Policy and Practice (Advances in Learning and Behavioral Disabilities)

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POLICY AND PRACTICE

ADVANCES IN LEARNING AND BEHAVIORAL DISABILITIES Series Editors: Thomas E. Scruggs and Margo A. Mastropieri Recent Volumes: Volume 12:

Edited by Thomas E. Scruggs and Margo A. Mastropieri

Volume 13:

Edited by Thomas E. Scruggs and Margo A. Mastropieri Educational Interventions – Edited by Thomas E. Scruggs and Margo A. Mastropieri Technological Applications – Edited by Thomas E. Scruggs and Margo A. Mastropieri

Volume 14: Volume 15: Volume 16: Volume 17: Volume 18:

Volume 19:

Volume 20: Volume 21:

Identiﬁcation and Assessment – Edited by Thomas E. Scruggs and Margo A. Mastropieri Research in Secondary Schools – Edited by Thomas E. Scruggs and Margo A. Mastropieri Cognition and Learning in Diverse Settings – Edited by Thomas E. Scruggs and Margo A. Mastropieri Applications Of Research Methodology – Edited by Thomas E. Scruggs and Margo A. Mastropieri International Perspectives – Edited by Thomas E. Scruggs and Margo A. Mastropieri Personnel Preparation – Edited by Thomas E. Scruggs and Margo A. Mastropieri

ADVANCES IN LEARNING AND BEHAVIORAL DISABILITIES VOLUME 22

POLICY AND PRACTICE EDITED BY

THOMAS E. SCRUGGS George Mason University, Fairfax, USA

MARGO A. MASTROPIERI George Mason University, Fairfax, USA

United Kingdom – North America – Japan India – Malaysia – China

JAI Press is an imprint of Emerald Group Publishing Limited Howard House, Wagon Lane, Bingley BD16 1WA, UK First edition 2009 Copyright r 2009 Emerald Group Publishing Limited Reprints and permission service Contact: [email protected] No part of this book may be reproduced, stored in a retrieval system, transmitted in any form or by any means electronic, mechanical, photocopying, recording or otherwise without either the prior written permission of the publisher or a licence permitting restricted copying issued in the UK by The Copyright Licensing Agency and in the USA by The Copyright Clearance Center. No responsibility is accepted for the accuracy of information contained in the text, illustrations or advertisements. The opinions expressed in these chapters are not necessarily those of the Editor or the publisher. British Library Cataloguing in Publication Data A catalogue record for this book is available from the British Library ISBN: 978-1-84855-310-1 ISSN: 0735-004X (Series)

Awarded in recognition of Emerald’s production department’s adherence to quality systems and processes when preparing scholarly journals for print

CONTENTS LIST OF CONTRIBUTORS

vii

SPECIAL EDUCATION IN THE NEW MILLENNIUM: ACHIEVING EDUCATIONAL EQUITY FOR STUDENTS WITH LEARNING AND BEHAVIORAL DISABILITIES Margaret J. McLaughlin, Michael P. Krezmien and Mark Zablocki

1

ATTRIBUTIONS OF MALICE TO SPECIAL EDUCATION POLICY AND PRACTICE James M. Kauffman

33

RESPONSE TO INTERVENTION: A REALITY CHECK Amanda Kloo and Naomi Zigmond

67

THE NO CHILD LEFT BEHIND ACT AND HIGH SCHOOL GRADUATION FOR STUDENTS WITH AND WITHOUT DISABILITIES Wendy Morrison Cavendish

107

FUNCTIONAL BEHAVIORAL ASSESSMENT AND STUDENTS WITH EMOTIONAL/BEHAVIORAL DISORDERS: WHEN RESEARCH, POLICY, AND PRACTICE COLLIDE Maureen A. Conroy, Peter J. Alter and Terrance M. Scott

133

THE IMPACT OF POVERTY ON SPECIAL EDUCATION STUDENTS Elizabeth Halloran Tornquist, Margo A. Mastropieri, Thomas E. Scruggs, Hugh G. Berry and William D. Halloran v

169

vi

CONTENTS

INCREASING ACCESS TO HIGHER EDUCATION FOR STUDENTS WITH DISABILITIES AND STRENGTHENING THE PREPARATION OF PROFESSIONALS WHO INSTRUCT THEM: THE HIGHER EDUCATION OPPORTUNITY ACT OF 2008 Jane E. West INTERVENTION WITH STUDENTS WITH ADHD: ANALYSIS OF THE EFFECTS OF A MULTI-COMPONENT AND MULTICONTEXTUALIZED PROGRAM ON ACADEMIC AND SOCIO-EMOTIONAL ADJUSTMENT Ana Miranda, Marı´a Jesu´s Presentacio´n, Rosa Garcı´a and Rebeca Siegenthaler NONVERBAL LEARNING DISABILITIES AND ARITHMETIC PROBLEMS: THE EFFECTIVENESS OF AN EXPLICIT VERBAL INSTRUCTION MODEL Johannes E. H. Van Luit IMPLEMENTING RESPONSE TO INTERVENTION: THE SYNERGY OF BEGINNING READING INSTRUCTION AND EARLY INTERVENING SERVICES Stephanie Al Otaiba, Carol MacDonald Connor, Barbara Foorman, Luana Greulich and Jessica S. Folsom ADVANCES IN LITERACY PRACTICES FOR STUDENTS WITH EMOTIONAL AND BEHAVIORAL DISABILITIES Kelley S. Regan, Thomas E. Scruggs and Margo A. Mastropieri DESIGNING FUNCTIONAL ASSESSMENT-BASED INTERVENTIONS USING A SYSTEMATIC APPROACH: A PROMISING PRACTICE FOR SUPPORTING CHALLENGING BEHAVIOR Kathleen Lynne Lane, Allison L. Bruhn, Mary E. Crnobori and Anne Louise Sewell

189

227

265

291

317

341

LIST OF CONTRIBUTORS Stephanie Al Otaiba

College of Education and the Florida Center for Reading Research, Florida State University, Tallahassee, FL, USA

Peter J. Alter

Department of Teaching and Learning University of Louisville, Louisville, KY, USA

Hugh G. Berry

U. S. Department of Education, Washington, DC, USA

Allison L. Bruhn

Department of Special Education, Peabody College, Vanderbilt University, Nashville, TN, USA

Wendy Morrison Cavendish

Department of Teaching and Learning, University of Miami, Coral Gables, FL, USA

Carol MacDonald Connor

College of Education and the Florida Center for Reading Research, Florida State University, Tallahassee, FL, USA

Maureen A. Conroy

Department of Special Education and Disability Policy, Virginia Commonwealth University, Richmond, VA, USA

Mary E. Crnobori

Department of Special Education, Peabody College, Vanderbilt University, Nashville, TN, USA

Jessica S. Folsom

College Education and the Florida Center for Reading Research, Florida State University, Tallahassee, FL, USA

vii

viii

LIST OF CONTRIBUTORS

Barbara Foorman

College of Education and the Florida Center for Reading Research, Florida State University, Tallahassee, FL, USA

Rosa Garcı´a

Department of Developmental, Educational and Social Psychology, and Methodology, Jaume I University, Castello´n, Spain

Luana Greulich

College of Education and the Florida Center for Reading Research, Florida State University, Tallahassee, FL, USA

William D. Halloran

U. S. Department of Education, Washington, DC, USA (retired)

James M. Kauffman

Department of Curriculum, Instruction and Special Education, University of Virginia, Charlottesville, VA, USA

Amanda Kloo

Department of Instruction and Learning, University of Pittsburgh, Pittsburgh, PA, USA

Michael P. Krezmien

Amherst School of Education, University of Massachusetts, Amherst, MA, USA

Kathleen Lynne Lane

Department of Special Education, Peabody College, Vanderbilt University, Nashville, TN, USA

Margo A. Mastropieri

College of Education and Human Development, George Mason University, Fairfax, VA, USA

Margaret J. McLaughlin

Department of Special Education, University of Maryland, College Park, MD, USA

Ana Miranda

Department of Developmental and Educational Psychology, University of Valencia, Valencia, Spain

ix

List of Contributors

Marı´a Jesu´s Presentacio´n

Department of Developmental, Educational and Social Psychology, and Methodology, Jaume I University, Castello´n, Spain

Kelley S. Regan

College of Education and Human Development, George Mason University, Fairfax, VA, USA

Terrance M. Scott

Department of Teaching and Learning, University of Louisville, Louisville, KY, USA

Thomas E. Scruggs

College of Education and Human Development, George Mason University, Fairfax, VA, USA

Anne Louise Sewell

Department of Special Education, Peabody College, Vanderbilt University, Nashville, TN, USA

Rebeca Siegenthaler

Department of Developmental, Educational and Social Psychology, and Methodology, Jaume I University, Castello´n, Spain

Elizabeth Halloran Tornquist

Department of Special Education, University of Maryland, College Park, MD, USA

Johannes E. H. Van Luit

Department of Special Education, Utrecht University, Utrecht, The Netherlands

Jane E. West

American Association of Colleges for Teacher Education, Washington, DC, USA

Mark Zablocki

Department of Special Education, University of Maryland, College Park, MD, USA

Naomi Zigmond

Department of Instruction and Learning, University of Pittsburgh, Pittsburgh, PA, USA

SPECIAL EDUCATION IN THE NEW MILLENNIUM: ACHIEVING EDUCATIONAL EQUITY FOR STUDENTS WITH LEARNING AND BEHAVIORAL DISABILITIES Margaret J. McLaughlin, Michael P. Krezmien and Mark Zablocki ABSTRACT Different interpretations of what constitutes educational equity have shaped public policies and practices for students with disabilities over the past century. These differences are apparent in the clash between access to education as deﬁned in the Least Restrictive Environment (LRE), and access to more intensive educational services which smaller special education classrooms are designed to provide. This chapter examines these differences within the context of how services have historically been provided and how students have been assessed and have achieved academically. Speciﬁcally, this chapter also describes relevant literature and current data related to services and outcomes for youth with disabilities. We describe academic and behavioral interventions and strategies that have been used in different settings. We conclude by Policy and Practice Advances in Learning and Behavioral Disabilities, Volume 22, 1–31 Copyright r 2009 by Emerald Group Publishing Limited All rights of reproduction in any form reserved ISSN: 0735-004X/doi:10.1108/S0735-004X(2009)0000022003

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MARGARET J. MCLAUGHLIN ET AL.

offering recommendations for future research in developing effective interventions to help close the achievement gap and move toward true educational equity.

The continuous pursuit of equity characterizes the history of education of children with disabilities in America’s public schools. During long periods in America’s history, many children with disabilities were legally excluded from public education while others were segregated in special schools and classrooms. In addition, children with unrecognized disabilities struggled in general education classrooms, failed, and were retained in grades, until many eventually left school altogether. For those who advocated educational equity for students with disabilities, including policymakers, parents, advocates, and professionals, the struggle for equity appeared to culminate with the passage of the 1975 Education of All Handicapped Children Act (PL-94-142). This law, which created almost unprecedented protections and educational entitlements for children and youth with disabilities, held the promise of an equal opportunity for each child with a disability to receive a meaningful or at least an ‘‘appropriate’’ education. Despite the scope of the federal law, the struggle for equity did not end. While the law provided universal access to public education, some key professionals continued to deﬁne equity to mean full access to schools and classrooms in which typical children were enrolled. ‘‘Integration’’ or ‘‘inclusion’’ became synonymous with equality of opportunity. At the same time, others focused on the quality of the education students with disabilities were receiving, measured by acquisition of academic or functional skills and not where the education took place. Eventually, there was universal concern about the outcomes or ultimate post-school opportunities available to youth with disabilities. These differing interpretations of what constitutes educational ‘‘equity’’ have shaped public policies as well as the research and practices related to the education of children and youth with disabilities. However, as these students have been included in standards, assessments, and accountability policies, new interpretations of educational equity have emerged. These policies are forcing the ﬁeld of special education to grapple once again with the deﬁnition of ‘‘equity.’’ This new era of standards-driven accountability has been deﬁned through state policies as well as Title I of the Elementary and Secondary Education Act of 2001 (PL 107-110) and it may well mark the second signiﬁcant milestone in the quest for educational equity and equal opportunity for students with disabilities. However, the challenges schools are confronting

Special Education in the New Millennium

3

in implementing these new policies with these students are forcing an identity crisis within special education as public schools have been confronted with reconciling traditional special education policies, practices, and beliefs with universal standards, and high stakes assessments. Not only are there doubts about what should be happening in schools for students with disabilities, there are also doubts about whether the ﬁeld has the knowledge and tools needed to achieve the ambitious new goals of the standards movement. This chapter will focus on education equity and students with disabilities. Speciﬁcally, we will discuss the evolving interpretations of equity. We will then address what we know, and do not know, about how to educate students with behavioral and learning disabilities (LD) conforming to the new interpretations of equity.

THE SEARCH FOR EQUITY IN SPECIAL EDUCATION POLICY As noted earlier, federal special education policy was developed in response to the discrimination against students with disabilities in public education. As any student of special education knows, prior to the passage of the 1975 Federal Special Education Legislation PL 94-142 (The Education of All Handicapped Children Act of 1975), it was not unusual to have state laws that excluded children from public schools who were deemed unable to beneﬁt from education or were disruptive to the education of typical children (Ballard, Ramirez, & Weintraub, 1982; Yell, 2006). Yet, during the same period that states and school systems were denying access to public education to children and youth with some disabilities, they were also establishing special schools and classrooms for other students (Ballard et al., 1982; Franklin, 1994; Hendrick & Macmillan, 1987, 1989). The special classes, supported by both public and philanthropic funds, typically were ungraded and offered a curriculum of applied or functional vocational skills. Most of these ungraded classes and special schools were in larger cities (such as New York City, Philadelphia, Baltimore, and Los Angeles) with substantial immigrant populations and racial, ethnic, and economic diversity and enrolled predominantly non-white and/or immigrant children from poor families (Franklin; Hendrick & MacMillan). These classes did, however, serve a useful function in public schools as demonstrated by Hendrick and MacMillan’s history of New York City’s special education programs. They documented the rapid growth in the

4

MARGARET J. MCLAUGHLIN ET AL.

number of students placed in ungraded classrooms for students considered to have mental retardation, which was about ﬁve to seven times faster than the increase in general student enrollment. As a result, the superintendent of schools became very concerned about which students were being placed in these classes and implemented a classiﬁcation process that he believed could more properly identify students who had true mental retardation while preventing the placement of ‘‘normal’’ children who were not academically achieving as a result of not speaking English, culture, or poverty in the ungraded classes (Hendrick & MacMillan, 1989). Creating special classes and offering a special curriculum to ‘‘slow’’ and/or disruptive students reduced the pressure on general education classrooms. However, regardless of what these classes focused on, they offered little in the way of a standard academic curriculum. There was yet another group of students who were not considered to have mental retardation nor present major behavioral problems in the schools but who struggled academically. These students became categorized as students with speciﬁc LD in 1969 (Speece, 2008). While not ofﬁcially recognized in federal special education law until 1977 these students were deﬁned by a discrepancy between their ability (i.e., IQ) and their achievement. Unlike their peers, these students were considered to have ‘‘unexpected’’ learning difﬁculties because of their average IQ scores and often because of their social and cultural backgrounds. Thus, as the momentum began to build for the provision of equal education opportunity to students with disabilities, policymakers acknowledged that educational equity was not solely about providing access to a school. Also to be considered was what was to happen to the student in that school.

INTERPRETATIONS OF EQUITY IN SPECIAL EDUCATION LAW The 1975 legislation established the right of each eligible child with a disability to a ‘‘free and appropriate public education’’ (FAPE) (PL 94-142 Sec. 3(b)). This became and remains the standard of what constitutes educational equity for students with disabilities. The Individuals with Disabilities Education Act (IDEA) regulations deﬁne ‘‘appropriate’’ as special education and related services that have been speciﬁcally designed to meet a student’s individual needs that will enable the student to beneﬁt from public education as determined by a multi-disciplinary professional team in full cooperation with the

Special Education in the New Millennium

5

child’s parent or guardian. The Individualized Educational Program (IEP) represents FAPE for an individual child.

LRE and Equity The Least Restrictive Environment (LRE) provision within the IDEA requires that ‘‘to the maximum extent appropriate, children with disabilities, including children in public or private institutions or other care facilities, are educated with children who are not disabled, and special classes, separate schooling, or other removal of children with disabilities from the regular educational environment occurs only when the nature or severity of the disability of a child is such that education in regular classes with the use of supplementary aids and services cannot be achieved satisfactorily’’ (IDEA, 1997, 20 U.S.C. y1400). The IDEA states a preference for educating students with disabilities in general education classrooms and schools, but recognizes that placement in more restrictive settings may be necessary for some children for them to receive some beneﬁt from their education program. Equal access is therefore deﬁned by the acquisition of some knowledge or skill and not solely as access to the same place or same experiences as non-disabled students. Yet, this interpretation has not been without controversy for LRE is a core principle of all disability policy: individuals with disabilities should have an equal opportunity to participate in all aspects of daily life in the same way as non-disabled individuals (Gilhool, 1989; Silverstein, 2000). Advocates for full inclusion view the segregation of children with disabilities as no different from their segregation on the basis of race or other characteristics (Harry & Smith-Lewis, 1992). Segregation denies students an equal educational opportunity, deﬁned in large part as same experiences and contexts. When it comes to the LRE principle, equity can be deﬁned both horizontally, in terms of equal access to the same schools and classrooms as non-disabled students, and vertically, meaning that an individual student receives educational supports and services in the setting that allows him to beneﬁt from his education. These interpretations of equity are not mutually exclusive; however, they are ambiguous in practice. Considerations of horizontal and vertical equity are also the starting place for much of the tension that exists between special education policy and practice and the contemporary educational reform models of standards-driven accountability and choice. To explore these tensions further, it is probably a good idea to review the concept of educational beneﬁt.

6

MARGARET J. MCLAUGHLIN ET AL.

Educational Beneﬁt and Equity The notion of educational ‘‘beneﬁt’’ is central to interpreting what constitutes an ‘‘appropriate’’ education for an individual student. The prevailing legal standard for determining an appropriate education comes from the very ﬁrst US Supreme Court case to consider IDEA and its provisions Board of Education v. Rowley (1982). The decision in this case established the precedent that the federal statute was not intended to maximize the potential of a student served under the law. Instead, the Court determined that the statute was intended to provide access to education that would allow the student to ‘‘beneﬁt’’ from educational programs and services (Pullin, 2008; Yell, 2006). The Court further established the importance of developing an educational program according to the procedures and timelines established in the federal statute and state regulations. This is generally interpreted to mean that an educational program should be tailored to an individual student’s needs and goals according to the procedures established for developing IEPs. Subsequent to the Rowley decision, lower federal court cases have further established that the educational beneﬁt due to students with disabilities must be ‘‘more than trivial’’ (Polk v. Central Susquehanna Intermediate Unit 16, 1988). These legal decisions have deﬁned equity in terms of an individual student’s access to equal treatment deﬁned through procedures to be deﬁned on a case-by-case basis. The dilemma has been how to deﬁne beneﬁt. By which standard do we determine that we have sufﬁcient beneﬁt to have met the appropriate standard? The lack of clear standards beyond the procedural standards established in law often creates a situation in which IEP team decisions default to parental preference or professional judgments about beneﬁt. Sometimes these interpretations can result in disputes between parents and professionals. More often, they create a general sense of unease and tension in schools. Despite the lack of a clear target or standard by which to deﬁne educational equity, there are some data that may be examined to assess the differing perspectives of equity.

Where Has Equity Been Achieved? One way to measure educational equity for students with disabilities is to examine the degree to which such students are receiving education in regular schools and classrooms. Table 1 shows the percentage distribution of special education students nationally by the educational environment from 1989 to

7

Special Education in the New Millennium

Table 1. Percentage Distribution of Students with Disabilities 6–21 Years Old Receiving Education Services by Educational Setting: All Students with Disabilities from 1989 to 2005. Year Regular School, Outside Separate General Class Public School Facility Less 21–60% More than than 21% 60% 1989 1990 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005

31.7 33.1 44.8 45.7 46.1 46.8 46.0 45.9 46.5 48.2 48.2 49.9 51.9 54.2

37.5 36.4 28.5 28.5 28.3 28.8 29.9 29.8 29.8 28.5 28.7 27.7 26.5 25.1

24.9 25.0 22.4 21.5 21.4 20.4 20.0 20.3 19.5 19.2 19.0 18.5 17.6 16.7

3.2 2.9 2.0 2.1 2.0 1.8 1.8 1.9 1.9 1.7 1.7 1.7 1.8 1.8

Separate Private School Facility

1.3 1.3 1.0 1.0 1.0 1.0 1.1 1.0 1.1 1.2 1.2 1.1 1.2 1.2

Public Private Homebound/ Residential Residential Hospital Facility Facility Placement

0.7 0.6 0.5 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.3 0.3 0.3 0.3

0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.4 0.4 0.4 0.3 0.3

0.6 0.5 0.6 0.5 0.5 0.5 0.5 0.5 0.5 0.4 0.5 0.5 0.4 0.5

Notes: Data are for the 50 United States, the District of Columbia, and the Bureau of Indian Affairs schools taken on the child count date of the last Friday in October or December 1. Data by disability status are only reported for 6- to 21-year-old students. Detail may not sum to totals because of rounding. Source: U.S. Department of Education, Ofﬁce of Special Education Programs, Individuals with Disabilities Education Act (IDEA) database. Retrieved on August 2008.

2005 as reported by The US Department of Education Ofﬁce of Special Education Programs. As the table shows, the percentage of special education students who receive instruction in a regular school outside the general education setting less than 21% of the time has increased over the 14-year period. Accordingly, the percentages of students who receive education in a regular school outside the general class for 21–60% and more than 60% have decreased as have the percentages of students educated in separate public school facilities and public residential facilities. However, the percentages educated in separate private school facilities, private residential facilities, and homebound hospital placements have remained relatively stable over this period.

8

MARGARET J. MCLAUGHLIN ET AL.

Table 2 shows 2005 data from the same report, but the data have been disaggregated by disability categories. The percentages of students who receive education in regular schools outside the general class less than 21% of the time vary by disability category. For instance, nearly all of the students with speech or language impairments are educated in this environment compared to students with mental retardation, multiple disabilities, and deafness–blindness who seldom receive their education in this setting. Further, while only 4% of the total population of students with disabilities are educated outside the regular schools, the percentages vary greatly by disability category. Depending on one’s perspective of horizontal or vertical equity, the LRE data may suggest that students are given access to settings that afford them a full and equal education opportunity. Conversely, they can also substantiate signiﬁcant inequities in the education of children with some disabilities. If one views placement in more segregated settings as an indications of greater inequity, then those students identiﬁed as having deafness–blindness, a multiple disability, emotional disturbance, hearing impairments, or autism are being denied equal opportunities. The LRE data by themselves do not adequately address questions about vertical equity. Arguments for full access to the same (horizontal equity) setting (i.e., general education classrooms) also argue for full access to the speciﬁc services and supports needed for the student to receive educational beneﬁt (vertical equity). The question becomes one of deﬁning beneﬁt. A general education classroom or a regular school cannot provide the intensity or type of services needed by some students. For instance, it may be impossible to provide an adolescent with severe schizophrenia the necessary level of support of behavioral or mental health experts in a typical high school. Similarly, there may be a substantial proportion of students with deafness–blindness who are best served in separate schools with programs speciﬁcally designed to meet their unique needs. One cannot judge how equitable these settings are without considering how to deﬁne what educational beneﬁt means for these students.

EDUCATIONAL OUTCOMES AND EDUCATIONAL BENEFIT Obviously, educational beneﬁt is an important construct in special education policy. Another way to understand beneﬁt and to assess

25.1 33.7

6.2

29.1 21.6 16.9 18.3 18.1 28.0

15.2 18.2 15.1 27.5 23.4

88.7

14.1 34.7 13.3 48.8 49.5 56.0

58.2 31.4 22.8 40.0 59.5

21–60%

54.2 54.5

Less than 21%

14.2 39.8 33.6 24.5 15.8

50.2 26.8 45.1 19.5 25.7 12.8

4.6

16.7 10.9

More than 60%

Regular School, Outside General Class

4.1 5.1 10.1 2.8 0.7

4.6 6.9 12.2 4.8 4.1 0.8

0.1

1.8 0.3

Separate Public School Facility

1.6 4.4 7.3 3.0 0.3

1.0 5.7 8.0 2.3 0.8 0.8

0.3

1.2 0.3

Separate Private School Facility

5.4 0.1 6.6 0.2 0.1

#

0.7 0.6 3.2 0.5

0.3 1.8 1.3 0.4 0.1 0.2

#

#

0.2 1.2 0.9 5.8 0.1 0.1

0.3 0.1

Private Residential Facility

0.3 0.1

Public Residential Facility

0.6 0.4 1.4 1.5 0.2

0.5 1.3 2.3 0.2 1.6 1.3

0.1

0.5 0.2

Homebound/ Hospital Placement

12.4 10.7 28.5 8.0 1.3

6.7 16.8 24.6 13.5 6.8 3.2

0.5

4.0 1.0

Total Out of Regular School

a

Rounds to zero. Other health impairments include having limited strength, vitality, or alertness due to chronic or acute health problems such as a heart condition, tuberculosis, rheumatic fever, nephritis, asthma, sickle cell anemia, hemophilia, epilepsy, lead poisoning, leukemia, or diabetes. Notes: Data are for the 50 United States, the District of Columbia, and the Bureau of Indian Affairs schools taken on the child count date of the last Friday in October or December 1. Data by disability status are only reported for 6- to 21-year-old students. Detail may not sum to totals because of rounding. Source: U.S. Department of Education, Ofﬁce of Special Education Programs, Individuals with Disabilities Education Act (IDEA) database. Retrieved on August 2008.

#

All disabilities Speciﬁc learning disabilities Speech or language impairments Mental retardation Emotional disturbance Multiple disabilities Hearing impairments Orthopedic impairments Other health impairmentsa Visual impairments Autism Deaf-blindness Traumatic brain injury Developmental delay

Type of Disability

Table 2. Percentage Distribution of Students with Disabilities 6–21 Years Old Receiving Education Services by Educational Setting. All Students with Disabilities Disaggregated by Disability Category: 2005. Special Education in the New Millennium 9

10

MARGARET J. MCLAUGHLIN ET AL.

educational equity is to examine the educational outcomes of students with disabilities, including their performance on standardized measures of achievement. Until recently, very little was known about the aggregate academic performance or other educational outcomes of students with disabilities. These students were routinely exempted from the National Assessment of Educational Progress (NAEP) as well as state and local assessments unless they were able to participate without accommodations. Moreover, when these students did participate, their scores were often excluded from assessment reports or were not disaggregated (McLaughlin & Thurlow, 2003). Consistent with the reasoning that assessments and accountability beneﬁted students, the lack of access to the assessments and/or to accountability constituted a denial of an equal opportunity of this educational beneﬁt. Thus, since the mid-1990s, speciﬁcally since the 1997 reauthorization of IDEA, students with disabilities must be included in state and local assessments with appropriate accommodations and their results must be reported both as part of overall student performance as well as disaggregated. Requirements for mandatory participation in assessments and reporting became even more explicit in the Elementary and Secondary Education Act (ESEA) and the 2004 IDEA amendments. Now performance on standardized assessments can provide a way to examine educational equity for students with disabilities. Assessment results can be compared to those of students without disabilities. This comparative perspective is a new way to consider equity. The achievement gap between students with and without disabilities provides a benchmark for considering vertical equity. The achievement gap, in test scores, graduation rates, and similar educational indicators, has become the metric for determining educational inequities between and among groups of students including males and females, those from different racial and ethnic groups and high and low poverty schools. Closing the achievement gap has been and remains a central goal of K-12 educational policies in the United States and has deﬁned Title I of the ESEA. This concept of equity is, however, unique within special education policy. Beginning in 1998, students with disabilities were permitted to have accommodations on the National Assessment of Education Progress (NAEP) and their scores were disaggregated. As a result, one source of data regarding the academic performance of students with disabilities compared to their peers is the NAEP scores. Another source is the state reports on assessment results submitted to the U.S. Department of Education. Additional data on both the academic and functional performance of students receiving special

Special Education in the New Millennium

11

education as well as data related to other outcomes such as graduation and dropout rates are available from several nationally representative, longitudinal studies as well as state reports.

NAEP In 1996, NAEP began efforts to study the effect of assessment accommodations on NAEP results, and initiated a transition in which NAEP ofﬁcial reporting samples would come to include students assessed with accommodations. The NAEP national samples in science and mathematics assessments were split between settings in which testing accommodations were not allowed and settings in which they were. This enabled the program to maintain data trends of the past, to study the effects of providing assessment accommodations, and to begin new trend baselines in which accommodations were allowed. NAEP’s guidelines to schools for determining which students should participate in the assessment were also revised. Beginning with the 2002 assessments, NAEP has offered accommodations to all students who need them which has increased the numbers of students with disabilities included in NAEP testing. As an example, in the most recent 2006 Civics test between 10–13% of the 4th, 8th, and 12th grade samples were identiﬁed as students with disabilities and also between 2 and 3% of these students were not tested because the students required accommodations that NAEP did not permit (http://nces.ed.gov/ nationsreportcard/about/inclusion.asp#history). Figs. 1–6 display the assessment data from the NAEP data viewer. The data were retrieved from the NAEP website (http://nces.ed.gov/nationsreportcard/nde/) and transferred into an Excel database to create the ﬁgures presented in this chapter. As indicated by these data, mean outcomes in reading for students with disabilities were signiﬁcantly lower than those for students without disabilities at 4th, 8th, and 12th grades. However, the reading data indicate that 4th grade students with disabilities had a higher average score and a higher percentage scoring at or above Proﬁcient in 2007 than in any of the previous year’s data. Eighthgrade students with disabilities had a higher average score in 2007 than in 2003. The percent of 12th grade students with disabilities scoring at or above Proﬁcient was lower than for 8th graders who were lower than 4th grade students. Additionally, the disparity between students with and without disabilities was greater in the 12th and 8th grades than in the 4th grade.

MARGARET J. MCLAUGHLIN ET AL. Students with No Disabilities

12

At or Above Proficiency

Below Proficiency

1998 2000 2002 2003

Students with Disabilities

2005

100%

2007

80%

60%

40%

20%

0

20%

40%

Fig. 1. Percentages of 4th Grade Students with and without Disabilities at or above Proﬁciency and below Proﬁciency for Reading: 1998, 2000, 2002, 2003, 2005, and 2007.

The trends for the students with disabilities in mathematics were similar to those in reading, although there appeared to be greater increases in the percentage of students scoring at or above basic for 4th grade and 8th grade students in mathematics than in reading (Figs. 4–6). Students with disabilities had a higher average score and a higher percentage performing at or above Proﬁcient in 2005 than in any previous assessment year at grades 4, 8, and 12. However, less than 10% of 8th grade and 12th grade students with disabilities were at or above Proﬁcient in 2005. It is important to note that the NAEP 12th grade mathematics assessment was updated in 2005, and the difference in the assessment should be considered in making comparisons. Similar to reading, mean outcomes in mathematics for students with disabilities in each year were signiﬁcantly lower than mean outcomes for students without disabilities. One important caution in interpreting the meaning of these trends across grades is the changing population of students who receive special education across the age ranges. For example, in examining the relationship between mobility and academic achievement within one state, Ysseldyke and Bielinski (2002) found that the achievement scores of students who exited

13

Students with No Disabilities

Special Education in the New Millennium

At or Above Proficiency

Below Proficiency

1998 2002

Students with Disabilities

2003

100%

2005 2007

80%

60%

40%

20%

0

20%

40%

Fig. 2. Percentages of 8th Grade Students with and without Disabilities at or above Proﬁciency and below Proﬁciency for Reading: 1998, 2002, 2003, 2005, and 2007.

special education were roughly 0.50 standard deviations higher than those who remained in special education. In contrast, the achievement scores of students who entered special education averaged 0.75 standard deviations below those who exited special education. This movement of students in and out of special education results in unstable groups from year to year. Moreover, the relationship of this movement to academic achievement leads to a subgroup of increasingly lower-achieving students.

State NCLB Assessments It is difﬁcult to draw any deﬁnitive conclusions about the overall performance of students with disabilities on state assessments due to the variation among state standards, tests, and accommodation policies. However, states are required under IDEA to report annually to the US Department of Education information on a variety of indicators, including assessment participation and performance results for state assessments (IDEA, 2007, 34 CFR, y300.160 (f )(4)(5)).

MARGARET J. MCLAUGHLIN ET AL.

14

Students with No Disabilities

Below Proficiency

At or Above Proficiency

Students with Disabilities

1998 2002 2005

100%

Fig. 3.

80%

60%

40%

20%

0

20%

40%

Percentages of 12th Grade Students with and without disabilities at or above Proﬁciency and below Proﬁciency for Reading: 1998, 2002, and 2005.

The 2003/2004 and 2005/2006 state assessment data submitted by states were summarized by the National Center on Educational Outcomes (NCEO) using a common approach to construct numerators and denominators for determining percentages (Thurlow, Altman, Cuthbert, & Moen, 2007). Under No Child Left Behind (NCLB), each state is required to establish, at a minimum, three performance levels, basic, proﬁcient, and advanced, for the state assessments. However, some states report ﬁve levels (e.g., below basic, basic, proﬁcient, advanced, and very advanced). The data, as reported to NCEO, include the numbers of students with disabilities tested at the percentage scoring at each of the states performance levels. The individual state data for years were retrieved from the NCEO website and were entered into an Excel database. The data from each state were collapsed into two categories: Proﬁcient and Non-Proﬁcient, and were then aggregated at the national level. Figs. 7 and 8 display the percentages of students with disabilities at the proﬁcient and non-proﬁcient levels as reported by the states. This includes all students taking regular assessments

15

Students with No Disabilities

Special Education in the New Millennium

Below Proficiency

At or Above Proficiency

1996

Students with Disabilities

2000 2003 2005 2007

100%

80%

60%

40%

20%

0

20%

40%

Fig. 4. Percentages of 4th Grade Students with and without Disabilities at or above Proﬁciency and below Proﬁciency for Mathematics: 1996, 2000, 2003, 2005, and 2007.

with and without accommodations. In general, approximately 61–65% of students with IEPs used accommodations on the regular assessment. Fig. 7 displays the percentages of special education students at Proﬁcient and Non-Proﬁcient levels on state reading assessments as reported by the NCEO. In the 3rd grade, less than 40% of the students scored in the Proﬁcient range, with some variability across the years. There is a decreasing trend in the percentage of students at the Proﬁcient level as grade level increases, although the percentage of 12th grade students at the Proﬁcient level is slightly higher than thatof 8th grade students at or above the Proﬁcient level for each of the three years reported. Fig. 8 displays the percentages of special education students at Proﬁcient and Non-Proﬁcient levels on state mathematics assessments as reported by the NCEO. At the 3rd grade level, a greater percentage of the special education students scored at the Proﬁcient level than on the reading assessment, with more than 40% achieving proﬁciency in 2003–2004 and in 2005–2006. However, the decreasing trend as grade level increases is greater for the mathematics assessment than for the reading assessment. On the 8th grade assessment less than 20% of the students scored at the Proﬁcient level for two of the three years, including 2005–2006.

MARGARET J. MCLAUGHLIN ET AL.

16

Students with No Disabilities

Below Proficiency

At or Above Proficiency

1996 2000 2003

Students with Disabilities

2005

100%

2007

80%

60%

40%

20%

0

20%

40%

Fig. 5. Percentages of 8th Grade Students with and without Disabilities at or above Proﬁciency and below Proﬁciency for Mathematics: 1996, 2000, 2003, 2005, and 2007.

Graduation Rates and Post-Secondary Outcomes Compared to the relatively new focus on improving the achievement levels of students with disabilities on state and national assessments, increasing graduation rates and improving post-secondary outcomes has been a key policy goal in special education for some time. The IDEA requires states to set targets for increasing graduation rates and decreasing dropouts among students with disabilities. Graduation rates. Data obtained from the Ofﬁce of Special Education Programs website showed slightly over half of all students with disabilities graduated with a diploma in 2006/2007. Fig. 9 presents the annual percentage of students’ aged 14–21 who ﬁnished high school or dropped out over the past decade. The data presented earlier suggests that states are making real progress in reducing dropouts and increasing graduation rates; however, interpretations of these are complicated by the variability across states in terms of their

17

Students with No Disabilities

Special Education in the New Millennium At or Above Proficiency

Below Proficiency

1996 Students with Disabilities

2000 2005

100%

80%

60%

40%

20%

0

20%

40%

Fig. 6. Percentages of 12th Grade Students with and without Disabilities at or above Proﬁciency and below Proﬁciency for Mathematics: 1996, 2000, and 2005.

graduation requirements for students with and without disabilities. Additionally, the dropout rates can be calculated using multiple computational approaches, and the accuracy of these rates should be carefully scrutinized. Post-secondary outcomes. The post-school outcomes, particularly rates of employment, have been scrutinized for some time in special education. In fact, the ﬁrst nationally representative study of students with disabilities, the National Longitudinal Transition Study (NLTS), was conducted in the mid-1980s and focused on the transition from high school to post-school life (Wagner, Blackorby, Cameto, Hebbeler, & Newman, 1993). The National Longitudinal Transition Study2, (NLTS2) which began in 2001 builds on and expands the previous study and provides information on post-school outcomes. For instance, the ﬁrst post-school data from the NLTS were collected in 2003 from the ﬁrst group of students within the NLTS2 sample who had left secondary school. These students represented 28% of the original sample (Wagner, Newman, Cameto, Garza, & Levine, 2005).

