & Williams, W. B. (1988). Word express: The 1st hundred words of spoken English. Novato, CA: Academic Therapy Publications. Stephenson, J. (1995). Sick kids find help in a cyberspace world. Journal of the American Medical Association, 274(24), 1899–1901. doi:10.1001/jama.274.24.1899 Stewart, D. A., & Kluwin, T. N. (2001). Teaching deaf and hard of hearing students: Content, strategies, and curriculum. Needham Heights, MA: Allyn & Bacon. Stichter, J. P., Herzog, M.J., Visovsky, K., Schmidt, C., Randolph, J., Schultz, T., & Gage, N. (in review). Social competence intervention for youth with Asperger Syndrome and high-functioning autism: An initial investigation. Submitted to review in the Journal of Autism and Developmental Disorders. Stichter, J. P., Randolph, J., Gage, N., & Schmidt, C. (2007). A review of recommended practices in effective social competency programs for students with ASD. exceptionality, 15, 219-232. Stiggins, R. J. (1987). The design and development of performance assessments. Educational Measurement: Issues and Practice, 6, 33–42. doi:10.1111/j.1745-3992.1987. tb00507.x Stoof, A., Martens, R., & Merriënboer, J. (2007, August). Web-based support for constructing competence maps: Design and formative evaluation. Educational Technology Research and Development, 55(4), 347–368. doi:10.1007/s11423-006-9014-5 Storbeck, C., & Calvert-Evers, J. (2008). Towards integrated practices in early detection of and intervention for deaf and hard of hearing children. American Annals of the Deaf, 153(3), 314–321. doi:10.1353/aad.0.0047 Stover, D. L., & Pendegraft, N. (2005). Revisiting computer-aided notetaking: Technological assistive devices for hearing-impaired students [Electronic version]. Clearing House (Menasha, Wis.), 79(2), 94–97. doi:10.3200/TCHS.79.2.94-97

Strangman, N., & Dalton, B. (2005). Technology for struggling readers: A review of the research. In Edyburn, D. L., Higgins, K., & Boone, R. (Eds.), Handbook of special education technology research and practice (pp. 545–569). Whitefish Bay, WI: Knowledge by Design. Strangman, N., & Hall, T. (2003). Text transformations. Wakefield, MA: National Center on Accessing the General Curriculum. Retrieved February 23, 2007, from http:// www.cast.org/publications/ncac/ncac textrans.html Stuart, S., & Parette, H. P. (2002). Native Americans and augmentative and alternative communication issues. Multiple Voices, 5(1), 38–53. SuccessMaker Enterprise. (n.d.). Retrieved July 24, 2009, from http://www.pearsonschool.com/index.cfm?locator =PSZ16c&PMDBSUBCATEGORYID=&PMDBSITEI D=2781&PMDBSUBSOLUTIONID=&PMDBSOLUTI ONID=6724&PMDBSUBJECTAREAID=&PMDBCA TEGORYID=1662&PMDbProgramId=32505 Sullivan, M. W., & Lewis, M. (2000). Assistive technology for the very young: Creating responsive environments. Infants and Young Children, 12, 34–52. Swanson, H. L., & Siegel, L. (2001). Learning disabilities as a working memory deficit. Issues in Education: Contributions of Educational Psychology, 7(1), 1–48. Sweller, J. (1988). Cognitive load during problem-solving: Effects on learning. Cognitive Science, 12(1), 257–285. Sweller, J. (1994). Cognitive load theory, learning difficulty, and instructional design. Learning and Instruction, 4, 295–312. doi:10.1016/0959-4752(94)90003-5 Sweller, J. (1999). Instructional design in technical areas. Australia: ACER Press. Sweller, J. (2005). Implications of cognitive load theory for multimedia learning. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning (pp. 19–30). New York: Cambridge University Press. Sweller, J. (2005). The redundancy principle in multimedia learning. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia learning (pp. 159–167). New York: Cambridge University Press.

437

Compilation of References

Sweller, J., & Chandler, P. (1994). Why some material is difficult to learn. Cognition and Instruction, 12(3), 185–233. doi:10.1207/s1532690xci1203_1 Sweller, J., & Cooper, G. A. (1985). The use of worked examples as a substitute for problem solving in learning algebra. Cognition and Instruction, 2(1), 59–89. doi:10.1207/s1532690xci0201_3 Sweller, J., Chandler, P., Tierney, P., & Cooper, M. (1990). Cognitive load as a factor in the structuring of technical material. Journal of Experimental Psychology. General, 119(2), 176–192. doi:10.1037/0096-3445.119.2.176 Sweller, J., van Merrienboer, J. J. G., & Paas, F. G. W. C. (1998). Cognitive architecture and instructional design. Educational Psychology Review, 10(3), 251–296. doi:10.1023/A:1022193728205 Tager-Flusberg, H. (2004). Language and communication disorders in autism spectrum disorders. In Bauman, M., & Kemper, T. (Eds.), The neurobiology of Autism (2nd ed., pp. 45–58). Baltimore, MD: Johns Hopkins University Press. Tager-Flusberg, H., & Calkins, S. (1990). Does imitation facilitate the acquisition of grammar? Evidence from a study of autistic, Down syndrome and normal children. Journal of Child Language, 17, 591–606. doi:10.1017/ S0305000900010898 Tait, K., Hartley, J., & Anderson, R. (1973). Feedback procedures in computer-assisted arithmetic instruction. The British Journal of Educational Psychology, 43, 161–171. Tal, N. F., & Siegel, L. S. (1996). Pseudoword reading errors of poor, dyslexic and normally achieving readers on multisyllable pseudowords. Applied Psycholinguistics, 17, 215–232. doi:10.1017/S0142716400007645 Tapscott, D. (1997). Growing up digital: The rise of the net generation. New York: McGraw Hill. Tarmizi, R. A., & Sweller, J. (1988). Guidance during mathematical problem solving. Journal of Educational Psychology, 80(4), 424–436. doi:10.1037/00220663.80.4.424

438

Technical-Related Assistance for Individuals with Disabilities Act of 1988 (Tech Act). (1998). Catalogue No. 850.(Senate Report 100-438). Washington, DC: US Government Printing Office. Technology-Related Assistance for Individuals with Disabilities Act of 1988, PL 100-407. (August 19, 1988). Title 29, U.S.C. 2201 et seq: U.S. Statutes at Large, 102, 1044-1065. Technology-Related Assistance for Individuals with Disabilities Act of 1988. (Tech Act). (1988). Public Law 100-407 The ADA Amendments Act of 2008. (2008). Section 2 (b) (1). Retrieved from http://www.access-board.gov/about/ laws/ada-amendments.htm Theng, Y. L. (1997), Addressing the ‘lost in hyperspace’ problem in hypertext. PhD Thesis, Middlesex University (London). Theng, Y. L., Jones, M., & Thimbleby, H. (1995a). Reducing information overload: A comparative study of hypertext systems. IEEE Colloquium on Information Overload, 95(223), 6/1-6/5. Thoma, C. A., Rogan, P., & Baker, S. R. (2001). Student involvement in transition planning: Unheard voices. Education and Training in Mental Retardation and Developmental Disabilities, 36(1), 16–29. Thuring, M., Hannemann, J., & Haake, J. M. (1995). Hypermedia and cognition: Designing for comprehension. Communications of the ACM, 38(8), 57–66. doi:10.1145/208344.208348 Tiala, S. (2007). Integrating virtual reality into technology education labs. Technology Teacher, 66(4), 9–13. Tindall-Ford, S., Chandler, P., & Sweller, J. (1997). When two sensory modes are better than one. Journal of Experimental Psychology. Applied, 3(4), 257–287. doi:10.1037/1076-898X.3.4.257 Toth, G., & Siegel, L. S. (1994). A critical evaluation of the IQ-achievement discrepancy based definition of dyslexia. In L. S. S. K. P. van den Bos, D. J., & D. L. S. Bakker

Compilation of References

(Eds.), Current directions in Dyslexia research (pp. 45–70). Lisse, The Netherlands: Swets & Zeitlinger. Trantham, C., & Pedersen, J. (1976). Normal language development: The key to diagnosis and therapy for language-disordered children. Baltimore: The Williams & Wilkins Company. Traxler, C. B. (2000). Measuring up to performance standards in reading and mathematics: Achievement of selected deaf and hard-of-hearing students in the national norming of the 9th Edition Stanford Achievement Test. Journal of Deaf Studies and Deaf Education, 5, 337–348. doi:10.1093/deafed/5.4.337 Trepanier, N. S. (2005). Toward an ecological risk assessment framework for special education. International Journal of Special Education, 20(1). Tripp, S. D., & Roby, W. (1990). Orientation and disorientation in a hypertext lexicon. Journal of Computer-Based Instruction, 17(4), 120–124. Tubau, E., Hommel, B., & Lapez-Moliner, J. (2007). Modes of executive control in sequence learning: From stimulus-based to plan-based control. Journal of Experimental Psychology. General, 136(1), 43–63. doi:10.1037/0096-3445.136.1.43 Tulving, E. (1983). Elements of episodic memory. Oxford, UK: Oxford University Press. Tulving, E. (2002). Episodic memory: From mind to brain. Annual Review of Psychology, 53, 1–25. doi:10.1146/annurev.psych.53.100901.135114 Turnbull, A. P., Summers, J., Turnbull, R., Brotherson, M. J., Winton, P., & Roberts, R. (2007). Family supports and services in early intervention. A bold vision. Journal of Early Intervention, 29, 187–206. doi:10.1177/105381510702900301 Turnbull, A. P., Turnbull, H. R., Erwin, E., & Soodak, L. (2006). Families, professionals, and exceptionality: Positive outcomes through partnership and trust. Columbus, OH: Merrill/Prentice Hall. Turnbull, A., Turnbull, R., & Wehmeyer, M. (2007). Exceptional lives (5th ed.). Upper Saddle River, NJ: Merrill.