MARGARET J. MCLAUGHLIN ET AL.

18 Non-Proficient

Proficient

Grade 3 Grade 4

Grade 5

2002-2003 2003-2004

Grade 6

2005-2006

Grade 7

Grade 8 High School 100%

80%

60%

40%

20%

0%

20%

40%

60%

Fig. 7. Percentages of Special Educations Students at Proﬁcient and Non-Proﬁcient Levels on State Reading Assessments as Reported by the NCEO: 2002–2003, 2003–2004, and 2005–2006.

The NLTS2 found that about 28% of this subsample had left school without receiving a diploma and that dropout rates were highest (44%) among youth with educational disabilities (ED). At the ﬁrst follow-up, 8 in 10 of the youth with disabilities were enrolled in post-secondary education, employed, or receiving training for employment. About 40% of the youth were employed at the time of the ﬁrst follow-up, which was substantially below the 63% employment rate among students without disabilities in the same age group. About 3 in 10 of the youth had enrolled in at least one postsecondary class, about 9% of the group had attended a 4-year college, 10% had attended two-year community colleges, and about 5% of the subsample was attending vocational, business, or technical schools. About 40% of the sample was working full-time and among this group about 40% was earning more than $7.00 per hour. However, only a third of all those employed were receiving any beneﬁts with their employment. Further, about 1 in 10 reported participating in some type of government beneﬁt program, such as vocational rehabilitation. Two years after high school, 16% of the students reported having spent at least one night in jail; 3 in 10 had been arrested at

19

Special Education in the New Millennium Non-Proficient

Proficient

Grade 3 Grade 4 Grade 5

2002-2003 2003-2004

Grade 6

2005-2006

Grade 7 Grade 8 High School 100%

80%

60%

40%

20%

0%

20%

40%

60%

Fig. 8. Percentages of Special Educations Students at Proﬁcient and Non-Proﬁcient Levels on State Reading Assessments as Reported by the NCEO: 2002–2003, 2003–2004, and 2005–2006.

100% 90% 80% 70%

Dropped out

60% Received a certificate

50% 40%

Graduated with a diploma

30% 20% 10%

3 20 04 -0 5

-0 20 02

-9 9 20 00 -0 1

19 98

19

96 -9 7

0%

Fig. 9. Percentages of Exiting Students, Ages 14–21, who Graduated, Received a Certiﬁcate, or Dropped out: 1996–2006. Source: Calculated from https://www. ideadata.org/tables30th/ar_4-3.xls. Retrieved on December 3, 2007.

20

MARGARET J. MCLAUGHLIN ET AL.

least once (a rate similar to that of youth in the general population); and 1 in 5 was on probation or parole (Wagner et al., 2005). The percentage of students with LD enrolling in two-year colleges has increased from 3% in 1987 to 23% in 2003. Though students with ED have improved on fewer post-school outcomes, the data show progress in the areas of completing high school, enrolling in two-year college, and earning more than the minimum wage. For instance, the percentage of students with ED who had completed high school has increased from 39% in 1987 to 56% in 2003. Obviously, the post-school outcomes varied by the type of disability as well as by whether the student had received a high school diploma. For instance, dropouts were far less likely to be engaged in post-school work or education and were 10 times more likely than students with disabilities who had ﬁnished high school to have been arrested. Among all categories, students with ED were most likely to have dropped out; less likely to live with parents; more likely to have a child; and most likely (58%) to have been arrested at least once. Youths with mental retardation were least likely to have graduated with a diploma and had the lowest employment rates among all disability categories. In contrast, over 90% of the students with visual or hearing impairments received a regular diploma and were twice as likely to have enrolled in some type of post-secondary school (Wagner et al., 2005).

Summary of Educational Outcomes and Academic Performance The NAEP results as well as the state reported data and the ﬁndings from the NLTS2 study point to inequities in outcomes among students with disabilities. That is, the students receiving special education consistently perform more poorly in both mathematics and reading than their peers without disabilities. Further, the disparity appears to increase as students move into middle school and high school. According to the NAEP reports, 4th grade reading outcomes for students with disabilities improved from 1998 to 2005, but similar improvements were not observed at 8th grade or 12th grade. At 12th grade, 72% of the students with disabilities scored below the basic level in reading, three times the percentage of students without disabilities. The data from the NCEO reports are consistent, with less than 30% of the 8th or 12th grade students achieving proﬁciency in reading. The outcomes in mathematics are somewhat better at the early grades, but less than 10% of 8th grade and 12th grade students with disabilities scored at or above Proﬁciency on the NAEP assessments. This trend was also observed in the NCEO data which showed that only about

Special Education in the New Millennium

21

20% of 8th graders and 12th graders were at the Proﬁcient level, less than half the percentage at 3rd grade. The data from the NLTS2 show some progress being made in both increasing graduation and post-school outcomes such as employment and enrollment in post-secondary education or training (Wagner et al., 2005). However, most of the progress can be attributed to students with LD, visual impairments, and hearing impairments in the areas of completing high school, enrolling in post-secondary education (including both two-year and four-year colleges), having worked for pay since leaving high school, and having participated in post-secondary education and paid employment since leaving high school. A number of factors likely affect the academic performance of students with disabilities including the characteristics and disabilities of the student, instructional setting, the type and amount of academic and behavioral support, and the qualiﬁcations of the professionals who provide special education and related services. These are not independent considerations because individual student characteristics and learning needs should determine to some extent the educational experiences of the students. For instance, the NLTS2 documented the taking of courses among secondary students with disabilities and found that, on average, over half (59%) of the courses students with disabilities took in a given semester were academic (Wagner, Newman, Cameto, Levine, & Marder, 2003). However, 60% of the students received this academic instruction in special education classrooms and another 25% were enrolled in below grade level mathematics courses and 16% were in below grade-level language arts classes. These percentages do differ by disability type. For instance, 94% secondary students with LD take at least one class in a general education setting, and 80% take one or more courses; however, these students are equally likely to take language arts courses in general education and special education settings. Mathematics is more likely to be taken in general education settings (62% vs. 43%), as are science (74% vs. 29%), social studies (71% vs. 32%), and foreign languages (90% vs. 9%) courses (Newman, 2006). It is difﬁcult to know what to make of all these data. Should we expect to close the achievement gap in reading and mathematics and if so by how much? Should we accept the diversity in educational settings and the taking of courses as a response to the need for vertical equity? These are difﬁcult and uncomfortable questions and call for new perspectives on how we think about the special education policy and research. For instance, having access to a range of course options could be seen as providing equal opportunity.

22

MARGARET J. MCLAUGHLIN ET AL.

However, if equity is viewed in terms of an outcome and not access, would this curriculum organization still be valued? An interesting recent research study (Wilson, 2008) examined the effect of having a broad or more constricted array of mathematics courses on the mathematics achievement of secondary students with IEPs. This study which utilized data from the nationally representative 2002 Educational Longitudinal Study (ELS:02) found that after controlling for student and school-level race and socioeconomic status, mathematics achievement among 12th grade students with IEPs was higher for those students who attended high schools with a restricted curriculum (only offering higher level mathematics courses) than for those students attending schools that had a broad mathematics curriculum including basic mathematics and business mathematics courses. These questions and others like them lead us to question just how well equipped we are to understand and achieve education equity for students with disabilities.

EQUITY AND SPECIAL EDUCATION RESEARCH Achieving equity in educational attainment for students with disabilities depends heavily on the capacity of schools and school systems to implement empirically validated interventions. The question is, does the special education research support this goal? In order to better understand the depth and breadth of the special education research base as it relates to the conception of equity as access to equal outcomes, we reviewed the metaanalyses and comprehensive literature reviews of research in the areas of reading, mathematics, and social and behavioral adjustment for students with high incidence disabilities (i.e., LD, emotional and behavioral disorders, and attention deﬁcit disorders). Speciﬁcally, we utilized several search strategies which included electronic searches of the National Dissemination Center for Children with Disability’s (NICHCY) Research Center1 (http://research.nichcy.org/search.asp); the US Department of Education’s What Works Clearinghouse (http://ies.ed.gov/ncee/wwc/); Academic SearchPremier; the Educational Resources Information Center (ERIC); the SocIndex; and the PsychINFO electronic databases. We limited the search to meta- analyses, syntheses, and literature reviews pertaining to the education of students with disabilities. In each search we used either the term ‘‘special education’’ or ‘‘disability.’’ In each search we also used the term ‘‘meta’’ or the term ‘‘meta-analysis’’ or the term ‘‘meta analysis,’’ or

Special Education in the New Millennium

23

the term ‘‘literature review.’’ Finally, in each search we used one of the following terms: ‘‘interventions,’’ ‘‘reading,’’ ‘‘literacy,’’ ‘‘ﬂuency,’’ ‘‘decoding,’’ ‘‘mathematics,’’ ‘‘math,’’ ‘‘behavior,’’ ‘‘social skills,’’ ‘‘behavior disorder,’’ ‘‘CBT,’’ ‘‘CBI,’’ ‘‘cognitive behavior therapy,’’ ‘‘ADHD,’’ ‘‘ADD,’’ ‘‘LD,’’ or ‘‘learning disability.’’ Each combination of terms was used. We also chose to limit the search to elementary, middle, and secondary levels (see McLaughlin, Krezmien, Zablocki, & Micelli, 2007). Table 3 presents the syntheses and meta-analyses that we identiﬁed and reviewed. While this review was not intended to be exhaustive, it was conducted to determine what research was available to inform equity. We concluded from our review that special education research has resulted in the development of several powerful interventions in literacy acquisition and early mathematics instruction, most of which has focused on primary and elementary grades. Similarly, we identiﬁed a strong research base in the area of social and behavioral adjustment, including some emergent research related to schoolwide interventions and large-scale implementation of interventions. However, there were also substantial gaps in the knowledge base.

Academic Interventions In both reading and mathematics, the outcome measures used in the studies were predominately discrete skills such as phonemic analysis, oral reading ﬂuency, comprehension, or mathematics computation or simple problemsolving strategies. Most of the academic interventions research has been conducted with relatively small samples of students with LD/low achievement and there have been limited investigations of the interventions applied in natural or typical classroom settings. The studies had strong internal validity and moderate-to-strong effect sizes, but there were substantial omissions in the literature. Few studies addressed students with emotional and behavioral disorders or secondary students with disabilities. There were few investigations of interventions designed to teach secondary content (e.g., Algebra I or II, English, Social Studies, or Science) to students with disabilities, and a limited number of studies investigating reading or mathematics interventions at the secondary level. In short, the research in the two most important academic content areas seems insufﬁcient to address the challenge of helping students with disabilities meet or progress toward rigorous academic standards.

Lane (2004)

National Dissemination Center for Children with Disabilities (NICHCY) (2007a, 2007b, 2007c, 2007d) National Dissemination Center for Children with Disabilities (NICHCY) (2007a, 2007b, 2007c, 2007d) National Dissemination Center for Children with Disabilities (NICHCY) (2007a, 2007b, 2007c, 2007d) National Dissemination Center for Children with Disabilities (NICHCY) (2007a, 2007b, 2007c, 2007d) Xin and Jitendra (1999)

Gersten, Fuchs, Williams, and Baker (2001)

Lane (2004)

Therrien (2004)

Swanson and Sachse-Lee (2000)

Swanson (1999)

Mastropieri and Scruggs (1997)

Kroesbergen and Van Luit (2003)

Mathematics Interventions

Gajria, Jitendra, Sacks, and Sood (2007)

Reading Interventions

Smith, Lochman, and Daunic (2005)

Schneider (1992)

Reid, Schartz, and Trout (2005)

Quinn, Kavale, Mathur, Rutherford, and Forness (1999)

Maag and Swearer (2005)

King, Heyne, and Ollendick (2005)

Kavale and Mostert (2004)

Behavior Interventions

Swanson (2001)

Carnine and colleague at the Institute for Academic Access Deshler and colleague at University of Kansas Center for Research National Dissemination Center for Children with Disabilities (NICHCY) (2007a, 2007b, 2007c, 2007d) National Dissemination Center for Children with Disabilities (NICHCY) (2007a, 2007b, 2007c, 2007d) National Dissemination Center for Children with Disabilities (NICHCY) (2007a, 2007b, 2007c, 2007d) Ryan, Reid, and Epstein (2004)

Interventions for Secondary Students with Disabilities

Sugai and Horner (2007)

NASDSE/CASE (2006)

Mellard, Byrd, Johnson, Tollefson, and Boesche (2004)

Liaupsin, Jolivette, and Scott (2004)

Hollenbeck (2007)

Fuchs and Deshler (2007)

Burns, Appleton, and Stehouwer (2005)

Schoolwide Interventions

Table 3. Summary of Special Education Research Meta-Analyses and Comprehensive Literature Reviews in Areas of Reading Interventions, Mathematics Interventions, Behavior Interventions, Interventions for Secondary Students with Disabilities, and Schoolwide Interventions.

24 MARGARET J. MCLAUGHLIN ET AL.

Special Education in the New Millennium

25

Behavioral Interventions We also reviewed the research in the area of behavioral interventions. Public schools struggle with discipline and behavior issues, such as oppositional and aggressive behaviors as well as hyperactivity and impulsivity which accounts for a high proportion of ofﬁce referrals, school removal, and changes to more restrictive placements (e.g., self-contained classrooms or alternative schools) for students with disabilities. There is a long history of research related to the management or modiﬁcation of ‘‘bad’’ behaviors and the teaching of positive social and behavioral skills. Most of the interventions identiﬁed in the meta-analyses have utilized behavioral modiﬁcation strategies or explicit social skills training. More recently, special education researchers have begun to incorporate cognitive behavioral therapies into behavioral research, borrowing from a long line of psychological research. The research that has focused on developing strategies for improving the behaviors of students with and without disabilities who exhibit problem behaviors is similar to the academic intervention research in several ways. Most of the studies of behavioral interventions have employed single subject or applied behavioral analysis designs and have focused on discrete outcomes. Further, the majority of the studies were conducted in carefully controlled environments and did not examine the extent to which learned behaviors are transferred to different settings or situations. In fact, the impact of setting or context such as school organization or teacher quality on educational outcomes has not been investigated to any real extent in the special education research. Recently, however, two schoolwide interventions have emerged in the school education research.

Schoolwide Interventions Finally, we examined the research supporting the two primary schoolwide interventions, response to intervention (RTI) and positive behavioral supports and interventions (PBIS). Embedded within both these models are a number of separate and strong practices, including individual student progress monitoring and the concept of universal screening and tiered interventions. Yet, as noted by others (Fuchs & Deshler, 2007; Hollenbeck, 2007; Liaupsin, Jolivette, & Scott, 2004), the body of research supporting the schoolwide or large-scale implementation of these interventions also had noteworthy gaps. For instance, research documenting the effectiveness of

26

MARGARET J. MCLAUGHLIN ET AL.

RTI models consists of a number of small, carefully controlled studies, mostly focused in the area of reading and mostly conducted in the early grades. The research of PBIS models had similar promise with regard to improved behavioral outcomes for schools and individual students. However, the body of research as a whole had a number of methodological ﬂaws including difﬁculty in demonstrating ﬁdelity of the treatment and questionable outcome measures. Many of the large-scale schoolwide intervention studies used ofﬁce referrals, which have questionable reliability, as the primary outcome measure.

SUMMARY Special education research has long been concentrated on improving the academic and behavioral outcomes of students with disabilities through a commitment to conducting applied research on speciﬁc strategies and approaches that can be used by teachers and practitioners with individual students. The ﬁeld has compiled a broad base of experimental, quasiexperimental, and non-experimental research into the efﬁcacy of various academic, behavioral, and social skills interventions. The very brief overview of research supports the conclusion that the ﬁeld of special education does have a strong knowledge base in some areas. For instance, the ﬁeld knows a great deal about what works to improve early reading instruction among students with LD and other low achievers. In part, the achievement gains among students with disabilities as reported for NAEP and for state assessments may indicate that the investments in reading research are beginning to pay off. However, compared to reading, we know substantially less about how to teach mathematics, particularly higher-level mathematics to students with disabilities. We have a limited amount of research related to academic instruction involving secondary students and have limited research about effective interventions in the secondary content areas. Further, much of the existing academic interventions have focused on the acquisition of discrete strategies or skills as opposed to more cognitively complex subject matter as reﬂected in the content standards adopted by states. We also do not know much at all about academic instruction with adolescents with moderate to signiﬁcant cognitive disabilities nor do we have effective instructional models for adolescents whose emotional and behavioral problems interfere with their learning. Finally, many of the intervention studies in special education have been conducted in controlled research conditions and have

Special Education in the New Millennium

27

not been tested in rigorous multi-classroom or multi-site studies. In only a few areas, notably early literacy instruction, have speciﬁc interventions been ‘‘scaled up’’ to multi-sites or whole systems. The evidence points to a need for a multi-level approach that involves a number of strategies including involving practitioners as implementers of interventions, skill-based training and coaching, careful evaluation and feedback, and administrative practices that facilitate and support the interventions. Individual interventions must become part of a larger coordinated effort to improve outcomes. The need to explore these broader contextual factors will make for ‘‘messier’’ designs but are necessary to understand how to create a better ‘‘ﬁt’’ between effective practices for students with disabilities within the larger context of schooling. The research arm of special education needs to study the degree to which the interventions are currently being used in classrooms. Until then, when we see the rather discouraging performance trends and other educational outcomes, we will be unable to determine the degree to which students with disabilities truly have an equal opportunity to reach the standards that have been established across the states. If the evolving interpretation of equity for many if not all students with disabilities is becoming proﬁcient in academic content domains, then one must conclude that special education practitioners need a great deal more help from the research world.

NOTE 1. NICHCY is compiling a database of meta-analytical studies conducted in special education over the past 20 years. Currently, the database consists of 147 meta-analytic studies in seven areas such as speciﬁc academic subject matter (i.e., reading), teaching, problem solving, and behavioral interventions.

REFERENCES Ballard, J., Ramirez, B. A., & Weintraub, F. J. (Eds). (1982). Special education in America: Its legal and governmental foundations. Reston, VA: Council for Exceptional Children. Board of Education of the Hendrick Hudson Central School District v. Rowley. (1982). 458 U.S. 176. Burns, M. K., Appleton, J. J., & Stehouwer, J. D. (2005). Meta-analysis of response-tointervention research: Examining ﬁeld-based and research-implemented models. Journal of Psychoeducational Assessment, 23(4), 381–394. Carnine and colleague at the Institute for Academic. Available at http://www.ku-crl.org/ IAA%20Web/index.html

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Deshler and colleague at University of Kansas Center for Research. Available at http:// www.ku-crl.org/library/publist.shtml#adolescent Education for All Handicapped Children Act of 1975, P.L. 94–142. Franklin, B. M. (1994). From ‘‘backwardness’’ to ‘‘at-risk’’: Childhood learning difﬁculties and the contradictions of school reform. Albany: State University of New York Press. Fuchs, D., & Deshler, D. D. (2007). What we need to know about responsiveness to intervention (and shouldn’t be afraid to ask). Learning Disabilities Research and Practice, 22(2), 129–136. Gajria, M., Jitendra, A. K., Sacks, S., & Sood, S. (2007). Improving content area instruction for students with learning disabilities: A meta-analysis. Journal of Learning Disabilities, 40(3), 210–225. Gersten, R., Fuchs, L. S., Williams, J. P., & Baker, S. (2001). Teaching reading comprehension strategies to students with learning disabilities: A review of the research. Review of Educational Research, 71(2), 279–320. Gilhool, T. K. (1989). The right to an effective education: From Brown to P.L. 94-142 and beyond. In: D. K. Lipsky & A. Gartner (Eds), Beyond separate education: Quality education for all (pp. 243–254). Baltimore: Paul Brookes. Harry, B., & Smith-Lewis, M. (1992). The REI as a civil rights issue: A response to Kauffman. Journal of Special Education, 25(4), 527–529. Hendrick, J. G., & MacMillan, D. L. (1987). Coping with diversity of school systems: The role of mental testing in shaping special classes for mentally retarded children in Los Angeles. 1900–1930. Education and Training in Mental Retardation, 22(1), 10–17. Hendrick, J. G., & MacMillan, D. L. (1989). Selecting children for special education in New York City: William Maxwell, Elizabeth Farrell, and the development of ungraded classes, 1900–1920. The Journal of Special Education, 22(4), 395–417. Hollenbeck, A. F. (2007). From IDEA to implementation: A discussion of foundational and future. Responsiveness-to-intervention. Learning Disabilities: Research and Practice, 22(2), 137–146. Individuals with Disabilities Education Act (IDEA) Amendments of 1997, 20 U.S.C. 1400. Individuals with Disabilities Education Act (IDEA) Regulations, 34 C.F.R. Part 300 (2007). Kavale, K. A., & Mostert, M. P. (2004). Social skills interventions for individuals with learning disabilities. Learning Disability Quarterly, 27(1), 31–43. King, N. J., Heyne, D., & Ollendick, T. H. (2005). Cognitive-behavioral treatments for anxiety and phobic disorders in children and adolescents: A review. Behavioral Disorders, 30(3), 241–257. Kroesbergen, E. H., & Van Luit, J. E. H. (2003). Mathematical interventions for children with special educational needs. Remedial and Special Education, 24(2), 97–114. Lane, K. L. (2004). Academic instruction and tutoring interventions for students with emotional and behavioral disorders: 1990 to the present. In: R. B. Rutherford, M. M. Quinn & S. R. Mathur (Eds), Handbook of research in emotional and behavioral disorders (pp. 462–486). New York: Guilford. Liaupsin, C. J., Jolivette, K., & Scott, T. M. (2004). Schoolwide systems of behavior support. In: R. B. Rutherford, Jr., M. Magee Quinn & S. Mathur (Eds), Handbook of research in emotional and behavioral disorders (pp. 487–501). New York: Guilford Press. Maag, J. W., & Swearer, S. M. (2005). Cognitive-behavioral interventions for depression: Review and implications for school personnel. Behavioral Disorders, 30(3), 259–276.

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ATTRIBUTIONS OF MALICE TO SPECIAL EDUCATION POLICY AND PRACTICE James M. Kauffman ABSTRACT Malice – knowingly doing harm – has been attributed to special education, threatening its continued existence. Malicious education may include inferior education, exclusion from opportunities, miseducation, unnecessary stigmatization, or failure to meet individual needs. Malice may be overt or covert, unselective or selective, or be directed toward those included or those excluded. Attributions of malice may be evaluated by a series of questions comprising a decision model, and this decision model may be applied to attributions of malice to special education. Suggestions that special education is malicious are not conﬁrmed by application of the decision model. False accusations that special education is malicious are derived from inappropriate comparisons, unreasonable expectations, and assertions that are not grounded in realities.

If someone wants to kill special education, one way of attempting to do so is to say that the concepts undergirding special education are malicious – that the very ideas about or attitudes toward exceptionality on which special education is based are harmful to children and that we know it. As a society, Policy and Practice Advances in Learning and Behavioral Disabilities, Volume 22, 33–66 Copyright r 2009 by Emerald Group Publishing Limited All rights of reproduction in any form reserved ISSN: 0735-004X/doi:10.1108/S0735-004X(2009)0000022004

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we do not condone harming children, and we often enact policies designed to protect children from harm. Our educational policies are designed to both enhance the development of children and shield them from harm, especially calculated or deliberate harm. Educational policy is often assumed to be completely separate from practice, but as Gallagher (2007) has noted policy decisions often cast long shadows on practice. Policy often both prescribes and proscribes practices. Ultimately, policy is based on a conceptual model that governs practice, and both policy and practice must therefore be considered in judgments of appropriateness and success (Kauffman, 2007, 2008). If special education is found to be a malicious system, then it is highly likely that policies will be enacted to preclude the practice of special education, such that children can no longer be identiﬁed as exceptional and be provided education that is different from that of the general population. This chapter therefore deals with accusations of malice. In Part I, I brieﬂy state why malice has become an important issue in special education, recounting how accusations that special education is malicious have been made and how they threaten special education’s existence. In Part II, I consider in more detail the concept of malice and its practice. Although I relate ideas about malice to education, I also consider their broader application to various social problems. In Part III, I suggest a way of testing the veracity of accusations of malice. That is, given an accusation, how should we go about deciding whether the evidence supports the accusation? I suggest a decision model that might be applied to any program or practice in education. In Part IV, I suggest how the decision model might be applied to special education. Part V is my conclusions.

PART I. WHY IS MALICE AN IMPORTANT ISSUE IN SPECIAL EDUCATION? Among the policy and practice issues of the late 20th and early 21st centuries is the question of whether special education is at root a malicious practice, if not a malicious idea. Typically, public education is not thought to be malicious in concept or practice, but even it – public general education – is assumed by some to be malicious. The practice of home schooling is no doubt seen by some parents as necessary because contemporary public schooling is a deliberate attempt by local, state, and national education authorities to corrupt or miseducate their children. An educator who holds a

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doctoral degree from a major research university expressed to me the opinion that public education in the United States was initiated for the purpose of providing inferior education to African American children, the lower standardized achievement test scores of African American compared to European American students in the late 20th century apparently being sufﬁcient evidence of the malevolence of those who initiated public education in the 19th century. Attributions of malice to those who launched or have supported public education in the United States made me realize that malice has been attributed by someone to educational programs of nearly every description, particularly if the education is in any way different from the ‘‘standard issue’’ education offered to all without differentiation (e.g., vocational education or college preparatory education programs, which are usually offered to some but not prescribed for all and are, therefore, suspect because of presumed malice toward those selected for or not selected for the program). Such accusations also caused me to (a) become aware of attributions of malice to special education policy and practice, (b) think about the nature of malice in policy and practice in all ﬁelds, but particularly in education, (c) try to devise a decision model for evaluating whether accusations of malice to educational programs are justiﬁed, and (d) apply the decision model to special education. I begin with the ways in which accusations of malice have been launched toward special education policies and practices.

Attributions of Malice to Special Education Policy and Practice From its beginning, the concept and practice of special education have included only good intentions. The main idea behind special education was to give exceptional children educational opportunities that they otherwise would not have. But, of course, special education policy and practice have not always worked as intended. ‘‘If things did succeed as planned, the history of special education would be a fairy tale of success – of cures and caring, of optimized potential, of freedom from fear and stigma, of efﬁcient management, and of social harmony’’ (Kauffman, 1981, p. 20). Special education has not reached its highest ideals and aspirations for a variety of reasons (see Hallahan, Kauffman, & Pullen, 2009; Kauffman, 1981; Kauffman & Hallahan, 2005; Kauffman & Landrum, 2006; Mann, 1979, for discussion of some of these reasons). Moreover, as we shall see, malice has been attributed to the very concept of special education and to its

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practice (e.g., Brantlinger, 2006; Harry & Klingner, 2006; Lipsky & Gartner, 1996). Before the midpoint of the 20th century, malice was seldom or never attributed to the idea of special education or to its implementation. Until then, most people saw it as beneﬁting exceptional children. The assumption was that exceptional children would otherwise be ignored by public education. Nevertheless, from about 1970 until at least 2008 (and, very likely, well beyond), some of special education’s critics have described it as part of a pattern of racial discrimination, personal insults, and attempts to foist a second class education upon unsuspecting and powerless parents (e.g., Brantlinger, 2006; Dunn, 1969; Gartner & Lipsky, 1987, 1989; Harry & Klingner, 2006, 2007; Landsman, 2001; Lipsky & Gartner, 1996; Stainback & Stainback, 1991). It has been said to be like slavery or racial discrimination (e.g., it has been compared to South Africa’s racially discriminatory policy known as Apartheid). It has also been described as disgraceful and demeaning to many or all who receive it and to be of questionable value, if not harmful. Moreover, special education is obviously different from the education offered to most students, and it therefore draws ﬁre from critics not only because it is different but because it is more expensive as well (Hier, 2007). Lipsky and Gartner (1996) condemned the special education system. They stated that ‘‘the system of special education, and the attitudes toward disability that undergird it, have harmful consequences for both those labeled ‘disabled’ and those not’’ (p. 767), a clear statement that special education is malicious – knowingly and deliberately hurtful. But this is only one example of the torrent of criticism of special education. Special education has also been described as a scandal that ‘‘wastes money and hurts the poor’’ and as ‘‘the road to hell’’ (Worth, 1999). It has been called ‘‘the gold-plated garbage can of American schooling’’ (Fisher, 2001) and ‘‘a disaster’’ that is ‘‘poorly deﬁned, poorly run, poorly enforced’’ (Cottle, 2001). Moreover, some special educators have suggested that special education offers students no advantage and simply does not work when it is a separate entity (e.g., Gartner & Lipsky, 1987, 1989; Reynolds, 1989). Unfair and relentless criticisms of special education as a malicious venture led two special education researchers to remark in the 1990s: On December 9, 1993, special education was mugged in a dark alley. The thugs were Joe Shapiro and his gang at U.S. News and World Report (cf. Shapiro et al., 1993). Their brass knuckles and tire irons were the half-truths and full-blown distortions they patched together (with the ﬁnesse of a Mike Tyson) into a cover story entitled ‘‘Separate and

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Malice Unequal: How Special Education Programs Are Cheating Our Children and Costing Taxpayers Billions Each Year.’’ (Fuchs & Fuchs, 1995, p. 363)

How Accusations of Malice Threaten the Existence of Special Education I have recounted only a few examples one could give of suggestions that special education is or may be a malicious program – malicious as policy and as a practice. Such accusations of malice are quite at odds with the perspectives of some special educators, who describe special education as a benevolent way of responding to the diversity of students found in public schools (e.g., Cook & Schirmer, 2006; Hallahan et al., 2009; Heward & Silvestri, 2005; Kauffman & Hallahan, 2005; Walker, 2003; Zigmond, 1997, 2003, 2007). Nevertheless, the suggestion that special education is malicious, whether the words malice or malicious are used to describe its nefarious effects, threatens its continued existence. If citizens or their elected representatives in government become convinced by repeated accusations that special education is malicious, then it is likely that policies proscribing special education as a response to diversity among learners will be enacted. That is, if the very attitudes toward disabilities that undergird special education are believed to do harm to children, then practices based on such attitudes are very likely to be declared unlawful. Therefore, we should consider in more detail the meaning of malice – what it is, what forms it takes, and how it is judged – if we are to respond reasonably to accusations that special education is a malicious idea or that its practice is malicious.

PART II. THE CONCEPT OF MALICE AND ITS PRACTICE The Nature of Malice and Its Attribution Malice implies intentional harm – planned hurt, which cannot be accomplished without forethought. People who practice malice want to hurt others or do not care if they do. Their cruelty is calculated. They know that they are doing harm to particular people and they do it anyway, sometimes justifying their savagery by an ideology. Accidents sometimes happen without any evidence of malice or even the suspicion or accusation of malice. Unfortunately, not all accidents can be

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prevented, even with the greatest effort. Moreover, sometimes harm is incidental to doing a greater good for the individual who is hurt. We accept the fact that medical procedures or social policies or educational programs may cause a person pain, side effects, anxiety, or inconvenience in the short term but be beneﬁcial to that person in the long run. We know that sometimes people see the ultimate positive outcomes of short-term harm, and we do not then attribute malice to their behavior. In fact, we often see mercy in immediate pain for long-term gain. Sometimes policy initiatives launched with the best of intentions go awry, so they are not judged to be malicious in concept (Gillon, 2000). Nevertheless, if a program begun without malice turns out to have predominately negative long-term effects, then its perpetuation can be judged malicious because then it is continued in the face of evidence that it is harmful. Malice may be practiced in a variety of ways. Some malice is overt and some covert, some diffuse and some highly focused, some targets the included group, and some the excluded group. Moreover, malice may be misattributed to people, policies, or practices. Sometimes there is a set-up for the false accusation of malice – a way of looking at educational problems that can only result in fodder for false accusation. Sorting through the different kinds of malice is important before considering whether to attribute malice to speciﬁc educational programs. Understanding the nature of malice – what it is and how it works – is necessary if we are to distinguish between malicious and non-malicious programs. ‘‘First, do no harm’’ may be a good injunction. ‘‘First, do no intentional long-term harm’’ is probably better. People who do malicious things may claim that their cruelty is incidental to a larger good. But the larger good is not for the beneﬁt of the individual(s) they harm, only for an ideology. To the person whose malice is justiﬁed by ideology, the idea is more important than the individual. A focus on the individual is not accidental. Consideration of individuals, not groups, is a foundational principle of special education. Moreover, concern for the individual as opposed to the group is a foundation of much liberal teaching about social justice. True, liberal notions may ﬁnd their way into legislation or litigation on behalf of groups (e.g., minors, minorities, land owners, the poor, those with disabilities), but liberal thinking demands consideration and adjustment of social policies to address the effects on individuals. Recognizing the rationale of a larger good as opposed to emphasis on the individual is important because terrorists, despots, religious leaders, politicians, and charlatans of every stripe have always used the larger good as an excuse to do intentional harm to individuals. Perhaps there are

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circumstances in which a legitimate larger good should be served, but that does not erase the malice against individuals whose interests are sacriﬁced to serve the larger good. Social justice demands understanding which individuals are sacriﬁcing what for the common good and acknowledgment that individuals are being treated with malice for the sake of the common good when that occurs. Something taken to be a casus belli may or may not be legitimate, but war inevitably requires malice, including malice against those ordered into ‘‘just’’ battle.

Malice in Educational Practice Education is but one endeavor in which malice is possible. However, malice is not something that many people associate with education, especially special education. In fact, most people probably think of special education as serving a larger social good as well as serving the cause of social justice for individuals, such that the thought of special education being malicious (excluding some of their encounters with particular peers, teachers, administrators, or policies) never crosses their minds. Malicious special education might be considered that in which teachers or others knowingly, deliberately set out to harm students in one or more of the following ways: Giving students inferior education – Inferior in the facilities, instruction, knowledge or skills they are provided. Excluding students from educational opportunities that are provided to others and from which they could beneﬁt. Miseducating students by providing information that is known to be false or untrustworthy. Stigmatizing students with denigrating labels or otherwise identifying them unnecessarily or incorrectly as failing, lacking capability, or unteachable. Failing to provide education appropriate to the student’s individual needs, so that disabilities and gifts and talents are not accommodated.

Types of Malice Overt malice. Sometimes people set out to harm others and make no attempt to disguise their evil designs. Perhaps overt malice is best illustrated by the

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behavior of well-known despots such as Adolf Hitler, Joseph Stalin, Mao Tse-Tung, Pol Pot, Idi Amin, and Saddam Hussein. They made no secret of their intention to wipe out ethnic or ideological groups. In fact, as they consolidated their power they became bolder and more explicit about their evil intentions toward whatever group they wanted to exterminate. Osama bin Laden and many other terrorists clearly and overtly articulate their hatred of and intent to harm those they despise (Americans or anyone else they describe as an inﬁdel). No pretense is used to hide their malice. They wear it as a badge of honor in the service of what they see as a larger good (an Islamist society, for example). Slave owners and those who practice or recommend racial discrimination practice and champion overtly the bondage or maltreatment of others. They may cite religious or pseudoscientiﬁc or political reasons for their actions, but their malice toward those they consider their inferior is obvious. Religious doctrine may justify or require malicious action. Not only may religion be the basis for terrorism or war, but human suffering of individuals may be justiﬁed or even deliberately caused by what is termed ‘‘defense of the faith,’’ a call for behavior known to result in harm but justiﬁed by a ‘‘larger good.’’ Cases in point include past crusades and inquisitions in which people were tortured for their refusal to bow to church doctrine and contemporary teachings of religions in which individuals are deliberately demeaned, described as enemies or as subhuman, or suffer or die needlessly simply because of religious beliefs (e.g., suffering or death due to the refusal of medical care or because preventive measures are prohibited; persecution of homosexuals). In education, including special education, malice is seldom overt. That is, not often do we ﬁnd – at least not in contemporary American education – educators or politicians who say that their purpose is to hurt students. In nearly all cases in which any evidence of malice may be found, it is disguised as ‘‘improvement,’’ ‘‘reform,’’ ‘‘restructuring,’’ or other words describing only positive intentions. Thus it is important to consider how malice may be practiced covertly. Covert malice. Sometimes people intend to hurt others but cover up their intentions with actions or rhetoric disguising their true motive. That is, their malice is covert. Most observers do not perceive their malice, and if malice is attributed to their actions they deny it. They do not want others to know the motives of their actions, and usually have a plausible explanation for what they are doing. In this case, the attribution of malice is very tricky because, ﬁrst, the malicious person will deny malicious intent. The denial may or may not be valid, and the risk of false accusation is real. False accusation of malice itself can be malicious, and it is a favored tactic of demagogues such

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as the late Senator Joseph McCarthy. True, communists of the McCarthy era (1950s) may have harbored malice toward non-communist countries or individuals, but that in no way denies the obvious malice of Senator Joseph McCarthy in making false accusations and using innuendo to destroy the lives of others. Uncovering covert malice is not easy, and it can seldom be done quickly. It often depends on painstaking research and personal risk or whistleblowing, such as that involved in uncovering the motives of tobacco companies. It is complicated by the fact that beneﬁts of the policy or procedure can be clearly stated. For example, the economic beneﬁts of growing tobacco are clear, and the satisfaction of appetite for individuals is obvious. Moreover, tobacco companies have advertised their products with personal testimonials of satisfaction and beneﬁts, and physicians and politicians have been recruited to testify to the absence of any proven harmful effects of tobacco use. One marker of covert malice is the call for something that is not just difﬁcult or improbable but ﬂatly impossible. Another is the use of words to indicate something other than their plain meaning. Thus, if someone calls for educational reform that is statistically impossible and uses words in ways that belie their plain meaning (e.g., leaving no child ‘‘behind’’), then we might suspect a malicious motive for the proposed reform. However, the fact that the No Child Left Behind Act calls for the impossible and has nefarious effects on children’s mental health does not necessarily lead to the conclusion of malice, as it may have been enacted with good intentions and individuals implementing it may not realize that it has negative effects (see Ginicola & Saccoccio, 2008). Another marker of covert malice is false or misleading information, including hyperbole. False advertising, for example, leads people to purchase and use products to their detriment. Medicines, foods, transportation, and educational strategies have all been sold or promoted through false or misleading representations of their effectiveness, ingredients, reliability, or safety. The beneﬁts to the sellers have been obvious, and testimonials of satisﬁed consumers have been added to the patina of legitimacy of the products. But people have been harmed, sometimes deliberately in cover-ups of risks or outright denials of evidence that the claims of beneﬁt are bogus. Yet another marker of covert malice is appeal to a common or higher good as cover for covert malice. If the claim of a higher good involves civic policy that can be evaluated empirically, then it may be possible to show that on balance, more people were helped than were hurt. However, in the case of argument from religion, nothing other than belief (faith) can sustain

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the argument, and skepticism (doubt) cannot be satisﬁed by any empirical data. Covert malice may also be accomplished by the claim of victimization. Whatever religious group (fundamentalist Christians, Jews, or Muslims, for example), political or ideological persuasion (e.g., conservative Republicans, liberal Democrats, inclusionists), or ethnic group (e.g., Irish, African Americans, Serbians) can claim victimhood, can attribute malice to their ostensible oppressors. Of course, various societies have a history of victimizing others based on religion, political identiﬁcation, ethnicity, or disability, which makes the distinction between actual and claimed victimization difﬁcult. Virtually no one openly proposes harm to children, yet virtually every program of education has been said to be malicious on some grounds. Certainly, malice is plausible in some cases of educational policy or practice (recall racial segregation in public schools, for example), as the outcomes in some cases are known to be very bad. However, plausibility is not proof, and we must take care not to presume malice without careful examination of both the demonstrated or predictable negative consequences of a policy or practice and the evidence of intention of harm. Unselective and selective malice. Malicious people may strike out unselectively, intending to hurt as many as possible but no one in particular. Terrorism in its many forms and war are both examples of this kind of malice. Both demand a disregard for individuals and for ‘‘collateral damage’’ for the sake of some principle or ideology that is assumed to be more important than a single person. Unfocused malice is more frightening to people than is selective malice, for being harmed is regulated by probabilities that cannot be altered by reasonable individual action. Seldom is malice in education clearly unselective. That is, if the intent is to harm students, then the students to be harmed are seldom chosen at random. Special education almost always involves charges of selective malice because it can be directed toward particular individuals or very welldeﬁned groups. If a student is the target of selective malice, then the perpetrator is out to get that individual, either because he or she is the individual who is considered deserving of harm or because he or she is a member of the selected group toward which malice is directed. The difference between unselective and selective malice can be subtle. Sometimes, those targeted for harm are clearly particular individuals; other times, they are not, except that they are members of a particular targeted group. In education, malice seldom is expressed toward a particular individual, but it is clearly focused on a given group. Students of particular

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color, national origin, religion, income level, ability or disability, or other identifying characteristic may be those chosen for purposes said to be malicious. Malice toward the included and the excluded. Sometimes malice is directed toward the group that is included in a policy or designated to be among those receiving certain treatment. In special education, those who receive the program are usually the ones who are said to receive malicious treatment. For example, if education of students with disabilities is assumed to be second-rate, limiting, and discriminatory, then inclusion in special education will likely be described as malicious. However, if a policy or procedure is perceived to provide beneﬁt, then it is the excluded group that receives malicious treatment. In education, if a program is assumed to provide beneﬁts to participants, then malicious intent might be attributed to whatever criteria and procedures are used to exclude an individual from the program. For example, if private education, as opposed to public education, is assumed to provide better instruction, then malicious intentions are likely to be attributed to whatever criteria are used to exclude students from private education. Likewise, if the education provided to gifted and talented students is assumed to be superior in beneﬁt to the typical education provided in general education classes, then those not included in a program of gifted education may be assumed to be targets of malice.

Types of Malice and Problems in Attribution of Malice to Education Educational malice is typically more covert and more focused than malice in other areas of social policy. Particular groups may, indeed, be the focus of malicious educational policies, but the covert nature of malice in education has unfortunate consequences: It makes the attribution of malice very easy, but it also makes both conﬁrmation and refutation of malice very difﬁcult. Consideration of actual malice and the false accusation of malice are therefore extremely important and are topics of the next section. Of course, it is possible that an accusation of malice is never conﬁrmed and never disconﬁrmed to the extent that it satisﬁes reasonable skeptics. Some people are never skeptical in any serious sense, preferring to believe that the accusation itself is sufﬁcient evidence of malice. However, some skeptics are never satisﬁed, so that disconﬁrmation is simply not possible and neither is conﬁrmation; they demand evidence that they consider beyond any shadow of doubt, not just beyond reasonable doubt. But even if someone is skeptical in a reasonable way, some cases are ambiguous.

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Teachers and administrators may be left in a bind, not knowing whether their practices are or are not contributing to the malicious treatment of the students they are trying to help. Thus, it behooves us to try to devise a model for testing attributions of malice in education.

PART III. EVALUATING ACCUSATIONS OF MALICE A Decision Model for Evaluating Accusations of Malice Only the most naive or idealistic person will believe that malice is nonexistent or that false accusations of malice are never made in education. Still, it is one thing to recognize that harm may be intentional, even in education, and quite another to presume that it exists when it does not. An accusation of malice is a stain that often cannot be removed. Thus, false accusation is as important to recognize as actual malice. As is likely the case with racism, sexism, and sexual abuse, restitution and forgiveness are more easily granted in contemporary American culture to the false accuser than to the accused but exonerated. Proposing any educational policy or procedure is inherently risky, as accusations of malice are virtually certain to follow, either immediately or after some delay. The accusations may or may not be valid, but the accusations will often be taken as valid regardless of the evidence. What we need, then, is a way of checking things out, a way of determining whether an accusation of malice is likely true or false. Given the difﬁculty of separating true from false accusations of malice, it is tempting to assume either that in education (a) all accusations of malice are true or (b) all accusations of malice are false. Those leaning toward (a) tend to be suspicious of all education, assuming that any attempt to educate students is inherently malicious, at least if the students differ in any signiﬁcant way from individual-to-individual or group-to-group and receive education that is different in any way from that prescribed for others. Those leaning toward (b) tend to be idealists who believe that no one would ever advocate deliberate harm to any child; accusations of malice in education are, from this perspective, simply preposterous in all cases. The unfortunate truth, however, is more complicated than either (a) or (b). Our task, then, is to attempt to ﬁnd criteria for falsifying claims of malice. Accusations of malice based on the internal state of the accused cannot be falsiﬁed, simply because those internal states are not open to direct observation and empirical conﬁrmation. Non-falsiﬁable accusations of malice

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may indeed be used to attack individuals or programs with devastating results. Of course, both information and judgment are required in reaching conclusions about malice, which is not peculiar to the issue at hand but simply an aspect of the human condition. That is, judgment is required to resolve most issues of signiﬁcance.

Has an Accusation Been Made? If no one makes an accusation of malice, then the question is moot. Only after someone attributes malice to an educational program or at least raises the possibility that it is malicious is the question of intent to harm enlivened. Thus, accusation or suggestion is a necessary but not sufﬁcient condition for determining that a program of education is malicious, as shown in Fig. 1. That is, if there is no accusation, then there is no reason to go further. Programs may be malicious in the absence of accusations of malice. It is therefore wise for those concerned to be watchful and raise the possibility of malice if they have reason to be concerned. Nevertheless, accusation alone is insufﬁcient to reach a conclusion of malice, and false accusations themselves are damaging. Thus, one should take care to avoid raising unjustiﬁed suspicions.

Has Intent to Harm Been Stated? A statement of intention to do harm is sufﬁcient to make the case for malice, as shown in Fig. 1. That is, if someone says they want to harm children, that in itself is enough to establish malice. This kind of overt malice is sometimes seen in politics, including international relations and domestic contests, but it is seldom if ever seen in education, general or special. A caveat is important here. The intent to harm must be made by the program designer if a program itself is to be considered malicious. The reason for this is simply that false accusations often include statements that the program being criticized was intended from the beginning to harm when this is false. This is a basic set-up for a false accusation – the claim by someone other than the program designer that the intention of anyone who uses the program now is to do harm because harm has always been the purpose of the program. Of course, an individual using a program that was not designed with malicious intent may turn it to evil purpose and may state his or her intention to do harm.

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Necessary: Accusation of Malice? Yes

No

No Issue

Sufficient: Statement of Intent to Harm? No

Yes

If No, Examine:

Outcomes (Effects)

Degradation of Programs/Practices

Predictably Positive

Little or None

Unpredictable But Positive

Substantial but Not Pervasive

Unpredictable But Negative

Pervasive

? Predictably Negative

Conclusion: Fig. 1.

Confirmation: Confirmation: Accusation is True Attribution

Nonconfirmation: Accusation is Questionable

Unknown

Disconfirmation: Accusation is False

Decision Model for Evaluating Accusations of Malice.

Accusation Alone is Unconvincing The accusation of malice is easy and may be made for a variety of reasons, both political and professional. Attributing malice to one’s professional competitor is advantageous in academe and in the market place. The

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accusation puts the accuser on presumably higher moral ground and relegates the accused to the role of an abuser of children. The presumed higher moral ground gives the accuser advantages in publication, speaking engagements, and employment. Easy as it may be to make, the accusation of malice is not sufﬁcient to make the case for it. Accusation does arouse suspicion and may launch an investigation. But accusation should not convict someone ipso facto of malice. We must assume that, as is the case in all of American jurisprudence, a person or program must be presumed innocent until proven guilty. In education as in other endeavors, the accusation of malice is not sufﬁcient to make the case for it. Were accusation alone sufﬁcient to prove malice, then every (or very nearly every) education program would be found malicious. If there is a statement of intent to harm, then we may conclude that conﬁrmation of malice is justiﬁed. But a lack of stated intention to harm does not mean that a program or practice can be assumed to lack malice. Lack of stated intent to harm should prompt us to examine other evidence, speciﬁcally program outcomes or effects and the degradation of the program or practices, as shown in Fig. 1.

Issues in the Absence of Statement of Intent to Harm The ﬁrst questions we might ask about the potential maliciousness of any special education program involve what is known about the outcomes or effects of the program. After all, a program not advertised as malicious should be based primarily on what it does – the outcomes or effects on students. The secondary questions pertain to the degradation of the program and practices based on it – how well it has been implemented. Answers to the secondary questions about implementation play a supporting role, bolstering or failing to offer support for conclusions reached on the basis of outcomes. Predictable positive outcomes. Occasionally, a program may have beneﬁcial outcomes or effects that can be predicted with a very high degree of conﬁdence. Positive outcomes can be predicted only if the program has been tried before and shown through extensive ﬁeld-testing to have overwhelmingly positive effects. The fact that positive outcomes can be predicted does not necessarily immunize a program from accusations of malice, but such prediction on the basis of reliable data from extensive ﬁeld

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tests points unambiguously to disconﬁrmation of an accusation of malice – the conclusion that the accusation of malice is false, as shown in Fig. 1. Unpredictable outcomes. Sometimes programs are launched with the best of intentions and without anyone being able to predict what, eventually, turn out to be negative consequences. Gillon (2000) has detailed how government reform programs have often gone awry in surprising ways. People are not usually held responsible for consequences that are utterly unpredictable (Kauffman & Konold, 2007), but additional considerations are in order when negative outcomes are obtained. In some cases, the consequences of a program are predictable with reasonable knowledge, but in other cases the outcomes are truly unknowable in advance. In such cases, a judge or jury may be called upon to decide the outcome. Some programs of education have a history of inadequately measured outcomes, such that no one can make reasonable predictions of their effects. Sometimes one can make reasonable predictions based on very similar programs or logical analysis based on reliable data from other sources. For example, it may be possible to predict the poor outcomes for most students, particularly most of those who have difﬁculty in learning, of an educational program in which no rewarding extrinsic consequences of any kind are provided for correct performance. When outcomes are unpredictable, whether they are positive or negative, then the evidence points to non-conﬁrmation, as shown in Fig. 1. That is, if no prediction of the results of a program is possible, then judgment that the program is malicious is not justiﬁed, but neither can the program be exonerated. The only justiﬁed conclusion is that the accusation of malice is questionable. If the outcomes could not be predicted but are positive, then more trials to see whether the outcomes become predictably positive are in order. If the outcomes could not be predicted but are negative, then trying the same program again without modiﬁcations designed to produce positive outcomes would likely be questionable, if not clearly malicious. Predictable negative outcomes. Sometimes, the undesirable outcomes of a program of education seem entirely predictable to most people. Some individuals, including a few educators, may claim that we can never predict what will happen if we implement a given program or procedure. These tend to be those who believe that science is no more useful than any other ‘‘knowledge’’ and generally operate under the banner of ‘‘postmodernism’’ or other label indicating cognitive relativism. They tend to be those who deny our ability to use logic and scientiﬁc information to make decisions or those who believe that logic and scientiﬁc information are not particularly

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useful (see Kauffman & Sasso, 2006a, 2006b; Mostert, Kavale, & Kauffman, 2008; Sasso, 2007). However, they may also be educators or policy makers who choose to ignore the realities of science and mathematics (Kauffman & Konold, 2007). Most people, including many educators, think it is possible to make predictions about many things based on research or, if research is not available on the particular program in question, then on the basis of a logical analysis of the problem and the proposed solution. Those who believe that prediction is possible tend to believe that we can assess the probability of a given program producing a given outcome. That is, we can make a good guess that a program will or will not produce a speciﬁed outcome. For example, we might assume that failure to teach children speciﬁc sound–symbol correspondences (i.e., the sounds that letters make in words) will result in the failure of many children to learn to read by the usual age. Or we might conclude, based on the preponderance of evidence from psychological and educational research, that it is predictable that an unstructured classroom (one in which the consequences for particular behavior are inconsistent and in which routines are not followed) will result in a relatively high level of misbehavior. Sufﬁce it to say that when the outcomes of an educational program are judged to be both predictable and negative, then promoters of the program may be judged to be acting irresponsibly, if not with malice (Kauffman & Konold, 2007). The evidence when outcomes are predictably negative points to conﬁrmation of the accusation of malice, as shown in Fig. 1. Predictable negative outcomes are sufﬁcient to support a judgment of malice in many areas other than education. Malicious wounding means behaving in a way that predictably harms another person, regardless whether the perpetrator of the act stated his or her intent to do harm. The promotion of products whose use is very likely to produce predictably negative outcomes (e.g., cigarettes) may be judged malicious. Prediction of outcomes requires knowledge of basic statistical phenomena. Assuming that the average describes all cases or, on the other hand, that outliers describe the average, is illogical (Kauffman, 2002). Either or both the average and the outliers may be important to consider. But to confuse the two (average and outliers) or argue that one describes the other is nonsense. Nothing works in every case, and everything appears to have worked in at least one case. Thus, the fact that some children learn to read without explicit instruction does not make the case that most will; and the fact that most children learn to read with explicit instruction does not mean

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that all will. To make sense of the predictable consequences of an education program (or of anything else, for that matter), the base rate of a given outcome without the program must be compared to the base rate with the program. Only by comparing what is offered as treatment or risk reduction to what happens without the program can anyone make sense of the prediction of outcomes. To the extent that we can show that a given program produces predictably negative outcomes for most learners, we have made the case that the promotion of the program is malicious, whether or not the program or practice was originally designed with malice. Little or no degradation of the program or practices. Many programs are begun with the best of intentions but suffer degradation in practice over time. Moreover, nearly any program or procedure can be badly practiced, such that its implementation is badly botched and bears but little resemblance to the original idea. What may happen, then, is that the program was originated without malice but becomes malicious in practice. For example, any program in reading or any special education program may be launched with only beneﬁcial intentions, and the program may provide beneﬁt if implemented as intended. Later, because the program is used in ways for which it was not designed or because it is implemented without ﬁdelity to its design, it becomes useless or worse. However, some programs and practices suffer little or no degradation, either because they are relatively new or because the program’s designers took particular care to train and monitor the performance of its users. If the program or practice is implemented as intended, then the outcomes as an indicator of malice or lack of it are strengthened. That is, whatever conclusion the outcomes criterion suggests is made just that much stronger because the program or practice is implemented with ﬁdelity to the design of its originator. As shown in Fig. 1, little or no degradation in a program or practice suggests basing a conclusion on outcomes. Substantial, but not pervasive degradation of program or practice. Nearly any good idea or product can be corrupted or turned to evil purpose, regardless of the intention of its originator. In education, degradation of programs or practices is extremely common. That is, procedures designed by researchers or innovators often are not practiced with ﬁdelity. Naturally, when any program or practice produces poor outcomes, the predictable claim is that the program was implemented half-heartedly, inadequately, or in some way without ﬁdelity to the original idea. In some cases, if not in most, this is undoubtedly true. The real test of the program or practice is its results when it is implemented with ﬁdelity. A program or practice that

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consistently produces good results when implemented well can – and usually will – produce inferior results when poorly implemented. Degradation of ﬁdelity to the original idea cannot be taken as sufﬁcient evidence of the malice of the designer of a program. That is, poor outcomes are a necessary but not a sufﬁcient condition for attributing malice to program design. Program degradation may occur for a variety of reasons, including the mere passage of time, insufﬁcient training, misunderstanding, and faulty measurement. Any malice introduced into the program or practice may be attributed, then, to individuals who are poor implementers of the program, not to the designers of the program or to individuals who follow the program with ﬁdelity. Programs or practices may be designed free of malice but may be found to be inferior and, in fact malicious when implemented. Yet such procedures may be promoted for philosophical or pecuniary reasons. Promoting programs or practices known to produce inferior outcomes when implemented as planned may be sufﬁcient to justify the accusation of malice. However, caution is in order in considering accusations of malice. Even programs, products, and procedures that are generally practiced without malice may have their malicious users. That is, no program, product, or procedure can be made ‘‘malice-proof.’’ Someone, somehow can turn any useful tool to evil purpose. Thus, it would be a mistake to conclude that a program or procedure is malicious because one can cite examples of its malicious use. Nevertheless, we must try to assess or estimate the degree to which degradation of the program or practice has occurred. When we observe degradation, we must ask ourselves whether this substandard implementation of the program represents most cases. If program degradation is substantial but not pervasive, then the connection to conclusions based on outcomes is weakened, as shown by the dashed line in Fig. 1. Pervasive and unknown degradation of program or practice. When degradation is pervasive, or if the extent of degradation is simply unknown, then all bets are off when it comes to support of conclusions about an accusation of malice. That is, we simply do not know what to conclude about malice in those cases in which the program is seldom or never implemented as designed or in which no information about the ﬁdelity of implementation is available. As depicted in Fig. 1, pervasive or unknown degradation of the program or practice leaves us only with questions; our knowledge of degradation is sufﬁcient neither to strengthen nor to weaken our decision based on outcomes.

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Setups for False Accusations of Malice In some instances, malice cannot be attributed to a program without ﬁrst setting the stage for trumped-up charges. There are two primary ways of setting the stage, two fundamental strategies for the set-up. The ﬁrst strategy is simply to make or call for unfair comparisons. The second is a close cousin of the ﬁrst – denying reality by calling for something that is not just very difﬁcult or highly improbable but impossible. Unfair comparison. A critic of special education may set the stage for accusations of malice by making or requiring unfair comparisons. The comparisons demanded may be not only the wrong ones for fair assessment but be those that will always make the program being criticized look bad, whether it really is or not (Kauffman, 2008). We quickly recognize the craven unfairness in the saying ‘‘Heads, I win; tails, you lose,’’ but many people do not seem to recognize the way in which common comparisons of educational outcomes ensure the failure of a special education program that is being criticized. For example, comparing the mean achievement of students with disabilities to the mean achievement of those without disabilities assuredly, always, inevitably makes special education look bad. Such a comparison is nonsensical and a set-up for charges that special education is ineffective or worse, simply because disability for special education purposes is deﬁned in part by academic failure and, moreover, no one has a means of curing most disabilities or of erasing mean differences between students with disabilities and those without (Kauffman, 2005). The appropriate comparison is the achievement of students with disabilities who receive special education to those with very similar characteristics who do not receive special education (Kauffman, 2008; Kauffman & Hallahan, 2005). Also unfair is comparing the current achievement of students to hypothesized achievement if education were deemed ‘‘good.’’ The comparison inevitably results in current education being described unfavorably, regardless how good it may be, simply because one can always call for higher achievement regardless of the students’ performance. Thus, when critics call for ‘‘ratcheting up’’ or ‘‘ramping up’’ student achievement, the assumption is always that current education is not good enough – the conclusion that education is a failure is implicit in the statement of the problem or in the demanded comparison. Moreover, ‘‘ratcheting up’’ or ‘‘ramping up’’ achievement – setting higher standards – also inevitably, simply because of the mathematics involved, creates more failures. Denial of reality. Denial of reality may be explicit, but it is far more often only implicit in policies and proposals for reform. Usually, it involves the

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denial of a reality that is poorly understood, such as a statistical phenomenon. Calls for a universal standard of achievement that every student will be expected to meet exemplify this kind of denial (Kauffman & Konold, 2007). Unless the standard is set at zero, those who measure achievement (and, of course, standards without measurement cannot exist) must deny one or both of two realities: (a) the existence of those who cannot under any circumstance achieve the standard or (b) the existence of a statistical distribution of achievement outcomes. Another form of denial of reality is found in the idea that every student (or every school or every state or nation) should be ‘‘successful’’ by a common standard. This kind of denial is an unwillingness to face up to the mathematical certainty that when states, schools, classes, or students are ranked, half of them will be below the median and a substantial proportion will be below the mean (Rothstein, Jacobsen, & Wilder, 2006). Scores below the median and below the mean occur every single time a reasonable test of knowledge or performance is given to a typical group of learners, no exceptions, regardless of wishes or rhetoric. Having more than half of a tested group score above the mean (the arithmetic average) requires, mathematically, a negative skew (i.e., a negative skew puts more than half above the arithmetic mean, and a positive skew puts more than half below the mean, and the greater the skew the greater the percentage above or below the mean). Still another form of denial is found in the idea that abilities and disabilities are determined solely by environmental conditions or are randomly distributed across all subgroups of the general population. Perhaps the most coherent exposition of denial of biological contributions to learning and behavior – and the most convincing refutation of this premise – is The Blank Slate (Pinker, 2002). The idea that disabilities are randomly distributed regardless of environmental conditions or biological factors, and thus that they should be identiﬁed only in proportion across both sexes and all racial and ethnic groups, ﬂies in the face of what we know about why children have disabilities, particularly the most prevalent disabilities (Hallahan et al., 2009; Kauffman & Hallahan, 2005). Denying realities provides a platform from which to launch false accusations of malice. Accusations that are based on a denial of reality are on their face false, as the basis for these accusations are merely trumped up. Nevertheless, we must remember that accusations of malice toward a particular program may have both legitimate and non-legitimate bases. That is, there may be necessary and sufﬁcient cause to conclude that a program is malicious even though some of the accusations are false. We must deal with both justiﬁed and false accusations.

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PART IV. APPLICATION OF THE DECISION MODEL TO SPECIAL EDUCATION Evaluation of Malice in Special Education Policy and Practice The attribution of malice to special education is a necessary but not a sufﬁcient condition for a ﬁnding of malice. As noted in earlier discussion, numerous critics have accused special education of malice, so the question of accusation has been answered. Here, I explore the criteria for evaluating the accusations that special education is malicious.

Absence of Statement of Intent to Harm Special education was inaugurated with only good intentions. To my knowledge, no statements of intent to harm children in the special education literature have been found, except, of course, statements by those charging that special education is malicious. Otherwise, the literature contains only statements indicating a sincere desire to make the lives of exceptional children better. Statements about the intent of special education by its designers therefore carry no sufﬁcient reason to attribute malice to special education policy or practice. The statements accusing special education of malice appear to be blatant non sequiturs or self-contradictions and obvious setups for false accusations.

Outcomes The fact that special education has fallen short of its aspirations cannot reasonably be taken as an indication of its malice. As noted earlier, many programs begun without malice suffer degradation of program or practice, are poorly implemented, are misused or abused, and have disappointing outcomes, but this does not indicate that they are now or ever were malicious. Absence of predictable negative outcomes. The vast majority of parents do not prefer to have a child with disabilities and perceive having a disability as undesirable. This parental preference is not just predictable but desirable. That is, as caring human beings we do not want parents to prefer that their children have disabilities or want parents not to care whether their children have disabilities. Neither do we want our society to be one in which

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disability is seen as inconsequential, much less preferred (Kauffman & Hallahan, 2009). Probably a society that cares not whether its children have disabilities and treats all levels of ability the same is neither kinder nor gentler than one in which ability is seen as more desirable than disability, efforts are made to prevent disabilities, and children with disabilities are both identiﬁed and helped to do everything they can. Certainly, it is highly predictable that disability will carry some level of stigma in a society in which having a disability is seen as undesirable and, therefore, serious attempts are made to prevent it (Kauffman, 2003). Facing the reality of their child’s disability may be no easier for parents than facing the reality of their child’s serious injury or disease. These (disability, injury, disease of a serious nature) are not nice things that we hope will befall our children or about which we are indifferent – unless we have become truly and grotesquely misanthropic. Nevertheless, facing the unpleasant fact of disability is the ﬁrst step in taking constructive action. That is, although the disappointment, sadness, or even horror at recognizing the fact of disability is predictable, that predictable negative outcome is not the one on which we should focus. In fact, it is only the necessary ﬁrst step in offering solace, effective treatment, and the minimal stigma that follows from them. ‘‘Pretending that disability doesn’t exist only heightens stigma’’ (Kauffman, 2003, p. 196). But this question remains when trying to judge the validity of accusations of malice in special education: are students usually better off or worse off for having received special education? The evidence suggests that they are usually better off (Kauffman & Hallahan, 2005; Zigmond, 2007). Predictable positive outcomes. When implemented as intended, special education is known to have positive outcomes for most students who receive it (see Hallahan et al., 2009; Kauffman & Hallahan, 2005; Kauffman, Bantz, & McCullough, 2002; Pullen, 2004, for example). Students receive appropriate instruction, learn academic skills, learn appropriate behavior, make lasting friendships with peers and teachers, acquire appropriate selfperceptions, and are prepared for transition to further education or work (see, e.g., Cook & Schirmer, 2006). Early intervention with special education and other helpful services often make a signiﬁcant positive difference in the lives of children. As Jolivette, Gallagher, Morrier, and Lambert (2008) stated, ‘‘young children with behavioral problems who received appropriate, individualized and evidence-based interventions are more likely to experience school and life success’’ (p. 88). Reviews of the research and long-term follow-up studies clearly indicate the success of early intervention in special education, at least

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for those with emotional or behavioral disorders (e.g., Dunlap et al., 2006; Strain & Timm, 2001; Walker, Ramsey, & Gresham, 2004; Walker & Sprague, 2007). Education can go awry or fail in particular instances, but special education, to a greater extent than general education, succeeds with exceptional learners. Statistical prediction suggests that, for most students with disabilities, receiving special education produces more positive outcomes than does not receiving special education (see Carlberg & Kavale, 1980; Stage & Quiroz, 1997; Hanushek, Kain, & Rivkin, 2002, for statistical studies; Kauffman et al., 2002, for a descriptions of special education classes and their outcomes). Of course, special education can be poorly implemented, in which case it is reasonable to expect less favorable outcomes (see Kauffman, 2008). In fact, one can ﬁnd anecdotes illustrating the failure of general education, which does not suggest the overall failure of general education any more than anecdotes illustrating special education’s failure are convincing evidence of its overall failure.

Substantial but not Pervasive Degradation of Program or Practice Degradation of program and practice has without doubt occurred in special education. In fact, special education practice today often is not what it should be or what it originally claimed to be (and perhaps was at one time; see Kauffman, 2008; Zigmond, 1997). As conceptualized originally, it was simply education designed to meet the needs of the individual student in whatever venue the student was placed, neighborhood school and regular classroom included. It was to be individualized so as to provide the student with opportunities designed to make maximum use of the student’s abilities (see Kauffman, 1981; Kauffman & Landrum, 2006, 2007; Kauffman, Mock, Tankersley, & Landrum, 2008 for historical perspective). Perhaps special education’s degradation can be attributed in part to the demand that it be universally available within a relatively short time. That is, when the federal law that is now Individuals with Disabilities Education Act (IDEA) was enacted in 1975 (as Public Law 94-142, the Education of All Handicapped Children Act) it demanded extraordinarily fast growth in special education to meet its requirement that public schools serve all handicapped children by 1978. Nearly any program, whether social or material, that undergoes very rapid expansion suffers degradation in its output or product (see Hirschman, 1986; Kauffman, Lloyd, Astuto, & Hallahan, 1995). The federal requirement that all handicapped children be

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served by special education within three years contributed to the need of school systems to hire more special education teachers with inadequate preparation and otherwise to focus on legal compliance rather than on good teaching. Such practices continue. One might argue that schools were unlikely to provide special education for children with disabilities unless they were forced by law to do so and that laws and regulations do not preclude good education. Nevertheless, in a period of very rapid expansion and in the scramble to meet legal requirements, it is undoubtedly true that special education teachers were often ill-prepared and that educational services to children with disabilities suffered serious degradation. Perhaps one indication that this problem has not been adequately addressed is the fact that even today many special education teachers are not certiﬁed or endorsed by the state to teach children with disabilities. The question remains: Regardless of its heritage and the humanitarian impulses under which it was launched, is special education today a malicious enterprise, one that is known to harm students? Certainly, one can ﬁnd instances in which special education is poorly, even malevolently practiced, but this is true of any intervention one can name, even interventions in Western medicine and the ministrations of other professions that usually help people. The evidence suggests substantial but not pervasive degradation in special education’s programs and practices. Perhaps the focus of critics would better be on speciﬁc practices that are unjustiﬁed rather than special education as an idea.

Setups for False Accusations of Malice Misrepresentation of fact. Some accusations of malice are based on outright misrepresentations of fact, such as the following: What is known about the education of students labeled as handicapped? First, separate special education does not work. It does not do so by any measure of assessment – learning, development of self-esteem and social skills or preparation as student, worker, or citizen. Its failure is costly in several currencies – in dollars, in public conﬁdence and, most importantly, in students’ lives. (Gartner & Lipsky, 1989, p. 26)

This quotation seems to suggest that special education does not ‘‘work’’ if it is ‘‘separate’’ (whatever ‘‘works’’ and ‘‘separate’’ may be interpreted to mean) but does (or may?) ‘‘work’’ if it is not separate. There are no data showing that special education ‘‘works’’ only when it is not ‘‘separate.’’

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However, some data do suggest that special education can ‘‘work’’ (by the very criteria Gartner and Lipsky suggest – learning, development of selfesteem and social skills and preparation for being a student, worker, or citizen), when it is ‘‘separate’’ by any reasonable criterion (see Kauffman et al., 2002; Hallahan et al., 2009; Kauffman & Hallahan, 2005). Hyperbole and statements not grounded in reality are unhelpful and, in fact, can exacerbate social injustice, including racism. For example, Landsman (2001) refers on pages 111 and 157 of her book to racial (and racist) practices that apparently do not exist in special education. She states that she will work with others to get rid of ‘‘the practice of tracking all students of color into Special Education’’ (p. 157). No school in the United States is allowed by law to engage in such practices, and I have been unable to ﬁnd any evidence that such a practice exists. Landsman also refers to ‘‘automatically referring all Latino/a students to special education’’ (p. 111), something that apparently does not exist in policy or practice. It may be relevant to note that Hispanic students have been shown not to be overrepresented in special education (Donovan & Cross, 2002). Certainly, institutionalized racism – actually, racism per se – is a great evil, and it should be eliminated to the greatest extent possible in every facet of society, including special education. Harry and Klingner (2006, 2007) also misrepresent some of the facts regarding special education. For example, they inﬂated by approximately a factor of 5 the level of special education services to students (or the risk for being identiﬁed as needing special education) in the category of emotional disturbance or emotional and behavioral disorders (ED or EBD). In fact, they reported information obviously discrepant from the source they cited (Donovan & Cross, 2002) in support of their statement. Their statement about the level of service to students with EBD is also contradicted by all of the annual reports to Congress on implementation of the federal special education law since 1975. Moreover, Harry and Klingner give the impression that all minorities or ‘‘children of color’’ are overrepresented in special education, whereas the data show that in some categories the identiﬁcation rates of some minority ethnic groups approximate those for White students (Donovan & Cross, 2002). In fact, the data show that in some categories (e.g., ED) some ethnic groups that might be considered ‘‘children of color’’ (Hispanic and Asian/Paciﬁc Islander) are underrepresented in special education by a considerable margin. There is, indeed, school-to-school and state-to-state variation in proportionality of representation, but research indicates that some of the ‘‘judgmental,’’ highincidence categories about which Harry and Klingner have the most

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negative commentary are among the least variable from state to state (Hallahan et al., 2007). In any case, the charge that all ‘‘children of color’’ or all minority groups are overrepresented in special education is simply false (see also Kauffman, Mock, & Simpson, 2007). Misrepresentation of intention. Harry and Klingner (2007) suggest that special education is a way of letting general education off the hook. ‘‘The truth is that the law’s provision of disability categories for students who have learning and behavioral difﬁculties has become a way for schools to dodge their responsibility to provide high-quality general education’’ (p. 20). They appear to argue that special education is not really necessary for most of the students who receive it; it is just that general education is lacking, and children are therefore wrongly identiﬁed as having a ‘‘disability.’’ They offer the opinion that minority students are disproportionately identiﬁed for special education in part because identiﬁcation procedures are ambiguous and subjective, yet do not discuss the arbitrary and subjective aspects of identifying culture, ethnicity, or race. Finally, Harry and Klingner (2007) offer the false suggestion that children can be served without labels and recommend that children’s problems not be described as pathologies or deﬁcits but, rather, be seen as variations that can be identiﬁed by their response to intervention (RTI). Probably, service without labels is impossible (Kauffman, 2003, 2008). Moreover, RTI in no way resolves the problem of identifying and labeling students who need more help than is typical. Furthermore, RTI merely conﬁrms that the problem resides in the child, not the instruction offered to most students, as the child is identiﬁed as being unresponsive (a child problem) to good instruction (a good environmental condition). Few critics consider seriously the outcomes indicating that education, general or special, ‘‘works’’ (see Kauffman, 1990, 2002; Kauffman & Konold, 2007). That is, what would or should special education intend regarding the statistical distribution of outcomes, were it to be judged successful? Would the outcome be more or less variance or no change in variance, and what would be the shape of the distribution of outcomes (i.e., would there be no change in the symmetry of the distribution or, predictably, more or fewer scores above the mean – a positive or negative skew)? Some people may consider such questions too esoteric, but these are relatively simple mathematical–statistical concepts. Besides, they are the basic stuff with which policy makers and critics of education must deal if they are to make sense, not merely mouth platitudes and hurl groundless accusations. So far, policy makers and critics of general and special education seem to have gotten away with thinking very poorly about such fundamental issues or with

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not thinking about them at all (Kauffman, 2002, 2005, 2008; Kauffman & Konold, 2007). If education is to be improved, however, then the level of thinking about it will have to be considerably deeper than that exhibited so far by legislators and would-be reformers. A basic notion in philosophy and work for social justice is that it is nonsensical, not to mention unfair, to expect someone to do something that he or she simply cannot do. That is, we must assume that saying someone ought to do such-and-such implies that they can, in fact, do it. And a basic notion involving critical thinking is that one ought to be able to recognize what is simply impossible on the basis of logical deduction (implied, of course, is that the individual who ought to think critically about a matter can do so). Furthermore, critical thinking (and responsible writing) about any topic requires not only deﬁnition of terms but recognition of the fatuousness of calling for what already exists. But, then, what can be said of condemnations that special education ‘‘plays a sorting role’’ (something that, by simple logic, it must do; see Kauffman, 2008) or that it results in labeling (the alternative to labeling is simply not to talk about disabilities; see Kauffman, 2003) or that it is ‘‘separate’’ (special education cannot exist if it is not in any way separate; see Kauffman et al., 2008) or that it should be ‘‘integrated’’ (a term seeming to mean that special education should be indistinguishable from general education, meaning that special education could not exist; see Kauffman & Hallahan, 1993) or that it should be ‘‘reconceptualized as a service, not a place’’ (something stated by critics who apparently do not acknowledge the fact that special education has always been so conceptualized; see Kauffman & Hallahan, 2005)? Such condemnations are offensively illogical, fatuous, and serve only to puff up critics with a false sense of purpose and to damn special education for what it must be by deﬁnition. One of the most egregious setups for false accusations of malice is to compare educational outcomes (e.g., achievement test scores, employment) for children with disabilities to those without disabilities (Kauffman, 2008). This comparison is not only witless but results, reliably and entirely predictably, in portrayal of special education as a failure. Those who make such comparisons are either unable or unwilling to come to terms with the meaning of disability in education and to think clearly about comparisons that make sense. They seem determined to cast aspersions on special education, regardless of its merits, because the conclusion that special education has failed is utterly predictable if one accepts the premise on which their criticism is based. The difﬁculty of teaching children with disabilities is very often underestimated by both special educators themselves and others. Most disabilities

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are life-long conditions; there are no cures in the vast majority of cases, and spontaneous remissions are rare. Thus the expectation that a high percentage of children who are identiﬁed as having a disability and are receiving special education should lose their identity as having a disability is ﬂagrantly unrealistic, and charges that special education is a failure because relatively few students exit special education is a set-up. It is a set-up as surely as the expectation that educators should be able to teach so well that fewer than 25 percent of children fall below the 25th percentile on standardized tests.