Turnbull, A., Turnbull, R., & Wehmeyer, M. L. (2010). Exceptional lives: Special education in today’s school (6th ed.). Upper Saddle River, NJ: Pearson. Turner, J. D. (2007). Beyond cultural awareness: Prospective teachers’ visions of culturally responsive literacy teaching [Electronic version]. Action in Teacher Education, 29(3), 12–24. Twist, K. (2002). A nation online, but where are the Native Americans? Retrieved August 17, 2009, from http://www. digitaldivide.net/articles/view.php?ArticleID=153 Tye-Murray, N. (2009). Foundations of aural rehabilitations: Children, adults, and their family members (3rd ed.). Clifton Park, NY: Delmar. U.S. Department of Commerce. (2000). Falling through the net: Toward digital inclusion: A report on Americans’ access to technology tools. Washington, DC: National Telecommunications and Information. U.S. Department of Commerce. (2002). A nation online: How Americans are expanding their use of the Internet. Washington, DC: National Telecommunications and Information Administration, Economics and Statistics Administration (NTIA). Retrieved August 1, 2009, from www.ntia.doc.gov/ntiahome/dn/nationonline_020502. htm U.S. Department of Education Office of Special Education Programs (OSEP). (2006). Office of special education and rehabilitation services. Retrieved August 14, 2009, from http://www.ed.gov/about/ offices/list/osers/osep/ index.html?src=mr U.S. Department of Education, National Center for Education Statistics. (2003). Computer and Internet use by children and adolescents in 2001. NCES 2004–014. Retrieved June 2, 2009, from http://nces.ed.gov/ pubs2004/2004014.pdf U.S. General Accounting Office. (2001). Telecommunications: Characteristics and choices of Internet users. Washington, DC: USGPO. U.S. Office of Education. (1977, December 29). Assistance to states for education of handicapped children:

439

Compilation of References

Procedures for evaluating specific learning disabilities. [Washington, DC: U.S. Government Printing Office.]. Federal Register, 42(250), 65082–65085. United States Congress. (1998). Assistive Technology Act of 1998. Retrieved from http://section508.gov/docs/ AT1998.html US Department of Education. (2007). Twenty-seventh annual report to congress on the implementation of the Individuals with Disabilities Education Act. Washington, DC: Author. Retrieved on January 5, 2009, from http://www.ed.gov/offices/OSERS/OSEP/Products/ OSEP2007AnlRpt/ Utley, C. A., Delquadri, J. C., Obiakor, F. E., & Mims, V. A. (2000). General and special educators’ perceptions of teaching strategies for multicultural students. Teacher Education and Special Education, 23, 34–50. doi:10.1177/088840640002300107 Valentin, S. (2006). Addressing diversity in teacher education programs [Electronic version]. Education, 127, 196–202. Van der Wissel, A., & Zegers, F. E. (1985). Reading retardation revisited. The British Journal of Developmental Psychology, 3, 3–9. Van Gerven, P. W. M., Paas, F., Van Merrienboer, J. J. G., & Schmidt, H. G. (2006). Modality and variability as factors in training the elderly. Applied Cognitive Psychology, 20, 311–320. doi:10.1002/acp.1247 Van Laarhoven, T., Munk, D. D., Zurita, L. M., Lynch, K., Zurita, B., & Smith, T. (2009). The effectiveness of video tutorials for teaching preservice educators to use assistive technologies. Journal of Special Education Technology, 23(4), 31–45. van Merrienboer, J. J. G., & Ayres, P. (2005). Research on cognitive load theory and its design implications for e-learning. Educational Technology Research and Development, 53(3), 5–13. doi:10.1007/BF02504793 Vellutino, F., Scanlon, D., Sipay, E., Small, S., Pratt, S., Chen, R., & Denckla, M. B. (1996). Cognitive profiles of difficult-to-remediate and readily remediated poor

440

readers: Early intervention as a vehicle for distinguishing between cognitive and experiential deficits as basic causes of specific reading disability. Journal of Educational Psychology, 88(4), 601–638. doi:10.1037/00220663.88.4.601 Veronikas, S., & Shaughnessy, M. F. (2005). An interview with Richard Mayer. Educational Psychology Review, 17(2), 179–189. doi:10.1007/s10648-005-3952-z Vincelli, F., Choi, Y. H., Molinari, E., Wiederhold, B. K., & Rive, G. (2000). Experiential cognitive therapy for the treatment of panic disorder with agoraphobia: Definition of a clinical protocol. Cyberpsychology & Behavior, 3(3), 375–385. doi:10.1089/10949310050078823 Vogel, J., Bowers, C., Meehan, C., Hoeft, R., & Bradley, K. (2004). Virtual reality for life skills education: Program evaluation. Deafness & Education International, 6(1), 39–50. doi:10.1002/dei.162 Vygotsky, L. (1987). Thinking and speech. In R. R. A. Carton (Ed.), Collected works of l. S. Vygotsky: Vol. 1: Problems of general psychology (pp. 39–285). New York: Plenum. Wagner, M., Newman, L., Cameto, R., Garza, N., & Levine, P. (2005). After high school: A first look at the postschool experiences of youth with disabilities. Menlo Park, CA: SRI International. Waller, D., Hunt, E., & Knapp, D. (1998). The transfer of spatial knowledge in virtual environment training. Presence (Cambridge, Mass.), 7(2), 129–143. doi:10.1162/105474698565631 Ward, M., & Sweller, J. (1990). Structuring effective worked examples. Cognition and Instruction, 7(1), 1–39. doi:10.1207/s1532690xci0701_1 Ware, C. (2004). Information visualization: Perception for design (2nd ed.). San Francisco, CA: Morgan Kaufmann Publishers. Warger, C. L. (Ed.). (2005). Technology and media for accessing the curriculum. Instructional support for students with disabilities. Columbia, MD: Center for Technology in Education and Technology and Media Division.

Compilation of References

Warwick, D., Gasson, M., Hutt, B., Goodhew, I., Kyberd, P., & Andrews, B. (2003). The application of implant technology for cybernetic systems. Archives of Neurology, 60(10). doi:10.1001/archneur.60.10.1369 Watch, O. M. B. (2002). Closing the digital divide: Community technology centers. Retrieved August 17, 2009, from http://www.ombwatch.org/node/352 Wattenberg, T. (2004). Beyond legal compliance: Communities of advocacy that support accessible online learning. The Internet and Higher Education, 7, 123–139. doi:10.1016/j.iheduc.2004.03.002 Watts, E. H., O’Brian, M., & Wojcik, B. W. (2004). Four models of assistive technology consideration: How do they compare to recommended educational assessment practices? Journal of Special Education Technology, 19(1). Waugh, N. C., & Norman, D., A. (1965). Primary memory. Psychological Review, 72(2), 89–102. doi:10.1037/ h0021797 Way, R. (1993). Intelligent tutoring and training white paper. Houston, TX: National Aeronautics and Space Administration, Software Technology Branch. Wehmeyer, M. L., Palmer, S., Agran, M., Mithaug, D., & Martin, J. (2000). Promoting causal agency: The selfdetermined learning model of instruction. Exceptional Children, 66, 439–453. Wehmeyer, M., & Palmer, S. B. (2000). Promoting the acquisition and development of self-determination in young children with disabilities. Early Education and Development, 11, 465–481. doi:10.1207/s15566935eed1104_6 Weikle, B., & Hadadian, A. (2003). Can assistive technology help us to not leave any child behind? Preventing School Failure, 47(4), 181–186. doi:10.1080/10459880309603365 Wendling, B. J., & Mather, N. (2009). Essentials of evidence-based academic interventions (Kaufman, A. S., & Kaufman, N. L., Eds.). Hoboken, NJ: John Wiley & Sons.

Wertsch, J. (1998). Mind as action. New York: Oxford University Press. Wesson, C., & King, R. (1996). Portfolio assessment and special education students. Teaching Exceptional Children, 28, 44–48. Wexler, K. (1998). Very early parameter setting and the unique checking constraint: A new explanation of the optional infinitive stage. Lingua, 106, 23–79. doi:10.1016/ S0024-3841(98)00029-1 Whaley, K. K. (1990). The emergence of social play in infancy: A proposed developmental sequence of infantadult social play. Early Childhood Research Quarterly, 5, 347–358. doi:10.1016/0885-2006(90)90026-W Wheeler, A., Archbold, S., Gregory, S., & Skipp, A. (2007). Cochlear implants: The young people’s perspective. Journal of Deaf Studies and Deaf Education, 12(3), 303–316. doi:10.1093/deafed/enm018 Wheeler-Scruggs, K. (2002). Assessing the employment and independence of people who are deaf and low functioning [Electronic version]. American Annals of the Deaf, 147(4), 11–17. Wiederholt, J. L., & Blalock, V. (2000). Grays silent reading test. Austin, TX: Pro-ed. Wilcox, J. M., Dugan, L. M., Campbell, P. H., & Guimond, A. (2006). Recommended practices and parent perspectives regarding AT use in early intervention. Journal of Special Education Technology, 21, 7–16. Wilson, B. A. (1997). Cognitive rehabilitation: How it is and how it might be. Journal of the International Neuropsychological Society, 3(5), 487–496. Wilson, M. (1977). Syntax Remediation: A generative grammar approach to language development. Cambridge, MA: Educator’s Publishing Service, Inc. Wilson, M. (2000). The Wilson Syntax Screening Test. San Antonio: The Psychological Corporation. Wilson, M., & Fox, B. (1981). A study of feedback effects in microcomputer administered receptive language training. Unpublished manuscript.

441

Compilation of References

Wilson, M., & Fox, B. (1983). Microcomputers: A clinical aid. In Winitz, H. (Ed.), Treating language disorders: For clinicians by clinicians (pp. 235–248). Baltimore: University Park Press. Wilson, M., & Fox, B. (1986). Microcomputer language assessment, intervention, and enhancement. In Northern, J. (Ed.), The personal computer for speech, language, and hearing professionals (pp. 101–111). Boston: Little, Brown & Company. Wilson, M., & Fox, B. (2007). LanguageLinks: Syntax Assessment and Intervention. Winooski, VT: Laureate Learning Systems, Inc. Wilson, M., & Fox, B. (2007). Prepositions!Winooski, VT: Laureate Learning Systems, Inc. Wilson, M., & Pascoe, J. (1999). Evaluation of a grammatical markers screening test for specific language impairments. Paper presented at the annual meeting of the American Speech-Language-Hearing Association, San Francisco, November 1999. Wojcik, B. W., Peterson-Karlan, G., Watts, E. H., & Parette, H. P. (2004). Assistive technology in a teacher education curriculum. Assistive Technology Outcomes and Benefits, 1, 21–32. Wong, B. Y. L., Graham, L., Hoskyn, M., & Berman, J. (1996). The ABCs of learning disabilities (2nd ed.). New York: Elsevier/Academic Press. Woodward, J., & Rieth, H. (1997). A historical review of technology research in special education. Review of Educational Research, 67(4), 503–536. Wozney, L., Venketesh, V., & Abrami, P. (2006). Implementing computer technologies: Teachers’ perceptions and practices [Electronic version]. Journal of Technology and Teacher Education, 14(1), 173–207. Yoshinaga-Itano, C. (2003). Early intervention after universal neonatal hearing screening: Impact on outcomes [Electronic version]. Mental Retardation and Devel-

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opmental Disabilities Research Reviews, 9, 252–266. doi:10.1002/mrdd.10088 Yoshinaga-Itano, C., Coulter, D., & Thomson, V. (2000). The Colorado newborn hearing screening project: Effects on speech and language development for children with hearing loss [Electronic version]. Journal of Perinatology, 20, S132–S137. Zabala, J. S. (1995). The SETT framework: Critical areas to consider when making informed assistive technology decisions. Houston, TX: Region IV Education Service Center. ERIC Document Reproduction Service No. ED381962. Retrieved January 15, 2009, from http:// www.joyzabala.com Zaidman-Zait, A., & Dromi, E. (2007). Analogous and distinctive patterns of prelinguistic communication in toddlers with and without hearing loss [Electronic version]. Journal of Speech, Language, and Hearing Research: JSLHR, 50(5), 1166–1180. doi:10.1044/10924388(2007/081) Zehr, M. A. (2001). Language barriers. Education Week, 20(35), 28–30. Zhang, Y. (2000). Technology and the writing skills of students with learning disabilities. Journal of Research on Computing in Education, 32(4), 467–478. Zhu, E. (1999). Hypermedia interface design: The effects of number of links and granularity of nodes. Journal of Educational Multimedia and Hypermedia, 8(3), 331–359. Zimmerman, B., & Pike, E. (1972). Effects of modeling and reinforcement on the acquisition and generalization of question-asking behavior. Child Development, 43, 892–907. doi:10.2307/1127640 Zimmerman, B., & Rosenthal, T. (1974). Observational learning of rule-governed behavior by children. Psychological Bulletin, 81, 29–42. doi:10.1037/h0035553

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About the Contributors

Soonhwa Seok has an M.A. and Ph.D. in curriculum and instruction in special education from the University of Kansas. Dr. Seok has interests in educational communication and technology with applications for teaching English as a second language and special education. Most recently, as a post-doctoral researcher, Dr. Seok has examined and developed intersensory learning models, assistive technology, and motivation and feedback for students with learning disabilities. Another research focus is assistive technology evaluation, such as functional evaluation for assistive technology, and supports intensity scales implementing assistive technology for the students with disabilities. She has served as a peer reviewer for conference proposals, presented on web accessibility, and published articles on distance education and special education technology. Edward Meyen is a Budig professor of special education and co-director of the eLearning Design lab at the University of Kansas. His research interests are in the development of elearning tools for use by educators in K-12 and post secondary education. His current work is in developing online tools to enhance the blending of assessment with instruction that is aligned with curriculum standards K-12 Education. Boaventura DaCosta has a B.S. in computer science and an M.A. and Ph.D. in instructional systems design. Dr. DaCosta is a researcher and the cofounder of Solers Research Group, Inc. in Orlando, FL. Among his research interests in cognitive psychology and information and communication technology innovations, Dr. DaCosta is also interested in how games can be used in learning. Complimenting his work as a researcher, Dr. DaCosta has worked in the commercial and government training sectors for the past 15 years as a software engineer and has been involved in a number of defense programs. *** Rashida Banerjee is assistant professor and early childhood special education program coordinator at the University of Northern Colorado, School of Special Education. She is an alumnus of the Ford Foundation International Fellowships program. Rashida has received the J. David Sexton Doctoral Student Scholarship from the Division of Early Childhood, the Council for Exceptional Children, Division of Research Student Research Award, and the Outstanding Dissertation for the School of Education Award, University of Kansas. Rashida’s main emphasis has been acting as a catalyst to promote quality services for children with disabilities and their families in early childhood. As a classroom teacher, Rashida has worked extensively with children with significant support needs requiring assistive technology.