Components of Special Education Programs and Procedures The foregoing discussion involves special education in the general case. However, special education is made up of many component programs and procedures, each of which must be subjected to the same type of evaluation of accusations of malice as the more general program of special education. For example, instructional components or elements of special education such as mnemonic training, self-monitoring and other self-control procedures, direct instruction, and various behavior management procedures must be evaluated by the standards or decision model applied to the more general enterprise. Some components of special education are likely to fare quite well in any application of the proposed decision model. Others may not fare well and be suspected of malice because they are unsupported by any body of reliable scientiﬁc data and can on no reliable grounds be supported as having produced or as being likely to produce positive outcomes.

Individuals and Groups in Judgments of Malice The foregoing discussion has dealt with the typical effects or outcomes of programs, such that mean effects are assumed to be representative. In a sense they are, just as they are, in an important sense, for drugs or regimens based on physiology. For example, mean effects are important in judging the effectiveness of drugs or the effects of foods or exercise, but it is always important also for the practitioner to observe effects on individuals. A physician may realize that although an antibiotic drug is effective in promoting health in most patients, it is nevertheless toxic for an individual; a teacher may observe that although an instructional program generally produces favorable results, it is nonetheless ineffective for a particular

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student. Thus, educators must be aware that although no malice may be found in a program when used with most students, continuing to use the program with an individual student for whom it is known to be ineffective or worse may in fact be malicious. Seldom or never will a program be found effective for an individual but for no other student. Anecdotal data remain mere anecdotes until a program is tested with a larger group with known characteristics. Far more often, a program that has been tested and found effective with a larger group will be found ineffective with an individual. Perhaps it is a truism that nothing works in all cases, but it is also true that useful research tests the circumstances under which a given proposition is true or, in the case of education, the student characteristics deﬁning a group for which a given program is effective. The proposed decision model should be applied to both groups and individuals.

PART V. CONCLUSIONS Conclusions Regarding Malice in Special Education Policy and Practice The arguments that special education for children with disabilities is malicious are based on criteria that are not sufﬁcient to sustain a charge of malice. True, special education has been depicted as a failure that hurts children and requires unreasonable expenditures of those who fund it. That is, numerous accusations of malice have been made about special education, but none is supportable for special education in general on the basis of evidence or logic. Malice is attributable to special education only by means of the set-up – by false accusations derived from inappropriate comparisons, unreasonable expectations, and assertions that are not grounded in realities. Special education is not beyond criticism. Nevertheless, the ideas and attitudes toward exceptionality that undergird it are entirely justiﬁed, not malicious. We should resolve to make special education better so that it becomes more consistently and dependably the kind of beneﬁt we want it to be and the kind of help that parents will demand for children with exceptionalities.

ACKNOWLEDGMENT I am grateful to Jean B. Crockett for her many helpful suggestions during my preparation of this chapter.

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RESPONSE TO INTERVENTION: A REALITY CHECK Amanda Kloo and Naomi Zigmond ABSTRACT In this chapter, we describe the policy and practical decisions one school district and school had to make to implement a progress monitoring and Response to Intervention (RtI) model in an historically low-achieving school with a substantial population of students at risk tfor academic failure – characteristics that are common to many public schools across the nation. We contrast the lofty goals and theoretical orientations of RtI described in a burgeoning literature in special and general education with the ‘‘real life’’ burdens of capacity, resources, time, and school culture in a struggling school.

Proﬁcient reading skills are critical not only to success in school, but also to successful post-school outcomes. Students with poorly developed basic reading skills in the primary grades are placed at a signiﬁcant disadvantage in subsequent grades. Empirical evidence has suggested that the 3rd grade, and possibly even the 2nd grade, is too late for classroom instruction to have a signiﬁcant impact on reading acquisition (Chard & Kame’enui, 2000). Felton and Wood (1992) report that children who failed to demonstrate strong reading skills in the 1st grade had a 90% chance of remaining poor readers, even after three subsequent years of instruction. Policy and Practice Advances in Learning and Behavioral Disabilities, Volume 22, 67–105 Copyright r 2009 by Emerald Group Publishing Limited All rights of reproduction in any form reserved ISSN: 0735-004X/doi:10.1108/S0735-004X(2009)0000022005

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These ﬁndings replicate earlier evidence that there is a high probability (0.88) that students identiﬁed as poor readers at the end of the1st grade will also be so identiﬁed at the end of the 4th grade (Juel, 1988) and students identiﬁed as average readers at the end of the 1st grade have an equally high probability (0.87) of remaining so at the end of grade 4 (Juel, 1988). Reading failure, however, is not inevitable, and it can be prevented if identiﬁed early and treated vigorously (National Institute of Child Health and Human Development, 2000; National Research Council, 1998). Reading achievement of low-performing and at-risk students can be raised to grade-level expectations within the ﬁrst three years of school with appropriate instruction and timely interventions (Chard & Kame’enui, 2000; Coyne, Kame’enui, & Simmons, 2001; Good, Simmons, & Kame’enui, 2001; Torgeson, 2000; Torgeson et al., 2001). Moreover, early identiﬁcation and early intensive interventions can positively alter students’ reading trajectories (National Research Council, 1998; Torgeson et al., 2001). Building on these data, recent educational reform initiatives have focused on preventing students from falling behind in the ﬁrst place. Through the No Child Left Behind Act (NCLB, 2001) and the Individuals with Disabilities Education Improvement Act (IDEA, 2004), schools have been charged with the daunting task of developing schoolwide reading programs that begin in the early grades and prevent reading failure from taking hold. They have been encouraged to use progress-monitoring tools like oral reading ﬂuency measures to ensure the success of these prevention models. Progress monitoring involves evaluating student progress toward the acquisition of basic skills that are globally reﬂective of instruction within a curriculum (Deno, Fuchs, Marston, & Shinn, 2001; Shinn, Shinn, Hamilton, & Clarke, 2002; Stecker & Fuchs, 2000). Progress monitoring is a standardized procedure conducted repeatedly over time that provides information relevant to making decisions regarding student achievement (Deno, Espin, & Fuchs, 2002; Fuchs & Deno, 1991; Fuchs & Fuchs, 1999; Fuchs, Fuchs, Hosp, & Jenkins, 2001; Shinn et al., 2002). Progress monitoring can be used to create instructional groups (e.g., Fuchs, Fuchs, Bishop, & Hamlett, 1992), identify speciﬁc skill deﬁcits (e.g., Fuchs, Fuchs, Hamlett, & Allinder, 1991; Whinnery & Stecker, 1992), screen students for potential early school failure (e.g., Speece & Case, 2001), assist in eligibility decision-making (e.g., Shinn & Habedank, 1992), and evaluate the re-integration process for students moving from special to general education settings (e.g., Shinn, Powell-Smith, Good, & Baker, 1997). Progress monitoring has value when used with all students, including those

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at risk for academic problems, those already identiﬁed to be in need of special education, and those progressing adequately in general education. Progress monitoring has multiple components: establishing and measuring academic goals, providing a vehicle for understanding how students are progressing toward established goals, creating opportunities for class-, school-, and/or district-wide screening to identify students potentially at risk for academic failure, and offering data that can provide accountability evidence to parents, teachers, and educators about the impact of intervention programs. When progress monitoring is done on a frequent basis, it offers students a chance to see how they are moving toward goals, offers them a clearer understanding of the impact of the instruction they are receiving, and acts as a superb vehicle for communicating with parents (e.g., Fuchs, Fuchs, Hamlett, & Whinnery, 1991; Hosp & Hosp, 2003). Consistent with the requirements of laws such as NCLB (2001) and IDEA (2004) progress monitoring provides the careful link between assessment and the instructional process. Teachers who use progress-monitoring data plan more effective instruction and achieve greater student outcomes than those who do not (Fuchs, Fuchs, & Hamlett, 1989). Indeed, when progress-monitoring data are used by teachers to inform their modiﬁcations of instruction, outcomes are even higher than when the monitoring process alone is used (Capizzi & Fuchs, 2005; Fuchs, Butterworth, & Fuchs, 1989). Essentially the purpose of progress monitoring is to improve student performance. Progress monitoring using a general outcomes measurement approach has been around for over two decades (Fuchs & Deno, 1991; Shinn, 1989). Recently, however, the progress monitoring methodology has been redeﬁned for use in the identiﬁcation of students with learning disabilities and has led to the development of the Response to Intervention (RtI) model in which student eligibility for special education services is a function of the students’ non-responsiveness to high quality interventions (e.g., Bradley, Danielson, & Doolittle, 2005; Shinn & Habedank, 1992; Speece & Case, 2001; Speece, Case, & Molloy, 2003; Vaughn, Linan-Thompson, & Hickman, 2003). Although substantial research and development on the RtI model is still needed (e.g., Kavale, Holdnack, & Mostert, 2006), the use of progress monitoring within the RtI model appears to be unquestioned (e.g., Fuchs, Fuchs, & Compton, 2004). In August 2006, Zigmond and colleagues at the University of Pittsburgh and Shapiro and colleagues at Lehigh University responded to a call for proposals to document and evaluate the implementation of a progress monitoring model aimed at improving grade K-4 reading achievement. The project, Project MP3: Monitoring Progress of Pennsylvania Pupils,

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funded through the US Department of Education’s Ofﬁce of Special Education Programs, provided a unique opportunity to study progress monitoring and RtI adopted and adapted to a real-world context. The implementation of this new prevention-oriented policy initiative in one elementary school in Western Pennsylvania is the focus of this chapter. We will describe the policy and practical decisions this district and school had to make to implement progress monitoring and RtI in a historically low-achieving school with a substantial population of students at risk for academic failure – characteristics that are common to many public schools across the nation. We will contrast the lofty goals and theoretical orientations of RtI described in a burgeoning literature in special and general education with the ‘‘real life’’ burdens of capacity, resources, time, and school culture in a struggling school. Our goal is to demonstrate the value of an RtI orientation even if the model cannot be implemented with ﬁdelity and cannot, by itself, ‘‘turn a school around.’’

THE CONTEXT The Model Fig. 1 summarizes the MP3 model implemented in Western Pennsylvania and its relationship to Pennsylvania’s recommended RtI framework. The model is based on a three-tiered framework for reading instruction in kindergarten through 4th grade (Reschly, 2005; Vaughn Gross Center for Reading and Language Arts, 2005) (Fig. 1). In Tier One, all students are provided research-based grade-level reading instruction and all students are screened three times per year as part of primary prevention. Supplemental Tier Two intervention is provided for a subset of students who have not yet met benchmark goals, thereby demonstrating that Tier One core instruction alone is not sufﬁcient; those students’ reading skills are monitored at least twice per month. Supplemental Tier Three intervention is provided for a much smaller subset of students who are performing well below grade-level and appear to need more intensive reading support. Like most RtI models in the literature, this one shows instructional group size decreasing and instructional intensity increasing as students ‘‘move up’’ the pyramid, in order to halt and reverse reading failure as quickly as possible (Fig. 1). In the Pennsylvania version of this RtI model, special education is not a separate tier; given the state’s strong commitment to inclusion, students with disabilities may receive specially designed reading instruction at any tier.

RtI: Reality Check

Fig. 1.

71

Relationship between the MP3 Progress Monitoring Model Implemented in Western Pennsylvania and Pennsylvania RtI Framework.

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Students who are referred for special education services tend to have failed to adequately respond to either Tier Two or Tier Three interventions, or to both. Once referred, a multi-disciplinary evaluation is conducted and eligibility for special education services determined. In Pennsylvania, districts may choose to use an RtI approach to identify a speciﬁc learning disability in lieu of an assessment to determine an ability–achievement discrepancy. Students already eligible to receive special education and related services as well as students newly placed in special education still receive large group grade-level Tier One instruction. And, they still participate in instructionallevel Tier Two or Tier Three interventions, with progress monitoring linked to their Individualized Educational Program (IEP) goals.

The District Table 1 summarizes demographic and achievement data for the Alliance School District, the Western Pennsylvania host of the MP3 project. Alliance is a small school district with a kindergarten center, six elementary schools (two 1–8, two K-6, two K-5), one middle school (6–8), and one high school (9–12). The district is led by a committed and passionate Table 1.

2006 Demographics and Reading Achievement Data.

Alliance School District Enrollment Minority Free/reduced lunch % Proﬁcient 4th grade state test % Proﬁcient 3rd grade state test Larue School (Grades 1–5) Enrollment Minority Free/reduced lunch % Proﬁcient/advanced 4th grade state test % Proﬁcient/advanced 3rd grade state test

3,512 20% 53% 55% 56% 252 58% 92% 21% 29% Grade

% Above 40 percentile on IOWA reading subtest % ‘‘Low risk’’ on DIBELS ORF % ‘‘Average/above’’ on Maze

1 27

2 12

3 33

4 38

18 –

10 21

12 10

2 13

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RtI: Reality Check

superintendent who embodies many of the leadership qualities that research has shown to be closely related to sustained use of research-based reading practices (Klingner, Vaughn, Hughes, & Arguelles, 1999). His relentless and very vocal support for system-wide reading instruction improvement was a key factor in promoting administrator and faculty buy-in, ﬁdelity of implementation, and sustainability of the MP3 model. At early meetings with the superintendent in January 2006, he expressed concerns about the district’s elementary-level reading program; his recent review of endof-year achievement data showed steady declines in scores over a ﬁve-year period, particularly in grades 3 through 5. Moreover, the percentage of students achieving proﬁciency in the state accountability assessment in reading varied widely across the six elementary schools in the district from 87% Proﬁcient 5th graders in the top school to 13% Proﬁcient 5th graders in the bottom school. The superintendent volunteered the three lowest elementary schools to participate in the MP3 project and suggested that the project begin its work in the lowest achieving school, Larue Elementary. Administrators, teachers, and school board members agreed that Larue was in desperate need of what they called ‘‘intensive educational intervention’’ to break a dangerous cycle of academic and behavioral failure. School and classroom visits conﬁrmed the dismal state of academics, discipline, and motivation at the school and Larue Elementary became the pilot site for our project.

The School To establish baseline performance levels in reading, a team of researchers administered the DIBELS (Dynamic Indicators of Dynamic Literacy Skills; Good & Kaminski, 2002) and the Reading Maze (Shinn & Shinn, 2002) assessments to all students in grades 1–4 and 2 –4, respectively. Results showed fewer than 20% of students achieving at benchmark on the DIBELS ORF measure in the 1st grade, and only 2% ﬂuent readers at the 4th grade level. On the Iowa Tests of Basic Skills (Hoover, 2001), only 12% of the 2nd graders scored above the 40th percentile. On the MAZE measure, only 10% of the 3rd graders scored at Average or Above Average (Table 1). During the spring of 2006 (March through May), the research team visited Larue Elementary two or three days each week and talked with teachers, spent time in classrooms, interviewed the principal, met with district administrators, and observed reading instruction across grades 1–4. Curriculum staff reported that the district taught a ‘‘balanced literacy

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AMANDA KLOO AND NAOMI ZIGMOND

curriculum’’ in which instruction was centered on implementing Guided Reading (Fountas & Pinnell, 1991) to small groups or pairs of students using instructional-level material with a supplemental introduction of the weekly focus skills as outlined in the Harcourt Trophies (Beck, Farr, & Strickland, 2003) reading series. While the Guided Reading framework seemed to be working successfully in some elementary schools, as evidenced by their high numbers of proﬁcient students, this was clearly not the case for Larue. Classroom visits and teacher interviews revealed that reading instructional times varied from 40to 90 min per day across classrooms in Larue, depending on the proﬁciency level of the students, the number of small groups the teacher organized, and the classroom management skills of the teacher in balancing small group teacher-led instruction using leveled books with the rest of the class working independently at learning centers. Teachers reported that often, some reading groups would not receive any teacher-led reading instruction for days at a time because of the rotation schedule or schedule adjustments dictated by vacation days, snow days, special school events, or another group’s level of need. When things went smoothly, the weekly focus skills were introduced on Monday and reinforcement activities were assigned as homework or included as practice pages to be worked on at the learning centers for the rest of the week. Most weeks, however, Monday focus skills instruction occurred haphazardly or not at all. During the spring of observations and interviews at Larue, not a single grade 1–4 teacher was observed (or when interviewed reported) teaching a focus skill lessons detailed in the Trophies manual. Teachers explained that the Trophies series’ materials did not support the Guided Reading framework. Furthermore, in most classrooms of 20þ students there were only six Trophies student anthologies available and these were assigned at a listening center for use during Guided Reading time. None of the teachers had a complete class set of any student practice books or student anthologies. Instead, students were exposed to a variety of texts, encouraged to explore literature, and discover concepts about print; code-based reading instruction and explicit strategy instruction occurred only incidentally. The teaching staff at Larue Elementary were not a happy group. More than 85% of the faculty felt that the Guided Reading curriculum was not effectively or comprehensively meeting students’ needs. Only the special education teachers expressed any familiarity with progress monitoring or curriculum-based measurement practices beyond the use of running records to assign leveled books for small-group instruction. None of the teachers had been exposed to or been trained in the National Reading Panel’s ‘‘5 Big Ideas’’ (2000) of reading instruction. Nearly 80% of the teachers had

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RtI: Reality Check

graduated from the local state college teacher preparation program that was ﬁercely committed to a whole language-based approach to reading instruction. More than 80% of teachers believed that they were ‘‘not allowed’’ to teach phonics rules or explicit reading strategies to their students because these practices conﬂicted with the whole language ideologies of powerful district administrators. More than 80% of the teachers also believed that their students’ deﬁcient reading skills were due to ‘‘child-centered’’ factors over which they had no control (e.g., socio-economic status, race, limited parental involvement, lack of motivation, behavior problems, poor attitude, cognitive deﬁcits etc.) rather than ‘‘instructionally-centered’’ factors which they could manipulate. There were very few opportunities during the school day for classroom teachers to talk with one another either within a grade level or across grade levels. About 95% of teachers at Larue Elementary had been there for less than ﬁve years, and 65% of the teachers were recent district hires.

GETTING STARTED Before school started in the 2006–2007 school year, the Larue principal was reassigned to the high school and a new principal was appointed to Larue Elementary. This was her ﬁrst assignment as a principal and she enthusiastically embraced the challenge. The principal changed the school motto to ‘‘This School Reads!’’ and planned for schoolwide reading incentives and events to promote literacy and engage students and parents with reading data and achievement. Daily schedules were revised to include 120 min reading blocks at each grade level and common planning time was scheduled to accommodate grade-level meetings and collaboration. Monthly schoolwide ‘‘data review meetings’’ were put on the calendar. The superintendent and the director of Title One reassigned remedial reading staff from more-achieving elementary schools to Larue to make a larger teaching force available for small-group interventions. And, the district hired a ‘‘literacy coach’’ to support improved reading instruction and effective model implementation at Larue. The Director of Special Education mandated that special education teachers revise IEPs to link reading goals to progress monitoring data and intervention instruction. For the ﬁrst time in many years, professional development days were scheduled before the start of school. The Director of Curriculum, the principal, the local Intermediate Unit, and the Pennsylvania Training and Technical Assistance Network collaborated on planning reading and RtI workshops on district

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AMANDA KLOO AND NAOMI ZIGMOND

in-service days and offered voluntary monthly before- and after-school and Saturday trainings. District and building leaders also attended summer professional development training and conferences with MP3 staff about reading instructions and RtI. Finally, the district administrators committed to a long-term partnership with the University of Pittsburgh group to pilot the MP3 progress monitoring/RtI model in 2006–2007, reﬁne and expand implementation to two additional elementary schools during 2007–2008 and 2008–2009, then adopt and sustain the use of the model district-wide once grant funds were depleted. A ﬁve-point model RtI implementation and sustainability plan was drawn up that included: (1) screening and progress monitoring of all students; (2) systematic school, grade, and class-wide, data-based decision-making to improve reading instruction and reading achievement, (3) multiple tiers of intervention intensity for students at risk for reading failure, (4) a special education referral process integrated with RtI, and (5) ongoing professional development in research-based reading and assessment practices. Each of these points would be tackled gradually with our help over the three years of the model demonstration project. Before the sun’s rays waned on the last day of summer vacation, teacher plan books and ofﬁce walls were plastered with the MP3 model and RtI pyramid. The need was great, the goals were ambitious, and the plan was clear! That is, until the reality of life in a struggling school sunk in. Our work at Larue Elementary would be a model demonstration project in its truest form; it would provide a sobering window into model development and policy issues critical to RtI implementation.

THEORY INTO PRACTICE: MP3 COMES TO LARUE ELEMENTARY SCHOOL RtI IN THEORY 1. The ﬁrst tier of the RtI pyramid, or primary intervention, is grounded in ‘‘generally effective’’ reading instruction using a research-based core curriculum (NASDE, 2005).

RtI in Practice 1. Student achievement data from spring 2006, and additional data collected as school started in fall 2006, did not ﬁt the standard RtI pyramid. Instead

RtI: Reality Check

77

of 80% of students achieving ‘‘Benchmark’’ levels of proﬁciency on the DIBELS and needing only Tier One instruction, at Larue 65% of students scored within the ‘‘At Risk’’ range and were in need of the intensive interventions typically associated with Tier Three (see Fig. 2). The RtI pyramid was essentially inverted. Our ﬁrst undertaking was to revamp Tier One, the general reading curriculum, and we persuaded the district to adopt a core reading series, Harcourt Trophies. The series and the accompanying instructional materials and teachers’ guides arrived only days before school opened in the fall, so there was only one day of training for the classroom teachers on implementing the new series. Research staff and local educational consultants continued to help the teachers use Trophies in their daily 60–90 min reading block through coaching and consultation and by developing templates for ﬁve-day teaching units using the Trophies materials. Denton, Vaughn, and Fletcher (2003) assert that high quality general classroom instruction (like that needed to achieve 80% proﬁciency in Tier One) is the coordinated effort of teacher preparation, pre-service and in-service training, researchers, legislators, and schools systems. In short, it is multifaceted, time consuming, and challenging. The challenge is even greater, we discovered, in a school district (and state) strongly committed to full inclusion or at least placement of all students with learning disabilities, behavior disorders, and mild to moderate mental retardation in the general education classroom on grade-level for core reading instruction. The two special education teachers were deployed to co-teach during core reading instruction. One rotated 30 min stints in the four 1st grade classrooms, the three 2nd grade classrooms, and the three 3rd grade classrooms. The second divided her time among the three 4th grade classrooms and the three 5th grade classrooms. By October, all Larue 1–5 grades teachers were using the core-reading program with some level of ﬁdelity. Larue was on a better track, but the train was clearly not ready to leave the station! Some would argue that Larue was simply not ‘‘ready’’ to implement RtI and that we should have waited until the core had been effectively delivered and the distribution of students was closer to the theoretical 80% meeting benchmark goals before continuing with model implementation. However, we were committed to improving reading instruction through use of progress monitoring and data analysis. Once teachers would begin to look at data, there needed to be, in place, some way of differentiating instruction for students ‘‘falling behind.’’ Moreover, we considered recent National Assessment of Educational Progress (NAEP) statistics (NAEP, 2005) that

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AMANDA KLOO AND NAOMI ZIGMOND

School Population

Distribution 1: RtI in Theory – Tier 1 (80%), Tier 2 (15%) Tier 3 (5%) 1%

1%

.5

1% 1% 1% 1% 1% 1% 1% 1% 1%

1% 1% 1% 1% 1% 1% 1% 1% 1%

1% 1% 1% 1% 1% 1% 1% 1% 1%

.5

1%

1%

1%

1%

.5

1% 1% 1% 1% 1% 1% 1% 1% 1%

1% 1% 1% 1% 1% 1% 1% 1% 1%

1% 1% 1% 1% 1% 1% 1% 1% 1%

1% 1% 1% 1% 1% 1% 1% 1% 1%

1% 1% 1% 1% 1% 1% 1% 1% 1%

.5

1%

1%

1% 1% 1% 1% 1% 1% 1% 1% 1%

1% 1% 1% 1% 1% 1% 1% 1% 1%

School Population

Distribution 2: Larue Elementary at Baseline – Tier 1 (10%), Tier 2 (23%) Tier 3 (67%) 1%

1%

1%

1%

1%

1%

1%

1%

1%

1%

1% 1% 1% 1% 1% 1% 1% 1% 1%

1% 1% 1% 1% 1% .5 .5 1% 1% 1%

1% 1% 1% 1% 1% 1% 1% 1% 1%

1% 1% 1% 1% 1% 1% 1% 1% 1%

1% 1% 1% 1% 1% 1% 1% 1% 1%

1% 1% 1% 1% 1% 1% 1% 1% 1%

1% 1% 1% 1% 1% 1% 1% 1% 1%

1% 1% 1% 1% 1% 1% 1% 1% 1%

1% 1% 1% 1% 1% .5 .5 1% 1% 1%

1% 1% 1% 1% 1% 1% 1% 1% 1%

School Population

Distribution 3: Larue Elementary at End of Year 1 – Tier 1 (24%), Tier 2 (24%) Tier 3 (52%) 1% 1% 1% 1% 1% 1% 1% 1% 1% 1%

1% 1% 1% 1% 1% 1% .5 .5 1% 1% 1%

1% 1% 1% 1% 1% 1% 1% 1% 1% 1%

1% 1% 1% 1% 1% 1% 1% 1% 1% 1%

1% 1% 1% 1% 1% 1% 1% 1% 1% 1%

1% 1% 1% 1% 1% 1% 1% 1% 1% 1%

1% 1% 1% 1% 1% 1% 1% 1% 1% 1%

1% 1% 1% 1% 1% 1% 1% 1% 1% 1%

1% 1% 1% 1% 1% 1% .5 .5 1% 1% 1%

1% 1% 1% 1% 1% 1% 1% 1% 1% 1%

School Population

Distribution 4: Larue Elementary at End of Year 2 – Tier 1 (40%), Tier 2 (26%) Tier 3 (34%)

KEY:

Fig. 2.

1% 1% 1% 1% 1% 1%

1% 1% 1% 1% 1% 1%

1% 1% 1% 1% 1% 1%

1% 1% 1% 1% 1% 1%

1% 1% 1% 1% 1% 1%

1% 1% 1% 1% 1% 1%

1% 1% 1% 1% 1% 1%

1% 1% 1% 1% 1% 1%

1% 1% 1% 1% 1% 1%

1% 1% 1% 1% 1% 1%

1% 1% 1% 1%

.5 .5 1% 1% 1%

1% 1% 1% 1%

1% 1% 1% 1%

1% 1% 1% 1%

1% 1% 1% 1%

1% 1% 1% 1%

1% 1% 1% 1%

.5 .5 1% 1% 1%

1% 1% 1% 1%

Students performing at High Risk on DIBELS Benchmark testing Students performing at Some Risk on DIBELS Benchmark testing Students performing at or above Benchmark on DIBELS Benchmark testing

Distribution of Students in Grades 1–3: RtI in Theory vs. RtI in Larue Elementary.

79

RtI: Reality Check

only 31% of the nation’s 4th graders read at ‘‘Proﬁcient’’ levels and concluded that Larue’s achievement distribution was not uncommon. We also drew on the research data that show that students who fail to meet Benchmark goals need more than a core-reading program to become proﬁcient readers (see U.S. Department of Education (USDE), 2002). So, we waited six weeks for the teachers to develop a routine for the core reading block, then introduced Tiers Two and Three. RtI IN THEORY 2. In most RtI models, students responding successfully to Tier One intervention (i.e., students reaching grade-level benchmarks) are considered to be ‘‘healthy’’ readers; they do not receive additional reading instruction beyond the core program. While these ‘‘healthy’’ readers are doing something else, small groups of students who are performing below benchmark receive strategic or intensive instruction on deﬁcit skills. These pull-out or pull-aside interventions might be scheduled daily or the groups might meet two, or three, or four days per week.

RtI in Practice 2. At Larue Elementary, space and scheduling were real problems. Because the building housed both elementary (1–5) and middle school (6–8) grades, the school had to rotate breakfast, lunch, recess, and special-subject classes on a very tight schedule so as not to overlap class times or spaces. Furthermore, there were precious few ‘‘healthy’’ readers at Larue Elementary. ‘‘What’’ would those few proﬁcient children do (and ‘‘who’’ would do it with them) while other students received strategic or intensive interventions? The only feasible arrangement was to build ‘‘intervention time’’ into the daily schedule for all students, those at Benchmark, those below Benchmark, and those at serious risk. Beginning in the middle of October, the 60–90 min ‘‘core reading periods’’ were supplemented each day by a 45–60 min ‘‘reading intervention periods’’ scheduled for all elementary-level grades. In this way, all students, all available teachers, and all available instructional spaces could be reorganized for reading interventions at the same time. Problem solved? Not exactly.

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AMANDA KLOO AND NAOMI ZIGMOND

RtI IN THEORY 3. Scores from DIBELS benchmarking tests are used to create instructional groups. Interventions at Tiers Two and Three are distinguished by the size of the instructional group (intensive groups have fewer students than strategic groups); by the duration or frequency of group meetings (intensive groups meet more often for more time than strategic groups); and by the frequency of progress monitoring (students in intensive groups are monitored more often than students in strategic groups). RtI in Practice 3. When grade-level and school-level data teams convened in October to devise fall intervention groups based on screening data, they were shocked by the discrepancy between their students’ needs as deﬁned in the RtI literature and the school’s capacity in personnel, space, and intervention materials. To responsibly address students’ needs and reshape grade-level reading achievement within the reality of the school’s constraints, teacher teams had to work ‘‘from the bottom up’’ in assigning students and teachers to intervention groups. First, to make the best use of instructional staff, the decision was made to create intervention groups across classrooms rather than within them. Next, at each grade-level (1–4), students were rank-ordered based on their DIBELS scores. Then, the list of teaching staff available to provide intervention instruction was created; this included the classroom teachers, the Title One reading specialist(s), the special education teacher(s), and any other personnel not assigned to classroom instruction during the intervention time block. Working from the bottom of the list (i.e., the students with the lowest fall DIBELS scores), homogeneous instructional intervention groups were formed: ﬁrst intensive groups of 3–6 students each, then strategic groups of 8–12 students each. After all but one teacher were assigned to teach the neediest students, that one teacher was assigned to teach ‘‘everyone else.’’ Data teams labeled the ﬁnal large group of the highest achieving 15–25 students ‘‘Benchmark’’ although most students in that group had not actually met grade-level expectations. Table 2 provides a snapshot of the ‘‘grouping’’ decisions (and compromises) made that ﬁrst fall. In the 1st grade, 43 students scored in the ‘‘seriously at-risk’’ range, 16 students scored at the ‘‘strategic’’ level, and 10 students achieved ‘‘Benchmark’’ or higher. In a theoretical RtI model, Larue Elementary would have created 14 intensive intervention groups of 3–4 students each; three groups

7

Total

(Benchmarkþhigh strategic Benchmark 20–25 20 students/1 group or benchmarkþall students strategic) (Low strategicþ‘‘high’’ Strategic 10–12 students 24 students/2 groups intensive or high intensive only) (Lowest intensive) Intensive 5–6 students 24 students/4 groups

1st grade

4 1 1 1

Classroom Title one Special education Other

1st grade

10 students/1 group 16 students/3 groups 43 students/14 groups

1st grade

3rd grade

4th grade

6

3 1 1 1

3rd grade

20 students/1 group

20 students/2 groups

17 students/3 groups

25 students/2 groups

19 students/3 groups

3rd grade

19 students/1 group

2nd grade

4th grade

7

3 2 1 1

4th grade

24/4 groups

20 students/2 groups

21 students/1 group

Number of Students/Number of Groups Possible

6

3 1 1 1

2nd grade

8 students/1 group 4 students/1 group 7 students/1 group 11 students /2 groups 15 students /3 groups 10 students /2 groups 44 students/15 groups 38 students/13 groups 48 students/16 groups

2nd grade

Number of Students/Number of Groups Needed

Example of Necessary Intervention Group Decisions.

Benchmark 20–25 students Strategic 4–6 students Intensive 1–3 students

Resulting Intervention Groups Based on Capacity

Available Personnel

Intervention Level Derived from DIBELS Cut Scores

Table 2.

RtI: Reality Check 81

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of 5–6 students each for strategic instruction, and one group of 10 students performing at Benchmark. To do this they would have needed 18 teachers available for group instruction at the same time. However, only seven teachers were available to teach intervention groups – the four classroom teachers and three specialized staff. So, instead of 14 intensive intervention groups, the data decision-making team arranged for four, and instead of a maximum of three students per group, these were groups of six. Instead of three strategic groups of six students each, the remaining 19 students who scored at the ‘‘intensive’’ level and six of the 16 students who scored at the bottom of the ‘‘strategic’’ level were organized into two instructional groups of 12 students each, and the remaining 10 ‘‘strategic’’ students became part of a benchmark group of 20 students. The same process was used in grades 2, 3, and 4. Although assignment to groups became less arduous over time as students’ reading scores improved and the RtI pyramid began to reshape (Fig. 2), it has never been as straightforward as RtI theory implies. Because of scheduling, personnel, and space constraints, all intervention groups at a particular grade level met daily, and for the same amount of time (45 or 60 min depending on grade level). But even with that concession, students only had a total of 120 min of reading instruction each day (90 min of core plus 30 min of intervention, or 60 min of core and 60 min of intervention, depending on grade level), not the 150–165 min (90 min of core and 60–75 min of intervention) recommended for ‘‘intensive’’ students in some RtI models (Fuchs, Stecker, & Fuchs, 2008; Vaughn & LinanThompson, 2003). Larue Elementary only had a total of 215 min of instructional time available in the school day after accounting for lunch/ recess, one special-subject class, dismissal procedures, and transitions and reading was now scheduled for 55.8% of the day. RtI models suggest allocating as much as 75% of the school day to reading and reading interventions but Larue was already concerned about ‘‘making AYP’’ in mathematics and science, and had no time or staff available to increase instructional time in these areas. To increase the amount of reading intervention time for the lowest achieving readers, target students would have had to miss signiﬁcant portions of special classes, mathematics classes, content area classes, breakfast, lunch, or recess. It could not be done. One additional compromise was required in the Larue RtI implementation. There were only slight differences in the frequency of progress monitoring assessments. Because the majority of students in the Benchmark intervention groups really scored in the strategic range, progress of students in the benchmark groups was monitored two times per month instead of once per month. And because students in both strategic and intensive

83

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groups were at high risk for reading failure, students in both groups were assessed weekly. All these concessions to a tiered instructional model were certainly not ideal; nonetheless, they were necessary given available staff, scheduling, and instructional spaces. RtI IN THEORY 4. Once students are assigned to an intervention group, a standard research-based reading instruction protocol is implemented with ﬁdelity.

RtI in Practice 4. Regardless of which instructional group or level the Larue teachers were assigned to teach, they had to learn a second new reading series while they were still struggling to learn how to use the newly-adopted core reading series effectively. Each intensive and strategic group teacher adopted one of several reading programs, the MP3 project purchased for the school (the district had used up its materials budget with the purchase of the core reading series, K-6, for the kindergarten center and all six elementary schools). Standard protocol interventions were particularly well-suited to Larue teachers who had limited expertise in teaching reading. The sequenced, scripted lessons would ensure instructional integrity and student improvement when implemented with ﬁdelity (Denton, Fletcher, Anthony, & Francis, 2006; Vellutino, Scanlon, Small, & Fanuele, 2006). No standard protocol intervention programs had ever been used in the district prior to model implementation and the direct-instruction nature of the programs was foreign to these teachers who had been trained in whole language and Guided Reading approaches. Formal training plus extensive on-site coaching on the standard protocol materials had to be provided to those who volunteered to participate. Scores on ﬁdelity of implementation checklists developed for each program began low but with a combination of teacher self-monitoring and research team corrective feedback soon hovered at 80–85%. For a small group of teachers, however, ﬁdelity scores were particularly variable. These were teachers who found the ‘‘packaged’’ materials to be useful, practical, and efﬁcient, but also frustrating; they wanted to ‘‘own’’ the implementation of the standard protocol and make adaptations and modiﬁcations that were not sanctioned. Those teachers frequently modiﬁed the standard protocols on their own, sharply decreasing their ﬁdelity ratings.