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About the Contributors

Her research areas and interests are assessment of young children, specifically issues around diversity; effective community, family, and professional partnerships; effective inclusive intervention for young children; teacher preparation, and; international support systems for persons with disability. Marcie M. Belfi is a doctoral student at the University of Texas at Austin in the field of multicultural special education. She received her M.S. (2003) from the University of Houston in instructional technology, and her B.S. (1999) from the University of Texas at Austin in communication sciences and disorders. She has taught in a variety of settings, including residential centers, life skills and resource classrooms, as well as the university classroom. Her research interests are in preparing special education teachers to work within culturally and linguistically diverse populations, web-based teacher preparation, and assistive technology. Monica R. Brown is an associate professor in the Department of Special Education/Communication Disorders at New Mexico State University. Dr. Brown teaches graduate and undergraduate courses of a general special education nature as well as those courses (i.e., transition, secondary methods) specifically for the student, special and general education, seeking to work in a secondary classroom. Her current research interests include disaffected adolescents, multicultural special education, technology access and use, teacher preparation and secondary education. Brian R. Bryant lives and works in Austin, Texas. After teaching special education students for 3 years in Maine, 2 years in Grades K-8 and 1 year in Grades 9-12, Brian moved to Texas to work on his doctorate at The University of Texas at Austin. Since graduating in 1984, Brian has served in many professional capacities, including as the Director of Research at Pro-Ed, Inc., an educational publishing company located in Austin, Texas; adjunct faculty member at The University of Texas at Austin and Florida Atlantic University; Research Fellow at The University of Texas’ Vaughn Gross Center for Reading and Language Arts; and Project Manager of the Institute for Mathematics Disabilities and Difficulties in the Meadows Center for Preventing Educational Risk. His research interests involve service provision for individuals with learning disabilities and mental retardation, particularly with regards to reading, mathematics, and assistive technology applications throughout the lifespan. Jennifer Delisi works as the Therapeutic Services Coordinator and Neurologic Music Therapist for Lifeworks Services. She is a member of the Governor’s Advisory Council on Assistive Technology in Minnesota, and manages Lifeworks’ device lending library. Her clinical areas of interest are assistive technology and sensory impairments. Muhammet Demirbilek is a visiting Post Doctoral Researcher at Games, Learning, and Society (GLS) at the University of Wisconsin-Madison and an Assistant Professor of Educational Technology at Suleyman Demirel University. Demirbilek earned his doctorate and masters degree in Educational Technology program from the University of Florida. He also holds B.S. and MS degrees in electronics engineering. He worked on the PT3 project and served as a graduate assistant in the School of Teaching and Learning at the University of Florida. His dissertation research examined the effects of different modes of human-computer interfaces and individual differences on user disorientation and cognitive load in hypermedia learning environments. His current research interests include the impact of mobile media and digital games and simulations on teaching and learning; relationship between second language

444

About the Contributors

learning achievement and game play; how the electronic game environment helps adult players learn; and designing digital learning environments. Gary Paul Dotterer is an IT Developer / Trainer for Northeast Technology Center District (vocational and technical training) located in NE Oklahoma. He has worked as an educator and trainer of advanced technologies including assistive technologies. Gary is currently a graduate student at Oklahoma State University with his research emphasis in virtual environments utilizing advanced and assistive technology in individual learning processes. He is the recipient of the prestigious Ausburn Research Award at Oklahoma State University in 2009 and received the Outstanding Professional Development Award at the Career and Technical Education Research and Professional Development Conference in 2007. He is a consultant to the Electronic and Information Technology Accessibility Advisory Council for the state of Oklahoma. Gary has served as the president of the Phi chapter of Omicron Tau Theta and is a member of the Golden Key International Honor Society, The National Scholar Honor Society, and Phi Kappa Phi. Michael Dunn has taught at the elementary level as a special education consultant teacher in inclusive classrooms and English as a second language teacher for 11 years in the Toronto (Ontario) area. As a professor of special education and literacy at Washington State University Vancouver (WSUV) since 2005, Michael teaches courses applicable to K-12 educators in the Special Education Endorsement Program and Master’s in Teaching Certification Program. Michael conducts research in response to intervention and literacy skills/strategies. Recent research includes general educators’ perspectives about response to intervention as well as mnemonic strategy instruction for early-elementary students’ narrative story writing. Estrada-Hernández is an Assistant Professor in Rehabilitation Counseling with the Department of Counseling, Rehabilitation, and Student Development at the University of Iowa. Among his responsibilities Dr. Estrada-Hernandez coordinates research activities with the Iowa Center for Assistive Technology Education and Research as well as teaching various core courses in the MA program in rehabilitation counseling. His research interests include the areas of Psychosocial adaptation to disability, especially on persons with Albinism, Employment/Vocational outcomes on persons with visual impairments, and Assistive technology. Dr. Estrada-Hernandez is member of various professional organizations such as the American Counseling Association, American Rehabilitation Counseling Association, and National Council on Rehabilitation Education. Michael Fitzpatrick is an assistant professor in the college of Special Education / Communication Disorders at New Mexico State University. He currently teaches undergraduate and graduate courses and is involved with teacher preparation and technology integration across the lifespan. His research interests include increasing the academic and social outcomes for students with and without disabilities in urban school settings, policy and leadership, technology integration, multicultural education, and Media Literacy. Additional focus areas include infusing technology, cognitive based strategies, and behavior management systems to enhance the academic, social, emotional, and behavioral outcomes of students with mild-to-severe emotional and behavioral disorders.

445

About the Contributors

Joan B. Hodapp served nine years as a Special Education administrator for Area Education Agency 267 in Clear Lake, IA and supervised the Assistive Technology Resource Teams serving 61 school districts. Prior to that she served for 24 years as a school psychologist. Her research interests include curriculum-based measurement, behavioral interventions, study skills, and the impact of accommodations such as text-to-speech software. Eva Horn is a Professor of Early Childhood Education in the School of Education at the University of Kansas. Having worked as an early childhood special educator for 10 years, Dr. Horn focuses on the development of effective instructional approaches for infants, toddlers, and young children with developmental delays and disabilities. Her research examines how these effective strategies can be implemented within the context of ongoing routines and activities in inclusive and natural environments. She has led numerous research, demonstration, and personnel preparation projects. Dr. Horn has published numerous chapters and articles about early intervention and education and is the former editor of Young Exceptional Children. Vivian Johnson has been involved in seeking equity and since 1976 has created programs for recruiting, retaining, and improving the academic performance of women and under-represented students including those with learning differences in science, technology, engineering, and mathematics (STEM). Dr. Johnson also was High School science and computer science teacher who was the departmental liaison to the Child Study Team. Dr. Johnson is the parent of a 17-year-old girl diagnosed in 1st grade with severe dyslexia, central auditory processing deficit, and ADHA. She is a presenter on the topics of technology integration, technology-related professional development, and digital equity at local, regional, and national conferences. Kristen E. Jones is a doctoral student at the University of Texas at Austin in the field of multicultural special education with a focus in vocational rehabilitation and disability studies. She holds a M.Ed. (2006) in special education from the University of Houston. Her research interests focus on transition to adult life and post secondary education, self-determination, and assistive technology. Neha Khetrapal is currently a graduate student at the Center of Excellence “Cognitive Interaction Technology”, University of Bielefeld, Germany studying the interaction of spatial processes and language and is supported by a grant from by Deutsche Forschungsgemeinschaft (DFG) grant managed through the Graduate School of the Centre of Excellence “Cognitive Interaction Technology”. The author has been a holder of various prestigious awards and has done work on developing theoretical frameworks that have been well received both nationally and internationally. The most important recognition earned by her is from Marquis Who’s Who in the World for 2009. Carolyn Kinsell holds a PhD in Instructional Technology and a certification in Human Performance. Her career expands over 18 years in which she focused on the application of training that spans from analysis, to the development of virtual environments, to defining requirements and solutions for human performance standards; and, more recently, to research and development of training applications. She has worked closely with the military to include Cryptologists, Intelligence Specialists, Naval Diving and Salvage experts, to Foce XXI Battle Command Brigade and Below (FBCB2) Joint Capabilities

446

About the Contributors

Release (JCR). She has also supported commercial clients such as Cingular and North America Honda, to name a few. Barbara J. Kouba is an Assistive Technology Assessment & Training Specialist at California State University San Bernardino (CSUSB). She has 19 years technology training experience, the last 1 ½ years working with California Popartmont of Rehabilitation clients to narrow the digital divide. Ms. Kouba is also a co-instructor at CSUSB and utilizes her M. A. degree in Instructional Technology to effectively infuse technology into instruction to develop transformative instructional materials for all students, regardless of disabilities. James Laffey is a Professor in the School of Information Science and Learning Technologies and a former researcher and systems developer at Apple Computer, Inc. Dr. Laffey has a Ph.D. in Education from the University of Chicago and has won awards for the design of innovative, media-based computer systems. Through his design work and scholarship he is internationally recognized as an expert in the area of human-computer interaction. He currently teaches graduate level courses on development of systems to optimize HCI and learning, including methods to improve the social nature of online communities. He has received over $6 million of funding during the past 10 years, and is currently the principal investigator for grants from AutismSpeaks and the Institute of the Education Sciences to research and develop iSocial. Mary Ann Lowe is Program Professor in the Programs for Speech, Language, and Communication Disorders and Director of Academic and Faculty Support at Nova Southeastern University. She teaches courses in AAC and Language Disorders in Children. Dr Lowe earned her master’s degree in communication disorders from Florida Atlantic University, her Educational Specialist degree in Assistive Technology from the University of New Mexico and her doctorate from Nova Southeastern University. Mary Ann has presented at state, national, and international conferences on AAC topics. She is the Vice President for Professional Affairs of the United States on the Board of Directors for USSAAC as well as a member of the Steering Committee for the ASHA Division of AAC. Cindy Nankee is a RESNA certified ATP Assistive Technology Consultant. She has worked with WATI (Wisconsin Assistive Technology Initiative) and has a background as a school based Occupational Therapist. Cindy’s background has focused on learning, teaching and implementing switch technologies with an emphasis on the use of electronic switches for powered mobility and computer access while working on the Independence by Design project coordinated through WATI and Adaptive Switch Labs, Inc. Cindy has established UTLL (Universal Technology for Learning & Living) to provide consultation, professional development and implementation of assistive technology. Brian Newberry received his doctorate in Curriculum and Instruction with an emphasis in Educational Technology and communication from the University of Kansas in 2003. In addition to a successful career as a teacher, computer instructor and technology coordinator, Dr. Newberry has worked for a number of years to improve the use of technology in teaching and learning. Blessing Nma Okrigwe: I was born in 1949 in a town called Omoku in Rivers State of Nigeria. I am the first child of my parents. My childhood experience was very rewarding as my parents provided

447

About the Contributors

me with basic requirements to face the challenges of life. As luck will have it I was privileged to attend school at a time women’s education was not encouraged. My father’s motivation and encouragement propelled me in my academic pursuit. Presently, I hold PhD degree in Sociology of Education which I obtained in 1993 at the University of Port Harcourt in Nigeria. I was privileged to win a scholarship that enabled me to study abroad where I did my first and second degree. I specialized in Primary Education with a developmental course in Geography for my first degree then for my Masters I did comparative Education – all at the University of London, Institute of Education, London from 1974-1981. I have been a Lecturer at the College of Education Port Harcourt affiliate of University of Ibadan since 1982 till present. I became a Senior Lecturer in 1997 and thereafter I served one year Sabbatical Leave in a Federal College of Education 1997/1998 Session. I have held the following positions in the College – Director Remedial Studies, Head of Department for Primary Education Studies and Teaching Practice Coordinator. I have written five articles in some reputable journals, published two chapters in a book and have written five books. I am a member of four professional bodies, the most recent being Comparative Education and International Education Society. I have had the opportunity of visiting other countries like Russia, Spain, France and South Korea because of my love for traveling to acquire more empirical knowledge. I am a grandmother having married since 1972. Jeffrey Pascoe is a researcher and a member of the Curriculum Development Team at Laureate Learning Systems (Winooski, VT). Dr. Pascoe received his B.A. in Psychology from Framingham State College in Massachusetts, and his Ph.D. in Psychology from the University of Vermont, specializing in experimental psychology and neuroscience. He has coauthored a number of papers with Dr. Wilson in the area of using contemporary linguistic theory and research as a guide in developing more effective strategies for treating language disorders. Diane Plunkett serves as a Graduate Research Assistant for the Department of Special Education at the University of Kansas. Having completed her Master’s of Science in Education at the University of Kansas she is completing her doctoral coursework in special education with emphasis on early childhood intervention. She has several years experience working with young children in both public and private settings. Her research interests examine early literacy, assistive technology and bridging research to practice barriers for early childhood professionals working with young children. Carol Price, a graduate student at Hamline University, has been involved in education as a professional special education teacher, Master-Mentor Teacher, and Adjunct Professor at the University of New Orleans. Ms. Price has a long history of providing guidance, direction, and technical assistance to school, district, and state-level personnel regarding accommodations and assistive technology supports to students with disabilities and to English language learners for instruction and assessment. She is a presenter on the topics of assistive technologies, computer-based and typical large-scale assessments, federal legislation regarding the assessment of students with disabilities and English language learners, early learner literacy, and the assessment of preK children. Cinda Rachow holds degrees in the area of Child Psychology, Elementary Education and Special Education with emphasis on Learning Disabilities and Emotional / Behavioral disorders. She has been an educator for 33 years providing instruction as a General education teacher, Special education teacher for students with severe learning disabilities and behavioral/ emotional disorders. As a Special Education

448

About the Contributors

Consultant for Loess Hills Area Education Agency 13, Council Bluffs, IA, she focuses her experience on removing barriers to learning for students who struggle with reading by implementing assistive technology to support reading improvement. Her research interest is in examining the effectiveness of text-to-speech software. Matthew Schmidt is a PhD candidate in the School of Information Science and Learning Technologies at the University of Missouri. His current research interests focus on designing and implementing 3D virtual environments for individuals with autism spectrum disorders. He holds a B.A. and M.A. in German Language and Literature with an emphasis on Computer-Assisted Language Learning (CALL). He has designed and developed educational technologies and curricula for diverse disciplines including special education, second language acquisition, veterinary medicine, biological anthropology, nuclear engineering, and health physics. Matthew also serves as the project coordinator on a 3 year project funded by IES to advance methods for supporting youth with ASD to learn within 3D VLEs. Benjamin Slotznick is President, founder and principal of Point-and-Read, Inc. Dr. Slotznick is a lawyer and software developer, with broad research and interface design experience. He is the inventor of several Point-and-Read technologies (both patented and patent pending) and holds a number of other patents with respect to electronic products and interfaces for them. In a prior academic setting, he conducted laboratory studies of small-group decision-making. His recent research has focused on interfaces for screen readers, instant messaging and email software for users with cognitive and reading disabilities. In 2008, this research won a National Center for Technology Innovation grant award. For the past several years, Dr. Slotznick has presented results of this research at the following conferences: Closing the Gap, ATIA Orlando and CSUN (California State University Northridge). James R. Stachowiak is the associate director of the Iowa Center for Assistive Technology Education and Research (ICATER) in the College of Education at the University of Iowa. James has a BSE in Industrial and Operations Engineering and an MSE in Biomedical Engineering from the University of Michigan. James is a member of the Rehabilitation Engineering and Assistive Technology Society of North America (RESNA) and is a RESNA certified Assistive Technology Professional. James has also served three terms as the chair of RESNA’s Educator’s Professional Specialty Group. James has presented several presentations on providing AT training to pre-service teachers at conferences such as RESNA, Closing the Gap, ATIA, and the Technology, Reading, and Learning Diversity Conference. Janine Stichter is a Professor in the Department of Special Education and has worked with schools and students with Autism and behavioral needs for over 20 years. Dr. Stichter presents nationally and conducts research in the following areas: functional analysis, social competence and the correlation of instructional variables with in prosocial and academic behaviors. She has published over 50 peer reviewed articles and provided over 70 national presentations on her research. She currently directs or co-directs 4 federally funded grants over 4.5 million targeted at partnering with educational personnel to train educators and social competence programming in school-based contexts. Raschelle Theoharis graduated from the University of Kansas with a doctorate in Special Education. Currently, she is an assistant professor in the college of Education at Gallaudet University in Washington, DC, where she teaches undergraduate and graduate courses. The courses emphasize elementary

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About the Contributors

and early childhood instruction, specifically, curriculum, methods, and assessment. In addition, she also oversees practicum students and student teachers. Her research interest include teacher induction and mentoring programs for first-year teachers, special education teacher attrition and retention, and improving the academic and social success for students who are deaf and hard of hearing from nonEnglish speaking homes. Cynthia L. Wagner is an occupational therapist with Lifeworks. She is a member of the American Association of Multi-Sensory Environments. Her current work involves addressing sensory processing issues for children and adults with autism and developmental disabilities in the multi-sensory environments at Lifeworks. Mary Sweig Wilson is President of Laureate Learning Systems and Professor Emerita, Communication Sciences, University of Vermont. She received her B.A. from Smith College, her M.A. from Emerson College, and her Ph.D. in Communicative Disorders from Northwestern University. She has been the Principal Investigator on 12 grants from the National Institutes of Health (NIH) that supported development of Laureate’s Sterling Edition programs. She is an international presenter who has received numerous awards and honors including Fellow of the American Speech-Language-Hearing Association, Honors of the Vermont Speech-Language-Hearing Association, the TAM Leadership Award, and Emerson’s Alumni Achievement Award.