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Instruction for the ‘‘Benchmark’’ groups, however, was not standardprotocol based. Instead, Benchmark group teachers tried to reinforce and re-teach core skills using the supplemental programs provided by Harcourt Trophies, and used partner/repeated reading practice and cooperative learning activities (e.g., Literature Circles (Daniels, 2002); Readers Theater (Grifﬁth & Rasinski, 2004) to pass the time. Again, this complicated ﬁdelity/ integrity measurement. RtI IN THEORY 5. Most proposed RtI models recommend that a trained reading specialist, Title One teacher, or special educator provide Tiers Two or Three reading interventions.

RtI in Practice 5. As displayed in Table 2, 16 teachers were needed, theoretically, to provide Tiers Two and Three interventions to more than 50 students in Grade 3 falling below DIBELS Benchmark cut-points for their grade level (Table 2). But only three classroom teachers, one special education teacher, one Title One teacher, and the Literacy Coach were available to teach 3rd grade interventions. First, the special education teacher, Title One teacher, and Literacy Coach were assigned to intensive intervention groups of six students each, assigning the highest-skilled teachers to the lowest-skilled students. Next, the remaining 20 intensive readers were divided between two classroom teachers for intensive instruction in ‘‘strategic-sized’’ groups. Because there was only one teacher left, the 15 strategic students and their four Benchmark classmates were grouped together for large group enrichment and possibly some targeted intervention. Not only were group sizes for the 3rd grade students not ideal; the background and experience of the intervention teachers left much to be desired. Five Title One teachers had already been reassigned to work just at Larue but only one was available to help at the 3rd grade level. Adjusting the schedule was not an option. The other Title One teachers were already teaching other intervention groups the required times. The reassignment of the Literacy Coach to help with intensive interventions every morning was already problematic; she should have been coaching teachers on their implementation of the new core and standard protocol programs. The assignment of the two special education teachers to teach intensive

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intervention groups across grade levels left them little time to provide inclusion support to the students with IEPs integrated into general education classrooms during core reading. Mathematics, science, social studies, and special-subject classes were already adjusted, shortened, and consigned to the afternoons to accommodate reading interventions across grade levels. Every available adult, every available classroom space, and every available minute of the day was used to implement the model. RtI IN THEORY 6. When student data are reviewed, students who are not meeting their intervention goals are reassigned to a more intensive tier of reading intervention until their data trends improve.

RtI in Practice 6. Each grade-level team was scheduled to have a common planning period each week to analyze student assessment data and discuss students’ reading needs. Sometimes, when data analysis suggested that a student in the Benchmark intervention group was not making adequate progress, he/she was reassigned to a strategic intervention group until the assessment data trend improved. However, because most strategic groups were at maximum capacity and all available staff were assigned to existing groups, Benchmark intervention teachers more often simply made modiﬁcations to Benchmark instruction like increasing opportunities to respond (Heward, 1994), introducing self-graphing strategies (Mercer & Mercer, 2005), or providing systematic practice and reinforcement. The same problem existed in moving students among and between the strategic and intensive groups. Movement up and down the pyramid proved difﬁcult to engineer. Not only were the group sizes already at maximum, and all the teachers already assigned, but students in existing groups had worked through several lessons of a standard protocol reading program and adding a student to that group would have put the new student at a signiﬁcant disadvantage. Movement within a level of the pyramid was slightly more feasible. Progress monitoring data were used to regroup students within a layer of the pyramid in response to progress monitoring data that showed a particular student moving more quickly or more slowly through the standard protocol.

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RtI IN THEORY 7. Some proponents of RtI advocate that ‘‘special education’’ be considered Tier Four of the model. Progress monitoring data indicating non-responsiveness to core instruction (Tier One), then non-responsiveness to one or two rounds of small-group intervention (Tiers Two and Three) would trigger a referral to special education. In some states, RtI progress monitoring data might be sufﬁcient to warrant calling for an IEP meeting. In other states, the referral would be followed by a multidisciplinary team evaluation in which the RtI progress monitoring data were just one part of the evaluation data considered in making an eligibility decision. Recently, Fuchs, Stecker, and Fuchs (2008) have proposed that Tier Three intervention be considered ‘‘special education.’’ RtI in Practice 7. There were already 36 students in grades 1–4 assigned to receive special education and related services when Larue Elementary adopted the MP3 model and the RtI philosophy. Also, the district’s Special Education Director had strongly embraced Pennsylvania’s mandate to increase the access of students with disabilities to general education classrooms, general education peers, and the general education curriculum.1 A model of service delivery that placed students with IEPs in grade-appropriate classrooms for core reading instruction and utilized the special education teacher as one of the deliverers of intensive small-group intervention was seen by the special education director as one way to accomplish her inclusion goals. During the ﬁrst six weeks of the school year, before intervention groups were established, the students with IEPs were included at grade level for the 60–90 min of core reading instruction. The two special education teachers, one assigned to Larue’s 1st and 2nd grades, one assigned to Larue’s 3rd, 4th, and 5th grades, ‘‘co-taught’’ for some of that 90 min in each of the classrooms into which a special education student was placed. The co-teaching was generally limited to sitting next to the special education student and encouraging participation and work completion while discouraging outbursts and other disruptive behaviors. Because discipline was already a problem at Larue, special education students were not all integrated into core instruction in the same classroom; rather they were spread among the three or four classroom teachers at that grade level. When intervention groups were formed, the special education teacher was reassigned to teach an intensive intervention group of the lowest

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achievers at each grade level (as long as this group had at least one student with a disability assigned to it). To make maximum use of staff and thereby maximize the number of small instructional groups that could be formed, interventions and core reading classes were scheduled at alternating times. For example, the 1st grade scheduled core instruction ﬁrst followed by intervention groups, and the 2nd grade scheduled intervention groups ﬁrst followed by large group core instruction. The one special education teacher assigned to those grade levels taught a 2nd grade intensive intervention group ﬁrst while the 1st graders were in core instruction; then she taught a 1st grade intervention group while the 2nd graders were in core instruction. As a result, the 1st and 2nd grade teachers no longer had a second person in the room during core reading instruction but still had the special education student(s) in their class. This same scenario was played out in the 3rd and 4th grades. This service delivery model made neither the general education classroom teachers nor the special education teachers happy, but there simply were not enough staff to do everything. As instructional groups were formed in October 2006, students with IEPs were not always in the lowest groups. For example, in the 2nd grade, seven students with IEPs scored in the intensive range, but two students with IEPs scored in the strategic range and one student with an IEP scored in the Benchmark range. Of course, this should have been anticipated since students are eligible for special education services for more than just reading difﬁculties and at Larue, mental health and behavior had always been of serious concern. RtI IN THEORY 8. Implementation of an RtI model will increase overall academic achievement and reduce the number of referrals and placements into special education in a school.

RtI in Practice 8. Despite the changes to the model necessitated by real-world constraints many students in Tiers Two and Three responded to instructions and experienced reading growth. Fig. 3 depicts the gradual ‘‘trickle down’’ of students from tier to tier across two years of model implementation. While the relative proportion of students receiving strategic interventions appeared constant, the graphics clearly depict a reduction in students in Tier Three

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Fig. 3.

Summary of Devon’s Fall Intervention Plan.

and an increase in students in Tier One. Nevertheless, after two years, about one-third of the students in grades 1–4 were still at high risk for reading failure. Achievement was moving in the right direction, but the school had a long, long way to go. New referrals for special education came from all levels of the pyramid although legitimate questions were raised about the value-added of referring students who were not making progress in Tiers Two or Three interventions. Because of the inclusion philosophy, students with and without IEPs all participated in 60–90 min of core reading instruction at grade level. Then, all students, including those with an IEP, were assigned to a small-group intervention (the lowest groups likely being taught by the special education teacher or the Title One teacher); their progress was monitored, and the appropriateness of the educational plan was reviewed at monthly grade-level team data meetings. All students had annual reading goals based on baseline scores. All students were receiving 120 min of reading instruction in a 215 min day. More time for reading instruction (perhaps one-on-one) could, theoretically, have been found during the afternoons (in the mornings, the

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special educations teachers were busy teaching multiple intensive groups), but neither the principal nor the classroom teachers would accept that strategy. It would mean pulling the student out of mathematics, or science, or social studies, or physical education, subjects that are also integral to a basic education. The special education teachers wanted to spend afternoons tutoring students with IEPs in mathematics or science or co-teaching in those subjects when students were included in general education classrooms. So, if found eligible for special education services, what would change?

DEVON: AN ILLUSTRATIVE CASE STUDY Having enumerated the constraints in implementing with ﬁdelity an RtI model in an underachieving, resource-poor school, we follow in the footsteps of Fuchs, Stecker, and Fuchs (in press) and use a case study to make even more concrete our description of the real-world. Devon is a 4th grader at Larue Elementary. He has attended this school since 1st grade and has learned to read in a whole-language, guided reading framework. By the end of the 3rd grade, Devon read approximately 90 correct words per minute (wpm) on end-of-second-grade level books and approximately 80 correct wpm on beginning-of-third-grade level books. Devon’s third grade teacher described his reading: Devon deﬁnitely struggles with reading aloud. His reading is often choppy and he loses his place when he comes to a word he doesn’t know. He most often relies on three strategies to read unknown words: 1) look at the picture, 2) look for chunks, and 3) continue reading and use the other words in context to help ﬁgure out the unknown word. However, his success with these strategies varies from day to day. All of this causes his comprehension to suffer . . . I guess I would say that he is a struggling reader but he is deﬁnitely not the lowest in the class. His Guided Reading group worked through their books and moved up in levels faster than many of my other kids.

Devon’s end-of-third-grade scores on the Pennsylvania System of School Assessment (PSSA) reading test fell in the Below Basic range, the lowest performance level on the PSSA. In the fall of the 4th grade, Devon read 66 correct words in 1 min on the DIBELS benchmarking ORF subtest, placing him in the ‘‘At-Risk’’ category. On a Maze reading comprehension test, Devon successfully completed ﬁve close prompts in 3 min, scoring in the Well-Below-Average range. Six weeks into the Year 1 implementation of MP3, Devon’s 4th grade classroom teacher, Mrs M, and her colleagues on the school’s Data Decision Making Team (DDMT) met to develop an intervention plan for Devon.

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Although his assessment data suggested that he be placed in an ‘‘intensive’’ group of only three students to one teacher, the number of at-risk readers in 4th grade far exceeded the number of teachers available to teach small groups as well as the number of physical spaces that could house interventions. The DDMT placed him, instead, in a ‘‘strategic’’ group with nine other underachieving grade-mates. Fluency rates for the group ranged from 60–67 correct wpm with an average of 63. Devon’s 66 wpm put him clearly near the top of his group. Devon’s group was assigned to a Title One teacher, Mrs H. She began her intervention by setting ﬂuency goals for each student in Devon’s group for a 14-week intervention period (through to the winter benchmark testing). For Devon to move from the intensive level to the strategic level in that time, he would need to reach a goal of 88 correct wpm, a gain of þ1.6 correct words per week over the 14 weeks of intervention. To reach the benchmark level, he would need to be reading 105 correct wpm, a ﬂuency gain of þ3.0 correct words per week. Average 4th grade readers gain about 0.8 correct words per week; below-average readers performing at levels comparable levels to Larue’s 4th grade population (i.e., students in the 10th –25th percentile range) gain about þ0.7 correct words per week (Hosp, Hosp, & Howell, 2007). With concurrence from the DDMT, Mrs H set an ambitious goal for Devon of þ1.6 correct words per week for 14 weeks. Everyone recognized that, while it was important to have high expectations for improvement, setting unrealistic goals is not helpful to the student or his teachers (Adams, 1990). The team also decided that students in Devon’s intervention group would be monitored weekly on grade-level probes. They scheduled a follow-up meeting in six weeks to analyze Devon’s group’s progress monitoring graphs and intervention data to examine progress and determine what types of instructional or goal changes should occur. Mrs H worked with the literacy coach and research staff to plan a standard protocol intervention for Devon and his peers. Fig. 3 is a summary of Devon’s intervention plan. Devon participated in the 4th grade core reading instruction with his homeroom teacher each morning for 75 min. Either before or after core reading class (depending on the day of the week), Devon traveled to his intervention class in another 4th grade classroom where Mrs H, Devon, and nine other students in a strategic group worked at the table in the back of the room while Mr G, the special education teacher, worked with an intensive group at a table in the front of the room. Devon and his peers worked through a series of direct-instruction lessons in the Corrective Reading series (Engelmann et al., 1999) for 30 min of the intervention class.

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This standard protocol intervention, speciﬁcally designed for students in grades 3 and up who are reading well below grade level, provided intensive intervention through tightly sequenced lessons in decoding and comprehension. Mrs H enlarged lesson stimuli, student prompts, and language-pattern coding procedures and posted them onto a chart paper for student to reference. She used both choral responding and individual questions/ responses to engage students and pace the lesson efﬁciently. She followed the lesson script and corrective feedback procedures detailed in the teacher manual and, when necessary, the literacy coach or MP3 staff modeled lessons or the team taught with Mrs H to help improve her ﬁdelity of implementation and behavior management skills. For the last 10 min of class, Devon’s group alternated between working with a partner or with Mrs H on repeated oral reading activities (Rashotte & Torgeson, 1985) and sight word recognition practice. At the end of six weeks, Mrs H reported, Devon is a hard worker and really responds well to positive feedback. I can tell he really wants to please. Before each repeated reading or each progress monitoring he’ll say something like, ‘You gonna see how good I do. Jus’ look!’ Then afterward he will grab the timer and say, ‘Told ya!’ when he’s beat his last score. He is very rule-oriented and becomes frustrated when the other students in his group misbehave or disrupt the lesson. His agitation often leads to more disruption because he will reprimand other students, which then leads to arguments, seating rearrangements, and so on. He is engaged and actively participates in the Corrective Reading activities. His independent work is correct and mastery tests indicate that he is doing well. He responds better when I ask for individual answers than when I use choral response because he needs more time to think than most of his other classmates. Sometimes, he’ll simply quickly echo what his peers say. I try to carve out individual reinforcement time with him for a few minutes here and there but it’s tough. His ﬂuency is deﬁnitely improving. He’s even asked to take some used passages home to read to his grandmother to ‘prove how good [I] can read’. His reading is smoother and he’s gained words. But, his progress is slower than I’d like.

After seven weeks of intervention (a week late because of scheduling conﬂicts), Mrs H reviewed Devon’s progress monitoring data with the 4th grade DDMT. Devon’s data (see Fig. 4) showed an increasing trendline and a gain of 0.9 correct words per week. While this rate of improvement exceeded that of both below average and average students reported in the literature, Devon fell short of the ambitious goal his teacher had set. Devon was responding to intervention, but not responding ‘‘enough.’’ Similar patterns occurred for two of Devon’s group mates; their growth was also steady but not steep. For these three students, the DDMT explored a number of possible corrective

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actions. First, they reviewed the adaptations and changes to the Corrective Reading protocol Mrs H had already tried to see if any showed promise. Lesson plans showed that: (a) students self-graphed their repeated reading and progress monitoring data; (b) Mrs H incorporated mini lessons on multisyllabic word decoding and prosody into the intervention time; and (c) 5 min skill ‘‘check-ups’’ were completed with individual children on a rotating schedule throughout the week. These additions seemed effective for the group overall, but did not appear to impact the growth of these three students. So, the DDMT considered moving Devon and the other two group-mates to a 4th grade ‘‘strategic’’ intervention group being taught down the hall by Mrs L, another Title One teacher. She was also implementing Corrective Reading, so the team thought the students would have no difﬁculty ﬁtting in. But, moving Devon and his two non-responding peers to that group would increase the group size to 13 students, exceeding the physical space limits for the group as well as signiﬁcantly taxing Mrs L’s

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management skills. Furthermore, progress monitoring data showed an average ﬂuency rate for Mrs L’s group of 53 wpm, whereas Devon’s ﬂuency rate by week 7 was 71 correct wpm. Finally, results of a Corrective Reading placement test suggested an instructional starting point for Devon’s 8–11 lessons beyond Mrs L’s current group. Maybe changing groups was not such a good idea after all. The DDMT agreed that some specialized support and strategy instruction from the upper-elementary special education teacher, Mr G, might provide the differential boost needed by Devon and his peers. Unfortunately, during the timeslot scheduled for Devon’s intervention, Mr G was already occupied with an intensive intervention group made up of the six lowest performing readers in grade 4, who were scoring 7–17 correct wpm on 4th grade text. Scores in the other three ‘‘intensive’’ groups were equally low. Minimum and maximum ﬂuency scores for those students ranged from 15 correct wpm to 48 correct wpm; Maze comprehension scores ranged from 0–2 correct responses in three minutes. Devon’s reading ability far exceeded that; he could not join that group. Then the DDMT considered getting Devon 1:1 tutoring from one of the special education teachers. Unfortunately, when not teaching this 4th grade intervention group, Mr G was providing inclusion support to 5th graders in language arts and mathematics, or to 4th graders in mathematics, or performing assigned duties like monitoring lunch or recess. The schedule of the lower elementary grades special education teacher was even more full because she provided intervention and inclusion support to grades one through three. After much discussion, the DDMT decided that Devon and his peers would just have to stay where they were until the Winter Benchmarking when new grouping decisions would be made. In January, Devon read 80 correct wpm, missing his goal by eight correct wpm and scoring in the high-end of the intensive range once again. His slope of improvement was an increase of one correct word per week across the 14 weeks of intervention. The schoolwide DDMT and gradelevel data teams convened once again to review the data and were faced again with a troublesome decision. Devon was making progress and his growth rate was slowly accelerating, but he was not making ‘‘adequate’’ progress. However, he was not alone! There were 22 4th graders at Larue who scored below Devon on the winter Benchmark assessment and who were also not ‘‘adequately’’ responding to intervention. Again faced with resource and schedule constraints, the team assigned Devon to a group of eight students comprised of the highest ‘‘intensive’’ readers to work with Mrs L.

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Fig. 5. Summary of Devon’s Winter Intervention Plan.

On Devon’s mid-year intervention plan (see Fig. 5) the DDMT calculated that in order to reach the 4th grade-level spring benchmark goal of 118 correct wpm by year’s end, Devon would have to gain 2.2 correct words per week. That level of growth was nearly triple the rate of gain of typical ﬂuent peers. Understanding that this was an unrealistic goal for Devon and his teacher, they re-set the goal at þ1.6 correct words per week. At this rate, Devon would end the year scoring in the ‘‘some risk’’ range with 106 correct wpm. The instruction this time was to focus on using an accelerated skill cycle of the Corrective Reading program, as well as the Harcourt Trophies Intervention Kit for the 4th grade. Mrs L was familiar with the Corrective Reading program, so ﬁdelity of implementation was high. The Intervention Kit is a systematic instructional program aligned to the Trophies core curriculum designed to address the needs of students reading signiﬁcantly below grade level. Mrs L conscientiously followed the unit and lesson sequences and scripts.

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Mrs L ran a highly structured intervention session. Appropriate, on-task behavior was rewarded in a token reinforcement system. She called on individual students as well as used choral responding. She began each class with a 5 min review of core reading focus skills using the Intervention Kit skill cards or game boards. Forty minutes of Corrective Reading instruction was then provided three days per week and Intervention Kit instruction was provided two days per week each week. After collecting six data points, Mrs L could see that Devon’s skills were improving and that his reading conﬁdence was growing, but Devon’s scores still fell below his aimline and his improvement by the end of six weeks was only þ1.0 correct word per week (see Fig. 6). At the 7th week of the 2nd semester, the DDMT again brainstormed about Devon’s lack of ‘‘adequate’’ progress. First, they noticed that Devon had not actually received much intervention time during the winter months. School cancellations and delays due to inclement weather had wreaked havoc on the morning intervention schedule. Devon had also missed a few

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BLANKS: ≥ 3 days of missed intervention

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days here and there due to illness. Second, Devon’s reading skills, though deﬁcient, were much stronger than those of other students receiving intensive intervention (more than 15 wpm stronger on average). Moreover, he tested out of the Reading Mastery series that was being used in most of the intensive groups. The team had no alternative placement or teacher for Devon, so they decided that Devon would stay in Mrs L’s group. They encouraged Mrs L to restructure the group’s daily schedule to include less time in teacher-directed and more time in student-directed activities so that she would have some time during intervention to work more closely with Devon on skill building. Unfortunately, Devon’s ORF scores declined over the next few weeks. But, so did the scores of the majority of 4th graders. Intervention schedules were inconsistent. It was mid-winter. Intervention sessions were canceled because teachers were absent and substitute teachers did not know how to deliver the intervention protocols. Student absences increased even as the weather improved, and one could feel in the school an overall decrease in instructional momentum as the date for the spring accountability testing drew nearer. Then, days were disrupted for state and district testing and make-up test sessions. Instead of having 16 weeks of intervention between the January and May benchmarking periods, there were only 11 full weeks of intervention. In those 11 weeks, Devon attended 10 weeks’worth of intervention. His median score on the Spring ORF benchmark assessment was 98 correct wpm, placing him into the low-end of the some risk performance range. He had increased 18correct wpm on the end-of-year test, but the data showed an average gain from January until May of only þ0.3 words per week. He was certainly not demonstrating an adequate ‘‘response to intervention.’’ At the end of the school year, the schoolwide DDMT convened to review overall progress of 4th graders as well as the data for the individual students who showed an inadequate response to instruction. The team was blearyeyed by the stacks of students in the ‘‘to review’’ pile. In the 4th grade alone, 14 students (ﬁve with identiﬁed learning disabilities and IEPs, nine without) had not responded to intervention adequately. Devon was the highest performing of these 14 students. Should Devon be referred for special education services? At this rate of progress he will certainly fall farther and farther behind. If Devon were referred for special education services, should the other nine students also be referred? Or should no one in Larue be considered ‘‘unresponsive to instruction’’ until high quality research-based instruction is evident in every classroom at every grade and the ratio of responders and non-responders is back to ‘‘normal’’?

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DISCUSSION We could have wished that Larue Elementary were not a high-poverty, lowachieving school, but it is. We could have wished that classroom teachers at Larue Elementary were more skilled in teaching reading, but they are not. We could have wished that students at Larue arrived at school every day rested, well fed, and ready to learn, but they do not. We could have wished the school were not already performing so far below expectation, but it is. Yet we could not have wished for a better place to implement RtI as a school reform initiative, or a better place to learn about the limitations of RtI policy. RtI is the Regular Education Initiative (Will, 1986) of the 1980s, reinvented. It is a ‘‘special education’’ initiative meant to radically alter the delivery of general education instruction. It focuses on prevention of failure for most by teaching well the ﬁrst time around, screening and monitoring progress to quickly identify the few who are falling behind, and immediate, ﬂexible, and, whenever necessary, more and more intensive interventions to turn underachievers back into achievers as quickly as possible. When reading is the target academic skill, RtI implementation requires schoolwide adoption of a reading program that works well for most students. It requires personnel trained in the delivery of scientiﬁcally sound reading interventions. It requires schedule adjustments to accommodate small-group instruction supplemental to at least 90 min of core-reading instruction. It requires nooks and crannies where intensive small-group reading instructions can take place. It requires that grade-level teachers have a common planning time so they can meet together during the school day to review data and establish reading groups and reading goals. These were all things we knew when we began to implement the model. What we did not know is that an RtI implementation also requires that the school administration and its teachers rethink their priorities: (1) How much of the school day should be allocated to one subject or another? The Reading First initiative embedded in NCLB advocates a 90 min, uninterrupted reading instructional block in the elementary grades (USDE, 2002). When reading is the target of RtI, an additional 30–45 min of intervention time for some (or all) students must be scheduled. If mathematics were the RtI target, then mathematics intervention time would have to be scheduled in addition to 45–60 min of core mathematics instruction. Is there any time left in the schedule for science, social studies, art, music, physical education, foreign language learning? In a low-achieving school in which many students are not meeting benchmarks and many

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students are scheduled for interventions, is the curriculum to be stripped down to basic skills instruction during the ﬁrst three or four years of school? Can we expect teachers who are not yet teaching reading well (when all they are trying to do is teach reading) to infuse reading instruction into science or social studies content instruction? Is that prevention or drudgery? Is that early intervention or wait to fail? (2) What is the school’s commitment to inclusion of students with disabilities in general education classrooms? In early iterations of IDEA, the focus was on access of students with disabilities to general education peers (IDEA, 1997). Decisions revolved around where specially designed instruction would be provided to students with disabilities and any removal of the student with disabilities from the general education classroom setting needed to be justiﬁed. In more recent years, IDEA has emphasized access for students with disabilities to the general education curriculum (i.e., students with disabilities taught what every one else is learning) as well as placement of students with disabilities in general education classrooms (i.e., sitting next to students who do not have disabilities) (IDEA, 2004). Which is the more important emphasis, if both cannot be accomplished? Is 90 min of large-group reading core instruction at the 5th grade level for a student with disabilities who is reading at a 2nd grade level more productive (and more politically correct) than 90 min of intensive small-group instruction at the student’s instructional level delivered by a highly qualiﬁed special education teacher? If teacher time and teacher resources are at a premium, is having a special education teacher sitting next to that student with disabilities during core reading instruction to keep him/her quiet and on task a better use of the teacher-resource than having that teacher teaching a small instructional group in a quiet corner of the school? If both are desirable, should schools hire more special education teachers or relegate the in-class support activity to a paraprofessional and no longer pretend that such activities are actually ‘‘co-teaching.’’ Should school administrators aim for more homogeneous ability groupings in classrooms to make large group core instruction more manageable? Does ‘‘manageable’’ outweigh the advantages of heterogeneous classroom groups and reduce the value of inclusion? Can a school ‘‘buck the trend’’ and advocate for pull out small groups or one-on-one instruction for students who need more instruction (and more intensive instruction) than other students? (3) What is the measure of a successful RtI implementation? Yearly increases in the percentage of students at any grade level who reach the state’s standards of proﬁciency? Yearly decreases in the percentage of students at any grade level whose benchmark scores still place them at

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serious risk of academic failure? Decrease in the number of students referred and found eligible for special education and related services? Students with disabilities making more progress in academics than before? Better or different allocation of special education teaching resources? More students who do not have disabilities getting assistance from the special education teacher through early intervention/prevention or students with disabilities getting more intense and directed instruction from the special education teacher because that teacher has more time to give the students on his/her caseload? Despite all of the challenges along the way and metamorphoses of the RtI model required to implement multiple layers of intervention at Larue, students’ reading achievement has begun to change. With the exception of the 3rd grade, more students are ending each year reading more ﬂuently than the year before. Moreover, students’ rate of gain is steadily approaching and at times exceeding that of a normative group of average readers (see Table 3). Although the growth is not steep enough to narrow the achievement gap for Larue students, and the achievement changes have not yet positioned the school to meet state standards of proﬁciency or RtI estimates of the percentage of ‘‘healthy readers,’’ Larue’s progress is nothing short of remarkable given the school context. Teachers with limited teaching experience and only a superﬁcial understanding of reading instruction are now engaging in daily conversations and debates about phonology, ﬂuency, vocabulary, and comprehension. Students who believed that reading was an unattainable treasure reserved for a privileged few are taking books home to read to their families. School leaders who for years assumed that Larue would always be a failing school are celebrating students’ successes. Local newspaper reporters historically highlighting Larue’s failings now report that the school is transformed (Oravec, 2008). There are resounding calls in the ﬁeld for scaling up research studies on RtI (Danielson, Doolittle, & Bradley, 2007; Denton et al., 2003; Gersten & Dimino, 2006; Kovaleski, 2007). Such studies provide valuable data on student achievement following large-scale randomized trials. In this report, however, we have taken a different path, exploring the nuances and hurdles of the implementation process in the real world. Larue’s response to intervention experience resembles more of what Shinn (2007) describes as ‘‘little RtI,’’ that is, RtI that focuses on systems change to ensure that ALL students are receiving and beneﬁting from improved reading instruction. Shinn’s ‘‘Big RtI,’’ on the other hand, focuses on special education eligibility decisions based on an individual student’s inadequate response to reading intervention. We ﬁnd this a useful distinction and for underachieving

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Table 3. Changes in Larue Reading Achievement Across Two Years of RTI. Spring 2006 Spring 2007 Spring 2008 Grade One 1st grade 1st grade 1st grade 1st grade

average oral reading ﬂuency rates (wpm) average growth rate (wpm) % low risk on DIBELS ORF % at risk on DIBELS ORF

22 – 18% 65%

37 1.1 35% 45%

50 1.4 46% 32%

average oral reading ﬂuency rates average growth rate (wpm) % low risk on DIBELS ORF % at risk on DIBELS ORF

42 – 10% 83%

49 1 13% 73%

71 1.2 26% 41%

Grade Three 3rd grade average oral reading ﬂuency rates 3rd grade average growth rate (wpm) 3rd grade % low risk on DIBELS ORF 3rd grade % at risk on DIBELS ORF % Proﬁcient/advanced 3rd grade state test % Below basic on 3rd grade state test

83 – 12% 36% 29% 48%

82 1.3 21% 44% 37% 41%

80 1 19% 45% 32% 54%

Grade Four 4th grade average oral reading ﬂuency rates 4th grade average growth rate (wpm) 4th grade % low risk on DIBELS ORF 4th grade % at risk on DIBELS ORF % Proﬁcient/advanced 4th grade state test % Below basic on 4th grade state test

67 – 2% 85% 21% 54%

77 .6 6% 65% 38% 43%

89 .9 18% 60% 38% 40%

Grade Two 2nd grade 2nd grade 2nd grade 2nd grade

schools like Larue, ‘‘little RtI’’ (i.e., systems change) is the more immediate priority. Given time, ongoing training, and sustained practice in providing more effective instruction to all students, Larue may get to the point of implementing ‘‘big RtI’’ (i.e., RtI for eligibility decisions). However, time does not appear to be on Larue’s side. Pennsylvania recently adopted new regulations that require schools choose either ‘‘the new’’ RtI methodology or ‘‘the old’’ IQ-achievement discrepancy methodology as the approach to determining a speciﬁc learning disability (Pennsylvania Department of Education, 2008). This choice is to be made building by building, but it must be made now. The regulations caution schools not to implement RtIfor-special-education-eligibility before they are ‘‘ready’’ but readiness is a

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vague and undeﬁned state. Larue is certainly not ready to differentiate students with disabilities from students without disabilities on the basis of the progress monitoring data currently being collected. Is any low-achieving, low-resourced elementary school?

NOTE 1. The inclusion mandate stemmed from a 2005 settlement of the Gaskin v. Pennsylvania Department of Education case. The settlement is the resolution of a 1994 class-action lawsuit against the Pennsylvania Department of Education on behalf of a group of children with disabilities. It requires that Individualized Education Program (IEP) teams determine whether the goals in a student’s IEP can be implemented in the general education classroom with supplementary aids and services before considering a more restrictive educational placement.

REFERENCES Adams, M. (1990). Beginning to read: Thinking and learning about print. Cambridge, MA: MIT Press. Beck, I. L., Farr, R. C., & Strickland, D. S. (2003). Trophies: A Harcourt reading/language arts program. Orlando, FL: Harcourt. Bradley, R., Danielson, L., & Doolittle, J. (2005). Response to intervention. Journal of Learning Disabilities, 38, 485–486. Capizzi, A. M., & Fuchs, L. S. (2005). Effects of curriculum based measurement with and without diagnostic feedback on teacher planning. Remedial and Special Education, 26, 159–174. Chard, D. J., & Kame’enui, E. J. (2000). Struggling ﬁrst-grade readers: The frequency and progress of their reading. Journal of Special Education, 34, 28–38. Coyne, M. D., Kame’enui, E. J., & Simmons, D. C. (2001). Prevention and intervention in beginning reading: Two complex systems. Learning Disabilities Research and Practice, 16, 62–73. Daniels, H. (2002). Literature circles: Voice and choice in book clubs & reading groups. Portland, ME: Stenhouse. Danielson, L., Doolittle, J., & Bradley, R. (2007). Professional development, capacity building, and research needs: Critical issues for response to intervention implementation. School Psychology Review, 36, 632–637. Deno, S. L., Espin, C. A., & Fuchs, L. S. (2002). Evaluation strategies for preventing and remediating basic skill deﬁcits. In: G. Stoner, M. R. Shinn & H. M. Walker (Eds), Interventions for achievement and behavior problems. Washington, DC: National Association of School Psychologists. Deno, S. L., Fuchs, L. S., Marston, D., & Shinn, J. H. (2001). Using curriculum-based measurement to establish growth standards for students with learning disabilities. School Psychology Review, 30, 507–524.

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Denton, C. A., Fletcher, J. M., Anthony, J. L., & Francis, D. J. (2006). An evaluation of intensive intervention for students with persistent reading difﬁculties. Journal of Learning Disabilities, 39, 447–466. Denton, C. A., Vaughn, S., & Fletcher, J. M. (2003). Bringing research-based practice in reading intervention to scale. Learning Disabilities Research and Practice, 18, 201–211. Engelmann, S., Meyer, L., Carnine, L., Becker, W., Eisele, J., & Johnson, G. (1999). Corrective reading. Worthington, OH: Science Research Associates/McGraw-Hill. Felton, R. H., & Wood, F. B. (1992). A reading level match study of nonword reading skills in poor readers with varying IQ. Journal of Learning Disabilities, 25, 318–326. Fountas, I. C., & Pinnell, G. S. (1991). Guided reading: Good ﬁrst teaching for all children. Portsmouth, NH: Heinemann. Fuchs, D., Fuchs, L. S., & Compton, D. L. (2004). Identifying reading disabilities by responsiveness to instruction: Specifying measures and criteria. Learning Disability Quarterly, 27, 216–227. Fuchs, D., Stecker, P., & Fuchs, L. S. (2008). Tier 3: Why special education must be the most intensive tier in a standards-driven, No-Child-Left-Behind world. In: D. Fuchs, L. S. Fuchs, & S. Vaughn (Eds), A Response-to-Intervention framework for reading educators (pp. 71–104). Newark, DE: International Reading Association. Fuchs, L. S., Butterworth, J. R., & Fuchs, D. (1989). Effects of ongoing curriculum-based measurement on student awareness of goals and progress. Education and Treatment of Children, 12, 63–72. Fuchs, L. S., & Deno, S. L. (1991). Paradigmatic distinctions between instructionally relevant measurement models. Exceptional Children, 57, 488–499. Fuchs, L. S., & Fuchs, D. (1999). Monitoring student progress toward the development of reading competence: A review of three forms of classroom-based assessment. School Psychology Review, 2H, 659–671. Fuchs, L. S., Fuchs, D., Bishop, N., & Hamlett, C. (1992). Classwide decision-making strategies with curriculum-based measurement. Diagnostique, 18, 39–52. Fuchs, L. S., Fuchs, D., Hamlett, C., & Allinder, R. M. (1991). The contribution of skills analysis to curriculum-based measurement in spelling. Exceptional Children, 57, 443–452. Fuchs, L. S., Fuchs, D., & Hamlett, C. L. (1989). Effects of instrumental use of curriculumbased measurement to enhance instructional programs. Remedial and Special Education, 10, 43–52. Fuchs, L. S., Fuchs, D., Hamlett, D. L., & Whinnery, K. (1991). Effects of goal line feedback on level, slope, and stability of performance within curriculum-based measurement. Learning Disabilities Research and Practice, 6, 66–74. Fuchs, L. S., Fuchs, D., Hosp, M. K., & Jenkins, J. R. (2001). Oral reading ﬂuency as an indicator of reading competence: A theoretical, empirical, and historical analysis. Scientiﬁc Studies of Reading, 5, 239–256. Gersten, R., & Dimino, J. (2006). RTI (Response to Intervention): Rethinking special education for students with reading difﬁculties (yet again). Reading Research Quarterly, 41, 99–108. Good, R. H., III, & Kaminski, R. A. (Eds). (2002). Dynamic indicators of basic early literacy skills (6th ed.). Eugene, OR: Institute for the Development of Education Achievement. Available: http://dibels.uoregon.edu Good, R. H., III., Simmons, D. C., & Kame’enui, E. J. (2001). The importance and decisionmaking utility of a continuum of ﬂuency-based indicators of foundational reading skills for third-grade high-stakes outcomes. Scientiﬁc Studies of Reading, 5, 259–290.

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THE NO CHILD LEFT BEHIND ACT AND HIGH SCHOOL GRADUATION FOR STUDENTS WITH AND WITHOUT DISABILITIES Wendy Morrison Cavendish ABSTRACT The No Child Left Behind Act (NCLB) (2001) has led to widespread use of high-stakes assessment in determining graduation options for all students, including those with disabilities. In this chapter, we examine graduation trends in the state of Florida before and after the implementation of a high-stakes test used as a means to meet NCLB requirements and further examine speciﬁc trends in rates of graduation with a standard diploma attained by students with disabilities. As trends for students with disabilities reveal a reduction in standard diploma attainment, we discuss research related to the Individuals with Disabilities Education Improvement Act (IDEA) provisions for individualized education program (IEP) and transition planning for students with disabilities that are designed to improve students’ graduation and postschool outcomes. We discuss ways in which schools might improve student graduation rates within the context of both NCLB and IDEA. Speciﬁcally, we report ﬁndings from a study conducted in a school district in Florida that demonstrates a positive relationship between Policy and Practice Advances in Learning and Behavioral Disabilities, Volume 22, 107–132 Copyright r 2009 by Emerald Group Publishing Limited All rights of reproduction in any form reserved ISSN: 0735-004X/doi:10.1108/S0735-004X(2009)0000022006

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student perceptions of school’s efforts to facilitate student involvement in planning (as outlined by IDEA requirements) and the likelihood of graduation with a standard diploma (based on ‘‘passing’’ a high-stakes test) for students both with and without disabilities. Implications for policy and practice are discussed.