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Index

A AAC software 169 AAC users 169, 170, 171, 173, 174 ABLEDATA software 196 accelerated reader (AR) 201 adaptations 271 adaptive control of thought-rational (ACT-R) theory 301, 302, 305 advanced audio coding (AAC) 169, 170, 171, 172, 173, 174 African-American students 377, 378, 382 AlphaTalker AAC device 327 alternate assessment frameworks 160 alternate input software 366 alternative input devices 366 Americans with Disabilities Act (ADA) (1990) 177, 190, 191, 240, 342, 363, 364, 372, 373 amplification 178, 184 analysis of variance (ANOVA) 306, 307, 309 Anderson, John 301, 302, 303, 305 anger 99, 100 An Introduction to the Assistive Technology Project (lecture) 289 anthropology 389 anxiety 98, 99, 100, 102, 103, 105, 106 anxiety, selective processing in 98, 99, 106 apraxia 122 Area Education Agencies (AEA) 241, 245, 286, 287 artifacts 258, 262 Asperger’s disorder 338 Assessing Students’ Needs for Assistive Technology (ASNAT) guide 160, 162, 165, 167

assistive listening devices (ALD) 177, 178 assistive technologies (AT) 1, 4, 17, 18, 22, 44, 45, 54, 61, 62, 63, 65, 66, 67, 70, 71, 97, 98, 101, 109, 110, 114, 119, 133, 177, 178, 180, 183, 184, 192, 193, 194, 195, 196, 262, 263, 264, 265, 266, 267, 268, 269, 271, 272, 286, 287, 288, 289, 290, 291, 292, 293, 294, 295, 296, 297, 299, 300, 301, 302, 363, 364, 365, 367, 369, 371, 372, 373, 374, 375, 376, 380, 381, 382, 387 Assistive Technology Act (2004) 193 assistive technology / augmentative and alternative communication (AT/AAC) 251, 252, 253, 257, 258, 261 assistive technology professionals 159 assistive technology teams 160 associationism 18 associative systems 99 AT/AAC strategies 251 AT/AAC tools 251 AT continuum 160, 297 AT devices 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 265, 266, 271, 338 AT evaluation 265 attention 7, 13, 18, 19 attention deficit hyperactivity disorder (ADHD) 194 audiograms 191 auditory impairments 122 augmentative and alternative communication (AAC) 251, 252, 253, 257, 258, 260, 261, 325, 326, 327, 328, 329, 336, 337, 338

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Index

augmentative and alternative communication (AAC) systems 346, 357 augmentative communication tools 121, 122, 124, 125, 128, 129, 131 authentic assessment 237 autism spectrum disorders (ASD) 76, 77, 78, 92, 93, 94, 95, 97, 108, 121, 122, 124, 125, 129, 130, 131, 134, 338 automaticity 8, 11, 14, 15, 18 autonomic nervous system reaction 123 avatars 76, 79, 82, 83, 84, 85, 86, 95

B backwards fading 40 behavioral processes 98 behaviorism 5, 18, 19 between-subjects variability theory 66 bicultural area 338 boppy pillow 344, 358 Braille displays 366 Bush, Vannevar 110, 116

C CAST Strategy Tutor™ software 195 CAST UDL Book Builder™ software 195 central auditory processing deficits 194 central auditory processing disorder 122 cerebral palsy 344, 345 checklist of strengths and limitations 267 checklist of technology experiences 268 Chomsky, Noam 133, 134, 135, 139, 151, 152, 153 chunking 400 chunks 18, 302, 305 circuits, electrical 158, 161, 168 CLD backgrounds 374, 375 CLD students 374, 375, 376, 378, 380, 381, 382 closed captioning 181, 312 closed caption video 305 cochlea 178, 179, 185, 189 cochlear implants 177, 178, 179, 184, 185, 186, 189, 341 cognition 388, 400 cognitive access 218 cognitive architecture 96, 97, 103

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cognitive development 389, 390, 391, 392, 398, 400 cognitive development theory 389, 390 cognitive difficulties 97 cognitive disabilities 18, 21, 22, 193 cognitive functioning 96, 97, 98, 101 cognitive impairments 61, 62, 63, 64, 66, 67, 68, 69, 70, 71, 74, 122, 124, 158 cognitive limitations 253 cognitive load 21, 22, 23, 24, 25, 26, 27, 28, 29, 32, 33, 34, 35, 36, 38, 39, 40, 41, 114, 116, 119, cognitive load theory (CLT) 18, 22, 23, 26, 27, 28, 30, 34, 35, 36, 40, 46, 54, 58, 114, 116, 119, 301, 302, 305, 312 cognitive model of emotion 99, 107 cognitive overload 112, 113, 114, 115, 116 cognitive processes 98, 104, 105, 107, 389, 390 cognitive psychologists 390, 397 cognitive psychology 4, 5, 16, 18, 98, 389 cognitive rehabilitation 96, 97, 98, 104, 105 cognitive theory 389 cognitive theory of multimedia learning (CTML) 18, 22, 29, 32, 33, 40, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 58 cognitive views 389 communication boards 338 communication challenges 252 communication devices 158, 159 Compass Access Assessment Software 160 completion examples 40 complex transfer 67, 68 comprehensive understanding 390 computer-aided notetaking (CAN) 181 computer-based simulations 61, 62, 64, 66, 74 computers 158, 159, 160, 161, 162, 163, 167 concept mapping 400 concepts 400 concerns based adoption model (CBAM) 221, 222, 226, 228 concrete operational stage 390 conditional knowledge 18 conditioned response 393 content validity 250 contextual matching inventory 267

Index

Council for Exceptional Children (CEC) technology standards 245, 287 CoWriter:SOLO software 319, 320, 321 CTML, active processing assumption 46, 58 CTML, dual-channels assumption 46, 58 CTML, limited capacity assumption 44, 58, 59 cue 400 cultural and linguistic diversity (CLD) 325, 326, 327, 329, 333, 338, 387 curriculum-based measurement (CBM) 319, 323

D data analysis tools 220 data-based decision-making 271 deaf and hard of hearing (d/hh) students 176, 177, 178, 180, 181, 182, 183, 184, 185 Deaf community 176, 181, 182, 184, 185 deafness 134 declarative knowledge 18, 302, 305 DeltaTalker AAC device 327 DesktopChat® software 169, 171, 172, 173 desktop virtual reality (DVR) 299, 300, 301, 302, 303, 304, 305, 306, 307, 308, 310, 311, 312 determiner phrase (DP) 136, 139, 140 developmental disabilities 121, 122, 124, 126, 128, 129, 130, 131, 375 developmental psychology 389 digital divide 365, 374, 375, 376, 377, 379, 380, 381, 383, 384, 385, 386, 387 digital equity 375, 376, 382, 383, 384, 385, 387 digital portfolios 254, 262 digital text artifact matrix 222, 226 direct selection 159 disgust 99, 100 disorientation 109, 112, 113, 114, 115, 116, 117, 118, 119, diverse worked examples 35, 41 divided attention 18 Down Syndrome (DS) 122, 124, 134, 340, 349, 358 dual-coding theory 41, 44, 46, 58, 59 dynamic agents 95

Dynamic Indicators of Basic Early Literacy Skills (DIBELS) assessments 316 Dynavox AAC device 327, 336 DynaVox DV4 device 173, 174 dyslexia 194

E East, Inc. 173 echoic memory 18 ecological assessments 265, 268, 271 ecological AT assessment 265 educational programming suggestions 256 educational technology 374 effective load 25 egocentric mapping 301, 312 Einstein, Albert 393 electrocardiography (ECG) 307, 309, 310, 312 electronic portfolios 254, 255, 257, 258, 259, 260, 261, 262, 263 electronic text 169, 170, 174, 175 Elementary and Secondary Education Act (ESEA) (1965) 193 element interactivity 41 e-mail 169, 170, 171 emotional difficulties 97 emotional disorders 99, 100, 101, 108 emotional functioning 96 emotions 99, 100, 103, 107 emotions, complex 99, 100 emotions, disorders of 100 empiricism 19 employees with disabilities 299 English as a second language (ESL) 378 Enhancing Education Through Technology (ED Tech) program 377 episodic memory 19 e-portfolios 288, 291, 297 equity 376, 387 ethnic populations 327 Every Move Counts, Clicks and Chats (EMC3) assessment 160 executive control system 19 expectancy-value theory 67 experts 69, 70 expressive language skills 314 extraneous load 24, 25, 26, 41

453

Index

F face-to-face communication 170, 171 face validity 250 far transfer 41 fear 99, 100, 102, 103, 104, 106 fetal alcohol syndrome (FAS) 347 fonts 271 formal operation stage 390 free appropriate public education (FAPE) 133, 193, 197 frequency modulation (FM) systems 178, 179, 180, 184, 185 Functional Evaluation for Assistive Technology (FEAT) 264, 265, 266, 267, 269, 270

G Gates, Bill 393 general education 193 general education classrooms 133 general technological literacy 269 generative grammar theory 133, 135, 139 genetic epistemology 390 geocentric mapping 301, 312 germane load 25, 26, 34, 35, 41 global positioning system (GPS) 365, 367, 368, 369, 370, 373 grammar 133, 135, 137, 139, 142, 143, 153, 154, 155 Grays Silent Reading Test 267 growth portfolios 255