NO CHILD LEFT BEHIND The No Child Left Behind Act’s (NCLB) (2001) Section 1116 outlines mandates for states and local educational agencies (LEAs) regarding explicit use of state academic assessments to determine and report students’ academic performance. It states that Each local educational agency receiving funds under this part shall – (A) use the State academic assessments and other indicators described in the State plan to review annually the progress of each school served under this part to determine whether the school is making adequate yearly progress as deﬁned in section 1111(b)(2); (B) publicize and disseminate the results of the local annual review described in paragraph (1) to parents, teachers, principals, schools, and the community so that the teachers, principals, other staff, and schools can continually reﬁne, in an instructionally useful manner, the program of instruction to help all children served under this part meet the challenging State student academic achievement standards established under section 1111(b)(1).

As the NCLB Act (2001) is a reauthorization of the Secondary and Elementary Education Act (ESEA) (1965), many provisions outlined reﬂect the intent of the original law which was to provide educational equity to students of diverse racial and socioeconomic backgrounds. The NCLB Act explicitly ties funding to outcomes of built-in state accountability systems that include performance standards for all students, including those with disabilities and those who are English language learners (ELL). However, this provision for inclusion of all students in accountability systems was developed after Title I of the 1994 reauthorization of ESEA required that states assess all students and provide ‘‘reasonable’’ accommodations or adaptations for students with learning needs and those with limited English proﬁciency. It was found that ‘‘few states met the inclusion requirements when their assessment plans were ﬁst submitted’’ (p. 29) and that by 2001, 20% of states had still not met the requirement for inclusion of students with disabilities (National Center for Education Statistics, 2003). In recent years, and partly as a result of sanctions outlined in NCLB that in order for schools to demonstrate adequate yearly progress (AYP) 95% of

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all students must participate in testing, most states have included students with disabilities in state assessments. However, this inclusion has brought about its own set of issues for education stakeholders to contend with, namely, how to prepare students with disabilities for high-stakes assessment given the long documented ﬁndings that students with disabilities perform poorly on standardized measures of academic achievement relative to their non-disabled peers (Katsiyannis, Zhang, Ryan, & Jones, 2007; U.S. Department of Education, 2004; Wagner, Cameto, & Newman, 2003). Additionally, there has been concern that although NCLB aims to close the achievement gap among culturally and linguistically diverse students, its accountability provisions may create counterincentives for states that lead to higher rates of drop-out among students of color and students with disabilities (Darling-Hammond, 2006; McNeil, Coppola, Radigan, & Heilig, 2008). Speciﬁcally, McNeil et al. (2008) note that when high-stakes tests are used to determine eligibility for high school graduation to meet provisions of NCLB AYP, unintended negative consequences may include increased drop-out rates.

HIGH-STAKES TESTING AND HIGH SCHOOL GRADUATION It is important to keep in mind the intention of the law (NCLB) when we consider state graduation trends of students with and without disabilities. Testing and accountability systems are based on the assumptions that participation in high-stakes assessments modeled on state standards will establish high expectations for all students and ultimately lead to improved academic performance and increased graduation rates (deFur, 2002; Carter et al., 2005). However, state by state accountability reports note negligible change over the past ﬁve years in graduation rates for students with and without disabilities in states that require high-stakes testing for graduation. Nationally, the standard diploma graduation rate for students with disabilities has dropped slightly in the past decade but the number of diploma options has increased exponentially (Ysseldyke et al., 2004). Confounding these reports is the states’ use of different formulas to calculate graduation and drop-out rates (Greene & Winters, 2002). In 2005, the National Governors Association Task Force on State High School Graduation Data noted that many states had not collected accurate graduation and drop-out data and that furthermore, the

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‘‘quality of graduation and dropout data . . . [is] critical’’ (p. 7). Additionally, many states (Florida, in particular) have changed the formula that it uses to calculate graduation rates several times over the past decade (Center on Education Policy, 2004; Florida Department of Education [FLDOE], 2007). There is no consensus among state education stakeholders and researchers regarding the relationship between high-stakes testing and accountability systems and graduation rates for students with and without disabilities (Ysseldyke et al., 2004). This is due, in part, to the considerable variability among states in assessments used for high-stakes testing and accountability reporting. It must be noted that recent research has shown a relationship between number of drop-outs and higher accountability ratings in states that institute high-stakes testing as a graduation requirement (McNeil et al., 2008). It has been hypothesized that accountability systems may allow principals to retain students who are at risk of ‘‘failing’’ the state high-stakes test (thus, reducing the school’s accountability rating) and that these retained students may end up dropping out (McNeil et al., 2008). However, most ﬁndings that link high-stakes testing and reduced rates of high school graduation for general education students is correlational (Clarke, Haney, & Madaus, 2000). There is even less empirical evidence regarding the impact of high-stakes tests and graduation rates of students with disabilities.

FLORIDA GRADUATION TRENDS Graduation rates in Florida have been among the lowest in the nation even before the passage of NCLB. Greene and Winters (2002) calculated Florida’s high school graduation rate as the lowest in the Nation at B55% across a 10-year period (1990–2000). Their calculation does not include students who graduate with a general educational development (GED) diploma or a special diploma or who do not graduate within four years. The FLDOE includes GED and special diplomas in its calculation and reports graduations rates ranging from 60% to 67% for the same time period (FLDOE, 2007). Florida reported a four-year graduation rate of 72% in 2007; however, graduation rates with a standard diploma have dropped since high-stakes testing policy implementation in 2002 (Ofﬁce of Program Policy Analysis & Government Accountability, 2007). Following the passage of NCLB, Florida has used a high-stakes test, termed the Florida Comprehensive Assessment Test (FCAT), as a requirement for high school graduation with a standard diploma for all

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students, including those with disabilities. Of concern is that Florida continues to report a marked disparity in graduation rates among White, African-American, and Hispanic students. In 2005, FLDOE calculations reported graduation rates of 79% for White students (at odds with reports of 60% Florida graduation rates from national sources), 63% for Hispanic students, and 56% for African-American students (FLDOE, 2007; National Governors Association, 2005). This gap remained unchanged until 2004, when a growing disparity in the number of standard diplomas emerged. Although Florida reports that since the utilization of FCAT as a requirement for graduation, the ‘‘percentage of students who receive standard diplomas has not substantially changed’’ (p.3), an examination of differences amongst diploma types earned by diverse students reveals a troubling trend (Ofﬁce of Program Policy Analysis & Government Accountability, 2007). Fig. 1 reﬂects the trends in standard diplomas earned in Florida from 1983 to 2006. As noted earlier, Florida has reported increases in its overall graduation rate over the past decade; however, Fig. 1 demonstrates a decrease in standard diplomas earned as a percentage of all diploma types earned in Florida from 97% in 1983 to just under 86% in 2006. In recent years,

Florida Public High School Graduates Standard Diplomas as a Percentage of All Diplomas and Certificates Awarded 100

95 All Students 90

85

80

75 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 Florida Department of Education, 2007.

Fig. 1.

Standard Diplomas Earned as a Percentage of All Diplomas Earned in Florida.

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Florida has offered seven different types of diplomas: (1) a GED; (2) a GED Exit option whereby a standard diploma is awarded to students who pass both the FCAT and the GED tests but do not earn high school credits; (3) a standard diploma awarded to students who pass the FCAT and earn 24 high school credits; (4) a certiﬁcate of completion which is not a diploma but is awarded to students who fail to achieve the required 2.0 grade point average (GPA) ‘‘and/or’’ pass the grade 10 FCAT; (5) a standard diploma with an FCAT waiver for students with disabilities who earn 24 high school credits but are unable to pass the FCAT after multiple attempts and the individualized educational programs (IEP) team determines that the FCAT does not accurately measure student’s abilities even with testing accommodations; (6) a special diploma awarded to students with disabilities who earn the minimum number of course credits as determined by each district school board but are not required to maintain the 2.0 GPA or pass the FCAT; and (7) the special certiﬁcate of completion awarded to students with disabilities who are unable to meet the requirements of the special diploma but pass required special education (SE) courses. This proliferation of diploma options is to some extent counterintuitive to the intent of NCLB and the requirement that all students must ‘‘pass’’ a state assessment based on high academic standards in order to obtain a diploma. The purpose of requiring an assessment that measures number of students that meet the ‘‘high state standards’’ is to close the achievement gap and demonstrate a high level of academic achievement for America’s students. Florida reports that since 1999, it has ‘‘raised its standards for achievement three times in order to ensure students are prepared for the rigor of postsecondary education and the workforce’’ (FLDOE, 2007, p. 3). By offering ﬁve of seven diplomas that do not require students to meet the state academic standards measured by the high-stakes test, Florida’s ﬁgures should take into account the number of students that are not participating in the state accountability system when it comes to graduation. Particularly, these additional diploma options seem to be ‘‘skimming’’ the low performing students of color and students with disabilities off the accountability rolls. Fig. 2 provides the racial and ethnic differences in types of diplomas awarded. The racial and ethnic differences of those awarded standard diplomas as a percentage of all diplomas awarded in Florida have increased considerably over the past decade. The number of standard diplomas as a percentage of all diplomas awarded has dropped from 98% to 94% for White students, from 95% to 78% for African-American students, and from 98% to 85% for Hispanic students. This represents a widening of the achievement gap

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Florida Public High School Graduates - Selected Racial-Ethnic Groups Standard Diplomas as a Percentage of All Diplomas and Certificates Awarded 100 White Non-Hispanics

95 Hispanics

90 85 African Americans

80 75 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06

Fig. 2.

Racial and Ethnic Differences in Standard Diplomas as a Percentage of Diplomas Awarded in Florida.

from a 3% point difference to a 16% point difference between White and African-American students. Additionally, the Schott 50 State Report noted a 22% gap between graduation rates of White and African-American students in Florida in 2006. The increasing gap is evident in Table 1 that reports the percentage of diploma types by race and ethnicity for Florida. Table 1 reveals an increase in non-standard diplomas earned by all racial and ethnic groups in Florida. Particularly, there has been a large increase in the percentage of certiﬁcates of completion that have been awarded. Speciﬁcally, the increase in the percentage certiﬁcates of completion as a percentage of diplomas awarded has increased by 92%. This is troubling when we consider that the requirements for a certiﬁcate of completion do not meet state academic standards as measured by GPA or state assessment standards. Particularly daunting is that fully 11% and 14% of ‘‘diplomas’’ awarded to students of color (Hispanic and African-American, respectively) are certiﬁcates of completion. This indicates that even with Florida ‘‘raising its standards for achievement,’’ students of color are not achieving at this standard. Table 1 also reveals a marked increase in the percentage of special diplomas awarded. The increase in the percentage of special diplomas as a

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Table 1.

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Racial and Ethnic Differences of those Awarded Diplomas in Florida. Standard Diploma %

White 1989–1990 2005–2006 African American 1989–1990 2005–2006 Hispanic 1989–1990 2005–2006

Special Diploma %

Certiﬁcate of Completion %

98 94

2 4

.2 2

95 78

4 8

1 14

98 85

1 4

1 11

percentage of diplomas awarded has increased by 58%. As students with disabilities who earn a special diploma are not required to meet the state GPA or assessment standards, we must look to ways to improve graduation and post-school outcomes for youth with disabilities. Clearly, preparation for inclusion in high-state testing is not increasing the achievement of these students in Florida. This decrease in both general and SE students obtaining a standard diploma over the past several years reﬂects potentially decreased opportunities for post high school educational and employment success for these youth. Speciﬁcally, for all students (general and SE) in Florida who received a standard diploma in the 2005–2006 school year, 65% were continuing their education (university, community college, or vocational training) the following fall, 58% were employed, and 3% were receiving Temporary Assistance to Needy Families (TANF). This is contrasted with students who graduated with a special diploma whereby 7% were continuing their education, 44% were employed, and 14% were receiving TANF. Also, the percentages of students in general education who were unable to ‘‘pass’’ the FCAT and received a certiﬁcate of completion instead of a standard diploma reﬂect that 16% were continuing their education, 69% were employed (32% full-time), and 10% were receiving TANF (FLDOE: FETPIP, 2006a). These numbers suggest the need for research on factors that may impact student’s graduation track (standard diploma, special diploma, certiﬁcate of completion) and further indicate the importance for schools to make concerted efforts to ensure that students who are able to graduate with a standard diploma do so as the outcomes impact not only the students and their families but also the state in terms of costs.

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FACTORS CONTRIBUTING TO GRADUATION WITH A STANDARD DIPLOMA FOR STUDENTS WITH AND WITHOUT DISABILITIES WITHIN A FLORIDA SCHOOL DISTRICT Given the decreases in standard diploma attainment of diverse students in Florida, it was of interest to examine what factors aside from just raising testing standards might contribute to an increased likelihood of graduation with a standard diploma. These factors were of particular interest as our study was initiated within the context of a district-wide high school reform initiative that included goals to improve student engagement as well as academic outcomes for students across all academic levels. Speciﬁcally, this school district in Florida (the fourth largest school district in the U.S.) has invested resources, both ﬁnancial and personnel, into efforts to improve high school student performance on the state assessment, the FCAT, and has had limited success. The number of students in this school district graduating with a standard diploma has dropped from 92% of seniors in 1998 to just 79% of seniors in 2002 (Needs Assessment, The Children’s Trust, 2003). Furthermore, the number of students passing the FCAT and receiving a standard diploma has remained considerably below target goals (FLDOE, 2006b). Most troubling, the percentage of students who receive SE services who graduate with a standard diploma has dropped to just 36% in 2005 (FLDOE, 2007).

Research Questions The variables of interest in this study were gleaned from research in both special and general education. We examined the association between school efforts to facilitate student involvement, on the one hand, and student’s characteristics (e.g., school commitment and self determination) and educational outcomes (e.g., performance on statewide assessments and graduation track) on the other. This study addressed the following research questions: 1. Are there differences in student perceptions of school efforts to facilitate student involvement, school commitment, and self-determination between students receiving general education and SE services? 2. Do student perceptions of school efforts to facilitate student involvement, school commitment, and self-determination predict student academic

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performance, as measured by high school grades, controlling for academic achievement? 3. Do student perceptions of school efforts to facilitate student involvement, school commitment, and self determination predict FCAT performance controlling for academic achievement (and thus, graduation track for both general and SE students)? It was hypothesized that there would be differences in measures of reported school efforts to facilitate student involvement between students receiving SE services versus general education. These differences were expected to reﬂect greater efforts by schools to facilitate involvement as schools are required by provisions in IDEA to involve SE students in decisions and planning regarding their own education. Students in SE were not expected to differ signiﬁcantly from their general education peers in level of school commitment as all students were still regularly attending high school. However, it was hypothesized that students in SE may demonstrate less developed self-regulation and psychological empowerment self-determination skills than their peers in general education as the school district did not utilize a systematic self-determination or selfadvocacy curriculum as part of its SE programming at the time of the study.

Student Involvement in Educational Planning and Outcomes Much of the past research has examined student involvement and self-determination skills as it occurs in IEP or transition plan (ITP) meetings with SE students. This research has identiﬁed the need for supportive conditions that foster student involvement in order to effect positive school and post school outcomes for students with disabilities. Thus, student participation and involvement in educational planning has been recognized as ‘‘best practice’’ in SE (Almqvist & Granlund, 2005; Benz, Lindstrom, & Yovanoff, 2000; Lee & Burkham, 2003; Test et al., 2004; Test & Neale, 2004; Wehmeyer, Baker, Blumberg, & Harrison, 2004). Furthermore, in addition to being a ‘‘best practice’’ in developing SE IEPs and ITPs, student involvement has also been shown to enhance self-determination (Wehmeyer, Palmer, Agran, Mithaug, & Martin, 2000; Mason, Field, & Sawilowsy, 2004). The importance of school efforts

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to provide opportunities for student involvement is echoed in research ﬁndings that hold that student choice making is positively related to positive outcomes and that self-determination and decision-making skills cannot be properly developed without the opportunities to utilize them in the school context (Shogren, Faggella-Luby, Bae, & Wehmeyer, 2004; Wehmeyer, Field, Doren, Jones, & Mason, 2004). Research in education has also supported the notion that one of the factors that contribute to students’ achievement and positive post-school outcomes is the extent of students’ involvement in decisions concerning course selection, diploma options, and other aspects of preparation for postschool education or employment (Finn, 1989; Scanlon & Mellard, 2002; Schutz, 1997; Shogren et al., 2004). Teacher and administrative facilitation of student involvement has been described as relevant to fostering school commitment and self-determination and positive school outcomes crossculturally (Gibson & Bejinez, 2002; Levesque, Zuehlke, Stanek, & Ryan, 2004; Smyth, 1999). Additionally, recent research has demonstrated the impact of supportive contexts on student outcomes. Speciﬁcally, Patrick, Ryan, and Kaplan (2007) found that supportive class environments enhance student efﬁcacy and involvement. However, little research has examined student perceptions of school level efforts to involve students in the educational process. As schools can exert an inﬂuence on student outcomes through explicit efforts to engage students in meaningful partnerships related to educational decision making, greater partnerships are hypothesized to be associated with increased student involvement and ultimately with positive educational outcomes. Furthermore, schools have particular shared decision-making obligations relative to students receiving SE services. The 2004 reauthorization of IDEA stipulates that students are themselves to be consulted in regard to their IEP when appropriate. In particular, students should play a key role in developing their transition plan (federal law requires it be formalized no later than the student’s 16th birthday), which is designed to take into account their personal goals preferences as well as their academic and social competencies. Students should be part of the team that establishes student goals and determines what speciﬁc educational and related services will be provided to the student in order to assist the student to reach his or her goals. Given these requirements, it is possible that schools may exert greater involvement efforts vis-a´-vis students receiving SE services than they do vis-a´-vis students who are not receiving SE services.

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METHOD Participants Participants in this study were initially drawn from a federally funded ﬁveyear study (2001–2006) entitled, ‘‘A Longitudinal Study of Co-morbid Disorders in Children and Adolescents.’’ Data have been collected from participants in the longitudinal study in 10 waves (two data collection points per school year). The participants in the current study are drawn from data wave eight in 2005, when most students were attending 10th grade across 26 urban high schools within the same Florida school district. For this study, the school district’s database was used to locate the sample of students still enrolled in school. It should be noted that differences among the students who participated at data wave eight and those that did not or were unable to be located are unable to be determined. The participants in this study (data wave eight, N ¼ 154) include both students placed in SE classes (n ¼ 20) and non-SE students (n ¼ 134). The group demographics reﬂect those of the school district. The school district student demographics are 60% Latino, 30% African American, and 10% white non-Latino. The sample comprises 13% students receiving SE services and 87% enrolled in general education classes. This matches the approximate distribution of students in this school district where 12% of the students receive SE services.

Measures The measures used to examine factors that may be related to increased likelihood of students attaining a standard high school diploma are described below. School Commitment Index (SCI). The SCI is a 10-item index developed as a measure of student commitment to school and educational goals. Item responses are yes or no and are scored as either one or zero points depending on whether the response indicates a commitment to educational goals. These items include questions such as, ‘‘Do you think that most of your classes are important?’’ and ‘‘Does it matter a lot to you what your grades are?’’ The eight items were summed to measure school commitment. The internal consistency (coefﬁcient alpha) for the commitment scale with this sample was .69.

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The Arc’s Self-Determination Scale (AS-DS) (Adolescent Version). The AS-DS (Wehmeyer & Kelchner, 1995) is a student self-report measure of self-determination designed for use by adolescents with disabilities, particularly students with mild cognitive and learning disabilities. However, the AS-DS has been normed with student groups including youth both with and without disabilities. Although the AS-DS consists of four subdomains, two subdomain areas, self-regulation and psychological empowerment, were administered. Self-regulation includes cognitive-problem solving and goal setting items. Speciﬁcally, the self-regulation subdomain scale includes story completion items that ask a student to write out an action that would lead to a satisfactory solution to a reported issue and items that require the student to identify goals and break the goals into smaller steps. The subdomain of psychological empowerment measures the level of psychological empowerment reported by the student based on responses to two options given that are related to feelings of empowerment in various situations. Good internal consistency reliability was found for this sample of students on the self-regulation and psychological empowerment subdomains of the AS-DS (coefﬁcient alpha ¼ .71 and .90, respectively). Student Involvement Survey (SIS). A measure of student perceptions of school efforts to facilitate student involvement in educational planning was adapted, in part, from the 500-item parent involvement item bank used in the National Center for SE Accountability Monitoring (NCSEAM) National Item Validation Study – Part B Efforts Scale. Sixty items were identiﬁed for inclusion. These items were selected from the parent item bank Part B Efforts Scale for relevance to student experiences in school. A ﬁeld test of this instrument was conducted and modiﬁed for student relevance and vocabulary. Items are rated using a six-item Likert scale ranging from very strongly disagree to very strongly agree. The Rasch rating scale model was used to determine unidimensionality of the SIS measure (Bond & Fox, 2001). The set of observations adhered to Rasch’s mathematical model of expectations, thus the measure was held to be unidimensional; that is, the single difﬁculty/ability continuum was sufﬁcient to explain patterns of item/person responses (Bond & Fox, 2001). The person ability and item difﬁculty estimates have undergone log transformation and a logit scale is set as an interval scale where the unit intervals between the locations on the person-item map have a consistent value; the Rasch model has set 50% as the probability of success (or positive response) for any person on an item located at the same level on the itemperson logit scale (Bond & Fox, 2001).

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Furthermore, the Rasch model was used to determine the reliability of scores across persons and items on the SIS scale. The person reliability indicates the replicability of person placement across other items measuring the same construct, much like Cronbach’s alpha. The reliability estimate for persons in this sample was .95. Reliability for items was obtained and the scale item reliability was reported as .90. The Rasch analysis was further used in order to obtain measure scores for each item and person in the sample. These measure scores were used in the analyses rather than raw scores. The importance of using a Rasch model to transform raw scores obtained from measures in the social sciences has been demonstrated by past research (Bond & Fox, 2001). Gender. Gender was used as a categorical independent variable in all analyses. Gender was coded (0) for male and (1) for female. Special education status. SE status was used as a categorical independent variable in all analyses. Students who were receiving SE services were coded (1) for SE and (0) for no SE services received. Graduation track. Measures of student academic performance were obtained from the school district database and include student scores from the Florida Comprehensive Assessment Test – Sunshine State Standards (FCAT-SSS) in reading and mathematics. Students who do not obtain a ‘‘passing’’ score on the 10th grade FCAT-SSS are not eligible for a standard diploma. Furthermore, student scores were obtained from the Florida Comprehensive Assessment Test – Norm Referenced Test (FCAT-NRT), also known as the Stanford Achievement Test – Ninth Edition (SAT/9). Student grades were retrieved from the district database and reported for 2005 yearend grades in English and mathematics.

RESULTS Are there differences between students in general and SE in student perception of school efforts to facilitate student involvement, school commitment, and self-determination skills? The dependent variables of interest in this analysis are scores from the SCI, the SIS, and the AS-DS. The primary independent variable of interest is SE status. Gender was also entered as a categorical independent variable. Means and standard deviations across gender and SE status are reported in Tables 2 and 3. Group comparisons were conducted using two-way ANOVA procedures to examine differences between students in SE and general education across gender on the measures of school commitment, student perception of school

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Table 2. Means and Standard Deviations of Student Involvement, School Commitment, and Self-Determination by Gender. Gender

Male

Female

Total

SIS

SCI

AS-DS Self-Regulation

AS-DS Psychological Empowerment

Mean N SD Mean N SD

55.64 62 11.88 55.12 92 8.07

7.33 62 1.42 7.52 92 .85

14.12 62 3.88 14.89 92 3.92

14.85 62 1.67 15.27 92 1.28

Mean N SD

55.33 154 9.75

7.44 154 1.12

14.58 154 3.91

15.10 154 1.46

Note: SCI ¼ School Commitment Index, SIS ¼ Student Involvement Survey, AS-DS ¼ Arc’s Self-Determination Scale.

Table 3. Means and Standard Deviations of Student Involvement, School Commitment, and Self-Determination by Special Education Status. Education Status Non-SE

SE

Total

SIS

SCI

AS-DS Self-Regulation

AS-DS Psychological Empowerment

Mean N SD Mean N SD

55.27 134 9.92 55.73 20 8.79

7.54 134 1.00 6.80 20 1.60

14.73 134 3.95 13.55 20 3.44

15.15 134 1.33 14.80 20 2.16

Mean N SD

55.33 154 9.75

7.44 154 1.12

14.58 154 3.91

15.10 154 1.46

Note: SCI ¼ School Commitment Index, SE ¼ special education, SIS ¼ Student Involvement Survey, AS-DS ¼ Arc’s Self-Determination Scale.

efforts to facilitate involvement, and self-regulation and psychological empowerment subdomains of self-determination. No statistically signiﬁcant differences were found between the SE and general education groups on measures of student involvement, F(1, 150) ¼ .004, p ¼ .95, or on either the self-regulation domain, F(1, 150) ¼ 1.36, p ¼ .25, or psychological

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empowerment domain, F(1, 150) ¼ 1.12, p ¼ .29, of the AS-DS. These ﬁndings were to some extent unexpected as federal mandates (e.g., IDEA) requires schools to facilitate student involvement in educational planning for students in SE. However, there was a signiﬁcant main effect of SE status on school commitment, F(1, 150) ¼ 8.09, po.005, reﬂecting lower levels of school commitment reported by students in SE. Partial eta squared was obtained to measure the magnitude of the effect. The SE status effect on school commitment was reported as partial Z2 ¼ .05, indicating a small to medium effect size. Previous research ﬁndings with this sample also revealed that for students in SE, the level of school commitment decreased between 9th and 10th grade (data waves six and eight) (Morrison Cavendish, 2006). Additionally, a signiﬁcant main effect by gender was found on the psychological empowerment subdomain of the AS-DS, F(1, 50) ¼ 3.78, po.05, representing lower scores of psychological empowerment reported by males than females in this sample. This ﬁnding supports recent ﬁndings that have identiﬁed greater self-determination skills reported by females in schoolbased samples (Shogren et al., 2007). No interaction effects between gender and SE status were found for student perception of school effort to facilitate student involvement, school commitment, or on either subdomain of the Self-Determination Scale. Do student perceptions of school efforts to facilitate involvement, school commitment, and self-determination skills predict student academic performance as measured by English and math year-end grades? It was of interest to examine whether school commitment, student involvement, and selfdetermination predicted whether students were on track for graduation from high school as evidenced by academic credits earned in content area courses. As academic achievement may be related to positive educational outcomes such as graduation, these analyses included the students’ academic achievement scores from the reading and math sections of the FCATNRT (SAT/9) as independent variables. SE status was not included as a predictor variable in the logistic regression analyses as standardized test scores were used to control for prior levels of achievement instead. However, gender was included as a categorical independent variable. It should be noted that the results reported are for N ¼ 143 as analyses are conducted only for those students in the sample for whom grades and state assessment scores were available from the school district. Binomial logistic regression analysis methods were used to determine the predictive relationship among school commitment, student perceptions of school efforts to facilitate student involvement, and self-determination, controlling

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Table 4. Means and Standard Deviations of English and Math Year-End Grades by Gender and Special Education Status. Gender

2005 English Grade

2005 Math Grade

Mean N SD Mean N SD Total Mean N SD

2.05 56 1.03 2.26 78 1.04 2.17 134 1.04

1.46 56 1.16 1.86 80 1.08 1.70 136 1.12

Special education status Non–SE Mean N SD SE Mean N SD Sample Total Mean N SD

2.20 118 1.03 1.94 16 1.12 2.17 134 1.03

1.71 119 1.11 1.59 17 1.28 1.70 136 1.12

Male

Female

Sample

for prior academic achievement and gender, and school grades in English and mathematics which reﬂect credits earned for graduation. Means and standard deviations of English and mathematics grades are reported in Table 4. In general, the students in the sample were earning passing grades in English, but not math. Group comparisons were conducted using ANOVA procedures to examine differences between males and females and between SE and general education students on the year-end school grades in English and math. No statistically signiﬁcant differences were found between males and females on English or math year-end grades, F(1, 130) ¼ .56, p ¼ .46, and F(1, 132) ¼ 2.59, p ¼ .11, respectively. Additionally, no statistically signiﬁcant differences were found between special and general education students on English or math year-end grades, F(1, 130) ¼ .80, p ¼ .37, and F(1, 132) ¼ .15, p ¼ .70, respectively. No interaction effects between gender and SE status were found. In order to examine whether school commitment, student perceptions of school efforts to facilitate student involvement, and self-determination

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Table 5.

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Binomial Logistic Regression for Credits Earned: Odds Ratios.

Independent Variables

Gender School commitment Student involvement Self-determination: self-regulation Self-determination: psychological empowerment FCAT-NRT (SAT/9) – Math FCAT-NRT (SAT/9) – Reading Constant Chi-square

Math Credit Earned vs. No Credit

English Credit Earned vs. No Credit

.72 (.33) [.39] 1.26 (.23) [.18] 1.03 (.32) [.03] 1.07 (.66) [.05] 1.00 (.004) [.14] 1.00 (.004) [.01] N/A 6.17 9.81, 6 df

1.12 (.11) [.49] 1.43* (.39) [.20] 1.08* (.08) [.04] .96 (.04) [.07] 1.13 (.12) [.16] N/A 1.00 (.002) [.01] 7.98 15.78*, 6 df

Note: Beta coefﬁcients are in parentheses, Standard errors are in brackets. *po.05.

predicted whether students were earning credits for graduation, student grades were coded into passing and failing categories. The percentage of the total student sample who earned credits for English was 69% and for math, 56% earned course credit. The reference category for both analyses is no credits earned for the course. The beta coefﬁcients and odds ratios obtained are reported in Table 5 for both English and math credits earned. The results for the analyses indicate that student perception of school efforts to facilitate involvement and school commitment have independent predictive effects on the probability that a student earned English credits for graduation. For each 1-unit increase in school effort to facilitate student involvement, a student is 1.08 times as likely to have earned their English credits. Additionally, for each 1-unit increase in school commitment, students were 1.48 times as likely to have earned their English credits. These results reveal the potentially important effect that school level efforts and motivational individual factors may have on high school performance above and beyond the effect of prior academic achievement. The beta coefﬁcients and odds ratios obtained in the analyses examining the relationship between SCI, SIS, and AS-DS and probability of earning math credits did not reveal any signiﬁcant predictive effects. Also, it should

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be noted that prior mathematics achievement and reading achievement did not have a predictive effect on whether a student earned math or English credits. Do student perceptions of school efforts to facilitate student involvement, school commitment, and self-determination skills predict student academic performance and graduation track as measured by state assessment scores? It was of interest to further examine the predictive effect of SCI, SIS, and AS-DS on probabilities that students have passed the FCAT-SSS. Group comparisons were conducted using ANOVA procedures to examine differences between males and females and between SE and general education students on math and reading FCAT-SSS scores. Statistically signiﬁcant differences were found between males and females on both math and reading FCAT-SSS scores, F(1, 137) ¼ 6.32, po.05, partial Z2 ¼ .04 and F(1, 137) ¼ 4.15, po.05, partial Z2 ¼ .03, respectively. Females scored signiﬁcantly higher on both the math and the reading sections of the FCAT-SSS. However, partial eta squared indicates that the magnitude of effect by gender is small. Additionally, statistically signiﬁcant differences were found between special and general education students on both the math and the reading FCAT-SSS scores, F(1, 137) ¼ 18.53, po.001, partial Z2 ¼ .12 and F(1, 137) ¼ 18.83, po.001, partial Z2 ¼ .12, respectively. Students in general education scored signiﬁcantly higher on both sections of the FCAT-SSS than their peers in SE. Partial eta squared indicates that the magnitude of effect is medium to large. No interaction effects between gender and SE status were found for the reading FCAT-SSS. However, an interaction effect was found on the math FCAT-SSS, F(1, 137) ¼ 6.70, po.05, partial Z2 ¼ .05. The majority of the students in the sample (62%) did not pass the 10th grade FCAT-SSS as required for high school graduation with a standard diploma when they took the test in the 10th grade. However, some of the students later obtained passing FCAT scores from FCAT-SSS summer retakes. FCAT-SSS scores used in the analysis include retake scores. Of the four categories shown: (1) not passed the FCAT-SSS, (2) passed the math section, (3) passed the reading section, and (4) passed neither, the latter category of passed neither is the reference category. Beta coefﬁcients and odds ratios are reported in Table 6. No gender effects were found. Also, the two subdomains of selfdetermination were not found to have signiﬁcant predictive effects on the probabilities of passing all or either sections of the FCAT versus not passing.

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Table 6.

Multinomial Logistic Regression for FCAT Graduation Track: Odds Ratios. Passed FCAT vs. Passed None

Gender School commitment Student involvement Self-determination: selfregulation Self-determination: psychological empowerment

Passed Reading vs. Passed None

1.07 (.07) [.73] 1.28 (.25) [.26] 1.11* (.10) [.05] 1.05 (.04)

67 (.41) [.65] 1.95* (.67) [.34] 1.11* (.10) [.04] .86 (.15)

2.55 (.94) [.91] 1.10 (.09) [.32] .92 (.09) [.07] .95 (.05)

[.10] 1.57 (.45)

[.08] 1.13 (.12)

[.12] 1.99 (.70)

[.33] 1.08** (.07) [.02] FCAT-NRT (SAT/9) – Reading 1.08** (.08) [.02] Constant 120.45** Chi-square 162.13**, 21 df FCAT-NRT (SAT/9) – Math

Passed Math vs. Passed None

[.27] 1.08** (.08) [.02] 1.01 (.01) [.02] 66.27**

[.50] 99 (.01) [.02] 1.04 (.04) [.02] 23.48

Note: Beta coefﬁcients are in parentheses; Standard errors are in brackets. *po.05; **po.0.

Students’ academic achievement levels predicted increases in likelihood that a student would pass the FCAT-SSS as expected. For each 1-unit increase in reading achievement and math achievement on the FCAT-NRT (SAT/9), a student is 1.08 times as likely to have passed both sections of the FCAT-SSS versus not passing any section. Additionally, for each 1-unit increase in math achievement, the odds of passing the math FCAT-SSS versus neither section increases by 1.08 times. The predictive effects of reading achievement, as measured by the FCAT-NRT (SAT/9), on the probability of passing the reading FCAT-SSS versus neither section was not statistically signiﬁcant. School efforts to facilitate student involvement were signiﬁcant for predicting the likelihood that a student had passed the FCAT-SSS versus not passing either section. For each 1-unit increase in student involvement, students were 1.11 times as likely to have passed versus not. Also, for each 1-unit increase in student involvement, students were 1.11 times as likely to have passed the math section versus not passing either section. Additionally,

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school commitment was a predictor of passing the math FCAT. Speciﬁcally, for each 1-unit increase in school commitment, students were 1.95 times as likely to have passed the math section versus not passing either section.

DISCUSSION Signiﬁcant group differences were found between general and SE students on level of school commitment; however, no signiﬁcant group differences were found between general and SE students on reported levels of school efforts to facilitate student involvement or on either subdomain of selfdetermination. The results of the group comparisons were to some extent surprising as it was anticipated that SE students would report perceptions of greater school efforts to facilitate school involvement as a result of IEP and ITP meeting involvement that is federally mandated. SE students did not report higher levels of school efforts to facilitate involvement but did report lower levels of school commitment indicating a need to further examine the processes at work in schools that are designed to both involve and engage students. Additionally, as no signiﬁcant differences were found in self-determination skills between student groups, these ﬁndings indicate that students in SE (in this sample) do possess the self-determination skills needed to self-advocate and actively participate in educational and post-school planning. However, the results of the SIS also suggest that these students do not feel that they have been provided the opportunities to participate in educational planning. Also, it was expected that students with strong selfdetermination skills and opportunities to participate in their own educational planning would be on track for graduation. However, approximately only 50% of students in this study was on track for graduation with a standard diploma and had passed the FCAT-SSS and earned academic credits toward graduation. School commitment and student perceptions of school efforts to facilitate student involvement predicted whether students earned English credits for graduation. That is, students who reported lower levels of school commitment and school efforts to facilitate student involvement were less likely to have earned English credits for the school year, regardless of reading achievement level as measured by the FCAT-NRT (SAT/9). Unexpectedly, however, this relationship did not hold true for predicting whether students had earned mathematics credits. It can only be speculated that the nature

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of differentiated mathematics curriculum at the high school level could possibly explain why achievement did not predict passing. These same variables were examined as predictors to determine the relationship between these variables and the odds of passing the FCAT-SSS. As expected, higher FCAT-NRT (SAT/9) scores did increase the odds that students passed the FCAT-SSS for graduation. However, student perception of school efforts to facilitate student involvement had an independent predictive effect on passing the FCAT-SSS, and student involvement and school commitment also predicted whether students passed the math section of the FCAT versus passing neither section. However, for students who only passed the reading section of the FCAT-SSS, school commitment and school efforts to facilitate student involvement were not signiﬁcant predictors. In sum, these ﬁndings support the hypothesis that other factors such as school commitment and school efforts to facilitate student involvement have an impact on whether students are on track for high school graduation. This ﬁnding is particularly important given the declining trends noted in graduation rates for students in Florida. The ﬁndings further suggest that schools should actively promote student involvement and participation in their own educational planning in order to help students develop intrinsic school commitment. For participants in this study, it certainly seems that increased school efforts to facilitate student involvement and school commitment would improve the odds of successfully graduating from high school with a standard diploma.