H happiness 99, 100 Hawking, Stephen 361, 362 head-directionality parameter 135 headedness principle 134, 137 heads 134, 135, 137 hearing aids 177, 178, 179, 180, 184, 185, 189, 191 hearing aids, behind-the-ear (BTE) 179, 191 hearing impairment 314 hearing loss 177, 178, 179, 180, 183, 187, 189, 190, 191 hearing loss, postlingual 178, 191 hearing loss, prelingual 178, 191

454

Higginbotham, Jeff 173, 174 highly qualified teachers 176, 177, 187 high-tech devices 358 human cognition 21, 22, 23, 35 human-computer interfaces (HCI) 97 human information processing 21, 22, 392 human memory 112, 115, 116 Hunt, Earl 301, 302, 304, 305, 312 hypermedia 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, hypermedia learning environments (HLE) 109, 111, 112, 113, 114, 115, 116 hypertext 111, 113, 117, 118, 119,

I iconic memory 19 iGroup 81, 82, 83, 84, 85, 86, 89, 90, 92, 95 image instructional principle 51, 59 IM (instant message) 169, 170, 171, 172, 174, 175 implementation 217, 219, 236, 237, Improving America’s Schools Act (IASA) (1994) 193 individualized education programs (IEP) 160, 164, 165, 192, 194, 195, 197, 199, 202, 244, 245, 266, 271, 286, 314, 340, 341, 349, 352, 358, 364 Individualized Family Service Plans (IFSP) 340, 341, 343, 344, 347, 349, 350, 351, 352, 358 Individuals with Disabilities Education Act (IDEA) 61, 158, 161, 167, 168, 240, 248, 340, 341, 342, 348, 349, 350, 352, 353, 364 Individuals with Disabilities Education Act (IDEA) (1990) 240, 244, 248 Individuals with Disabilities Education Act (IDEA) (1994) 221 Individuals with Disabilities Education Act (IDEA) (1997) 193, 197, 199 Individuals with Disabilities Education Act (IDEA) (2004) 132, 176, 177, 193, 199, 240, 313, 318, 321 individual-technology evaluation scale 269 individual-technology evaluation worksheets 269

Index

individual-technology match 269 information/educational technology (I/ET) 374, 375, 376, 377, 378, 379, 380, 381, 382 information processing approach 389, 392 information processing models 5, 19, 392 information processing roadblocks 22 innate language faculty 133 innovation configuration 221, 222 input overload 301 instructional/educational technology 387 instructional principles 48, 50, 58, 59, 60 instructional principles, animation and interactivity 51, 58 instructional principles, cognitive aging 51, 58 instructional principles, coherence 48, 58 instructional principles, collaboration 51, 58 instructional principles, guided-discovery 51, 58 instructional principles, modality 50, 59 instructional principles, multimedia 51, 59 instructional principles, navigation 52, 59 instructional scaffolding 79 instructional technology (IT) 177, 178, 180, 184, 374 insufficient training 301 intellectual disabilities 124, 125, 130 international patient aid standards (IPAS) 63 intervention 313, 315, 318, 319, 323 intrinsic load 24, 25, 26, 31, 32, 34, 41 Iowa Assistive Technology Needs Assessment 239, 241, 243, 244, 245, 246, 247 Iowa Assistive Technology Text Reader Project 201 Iowa Center for Assistive Technology Education and Research (ICATER) 243, 244, 250, 286, 287, 288, 289, 290, 291, 292, 295, 296, 297 Iowa Department of Education 201, 216, 241, 246, 248 Iowa Test of Basic Skills (ITBS) 202 Iowa Text Reader Projects 221 Iowa Text Reader Study (2005-2006) 201, 202, 212, 213, 214, 220 Iowa Text Reader Study (2006-2007) 202, 206, 220

IQ (intelligence quotient) 314, 315, 317, 318, 319, 320, 322, 323, 324, 391 irrelevant load 41 iSocial project 76, 77, 78, 79, 81, 83, 86, 87, 90, 91, 92, 93, 94, 95 iTalk 81, 86, 87, 88, 89, 90, 91, 92, 95

K King, Thomas W. 362, 365, 372 Knapp, David 301, 302, 305, 312 knowledge, comorbidity—generalization of 98 Kurzweil 3000 text-to-speech software 200, 201, 202, 203, 204, 206, 209, 211, 213, 215, 219, 222, 223, 224, 226, 232, 238, 290, 295, 296 Kurzweil, Ray 363

L lack of preparation 301 language acquisition 133, 134, 135, 137, 142, 154 language acquisition needs 133 language disorders 135, 137, 138, 139, 143, 155 language impairment 134, 150, 151, 153, 154 language intervention software 132, 133, 143, 147, 152 LanguageLinks®: Syntax Assessment & Intervention program 134, 142, 143, 144, 146, 147, 148, 149, 150, 151, 155 Latino ethnic group 376, 377, 378, 382, 387 learner-centered education 19 learners with barriers 109 learning disabilities (LD) 4, 19, 22, 31, 32, 33, 36, 45, 54, 61, 313, 314, 315, 317, 318, 320, 321, 322, 323, 324, 325, 329, 330, 331, 332, 333 learning, knowledge-based 64, 65 learning promotion 313 learning, rule-based 64, 65 learning, skill-based 64, 65 learning, transfer of 61, 62, 63, 64, 65, 67, 69, 70, 71, 72, 73, 74 least restrictive environment (LRE) 133, 193, 197 level of use interviews 221, 226, 228

455

Index

level of use survey 222 lexicon 133, 135, 136, 137, 139, 143, 144, 155, 156 Liberator VOCA AAC device 327 Lifeworks Services 121, 124, 125, 126, 128, 129 limbic systems 123 linguistic theory 132, 133, 134, 135, 137, 140, 144, 146, 151, 154, 156 Local Education Agencies (LEA) 193 long-term memory (LTM) 6, 7, 8, 9, 10, 11, 13, 14, 15, 19, 23, 26, 46, 47, 301, 305, 392 low incidence disabilities 338 low socioeconomic status (SES) students 377 low-tech devices 358

M magnification software 366 mainstream education systems 109 Matthew effect 62 meaningful learning 45, 55, 59 medical information 256 memex machine 110 mental retardation 314 mental retardation and development disabilities (MRDD) 62, 73 metacognition 12, 15, 16, 19, 393, 400 metacognitive knowledge 19 metacognitive regulation 19 Minimalist Program 134, 135, 139, 142 mnemonic devices 400 mobile assistive technology (MAT) Lab 288, 289, 290, 291, 294, 297 modality principle 29, 30, 34, 41, 115 modal model of memory 19 modularized connectionist networks 99 moebius syndrome 345, 346 Montessori, Maria 393 motor speech deficits 122 multimedia 43, 44, 45, 46, 47, 50, 51, 54, 55, 56, 57, 58, 59 multimedia learning 45, 56, 58, 59 multi-sensory environments (MSE) 121, 122, 124, 125, 126, 127, 128, 129, 131

456

N National Center for Education Statistics 192, 196 National Center for Technology Innovation (NCTI) 170, 173, 174 National Early Childhood Technical Assistance Center (NECTAC) 340, 342, 356 National Longitudinal Transition Study 2 241 Native American students 376, 378, 379, 383, 384, 386, 387 near transfer 41, 68 needs assessment 239, 241, 242, 243, 244, 245, 246, 247, 250 negative transfer 67, 68 Neo2 mini-keyboards 319 neuroscience 389 No Child Left Behind Act (NCLB) (2001) 176, 177, 187, 188, 193, 199, 221, 234, 377 non-technical pointing devices 366 Norman, Donald 77, 94 Northeast Technology Center in Oklahoma 306 novices 69

O occupational therapists 159 Office of Special Education Programs (OSEP) 342, 343, 348, 349, 354, 356 on-screen keyboards 366 optical character recognition (OCR) 269, 271, 280, 283, 366, 373 optimum learning 301, 305 orientation 301, 302, 305 orientation and wayfinding theory 301, 305, 312 outcome measures 219, 237

P parent educator connection (PEC) group 244 Parents, Let’s Unite for Kids (PLUNK) software 196 pedagogical strategy 88, 95 peer-assisted learning strategies (PALS) 316 perception 19, 400 personal information 256