IMPLICATIONS FOR PRACTICE IDEA includes provisions to align itself with NCLB in that states must establish goals and standards for students with disabilities that align with AYP and address graduation rates. Furthermore, IDEA requires that students with disabilities be involved in the planning of their own education. These requirements have led districts to document student involvement in planning meetings; however, these mandates and requirements do not necessarily mean that teachers, counselors, and administrators present in these meetings encourage or value students input (Thoma, Rogan, & Baker, 2001). Speciﬁcally, research has demonstrated a need to examine parent, teacher, and student perspectives on implementation of practices in schools (Grigal, Neubert, Moon, & Graham, 2003; Wagner, Newman, Cameto, Levine, & Marder, 2007). The results of this study utilizing student

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perspectives suggest that students receiving SE services are not necessarily experiencing involvement in IEP and ITP meetings in a meaningful way. Research has reported many classroom and school level protocols and curricula designed and shown to foster student involvement and participation and self-determination (Test et al., 2004). However, students must be provided the opportunities for meaningful participation in planning. These opportunities may only be provided in a meaningful way if teachers, counselors, and school administrators work together to facilitate student involvement. Additionally, NCLB requires that all students, with and without disabilities, be accountable to ‘‘high’’ standards in order to obtain a standard high school diploma. Although this is an appropriate expectation, the demonstration of ‘‘high’’ standards is frequently tied solely to performance on state assessments. If students are unable to ‘‘pass’’ these assessments, they are tracked into special diploma or certiﬁcate of completion tracks. Research has demonstrated that students who do not graduate with a standard diploma often experience negative consequences (Erickson, Kleinhammer-Tramill, & Thurlow, 2007). With federal mandates determining requirements for both special and general education students, an examination of a broad range of factors related to student persistence in school is necessary. The results of this study indicate that other factors, in addition to academic achievement, have direct predictive effects on whether students are on track for high school graduation with a standard diploma. Particularly, the predictive effect of school efforts to facilitate student involvement on whether a student has passed the FCAT as required for graduation with a standard diploma has many implications for school practice. We know that previous student achievement predicts later student achievement, but what can educators do to improve the odds of academic success for students with poor previous academic performance? This study suggests that actively facilitating student involvement in educational planning and developing ‘‘partnerships’’ with secondary school students may lead to greater likelihood of successful graduation with a standard diploma under NCLB, above and beyond the impact of previous academic performance.

REFERENCES Almqvist, L., & Granlund, M. (2005). Participation in school environment of children and youth with disabilities: A person-oriented approach. Scandinavian Journal of Psychology, 46, 305–314.

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Benz, M., Lindstrom, L., & Yovanoff, P. (2000). Improving graduation and employment outcomes of students with disabilities: Predictive factors and student perspectives. Exceptional Children, 66, 509–529. Bond, T., & Fox, C. (2001). Applying the Rasch model: Fundamental measurement in the human sciences. Mahwah, NJ: Lawrence Erlbaum Associates. Carter, E., Wehby, J., Hughes, C., Johnson, S., Plank, D., Barton-Arwood, S., & Lunsford, L. (2005). Preparing adolescents with high-incidence disabilities for high-stakes testing with strategy instruction. Preventing School Failure, 49(2), 55–62. Center on Education Policy. (2004). State high school exit exams: A maturing reform. Washington, DC: Author. Clarke, M., Haney, W., & Madaus, G. (2000). High stakes testing and high school completion. Statements, 1(3)Available at www.bc.edu/research/nbetpp/publications. Retrieved on 12 August 2008. Darling-Hammond, L. (2006). No Child Left Behind and high school reform. Harvard Educational Review, 76, 642–647. deFur, S. H. (2002). Education reform, high-stakes assessment, and students with disabilities. Remedial and Special Education, 23, 203–211. Finn, J. (1989). Withdrawing from school. Review of Educational Research, 59(2), 117–142. Florida Department of Education. (2006a). Florida education and training placement information program (FETPIP). (Technical report). Tallahassee, FL: Author. Florida Department of Education. (2006b). LEA proﬁle. (Technical report). Tallahassee, FL: Author. Florida Department of Education. (2007). Florida’s statewide four-year graduation rates: 1998– 99 through 2006–07. Tallahassee, FL: Florida Department of Education. Gaumer Erickson, A., Kleinhammer-Tramill, J., & Thurlow, M. (2007). An analysis of the relationship between high school exit exams and diploma options and the impact on students with disabilities. Journal of Disability Policy Studies, 18, 117–128. Gibson, M., & Bejinez, L. (2002). Dropout prevention: How migrant education supports Mexican youth. Journal of Latinos and Education, 1, 155–175. Greene, J., & Winters, M. (2002). Public school graduation rates in the United States. Civic Report (31). Manhattan Institute for Policy Research. Grigal, M., Neubert, D., Moon, M., & Graham, S. (2003). Self-determination for students with disabilities: Views of parents and teachers. Exceptional Children, 70, 97–112. Katsiyannis, A., Zhang, D., Ryan, J., & Jones, J. (2007). High-stakes testing and students with disabilities: Challenges and promises. Journal of Disability Policy Studies, 18, 160–167. Lee, V., & Burkham, D. (2003). Dropping out of high school: The role of school organization and structure. American Educational Research Journal, 40, 353–393. Levesque, C., Zuehlke, N., Stanek, L., & Ryan, R. (2004). Autonomy and competence in German and U.S. university students: A comparative study based on self-determination theory. Journal of Educational Psychology, 96, 68–84. Mason, C., Field, S., & Sawilowsy, S. (2004). Implementation of self-determination activities and student participation in IEPs. Exceptional Children, 70, 441–451. McNeil, L. M., Coppola, E., Radigan, J., & Vasquez Heilig, J. (2008). Avoidable losses: High-stakes accountability and the dropout crisis. Education Policy Analysis Archives, 16(3). Morrison Cavendish, W. (2006). School commitment, student perception of school efforts to facilitate student involvement in the education process, self determination, and

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Wehmeyer, M., & Kelchner, K. (1995). The arc’s self determination scale. Washington, DC: The Arc of the United States. Wehmeyer, M., Palmer, S., Agran, M., Mithaug, D., & Martin, J. (2000). Promoting causal agency: The self-determined learning model of instruction. Exceptional Children, 66, 439–453. Ysseldyke, J., Nelson, J., Christenson, S., Johnson, D., Dennison, A., Treiezenberg, H., Sharpe, M., & Hawes, M. (2004). What we know and need to know about the consequences of high-stakes testing for students with disabilities. Exceptional Children, 71, 75–94.

FUNCTIONAL BEHAVIORAL ASSESSMENT AND STUDENTS WITH EMOTIONAL/BEHAVIORAL DISORDERS: WHEN RESEARCH, POLICY, AND PRACTICE COLLIDE Maureen A. Conroy, Peter J. Alter and Terrance M. Scott ABSTRACT The purpose of this chapter is to highlight issues related to the current policy, practice, and research in the area of functional behavioral assessment (FBA) for students with (or at risk for) emotional/behavioral disorders (EBD). Although a substantial research base exists validating the effectiveness of FBA and function-based interventions for students with developmental disabilities, we believe that these same FBA practices are less valid when employed for students with EBD in classroom settings. Following a review of the current research and a discussion of the practical issues that are encountered when implementing FBA in classroom settings serving students with EB, we outline a more responsive FBA model for students with EBD with an emphasis on future policy, research, and practice applications for the ﬁeld to consider. Policy and Practice Advances in Learning and Behavioral Disabilities, Volume 22, 133–167 Copyright r 2009 by Emerald Group Publishing Limited All rights of reproduction in any form reserved ISSN: 0735-004X/doi:10.1108/S0735-004X(2009)0000022007

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We are all familiar with the age-old adage, ‘‘If it ain’t broke don’t ﬁx it.’’ But what happens when a car breaks down over and over or it is involved in a collision? At ﬁrst the driver tries to ﬁx the car, repairing or replacing broken parts, painting over scratches or dents, and so forth, until the repairs become too costly, or the car becomes too old or unsightly. Eventually, due to ﬁnancial and labor costs, the driver decides to abandon the car and buy a newer and likely ‘‘jazzier’’ make or model that is more appealing than the old, run-down vehicle. In the ﬁeld of special education, we have seen this scenario occur repeatedly as new instructional approaches are unveiled or repackaged. Special education practitioners embrace the ‘‘instructional practice du jour’’ by rapidly gathering information, receiving in-service training, and developing policies to implement the practice. Often, however, this is done with insufﬁcient thought to the practicalities of real world implementation and effectiveness. Researchers and policy makers rapidly work to disseminate information about the new instructional strategy into the hands of practitioners, hoping to bridge the research-to-practice gap. At some point, after all this ﬂurry, practitioners often begin to ﬁnd components of the practices difﬁcult to implement, researchers don’t have all the answers as to how the practice should be implemented in applied settings, and in-service training resources are insufﬁcient. Too often administrators are caught between trying to help implement practices that meet the letter of the law and being limited from doing so because of the practical implications of implementing these practices in everyday educational settings with various competing demands. If the instructional practice is effective and user-friendly, practitioners gladly embrace and implement it in their classrooms. However, if the instructional practice is ineffective, too time intensive or costly, impractical or they simply do not know ‘‘how to drive,’’ they will often abandon the practice or they will imprudently adapt their use of the practice to meet their own needs or legal requirements. It will be our fundamental contention in this chapter that the current characterization of functional behavioral assessment (FBA) in the ﬁeld of emotional/behavioral disorders (EBD) has become the tired, old, unfashionable automobile. Like the old car, the FBA is repainted, tuned-up, and altered but still maintains many of the same worn parts and outdated features. Although we wish to be clear that old does not necessarily equal ‘‘outdated,’’ we have observed that many facets of the FBA process have been found to be lacking in either effectiveness or implementation and, in our view, many of the ﬁxes have been superﬁcial, superﬂuous, or otherwise

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ineffective (i.e., ‘‘band-aid solutions). In this chapter, we provide an analysis of the challenges confronting the effective use of FBA for students with EBD in school settings and propose directions for future research and practice that constitute the thoughtful reengineering of a more effective and efﬁcient model. Since the Individuals with Disabilities Educational Act (IDEA, 1997) reauthorization mandated the use of FBA, a considerable amount of research, training, and implementation has occurred. Researchers and practitioners have done their best to implement FBA techniques based on the existing literature with students with (or at risk for) EBD in classroom settings. However, when implemented for students with EBD, the traditional FBA strategies have limitations in their applicability and utility in school and classroom settings (Nelson, Roberts, Mathur, & Rutherford, 1999). As a result, teachers have voiced their concerns that the strategies are only effective for a small number of students and are not relevant for the large percentage of the students who demonstrate chronic problem behaviors in their classrooms (Scott, Liaupsin, Nelson, & McIntyre, 2005). Researchers, alike, have begun to voice the same concerns (see Sasso, Conroy, Stichter, & Fox, 2001). Recently, Scott and Kamps (2007) discussed the issues related to implementation of FBA in school settings, stating that ‘‘Although more recent research has certainly demonstrated that the principles associated with behavior analysis and FBA are as applicable to school settings as any other, there remain contexts for which our information and study is still inadequate’’ (p. 154). Not only is the research base inadequate, but the FBA training provided has not been sufﬁcient to develop the necessary skill level needed for school staff to implement these complex practices, and there is a dearth of studies related to training in school settings. To that point, Van Acker, Boreson, Gable, and Potterton (2005) determined that after a state-wide training effort (conducted by the senior author) for school teams across one state, the FBAs (which included behavioral intervention plans) that had been developed by school staff displayed serious ﬂaws in almost all facets of the FBA protocol. A national survey on the status of FBA in schools revealed similar shortcomings in terms of the dissemination, training, monitoring and the FBA resources themselves, with district personnel left to their own devices. As a result, FBA procedures may have been and continue to be inconsistently or inadequately applied to many students who need it the most (Weber, Killu, Derby, & Barretto, 2005). Although a critical component, staff training, alone is not sufﬁcient. An alternative or modiﬁed FBA model that is more responsive to the teacher’s

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needs, characteristics of students with EBD, and that is more applicable to classroom contexts within today’s schools is needed. Thus, the overall purpose of this chapter is to (1) provide a critical review of the current FBA approach employed with students with EBD and (2) propose a modiﬁed approach for the implementation of FBA with EBD students in classroom settings. We begin with a brief overview of the history of FBA and current literature.

HISTORICAL PERSPECTIVES AND CURRENT LITERATURE Use of FBA strategies has a long history before the federal mandate in IDEA (1997). As discussed by Gresham, Watson, and Skinner (2001), FBA has its origin in the operant learning literature, more precisely in the philosophy of functionalism, which emphasizes the need to understand the controlling variables or functions of behavior, rather than examining behavioral topography alone. Thus, the purpose of an FBA is to identify the environmental variables (i.e., antecedent and consequent events) that evoke or maintain behavior, with the goal of manipulating these environmental variables in order to decrease the problem behavior and increase appropriate responses that serve the same function as the problem behavior (Repp & Horner, 1999). In 1977, Carr wrote one of the earliest papers on the topic of functional assessment and function-based interventions. Carr proposed a number of ‘‘motivational sources’’ of self-injurious behavior and suggested employing a hypothesis-based intervention to decrease self-injurious behaviors. The original motivational sources (or functions) suggested by Carr included (1) positive socially mediated reinforcement (e.g., obtaining attention), (2) negative socially mediated reinforcement in the form of escaping aversive events (e.g., tasks or attention), (3) self-stimulation in form of sensory reinforcement, (4) an abnormal organic or physiological process, and (5) a psychodynamic process that results in reducing guilt or establishing ego boundaries. Following Carr (1977), Iwata and colleagues (Iwata et al., 1994b) developed analog probe assessment methodology referred to as ‘‘functional analysis,’’ which was designed to systematically assess the functions (or motivations) of self-injurious behavior proposed by Carr. Since these two seminal papers, the research on identifying functions of behavior through functional analysis methodology has signiﬁcantly increased with direct and systematic replications across behavioral

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topographies, populations, and settings (see Hanley, Iwata & McCord, 2003 for a review). Additionally, functional analysis methodology itself has been systematically modiﬁed to (1) examine various contextual aspects of the environment (e.g., inﬂuence of discriminative stimuli; Carr, Langdon, & Yarbrough, 1997; brief functional analysis in applied settings; Broussard and Northrup, 1995; Iwata, Dorsey, Slifer, Bauman, & Richman, 1994a) and (2) assist with analysis and interpretation of data patterns; Vollmer and Northrup (1996). A comprehensive review of the functional analysis literature is beyond the scope of this chapter. Needless to say, however, the ﬁeld has substantially evolved since Carr’s and Iwata’s early work and functional analysis has been widely demonstrated to be an effective tool in identifying environmental contributors to aberrant behavior (Carr et al., 1999). Although there are distinct differences in the deﬁnitions of FBA and functional analysis, it was this early work in functional analysis that has perhaps contributed most to the evolution of FBA as applied in school settings. A single deﬁnition of FBA does not exist in the literature; however, most researchers agree that FBA is a systematic, outcome-driven process, which includes various direct and indirect assessment strategies and results in the generation of information about antecedent and consequent events that surround an identiﬁed behavior (Gresham et al., 2001; Murdock, O’Neill, & Cunningham, 2005; Shriver, Anderson, & Proctor, 2001). Whereas a functional analysis refers to an experimental manipulation of environmental events to measure the effects on a targeted behavior (Ervin et al., 2001), FBA is often used as an overarching term that may or may not necessarily include functional analysis (Kates-McElrath, Agnew, Axelrod, & Bloh, 2007). Some researchers strongly recommend the inclusion of functional analyses in the FBA process (e.g., Asmus, Vollmer, & Borrero, 2002; Kamps, Wendland, & Culpepper, 2006), whereas others refer to FBA as a purely descriptive process (e.g., Murdock et al., 2005; Shriver et al., 2001). Overall, most researchers agree that FBA involves the following three steps: (1) developing hypotheses regarding the potential antecedents that may evoke (and consequences that may maintain) the behavior using multiple assessment sources (i.e., indirect and direct observational measures); (2) directly manipulating hypothesized antecedent and consequent events in naturalistic or analog settings to ‘‘test’’ the inﬂuence of these environmental factors on the behavior; and (3) developing, implementing, and evaluating interventions linked to assessment ﬁndings (Dunlap & Kern, 1993; O’Neill et al., 1997). Although this deﬁnition does not precisely describe how each step should be completed, the overall FBA process is clear.

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The FBA process outlined in IDEA (1997) is far less explicit and does not necessarily require school staff to follow the procedures outlined in the literature (Drasgow & Yell, 2001). IDEA (1997) mandates that the IEP team use positive behavioral interventions, strategies, and supports for students with disabilities (and who also demonstrate problem behaviors that interfere with their own or other’s learning) [IDEA, 20 U. S.C. y 1414 (d)(3)(B)(i)]. FBA, as outlined in IDEA, was intended to be part of the process for addressing problem behaviors demonstrated by students with disabilities. However, it is not speciﬁcally deﬁned within the law, and depending on the student’s situation, is not always required (e.g., an FBA is not required for students removed from school for less than 10 days) (Drasgow & Yell, 2001). In fact, the Department of Education intentionally made a decision to leave the composition of an FBA up to states, school districts, and IEP teams to decide (Drasgow & Yell, 2001). However, clariﬁcation of FBA was published in the Federal Register and deﬁned as ‘‘a process which searches for an explanation of the purpose behind a problem behavior’’ (Ofﬁce of Special Education Programs Questions and Answers, 1999). With such vague direction, it is not surprising that the composition of FBAs in schools is extremely varied and may range from single page checklists to more laborious but often no more valid processes involving a range of practices and procedures. This lack of a consistently deﬁned FBA process has been at the heart of a chasm between the research literature and FBA as practiced in schools, leading to numerous well-documented issues. As researchers seek to investigate the generality and applicability of FBAs across various student characteristics and educational settings, IEP teams are developing and implementing their own FBA process. Although there may be some overlap in these approaches, there is often a disconnect between the FBA tools employed by researchers (with more emphasis on validity and little thought afforded to practicality) and those used by practitioners (with more emphasis on practicality and little thought afforded to validity). For example, Blood and Neel (2007) examined existing student ﬁles to determine the types of FBA assessments used and found that (1) teacher interview and behavior rating scales were the FBA tools most often cited, (2) many FBAs did not include hypothesis statements, and (3) behavioral intervention plans were not necessarily linked to individualized FBAs. These ﬁndings lend support to our belief that researchers and practitioners are most likely approaching FBA differently. In the following section, we will review the application of FBA used for students with EBD, beginning with an overview of the characteristics of students with EBD and followed by a discussion of the existing research base.

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FBA AND STUDENTS WITH EBD Characteristics of Students with EBD The poor post-school outcomes experienced by individuals with EBD have been widely documented. In fact, individuals with EBD experience the least favorable outcomes of any group of individuals with disabilities (Kauffman & Landrum, 2008). Recent incidents of school violence also have raised concerns among the general public regarding school safety, whereby policies such as ‘‘zero tolerance’’ have the potential to further limit the educational beneﬁts these individuals receive. Those who advocate for this population are rightfully concerned about the degree to which individuals with EBD are able to positively contribute to society given their challenging behaviors and the manner in which schools typically perceive and interact with these students. In school, students with EBD often display characteristics that do not support success school or life-long success. Examples include (a) the inability to sustain or maintain appropriate social relationships with others, (b) academic difﬁculties in multiple content areas, and (c) chronic behavior problems, including noncompliance, aggression, and disrespect toward authority ﬁgures (IDEA, 2004; Kerr & Nelson, 2006). Clearly, these students present challenges for schools both in attempts to comply with federal law with regard to assessment and intervention requirements and with attempts to provide programs and procedures that are both effective and palatable for school personnel.

FBA Research with Students with EBD Because the original functional analysis and FBA research was primarily conducted for individuals with developmental disabilities, there is a dearth of research that extends the use of FBA to typically developing students, students with mild to moderate disruptive behavior, or adolescents (Boyajian, DuPaul, Handler, Eckert, & McGoey, 2001; Broussard & Northrup, 1997; Ervin, DuPaul, Kern, & Friman, 1998; Flood, Wilder, Flood, & Masuda, 2002; Jones, Drew, & Weber, 2000; Vollmer & Northrup, 1996). Of the scant research that has been conducted with these populations, there has been even less conducted within classroom contexts (Boyajian et al., 2001; Broussard & Northrup, 1995; Ervin et al., 1998). Following the reauthorization of IDEA (1997), professionals in the ﬁeld of EBD increased

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discussions on the applicability of FBA to the EBD population reviewing the current literature base and outlining future research directions (e.g., see Fox, Conroy, & Heckaman, 1998; Nelson et al., 1999; Heckaman, Conroy, Fox, & Chait, 2000; Lane, Umbreit, & Beebe-Frankenberger, 1999; Sasso et al., 2001). Kern, Dunlap, and colleagues conducted some of the earliest studies investigating the use of FBA with students with EBD (e.g., see Dunlap, Kern-Dunlap, Clarke, & Robbins, 1991; Dunlap et al., 1993; Dunlap, & Kern, 1993; Kern, Childs, Dunlap, Clarke, & Falk, 1994). Although identiﬁcation of functions has been an integral part of their research, a number of these studies focused on manipulation of antecedent variables (e.g., task difﬁculty, preference) as a means for minimizing the occurrence of the problem behaviors rather than solely identifying and manipulating consequences maintaining the problem behaviors. Ervin et al. (2001) conducted one of the most comprehensive reviews of school-based FBA, which included a meta-analysis of 100 research studies examining the use of FBA in school settings. In summary, her review indicated that a total of 278 students, with and without disabilities, who demonstrated an array of behavioral and academic problems, participated in these studies. Of this sample, 89% had identiﬁed disabilities, which included severe developmental and cognitive delays, speech and language disorders, learning disabilities, or EBD. Of the total sample of 278 students, only 11% (31) were identiﬁed as having an EBD. Additionally, the majority of the students included in the entire sample (64%) of the students were enrolled in a special education classroom and 64% of the FBAs were conducted in an analog or combined analog/natural setting. Given that this was a review of research studies, it is not surprising that 93% of the studies conducted an experimental analysis. Interestingly, 70% of the studies examined both antecedent and consequences related to problem behaviors and 30% of these experimental manipulations were conducted collaboratively by school staff and the researchers. On the basis of their review, Ervin and colleagues suggest that there is a growing body of FBA literature in applied settings, but ‘‘with regards to applications across target populations, behaviors, and settings, the existing school-based FA literature is limited in scope’’ (p. 205). They also conclude that some FBA components such as functional analyses may be difﬁcult to implement in classroom contexts and that FBA is not well suited for examining functions of low-rate, highintensity behaviors. Finally, they point out that there is a paucity of research examining the applicability, effectiveness, and social validity of FBA procedures used by school personnel.

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Since this earlier work, researchers have increased their investigations of the applicability of FBA for students with mild disabilities, including EBD, in school settings. More recently, Reid and Nelson (2002) conducted a review of the literature that examined the effectiveness, acceptability, and practicality of FBA in school settings for students with high-incidence problem behaviors. Fourteen studies met their inclusion criteria of ‘‘examining the use of FBA with a student without severe developmental disorders in a school setting’’ (p. 16). In regard to the effectiveness of FBA (which was deﬁned as behavioral improvement of the targeted student), they found that indeed researchers in 12 of the 14 studies were able to identify functions of problem behaviors through the use of FBA and that many of these studies conducted FBAs within the general education classroom. Only a single study examined the maintenance of these effects; thus, there is little information on whether the outcomes of these studies sustain over time. The acceptability of FBA was also examined and the authors found that only four of the 14 studies provided any information on the social validity of FBA in school setting. Given the nature of applied behavioral research and the emphasis on collecting more social validity data (Schwartz, 2003), it is surprising that more researchers have not tackled this aspect of the research. As reported by Reid and Nelson, in three studies, teachers stated that the FBA procedures were acceptable and improved student performance. Finally, Reid and Nelson reported on the practicality of FBA and found that in only one study in which school staff were involved in the implementation of the FBA; whereas in the other 13 studies all FBAs were conducted by the researchers. From an applied perspective, this ﬁnding is troubling and leaves open the question as to whether school staff can practically conduct FBA (as traditionally deﬁned) within a school setting. Of note is the fact that Reid and Nelson did not ﬁnd any studies addressing the target population outlined in IDEA (1997) (i.e., students who have had more than 10 days of suspension). Although the literature highlights some promising trends, there are a number of caveats that should be considered when reviewing the outcomes. First, the literature reviews presented examined empirical investigations that have been published in peer-reviewed journals. Therefore, it is not surprising that FBA was found to be generally effective, as studies reporting inconclusive or ineffective ﬁndings would be less likely to have been published. In addition, the results provide continued evidence of the very few studies examining the combined effectiveness, palatability, and social validity of FBA conducted by school staff with students with EBD in classrooms settings. Although additional research is continuing to be

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conducted, we found in our review that these issues still need to be addressed in future research endeavors as many of our existing research efforts persist in ignoring personal and contextual variables in its assessment of practice. As suggested by Reid and Nelson (2002), at least three critical issues should be addressed in future research. The ﬁrst issue is to examine whether FBA and its resulting function-based intervention has a positive impact on students with EBD and, if it does, whether it is more efﬁcacious and efﬁcient than implementation of other assessment and intervention options that may be easier to implement (e.g., life space interviews and cognitive therapy). Second, investigating teachers’ implementation of FBA is vital. The focus should be on whether teachers can and will implement typical procedures associated with function-based support planning. Third, examining teacher’s perceptions of FBA procedures and function-based intervention is imperative as well as the training and supports needed for successful implementation in schools. We agree with Reid and Nelson and presently, do not believe that we have the research available to answer these questions or know how to apply the principles underlying FBA to the EBD population. In the following section, we provide a more detailed assessment of the use of a traditional function-based approach for students with EBD, focusing on contexts and conditions that present speciﬁc challenges for the use of FBA with this population.

ASSESSMENT OF A TRADITIONAL FBA APPROACH WITH STUDENTS WITH EBD As discussed, following IDEA (1997), one of the ﬁrst issues that surfaced in the literature was a professional discussion regarding the applicability of what is considered a traditional FBA process in relation to the characteristics of the majority of students with chronic problem behaviors in classroom settings, including students with EBD. Not only has this issue been frequently discussed in the literature, we have also seen in our practice that not all traditional FBA components are matched well to the characteristics of the students we are intending for them to be used with. Although identiﬁcation and manipulation of maintaining consequences is an important part of changing behavior and can be a valuable and effective strategy, we are suggesting that it may be neither the most efﬁcient nor the most useful strategy when implementing FBA in schools with students with EBD. In this section, we critically review the issues related to using a

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traditional FBA approach for students with EBD and other high-incidence disabilities. The following sections present a critical analysis of the challenges confronting our current conceptualization and implementation of FBA in school settings. We address these issues not to denigrate the integrity of the underlying foundations of FBA, which we believe to be sound, but to illuminate where discussion and research must focus if we are ever to successfully transfer that technology to students with EBD in a typical classroom setting. The process of FBA normally involves not only the assessment itself but also the development of an effective intervention based on the results of that assessment. We shall refer to the entire process as a function-based intervention, denoting a behavior intervention plan that is based on the outcomes of an FBA. In the next several sections, we discuss the conditions under which function-based intervention might be considered unwieldy, inefﬁcient, or illogical.

Challenges for FBA: Training and Personnel Moving classroom teachers and other instructional school personnel to think functionally about problem behavior represents a paradigm shift that has been described as ‘‘systems change’’ (Scott, Nelson, & Zabala, 2003). If we are to move forward in our goal to facilitate the use of FBA and functionbased interventions in schools, we must recognize the roadblocks to effective implementation, develop effective solutions, and implement training. Although easily said, several issues continue to confound this process. Philosophy, personality, and FBA. Because of its inclusion in IDEA, it is likely that the tenets of FBA and its behavior analytic foundations are covered at least brieﬂy in most special education teacher preparation programs. However, it is equally likely that the term ‘‘FBA’’ is completely foreign to most other school personnel and that a behavior analytic perspective is antithetical to much of the basic pedagogical theory with which they have been indoctrinated in schools of education. For example, many general education teacher preparation programs are based on a constructivist approach to education. Thus, at times, we have encountered resistance from general educators to such behavioral practices as prompting desired behavior, reinforcing instances of appropriate behavior, or even teaching rules to facilitate appropriate behavior. For people who are averse to even these most basic behavioral practices, the aura of an entire process

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dedicated to assessing behavior for purposes of behavioral intervention will be a difﬁcult sell. Legal requirements provide some support in this battle, but as with most practices, fundamental philosophical disagreement is likely to lead to poor implementation and a lack of results. In other words, what people don’t believe in (or want to do) are things they won’t do well. And what they don’t do well won’t work. Given this roadblock, we are left with two options: (1) leave FBA to the special educators and specialists to implement within school settings or (2) change the way general educators think and act. The former option often represents the current state of attempts to implement FBA in school settings; but, if we are to make inroads into using FBA more proactively in these settings at some point the latter option must be addressed in a manner that is respectful of inevitably different philosophies and perspectives. For example, in special education, we often use acronyms or terminology or jargon that is difﬁcult for others to understand. Perhaps the term ‘‘function’’ could be rephrased and described as how behavior meets a student’s needs or as how behavior helps the student communicate. We believe that such changes are purely aesthetic – a ‘‘window dressing’’ to help sell the larger practice – and can be implemented while maintaining sufﬁcient integrity to the underlying behavior analytic principles of FBA. Our point is that the terminology we use in FBA trainings may inﬂuence how others embrace the practice. Thus, if we use a ‘‘window dressing’’ to clarify the terminology, we may ﬁnd school personnel are more receptive to the concept, which may facilitate the implementation. It is worth considering for any of us whether we would be inclined to accept and support a complex assessment and intervention program such as FBA including function-based intervention planning, assuming that we had no complimentary belief system or even a basic awareness of the wellresearched behavioral principles upon which it is founded. To be certain, education has been (and continues to be) an especially passive victim to fad (Kauffman, 2002). Given that school personnel have been subject to an array of interventions, philosophies, and programs that have come and gone – often more than once, why would we believe that teachers and other school personnel would jump on board with FBA? Of course the conundrum is that, in order to convince these individuals we must ﬁrst demonstrate the beneﬁcial effects, but in order to demonstrate the beneﬁcial effects, we will require a willingness to buy in and implement. Thus far we have discussed philosophies that are likely learned in teacher preparation programs, schools of education, or simply by experience in schools. But there is another more ominous philosophical roadblock that is in many instances more challenging as it likely represents a core personal

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belief rather than pedagogical philosophy. We are all familiar with educators who believe that rules outlining appropriate behavior represent an expectation that the student simply chooses to follow or not follow. This belief may be expressed, ‘‘he knows what to do and he just needs to do it – or else.’’ Often, persons espousing this viewpoint are resistant to behavior intervention planning, believing that increasingly harsh punitive consequences (rather than proactive and preventative practices) will result in eventual behavior change or provide proof of the incorrigible nature of the student. Some believe that these students are not appropriate for (or do not deserve to be in) a typical school setting. In a Darwinian ‘‘survival of the ﬁttest’’ manner of thinking, these students are simply to be weeded out of the general education process. Although such thinking contradicts the fundamentals of what it means to be a teacher (facilitating student success), it nevertheless perpetuates itself through negative reinforcement for the teacher. Harsh punishments and exclusions, for example, provide temporary relief for the teacher pending the point at which the student is permanently removed. We believe educators holding beliefs of this nature represent a much more formidable roadblock for the effective use of FBA. If we are to make gains with the effective use of FBA in schools, it would appear that we again have two options: change educators or work around them. Given that little has been written about this issue and few ideas have been offered as to how to initiate any sort of change in this belief system, an examination of the impact of philosophical beliefs on the implementation of FBA appears to be an important part of future training and research efforts. At this point it seems prudent to discuss training issues on the design and implementation of FBA support in a collaborative and consensual manner. Training issues in FBA. The issue of training school personnel in FBA is in some ways simple and straightforward and in other ways difﬁcult and complex. To be certain, effective and efﬁcient use of FBA and function-based interventions in the school will require that we train school personnel to use it in an effective and valid way. In addition, the structures are already in place and functioning for both pre-service (teacher training institutions) and inservice (district-level professional development) training. However, there currently is very little coordination among these entities and the delivery model is often sporadic and disjointed. It is likely that very few general education teachers are exposed to FBA at either the college level or as part of district training, as these areas have tended to be the domain of special education and school psychology. In addition, even our FBA training model in special education often consists of one lecture in a behavior management course and one- or two-day in-service trainings in the school district with little

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or no follow-up coaching. We treat other instructional areas of the curriculum (e.g., teaching of reading or math) with much greater intensity and consistency at both pre- and in-service levels. Moving forward with FBA will require a concerted effort to affect both the scope and intensity of training at the pre-service and in-service levels. Given our previous discussion of philosophical roadblocks, making these inroads into general education at the university level presents a major challenge. Inconsistent training in FBA. Further impeding the development of effective training is the fact that, although there may be general consensus as to the underlying principles of behavior analysis and FBA, there are still signiﬁcant differences with regard to the conceptualization of and practices involved in the FBA process. In a later section, we discuss completely the issues related to practice and some basic disagreements among researchers as to which practices should be used, when, and by whom. But at a more basic level, there exist differences across leaders in the ﬁeld even with how function is to be conceptualized. For example, Magg (2004) lists seven different ‘‘functions’’ including terms that we would argue are not sufﬁciently operationalized to have construct validity (e.g., power/control, expression of self, gratiﬁcation, and justice/revenge). Similarly, Frey and Wilhite (2005) list ﬁve ‘‘functions:’’ survival, belonging, power/self-worth, freedom, and fun. Such conceptualizations are in stark contrast to those that arose from the original experimental analyses from which the FBA technology was born (Carr & Durand, 1985) and to other published FBA manuals and texts (e.g., O’Neill et al., 1997; Umbreit, Ferro, Liaupsin, & Lane, 2007). A general consensus from the research literature denotes two functions: access to reinforcement and escape/ avoidance of aversive stimuli. Within this conceptualization is room for subcategories such as access to (or escape from) tangible reinforcers, attention, and sensory variables. However, in every instance a function is hypothesized through observation of a relationship between a behavior and a concrete consequent event. Because constructs such as ‘‘power’’ and ‘‘fun’’ represent immeasurable events, they do not ﬁt within the technical description of FBA as original conceived. That is not to say that such conceptualizations are worthless or irrelevant; they ﬁt nicely within a more cognitive approach toward management of behaviors. But we believe that such descriptions, couched within the context of FBA, are misplaced and provide a challenge to the quest of moving effective and efﬁcient FBA and function-based intervention planning into school settings. Any sound methodology must be deﬁned in a consistent and replicable manner – or we run the risk of watering down the technology to the point where it will be ineffective and become another in a line of fads.