Index

personalization instructional principle 51, 55, 57, 59 person-centered assessment approach 265, 266 person-technology match 265, 271 phonemic-awareness skills 314 phone-to-phone communication 171 phonological loop 19, 44, 46 physical access tools 288, 290 physical challenges 252 physical impairments 122, 131, 158 physical limitations 253 physical therapists 159 Piaget, Jean 389, 390, 391, 392, 398, 399, 400 Point-and-Chat® software 169, 170, 171, 172, 173, 174 Point-and-Read, Inc. 169, 172, 173 portfolios 251, 253, 254, 255, 256, 257, 258, 259, 260, 261, 262 positioning strategies 256 positive transfer 67 pragmatic language use 124 pragmatic skills 124 pre-operation stage 390 Prepositions! program 134, 142, 144, 146, 147, 148, 149, 150 preservice teacher education 286, 287 preservice teachers 325, 326, 332, 333, 336 pre-training instructional principle 50, 59 pre-training principle 41 prior knowledge 19 prior knowledge instructional principle 52, 59 problem-solving intervention model 317 procedural knowledge 19, 32, 41, 302, 305 process knowledge 41 production rules 302, 305 programmed learning 400 progress monitoring 219, 237 project portfolios 255 proprioception 123, 131 psycholinguistic research 133 psychological disorders 98, 105, 107 Public Law 94-142 (1975) 132, 193, 220, 240, 247

Q QuickTime virtual reality (QTVR) 302, 305, 307, 311, 312

R radical behaviorism 19 Rasmussen, Jens 64, 73 Read and Write Gold text-to-speech software 196, 200, 219, 290 reading and writing aids 288, 289, 295 reading disabilities 267 Reading Recovery intervention program 317, 321 Read Naturally software 319, 322 real time captioning (RTC) 181 real-world simulators 97 reasonable accommodation 250 receptive language skills 314 redundancy effect 114 redundancy instructional principle 48, 59 redundancy principle 31, 41 rehabilitation 96, 97, 98, 103, 104, 105, 106, 107 Rehabilitation Act Amendments 240 relay systems 191 research models 220 response to intervention (RTI) model 133, 150, 313, 315, 316, 317, 318, 319, 320, 321, 324 reticular activating system 123 RTI, problem-solving approach 324 RTI, standard-protocol approach 324 RTI, tiers of 316, 317, 318, 319, 324

S sadness 99, 100 Saltillo Corporation 169, 170, 171, 172, 173 scaffolding 79, 95, 400 scanning 271 schemata 11, 19, 69, 74, 400 Schematic, Propositional, Analogical and Associative Representational Systems (SPAARS) 99, 101, 102, 103, 107 Scherer, Marcia J. 361, 372 screen magnifying software 297

457

Index

screen readers 169, 171, 172 screen reading software 297, 365, 366 Section 504 of the Rehabilitation Act 342 segmentation instructional principle 50, 59 segmenting principle 33, 34, 41 selective attention 19 selective processing 98, 99, 106 self-explanation instructional principle 52, 59 self-help skills 347, 348 self-regulating behaviors 343 semantic memory 19 sensory challenges 121, 127 sensory impairments 122 sensory information 121 sensory integration 123, 126, 128, 130 sensory issues 131 sensory memory 6, 19 sensory motor stage 390 sensory needs 121, 122, 128 sensory registers 19, 392 sensory sensitivity 121, 123 SENSwitcher program suite 161, 167 short message service (SMS) 169, 170, 171, 175 short-term memory (STM) 6, 7, 8, 9, 14, 19, 20, 44, 122, 392 signaling instructional principle 49, 59 signaling principle 20 simple transfer 68 Simplex theory 66 site map instructional principle 52, 59 slot 20 social benefits 97 social interaction 391 social orthotics 76, 77, 78, 79, 80, 81, 82, 88, 90, 91, 92, 93, 95, social psychology 389 socio-cultural cognitive theory 389 socioeconomic status (SES) 315 spatial contiguity instructional principle 49, 59 special education 77, 110, 115, 116, 192, 193, 194, 326, 327, 329, 330, 333, 334, 336, 337, 338 special education services 61, 192, 315 special educators 133, 145 speech and language pathologists 133, 146, 159

458

speech recognition software 297 speech recognition technology 288 spell checkers 366, 367 split-attention effect 114, 116, 118 split-attention principle 28, 29, 41 Stages alternate assessment framework 160, 167 stages of concern survey 221 stenotype machines 181 sticky keys 366 structure dependence principle 134 student digital text matrix 221, 222, 223 student, environment, task, tool (SETT) framework 160, 167 student learning portfolios (SLP) 253, 256 student portfolios 254 students with disabilities 239, 240, 241, 243, 244, 247 subject-verb-object (SVO) pattern 135, 136 SuccessMaker Enterprise software 319, 323 survey strategies 220 Sweller, John 114, 115, 116, 118, 119, 301, 302, 304, 305, 311, 312 switches 157, 158, 159, 160, 161, 162, 163, 164, 166, 167, 168 switches, electronic 161 switches, fiber optic 161 switches, infra-red beam 161 switches, mechanical 161, 162 switches, mercury 161 switches, pneumatic 161 switches, proximity 161 switches, sound activated 161 switches, tilt 161 switches, wireless 161 symbol-based learning 288, 289 syntactic computational system 133, 139, 141 syntax 132, 133, 134, 137, 138, 142, 143, 144, 146, 147, 148, 149, 150, 151, 152, 154 synthesized computer voice 169 synthesized voices 170

T teacher digital text matrix 222, 223, 224 teacher educators 325, 336 team-based problem-solving 265, 266

Index

technology-centered approach 20 technology characteristics inventory 268 Technology in the Classroom course 288, 289, 295, 296 Technology-Related Assistance for Individuals with Disabilities Act (1988) 110, 119, 240, 364 Technology Related Assistance for Individuals with Disabilities Act (1992) 193, 195 telecomunications 191 telecomunications device for the deaf (TDD) 182, 191 teletype (TTY) 177, 178, 182, 188, 191 temporal contiguity instructional principle 50, 60 tense phrase (TP) 136 text messaging 169, 170, 171, 172, 173, 174, 175 text-to-speech software, implementation tools for 220 text-to-speech software (TTS) 199, 200, 201, 202, 203, 204, 206, 207, 209, 210, 211, 213, 214, 215, 216, 218, 219, , 220, 221, 222, 223, 225, 226, 228, 229, 230, 232, 237, 238 text-to-speech teacher portfolio artifacts 220 text-to-speech teacher portfolio artifacts, rubrics for 220 theoretical framework 74 threat evaluation system (TES) 98, 99 three dimensional (3D) virtual environments 76 three dimensional virtual learning environment (3D-VLE) 76, 77, 78, 79, 80, 81, 92, 93, 94, 95, time sequence differential concurrent (TSCD) model 216, 218, 219, 232, 238, Tourette syndrome 338 toys 159, 163 transdiagnostic approach 96, 98, 105, 107 transdiagnostic processes 96, 97, 98, 101, 103, 104 transfer of learning 41, 67, 72, 73, 74 transition portfolios 256, 262 traumatic brain injuries 122 triangulation 327 Tukey HSD 308, 309

U universal design 247, 250, 338 universal design for learning 177, 247, 250 universal design for learning aids 288 universal grammar 133, 134, 153, 156 University of Iowa College of Education 286, 297 University of Iowa (USA) 239, 243, 286, 287, 295, 296, 297 University of Missouri (USA) 76, 93 University of Oregon 316

V validated measures 201 validated measures, lack of 201 vestibular input 123, 131 vibrating pillow 344 virtual environments (VE) 97, 102 virtual learning environments (VLE) 78 virtual reality (VR) 96, 97, 102, 103, 104, 105, 106, 107, 301, 305, 311, 312 virtual tours 299, 303 visual access aids 288 visual environments 301 visual impairments 122, 314 visuospatial sketchpad 20, 44, 46 vocabulary 133, 142, 143, 146, 147, 148, 149, 150 Vocational Rehabilitation Amendments (1973) 363 voice instructional principle 51, 59 voice output communication aid (VOCA) 252, 257 Vygotsky, Lev 389, 390, 391, 392, 400

W Waller, David 301, 302, 304, 305, 312 wayfinding 301, 302, 304 Web accessibility 364, 373 Web-based treatments 305 wedge pillows 344 wheelchairs 159, 161, 162, 163, 165, 252 Wilson, Woodrow 393

459

Index

Wisconsin Assistive Technology Initiative (WATI) 160, 162, 163, 164, 165, 167, 168 WordQ 290 worked example-problem pairs 42 worked examples 27, 28, 35, 41, 42 worked-out example principle 52, 60 worked-out examples 41

working memory 9, 11, 20, 22, 23, 24, 25, 26, 28, 29, 30, 31, 32, 34, 35, 36, 37, 38, 39, 40, 41, 43, 44, 46, 47, 48, 50, 51, 53, 56, 58, 59, 301, 314 Wynn Scan and Read text-to-speech software 219

Z zone of proximal development (ZPD) 391

460