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Challenges for FBA: Behaviors and Settings Regardless of legislative mandates, there are two key considerations that may make the FBA and function-based intervention plan either ill-advised or unnecessary. The ﬁrst consideration is the topography of the problem behavior that is being targeted by the FBA process. Regrettably, a byproduct of IDEA legislation is that the FBA process must be immediately enacted for certain high magnitude problem behaviors. For example, the possession of a weapon or drugs would immediately necessitate a FBA and development of a function-based intervention. However, in many instances, these types of problem behaviors do not respond to the typical FBA process and function-based interventions that would be generated by this process. For example, if a student were caught bringing a gun to school, an FBA and behavioral intervention program (BIP) would be legally required to be developed. If, before the function-based intervention process began, it was determined that the student was bringing the gun because he needed protection from a group of bullies (rather than a function of obtaining peer attention), then a function-based intervention approach to ameliorate the weapon-carrying behavior would seem unproductive in solving the problem. Rather, the behavior of the ‘‘bullies’’ would need to be directly addressed and the target student would need further instruction in how to handle bullying situations. This situation would require considerable administrative intervention and various other school actions, but it is doubtful that the FBA and function-based intervention process would be particularly helpful. Infrequent but serious behavior. As detailed by Sprague and Horner (1999) many low-frequency, high-intensity behaviors require more complex measurement systems and a focus on response classes, setting events, and or establishing operations. The systems described seem to outpace both the skills and abilities of many school personnel and the time and energy available that this level of analysis would demand. For example, if a student is observed to engage in ﬁve to six serious ﬁghts during the duration of a school year, he or she very well may be suspended for more than the 10-day period outlined under IDEA. But what would a FBA look like for such a student if we were to set out to observe the behavior in pursuit of predictable patterns? It is unlikely that we would be able to observe such episodes short of following the student all day, every day for an extended period of time. Under such circumstances, it would be more prudent to use the full-time observer to follow and prevent ﬁghting rather than observe it. Reactivity. Related to the difﬁculties of observing infrequently occurring problem behaviors is the fact that the simple act of conducting the

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observation has a high likelihood of impacting the probability of the behavior occurring. With many problem behaviors exhibited by students who are not developmentally disabled, the presence and direct observation by an adult may impact the occurrence or the function of the behavior – referred to as behavioral control (Umbreit et al., 2007). Umbreit et al. (2007) compare this effect to placing a police ofﬁcer at a busy intersection to ticket drivers who drive through red lights. The sheer presence of the police ofﬁcer dramatically reduces the number of drivers going through red lights. The inability to directly observe the problem behaviors may impact the accuracy of the determination of function and the efﬁciency of the process to the point of making the process ill-advised and unnecessary, not to mention invalid. Moreover, functional analyses in typical classroom settings present not only a challenge for classroom personnel to implement in the scope of their full daily routine, but also a change in the dynamics of the entire classroom. That is, changing variables for one student invariably affects other students and the classroom milieu. Such changes present confounds to experimental analyses and further increase the potential for subject reactivity. Classroom instruction and management before FBA. Conceptually, in the literature FBA has been placed within the framework of tertiary levels of support for students who are treatment resisters – that is, after universal and secondary level strategies have failed. Thus, another issue related to the implementation of FBA within school settings is whether less time and effort-intensive strategies have been put into place with ﬁdelity in an honest attempt to alleviate concerns associated with the student’s problem behaviors prior to the implementation of FBA and a function-based intervention. Certainly, we are committing unnecessary effort in initiating a full function-based intervention process if basic classroom management and instruction have not ﬁrst been implemented. As any behavior consultant can attest, if the student has not been sufﬁciently taught what behaviors are appropriate or inappropriate and if no basic instructional classroom management practices are in place (e.g., teacher proximity, precorrection, praise, and so forth), these tactics should be implemented and assessed before undertaking an FBA. In a similar sense, we would not recommend specialized instructional programming and placement for a student who could not answer a basic math question if we believed that the math concept had not been taught. A lack of effective instruction and classroom management in the environment creates and perpetuates problem behavior that may not need to be addressed by function-based intervention, but rather could be ameliorated through effective instruction. If it is determined

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that less-intensive instructional and classroom management interventions have not been implemented with ﬁdelity, then these techniques should ﬁrst be attempted before beginning the FBA and function-based intervention process. Thus, preliminary interventions for students may be similar to those described in Hoff, Ervin, and Friman (2005). For a twelve-year old male in a general education setting, proximity to preferred peers and more or less preferred reading material was manipulated and resulted reduced occurrences of problem behavior. Although an FBA was used to generate the functions of access to peer attention and escape from academic tasks, it could be argued that changing a student’s seat and giving opportunities to complete easier academic tasks could have been easily implemented before a FBA process and function-based intervention was undertaken. Similarly, in early childhood settings, giving access to attention (e.g., high rates of praise) and preferred tangible items for pro-social behaviors and shortening activities that require sitting still for long periods of time could be easily implemented before a FBA and function-based intervention. More to the task of FBA and function-based intervention, determining the function of behavior and developing an intervention that teaches the student a replacement behavior seems likely to be a more onerous task as the student increases in age. Older students, especially those entering the middle and high school years, become far more inﬂuenced by complex and subtle social factors that will often defy detection or observation by typical FBA procedures. The look on the face of another student, a student’s perception of what an adult might consider a benign peer comment and other such instances common to adolescence create great difﬁculty for the accurate depiction of relevant antecedents and consequences necessary in an accurate FBA. Clearly, younger children and students with severe cognitive and language disabilities present fewer challenges to accurate observation. Complex behaviors and functions. Determining function in a precise manner is often clouded by single behaviors that serve multiple functions or a range (i.e., class) of behaviors that serve a single function. Both cases create challenges for the development of accurate function-based hypotheses. Hanley et al. (2003) estimated that 15% of functional analyses revealed multiple functions of challenging behavior. Particularly frequent among students with lower cognitive functioning is the use of one behavior to serve a multitude of functions. Such students may scream to gain access to attention, escape attention, or self-stimulate – depending on their own idiosyncratic perception of the environment. Among students of higher cognitive abilities, it is not unusual to see students who have developed a

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rich repertoire of behaviors to access the same function. They may scream, ignore, fall, or even sleep at different times – all to access the same reinforcer (e.g., teacher attention, escape, or avoidance of work). These are particularly difﬁcult for the FBA as the conditions in free operant environments may be so subtle and complex as to avoid simple analysis. That is, in the complex classroom social environment, students engage in various behaviors that may function in different ways, depending on extremely complex contexts. In such cases, it is unlikely that an intervention based on one snapshot of function can simultaneously account for multiple functions of behavior that may change across various setting events. Further compounding this obstacle is that there may be some speciﬁc behaviors that may be especially resistant to the FBA process. Limited research has investigated conducting FBA on internalizing behaviors (Stahr, Cushing, Lane, & Fox, 2006) and more attention needs to be directed toward behaviors that include withdrawal and passive refusal to complete schoolwork. Another consideration is the set of behaviors such as drug and alcohol use that may have the behavioral function of peer attention, but they also provide their own type of intrinsic reinforcement that is resistant to typical function-based interventions. This leads to various difﬁculties when behaviors have their own intrinsically reinforcing value. For example, students may engage in challenging behavior simply for their own entertainment. Consider a student who plays practical jokes on teachers and peers. If this student does not tell peers (indicating that it is not peer attention) and does not try to get caught (indicating that it is not motivated by teacher attention or is escape motivated), what is the function of this student’s practical joking behavior? Clearly, this type of behavior presents a challenge to the traditional FBA process. In addition, consider students who will continually engage in problem behaviors to avoid school work. While giving breaks and reducing a workload to allow students to effectively escape and avoid work may be a temporary function-based intervention, at some point the long-term goal is for the student to complete schoolwork. These considerations are all potential obstacles prohibiting how the function-based intervention process may be effectively implemented in students with or at risk for EBD across various settings including general education. Other difﬁculties occur when attempting to determine the function of the identiﬁed challenging behavior. After determining that a problem behavior is occurring, the ﬁrst recommended step is identifying the routine in which the challenging behavior occurs (Scott, Anderson, & Spaulding, 2008). Unfortunately, the assumption of stability for the function of a challenging behavior is suspect

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even within routines. It has been noted by numerous researchers that context is an important consideration in regard to behavioral function (Umbreit et al., 2007). For example, a student may seek peer attention only when certain peers are in proximity. Furthermore, researchers relate anecdotes of the function of a student’s same problem behavior (e.g., noise making) changing from escape/avoidance to peer attention depending on the amount of sleep he had gotten the night before (e.g., when the student was sleep-deprived, he engaged in problem behavior to escape academic tasks, but when the student had sufﬁcient sleep, he engaged in problem behavior to access peer attention) (Kennedy, 2005). These complex relationships between distal setting events and the changing functions of behaviors may make challenging behavior appear to be completely random or extremely difﬁcult to identify the salient environmental determinants. Teachers often contend that students engage in challenging behavior for ‘‘no reason’’ or that episodes of challenging behavior are ‘‘completely unpredictable.’’ Although this standpoint is antithetical to the basic foundations of applied behavior analysis (i.e., that behavior is predictably related to environmental stimuli), teachers’ responses may be indicative of the complexity between distal and proximal setting events, multiple antecedents, and multiple functions of behavior, making the behavior seem unpredictable or occurring for ‘‘no reason.’’ Explanations of the function of problem behavior may exist somewhere in the continuum between teachers’ assertions that the behavior is completely unpredictable and the existing philosophy that functions are consistent enough to be reliably and accurately determined. Research on FBA in general education settings will have to continue to try to determine how dynamic is the function of students challenging behavior and what are the most effective interventions to address it. One further issue worthy of note is the possibility that the teacher him or herself may represent an antecedent for problem behavior (Scott & Nelson, 1999). Training educators to consider how they may be required to change their own behavior as a component of a function-based intervention for student behavior is a paradigm shift for those who believe students simply must be expected to comply regardless of the environmental determinants. For example, it is not unusual for a teacher to say ‘‘I’m not going to remind him everyday, it’s his responsibility.’’ Although the argument might be easily made that to remind a student is to set them up for the reinforcement of success, thereby increasing future probability of success, those who believe behavior is totally within the domain of the student’s abilities likely will resist interventions aimed at changing their own teacher behavior.

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Challenges for FBA: Process and Context Clearly, legislative mandates and a strong empirical research base make the case that in many instances the FBA process should be used in school settings. Unfortunately, the failure to develop FBA as a meaningful school process with valid outcomes has (and will continue to) adversely impacted countless students who demonstrate problem behaviors. Because of the inverse relationship between effectiveness and efﬁciency, we are likely to produce effective interventions through a process either too unwieldy to be realistic or too simpliﬁed to be effective. In other words, when the FBA process and resulting function-based intervention is ineffective, school personnel become merely obligated to check the appropriate boxes and sign the appropriate forms with no true beneﬁt to the student. Thus, FBAs change from a process that is supported by research and considered ‘‘recommended practice’’ in the ﬁeld (Arndorfer & Miltenberger, 1993; National Institute of Health, 1989) to a superﬂuous exercise in mindless, rules-driven bureaucratic paperwork. Problems with the process may impact the information gathering assessment process that assesses the relationship between the environment and the target behavior or may afﬂict the design and implementation of the interventions based on the assessment data. Clearly, there are problems within the entire FBA process as it is applied in classroom contexts. These problems will be discussed under three broad categories: (1) when to engage the FBA process, (2) who to involve in the process, and (3) the practices and procedures that make up the process – how it is to be completed. Timing: When should an FBA be implemented? A direct result of IDEA (1997) is its impact on the timing of initiating the FBA process in schools. Because a FBA is not mandatory until severe disciplinary measures are being put into place, and because its utility for school personnel remains questionable (Sasso et al., 2001), the implementation of the FBA process is often considered a last resort to be used well after patterns of problem behaviors are deeply entrenched. This consideration of when FBAs and function-based interventions are implemented is an important decision for school personnel and researchers. Conroy, Clark, Gable, and Fox (1999) noted that schools must proactively address students’ behavioral needs with FBA technology rather than waiting for legal mandates to force them into a reactive stance. It has been documented that, without intervention, challenging behaviors such as aggression tend to increase in both rate and severity over time (Reid & Patterson, 1991). Early behavior problems have

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been linked with more severe problems such as conduct disorders, antisocial behavior, substance abuse, unemployment, criminal behavior, and psychiatric disorders (Kellam, Rebok, Ialongo & Mayer, 1994; Reid and Patterson, 1991). Furthermore, these students are at elevated risk for school drop-out and a long list of negative life outcomes, including involvement with social services, drug use, the correctional system, automobile accidents, and so forth (Duncan, Forness, & Hartsough, 1995; Sprague et al., 2001). Simply, the young child who chooses to use aggression to achieve a goal such as gaining access to a toy is more likely to use aggression in the future to achieve goals. This synergistic self-perpetuating cycle continues such that the more an undesirable behavior such as aggression is used, the more likely a child will continue to engage in the same behavior across time and contexts. Whether this is conceived of the development of a cognitive habit or described as the outcome of a sequence of learning and reinforcement, the results are predictably similar. In either case, the reactive nature of the FBA and function-based intervention process, as it currently exists in schools, is ill-timed to prevent lifelong problem behavior, occurring only after the synergy of the cycle has been established. It is unlikely that school administrators will use these measures for ﬁrst time minor offenses. As noted by Weber et al. (2005), the fact that FBA procedures are couched in a state’s disciplinary procedures suggests that FBA will only be used when disciplining students, a post hoc reaction to behavior that has already occurred. Additionally, within the function-based intervention process, teachers often produce and try to address a lengthy list of multiple and varied problem behaviors that are impacting a student’s educational process (Quinn et al., 2001). When a student has numerous challenging behaviors in their repertoire, the efﬁcacy of the function-based intervention process becomes even more dubious as teachers note that while he may have stopped engaging in this challenging behavior, the intervention has increased the amount of time he spends engaging in that challenging behavior. Teachers’ perceptions of the FBA and function-based intervention process as ‘‘too little, too late’’ further reinforce the idea that this process is meaningless paperwork that has no real impact on students. This problem is regularly apparent when schools, following IDEA guidelines (e.g., exceeding 10 days of suspension out of school or being placed in an interim alternative educational setting), introduce the FBA only after a student is facing extensive disciplinary consequences. At this point, the FBA and functionbased intervention typically must address a number of severe behaviors. Besides these reactive applications of the FBA process, there are other temporal considerations.

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The question of temporal efﬁciency still looms as a question that has not bridged the ‘‘research to practice’’ gap. In addition to temporal concerns, issues of personnel and student characteristics in school-based FBAs have been overlooked or understudied in the literature. Personnel: Who should conduct the FBA? The second problem category relates to who is creating and implementing the FBA and function-based interventions. We have previously discussed issues related to training and skill vs. performance deﬁcits. Here we address who among school personnel will be responsible for implementing the FBA process and functionbased intervention. This question remains difﬁcult to answer as titles (e.g., Behavior Resource Teacher, Behavior Specialist, School Counselor) and responsibilities remain idiosyncratic to school districts. It has been recommended that a teaming approach that includes someone with behavioral expertise and individuals who know the student and the contexts of the problem behavior (e.g., teachers, the student family representatives, friends, siblings) be included on the team (Fairbanks, Simonsen, & Sugai, 2008). For instance, the importance of including someone with behavioral expertise on the intervention team was demonstrated when Hsiao and Albin (2000) noted that without someone to translate the information, FBA information had no impact on school personnel’s recommendations for behavior support plans. Furthermore, Scott et al. (2005) demonstrated that school-based personnel were more likely to select punitive and exclusionary strategies, regardless of function. But it is important for researchers to recognize the practical reality of the demand placed on the professionals charged with the obligation of assessment and address how these needs will be met. Although a teaming approach might be ideal for the formulation of the FBA, the responsibilities of creation and formulation most often fall to the classroom teacher. Chandler, Dahlquist, Repp, and Feltz (1999) identiﬁed the importance of training teachers as the creators and implementers of the FBAs. Through a series of workshops teachers were given the requisite knowledge to generate effective FBAs for entire classes. The emphasis on training for class-wide implementation is indicative of the importance of implementer characteristics. But this also points to a shortcoming in the ﬁeld, namely, no uniﬁed training protocol for school personnel. Although researchers have decried the use of hit and run in-service models (Scott, Nelson, & Zabala, 2003), no minimum level of proﬁciency has been established. Because FBA and function-based interventions were introduced after many teachers would have gone through university teacher-training programs, it is singularly important to determine what individuals in a

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district should receive what amount of training. Additional research considerations must also be given to the use of teaming models in applied setting for the FBA process. Research that examines behavior support teams are an important step but must move beyond hypothetical vignettes (Benazzi, Horner, & Good, 2006) to real-world applications across time to evaluate efﬁciency, effectiveness, and durability. These teams must then be equipped with the most efﬁcient and effective means to conduct the FBA process – in other words, continued reﬁnement in how FBA and functionbased interventions are created. Practice: How should an FBA be conducted? Numerous journal articles, book chapters, and books have outlined the steps in generating an effective FBA and function-based intervention. Identifying and operationally deﬁning a speciﬁc challenging behavior is typically listed as the ﬁrst step. However, this task remains difﬁcult, especially in light of the widespread application of FBA. In consideration of topography, operationally deﬁning problem behaviors is a complex yet critical element for accurate functional assessment and intervention. In fact, the importance of a rigorous deﬁnition of the target behavior has been referred to as the ‘‘sine qua non’’ of the FBA process (Quinn et al., 2001). There are multiple reasons this important step can be an obstacle in the overall process. First, determining that a speciﬁc behavior or class of behaviors should be targeted for intervention can be a difﬁcult task across school personnel. For example, some school personnel may view teasing between students (e.g., ‘‘Your momma . . . ’’) as typical, lighthearted fun, whereas other personnel may view it as disruptive, rude, and a precursor to physical aggression. Next, even after a target behavior has been identiﬁed and deﬁned, consistently observing, assessing, and intervening with that behavior can be particularly difﬁcult. To this point, researchers train and then continually measure their interobserver agreement in research studies because it is so easy for two different people to observe and interpret behavior differently. This level of rigor (i.e., documenting interobserver agreement) may be especially unrealistic for school personnel given their wide range of other responsibilities, but is indicative of the variation of perceptions of students’ challenging behavior between individuals. Finally, because the FBA process is dynamic, new behavioral deﬁnitions will constantly have to be developed as old challenging behaviors are reduced and extinguished, and new challenging behaviors are addressed. The fact that a number of methods for conducting an FBA have been developed, studied, and marketed in the literature is both a blessing and a curse. Although we do not view any single method as sufﬁcient to

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accommodate all assessment needs, we believe the wide array of choices with no clear decision rules creates a larger problem – people gravitate toward what is most simple, convenient, or familiar rather than what is most effective or logical. As Yarborough and Carr (2000, p. 133) have so pointedly observed, ‘‘Given the different options available for conducting a functional assessment, the question regarding which approach practitioners ought to use to assess problem behavior is paramount.’’ To date, this question remains unanswered by researchers – particularly for students with EBD in general education settings. There are essentially two broad methods for generating hypothesized functions of a problem behavior: (1) indirect descriptive measures that are typically post-hoc in nature and include checklists, assessment scales, and interviews and (2) direct descriptive measures that include direct observations of behavior the surrounding environmental determinants in natural contexts. Both the procedures have beneﬁts and drawbacks. Indirect assessments rely on the subjective judgments of a third party, and direct observations can be context speciﬁc and inefﬁcient in capturing the occurrence of a challenging behavior and its antecedents and consequences (Floyd, Phaneuf & Wilczynski, 2005). Furthermore, direct observations are inefﬁcient because the probability of actually observing the challenging behavior can be relatively low, necessitating long and/or frequent observation periods (Scott et al., 2004). Thus, undetermined ‘‘best methods’’ or best-ﬁt combinations of methods limit the effectiveness and efﬁciency of the function-based intervention process. In some ways, direct methods are reliant on indirect methods to direct the timing and context with which observations are to best be conducted. But there is little direction in the literature as to how this relationship is best developed. That is, there is no clear direction as to how much indirect assessment is necessary to inform a direct observation or how to determine whether indirect assessment has produced sufﬁcient information for a hypothesis and intervention in the absence of direct observation. The necessity of hypothesis conﬁrmation before intervention is an issue of some controversy in the ﬁeld. One view is that interventions must be based on hypotheses that have been conﬁrmed by experimental analyses (e.g., Asmus et al., 2002; Kamps et al., 2006). On the other end of the spectrum is the view that, in many cases, function is sufﬁciently obvious that intervention should be implemented in a timely manner, allowing the effect of intervention to act as evidence of the accuracy of the functional hypothesis (e.g., Murdock et al., 2005; Shriver et al., 2001). Although functional analysis is logically sound as a method of verifying function, it

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has been identiﬁed as too time consuming and technical for practitioners to conduct, and lacking external validity due to the high degree of experimental control (i.e., the highly controlled conditions in which it is conducted) (Ellingson, Miltenberger, Stricker, Galensky, & Garlinghouse, 2000). Even simpliﬁed veriﬁcation methods such as the brief functional analysis (e.g., Dunlap et al., 1993), which involves alternating introduction of a few speciﬁed consequences, present an obligation for time that is far beyond what teachers typically have to commit to an assessment – even if they understand and agree with the principles. Compounding this are issues related to the complexity of the typical classroom environment. Variation in student seating arrangements, daily lesson content, and an endless array of potential setting events create serious threats to the internal validity of such experimental procedures. With all experimental veriﬁcation, manipulation of consequences that either inhibit or predict dangerous or disruptive behavior or reversals/time lags of effective intervention are difﬁcult to justify ethically. Another variation of experimental veriﬁcation is the structural analysis which is focused on manipulation of antecedents as opposed to consequences. Although such procedures present some of the same time challenges as functional analysis, the manipulation of antecedent events (e. g., routines, reminders) in the classroom is typically more palatable for teachers. At this point, there is no clear consensus as to when or whether validation procedures should be undertaken and no guidelines for decision-making. In practice, it is unlikely that experimental hypothesis testing is ever implemented by school personnel.

Conclusions and Recommendations As was previously mentioned, it has been postulated that ‘‘the relationship between empirical rigor and practical application is, to some extent, inverse’’ (Scott et al., 2004, p. 191). If accurate, this creates a difﬁcult conundrum. If a FBA and function-based intervention is inaccurate, it will be ineffective and school personnel will not use it, but if it is impractical, it will be inefﬁcient and school personnel will not use it. Thus, teachers must be equipped with strategies that determine the function of a problem behavior in an accurate and efﬁcient manner, leading to effective interventions – or the process is unlikely to be of any beneﬁt outside of meeting the letter of a legal mandate. It may be advisable to have different levels of formality and

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intensiveness within the process to achieve the appropriate balance, starting with classroom interventions based on simple functional considerations as part of a self-talk strategy (e.g., ‘‘What is he/ she getting out of this behavior?’’), moving to an efﬁcient small-team-based FBA and culminating with a more formal function-based intervention procedures (Scott et al., 2008). Still, at this point there is no persuasive data to support such levels. To date, schools have demonstrated that if the process is either ineffective (does not immediately decrease problem behaviors) or unrealistic (time-consuming and technically complex), the FBA process will become another bureaucratic chore that will not positively impact children (Scott et al., 2004). So, where should the ﬁeld go from here? What is the solution to the problems that plague the use of FBA with students with EBD in school settings? In the ﬁnal section of this chapter, we will discuss future directions and recommendations for policy, research, and practice.

FUTURE DIRECTIONS AND RECOMMENDATIONS FOR POLICY, RESEARCH, AND PRACTICE Without question, policy, research, and practice in regard to the implementation of FBA for students with EBD in classroom settings are colliding. Although the requirements related to FBA in IDEA (1997) have brought about positive changes toward addressing student behavior, researchers and practitioners in the ﬁeld have also had to respond to many challenges. In the ﬁnal section of this chapter, we propose directions that policy makers, researchers, and practitioners may want to consider as the FBA practice continues to evolve. Reforming FBA Policy Policy often provides the motivation for change. That is, without policy, change is much less likely to occur. Although the FBA policy outlined in IDEA has produced a number of positive changes, as we reﬂect on the outcomes and challenges we believe the current policy has ‘‘broken down,’’ like an old, damaged car, in a number of places and should be reformed or repaired. First, policy makers should consider re-evaluating the regulations related to the implementation of an FBA following 10 consecutive days of suspension or placement in an interim alternative educational setting due

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to a weapon infraction. These seem to be in conﬂict with the theoretical foundations of FBA as well as the practical applicability. We suggest that the FBA policy should be reformed to address students’ chronic behavior within a three-tiered intervention framework, emphasizing tier 1 and tier 2 proactive and preventative approaches toward ameliorating problem behavior before implementing individualized, intensive interventions (tier 3). Similar to the current models of response to intervention (RtI), policy for implementation of FBA within school settings should be designed to address only those students whose behaviors have been resistant to universal and secondary intervention strategies. Formulation of this policy should put a premium on copious documentation of strategies attempted, progress monitoring and data-based decision-making. Additionally, policy should provide guidance and differentiate the types of situations and topography of behaviors that are most applicable to FBA procedures, such as high-frequency behaviors, and provide alternative intervention guidelines for those behaviors where FBA is less applicable (e.g., high-intensity, low-rate).

Reforming the FBA Model Although policy reform should be one of our goals, leaders in the ﬁeld of EBD also need to further reﬁne and develop a FBA model for students with EBD in classroom settings that is more efﬁcient, applicable, and thus, effective in decreasing students’ challenging behaviors. As researchers ourselves, we believe that for the most part much of the research has been tied to ‘‘the old way’’ of conducting FBA. A more realistic and responsive FBA approach that can address the needs of students with EBD in a classroom setting and their classroom teachers is warranted. We believe a more relevant FBA model would increase the emphasis on preventive strategies including antecedent interventions and effective classroom instructional and behavioral practices. A more responsive FBA approach would expand the traditional emphasis on consequence-based only (or function-based only) interventions and increase teachers’ use of preventative instructional and classroom management practices with integrity while systematically evaluating the outcomes of these interventions on student behavior. Examining both temporally distant and concurrent setting events and multiple discriminative stimuli and functions should also be emphasized. As researchers reform and expand a more responsive FBA model, they will want to be sure to collaborate with practitioners to help increase

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the internal, external, construct, and social validity of the practices and to be ever mindful that the creation of a FBA and implementation of functionbased interventions will always be just one of a myriad of tasks for the typical classroom teacher. As stated earlier, researchers need to provide practitioners guidance regarding the types of behaviors, contexts, and situations that are most applicable to FBA (e.g., socially mediated behaviors). Alternative behavioral management, disciplinary strategies, and wrap-around services should be developed for students who demonstrate serious behaviors or situations that are not appropriate for a FBA, such as many internalizing problem behaviors (e.g., depression), and criminal offenses. When an FBA and a function-based intervention is warranted, systematic manipulation and evaluation of the process and subsequent intervention should occur. As we reform policy and practice, the focus should be on measuring the effectiveness and outcomes of the strategies we use (e.g., Is there a decrease in problem behavior?) rather than trying to ﬁt FBA to work in situations that are unsuitable or nonsensical.

Reforming Training and Technical Assistance While reforming policy and practice is critical, building competence in teachers and staff to implement those policies and practices with integrity is vital. We believe that increased training and technical assistance with an emphasis on collaboration between teachers and researchers on the development of socially valid and responsive FBA practices is needed to bridge the gap between research and practice. Training and technical assistance should emphasize a team-based approach in implementing FBA and function-based interventions, addressing differences in teacher beliefs toward behavioral intervention practices with a focus on building positive outcomes for teachers, children, and classrooms, and schools. As we further develop a more responsive FBA model for students with EBD in classroom settings, our focus should be on working with teachers collaboratively to develop and train them in a model that is effective in addressing their students’ behavioral needs and is socially valid for their classroom setting. Training should begin at the pre-service and in-service levels. At the basic level, information regarding universal behavioral intervention and classroom management strategies and FBA and function-based interventions

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should be infused into training programs for general educators. Additionally, special educators and school psychologists should receive intensive and advanced training in these areas. Although we believe training at the pre-service and in-service levels is necessary, we also know that it is not sufﬁcient. When chronic problem behaviors occur over time between a teacher and a student in a classroom, coercive relationships often occur, which is likely to produce a negative classroom environment. As preventative and proactive instructional practices are put into place, the atmosphere of the classroom can transition from a negative and coercive atmosphere to a positive classroom atmosphere. Once these practices are in place, there may still be a need to implement an individualized FBA and function-based intervention with a student has demonstrated resistance to tier 1 and tier 2 intervention strategies. At this point, a more comprehensive approach to training and technical assistance may need to occur with behavioral consultation services by a behavior specialist to address the complex needs of the student and help the teacher learn effective strategies for ameliorating the chronic problem behavior. Through a comprehensive approach to training and technical assistance (that includes pre-service, in-service, and intensive behavioral consultation services), we can build competence in teachers so that FBA practices will be implemented with integrity and effectiveness.

The Future of FBA Research: Priorities As suggested by Reid and Nelson (2002), there are several critical issues that should be addressed in future research. The ﬁrst issue is to examine the effectiveness of a reformed FBA and function-based intervention model on outcomes for students with EBD and comparing the effectiveness of this FBA model to other interventions that may be equally effective and easier to implement (e.g., token reinforcement systems). The second issue and equally important is to examine teachers’ perceptions of this model and their ability to implement the model with integrity. Examining mediators and moderators (such as teachers’ beliefs) that may inﬂuence the feasibility of model implementation is important as well. The third issue, that would be a departure from the current trend of only publishing studies in which FBA and function-based interventions were effective, is to solicit from the ﬁeld case examples and studies of when these measures were ineffective. The effort would be to construct a database that identiﬁed when FBA did and

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did not work and to identify the salient elements that contributed to either result. Finally, researchers need to examine the training and supports needed for successful implementation of the reformed FBA practices with students with EBD in school settings. For instance, we need to examine how to develop and train school-based teams that can independently implement and sustain these practices in an effective manner.

CONCLUSION In this chapter we have attempted to elucidate the current problems plaguing the implementation of FBA in our schools. We believe the problem stems from a mismatch between the traditionally conceptualized FBA to the characteristics of the target population and the settings in which it is legally to be applied. Our current deﬁnition of FBA is based on the functional analysis literature and was developed primarily for individuals with developmental disabilities. We believe this conceptualization in not necessarily applicable across all topographies of behaviors demonstrated by students with EBD and the educational settings that serve these students. Thus, we propose (1) a reconceptualization of policy and practice that addresses a more responsive and socially valid approach to FBA and function-based interventions for students with or at risk for EBD in school settings, (2) a comprehensive training and technical assistance agenda that builds competence in FBA practices for all teachers and staff in school settings working with students with EBD, and (3) a research agenda that examines the internal, external, and social validity of these practices. If, as a ﬁeld, we are serious about helping children with EBD, we believe the ﬁeld needs to stop ‘‘driving down the same road in the same old, broken down car.’’ We need to rise to the challenges we currently face and develop a new route.

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Jones, K. M., Drew, H. A., & Weber, N. L. (2000). Noncontingent peer attention as treatment for disruptive classroom behavior. Journal of Applied Behavior Analysis, 33, 342–346. Kamps, D., Wendland, M., & Culpepper, M. (2006). Active teacher participation in functional behavior assessment for students with emotional and behavioral disorders risks in general education classrooms. Behavioral Disorders, 31, 128–146. Kates-McElrath, K., Agnew, M., Axelrod, S., & Bloh, C. L. (2007). Identiﬁcation of behavioral function in public schools and a clariﬁcation of terms. Behavioral Interventions, 22, 47–56. Kauffman, J. M. (2002). Education deform: Bright people sometimes say stupid things about education. Lanham, MD: Scarecrow Press. Kauffman, J. M., & Landrum, T. J. (2008). Characteristics of emotional and behavioral disorders of children and youth (9th ed.). Upper Saddle River, NJ: Pearson. Kellam, S. G., Rebok, G. W., Ialongo, N., & Mayer, L. S. (1994). The course and malleability of aggressive behavior from early ﬁrst grade into middle school: Results of a developmental epidemiologically-based preventative trial. Journal of Child Psychology & Psychiatry & Allied Disciplines, 35, 259–281. Kennedy, C. H. (2005). Single-case designs for educational research. Boston, MA: Allyn & Bacon. Kern, L., Childs, K. E., Dunlap, G., Clarke, S., & Falk, G. D. (1994). Using assessment-based curricular intervention to improve the classroom behavior of a student with emotional and behavioral challenges. Journal of Applied Behavior Analysis, 27, 7–19. Kerr, M. M., & Nelson, C. M. (2006). Strategies for addressing behavior problems in the classroom (5th ed.). Upper Saddle River, NJ: Pearson. Lane, K. L., Umbreit, J., & Beebe-Frankenberger, M. E. (1999). Functional assessment research on students with or at risk for EBD: 1990 to the present. Journal of Positive Behavior Interventions, 1, 101–111. Magg, J. W. (2004). Behavior management: From theoretical implications to practical applications (2nd ed.). Belmont, CA: Thomson Wadsworth. Murdock, S. G., O’Neill, R. E., & Cunningham, E. (2005). A comparison of results and acceptability of functional behavioral assessment procedures with a group pf middle school students with emotional/behavioral disorders (E/BD). Journal of Behavioral Education, 14, 5–18. National Institute of Health. (1989). NIH consensus on the treatment of destructive behaviors in persons with developmental disabilities. Bethesda, MD: Author. Nelson, J. R., Roberts, M., Mathur, S., & Rutherford, R. B. (1999). Has public policy exceeded our knowledge base? A review of the functional behavioral assessment literature. Behavioral Disorders, 24, 169–179. Ofﬁce of Special Education Programs Questions and Answers. (1999, March 12). Federal Register, 64, 12617–12632. Volume 64, No. 48. O’Neill, R. E., Horner, R. H., Albin, R. W., Sprague, J. R., Storey, K., & Newton, J. S. (1997). Functional assessment and program development for problem behavior: A practical handbook. Paciﬁc Grove, CA: Brooks/Cole. Quinn, M. M., Gable, R. A., Fox, J. J., Rutherford, R. B., Van Acker, R., & Conroy, M. A. (2001). Putting quality functional assessment into practice in schools: A research agenda on behalf of E/BD students. Education and Treatment of Children, 24, 261–276.

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THE IMPACT OF POVERTY ON SPECIAL EDUCATION STUDENTS Elizabeth Halloran Tornquist, Margo A. Mastropieri, Thomas E. Scruggs, Hugh G. Berry and William D. Halloran ABSTRACT This study examined the impact of poverty using multiple poverty measures on students with disabilities, using data from the ﬁrst wave of the Special Education Longitudinal Study (SEELS; Wagner, Marder, Blackorby, & Cardosa, 2004). Multiple deﬁnitions of poverty based on previous research were employed in the present study, to address limitations of the federal poverty measure. These deﬁnitions included (a) 50% of the federal threshold (extreme poverty), (b) the federal threshold, (c) 150%, and (d) 200% of the federal threshold. These measures were then used with the SEELS data that were obtained from 9,747 parent interviews and 4,912 student assessments based on subtests of the Woodcock-Johnson Tests of Achievement. Both student and household characteristics data were used to identify the extent to which income and poverty were associated with academic achievement and disability using multiple poverty measures. Findings of interest were uncovered in the extreme poverty category, with more pronounced differences revealed in gender and ethnicity. Overall, this research suggests that poverty is a better predictor of academic achievement than Policy and Practice Advances in Learning and Behavioral Disabilities, Volume 22, 169–187 Copyright r 2009 by Emerald Group Publishing Limited All rights of reproduction in any form reserved ISSN: 0735-004X/doi:10.1108/S0735-004X(2009)0000022008

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ethnicity, and that life circumstances become increasingly less positive as family income declines. Future research and policy implications are discussed.

In 2000, the U.S. population included approximately 70 million children (or 26% of the population). A signiﬁcant number of these children were living in households at or below the federal poverty threshold, according to the U.S. Census Bureau’s (2000) Small Area Income and Poverty Estimates Program: Age 0–17: 11,587,118, or 16.2% of U.S. population of children. Age 5–17: 7,536,575, or 14.6% of U.S. population of children. Age 0–5: 3,583,098, or 18.7% of U.S. population of children. These breakdowns reveal that the higher percentage is in the age 0–5 category, suggesting that poverty may be increasing. Similarly, the Center on Budget Policy and Priorities (2003) reported that childhood poverty may be on the rise, with 400,000 more children being poor in 2003 than in the previous year. Of particular concern are the proportions of minority children in poverty. In 2001, 9% of White children, 30% of African American children, and 27% of Hispanic children lived in poverty (Benson, 2003; Center on Budget Policy and Priorities, 2003). Female-headed households are at the greatest risk for poverty status – in 2001, 39% of children in female-headed households were living in poverty (Benson, 2003). Being African American and in a female-headed household may pose a double threat, as 47% of these children lived in poverty in 2001 (Benson, 2003). Disability may be the largest public health issue facing the United States, and poverty acts as a proxy for many of the variables that increase the risk of disability (National Organization on Disability, 2004; Seelman & Sweeney, 1995). The causal relation between poverty and disability is equivocal – like the chicken and the egg, one can argue for either as the ﬁrst cause. Income for adults with disabilities is substantially lower than that for non-disabled people; and people below the poverty line had a 21.3% rate of disability, compared with 13.3% for those above the poverty line (Seelman & Sweeney, 1995). In 1988, the average income for the general population was $34,017, and the median family income for people with disabilities was roughly $18,000 (Seelman & Sweeney, 1995). The 2004 Harris Poll reported that only 35% of adults with disabilities reported being employed

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full or part-time, compared with 78% of non-disabled adults (National Organization on Disability, 2004). Kruse (1998) reported that, because of lower employment rates and other labor market difﬁculties persons with disabilities tend to experience, they were twice as likely to live in poverty as persons without disabilities. Disabled adults are more likely to be poor, and poor families are more likely to have children with disabilities. Three times as many adults with disabilities live in poverty with annual household incomes below $15,000; that is, 26%, as compared with 9% of non-disabled adults (National Organization on Disability, 2004). Nearly half of single mothers receiving Temporary Aid for Needy Families (TANF) have a disability or a child with a disability, and low-income families with incomes below twice the poverty line are 50% more likely to have a disabled child (Lee, Sills, & Gi-Taiket, 2002).

POVERTY AND ACADEMIC ACHIEVEMENT Poor children tend to be lower academic achievers. Bradley, Corwyn, McAdoo, and Coll (2001) analyzed data from the National Longitudinal Survey of Youth and concluded that poverty decreases the likelihood that children will have exposure to developmentally enriching materials and experiences both in and out of their homes, such as access to developmentally appropriate books, or having a family member read to them or work with them on school-related lessons. Across all ethnic groups, non-poverty children were twice as likely to be taken to museums and one and a half times more likely to be taken to the theater (Bradley et al., 2001). Poverty can impact a child’s learning ability as well. Early childhood IQ scores are associated with a family’s ability to provide intellectually stimulating activities and experiences (Park, Turnbull, & Turnbull, 2002), and the absence of these may negatively inﬂuence development. Growing up in a low-income family, a child is more likely to experience difﬁculties in school, have higher rates of teen parenthood, earn less money as an adult, and experience higher rates of unemployment (Brown et al., 1999). A student’s academic achievement has a long-term impact throughout adult life, and poor children overall experience a lower level of achievement than middle and upper class students. Why is academic achievement so important? Guo (1998) concluded that a connection exists between lower academic achievement and lower earnings, higher unemployment rates, higher rates of adult poverty, and higher rates of welfare receipt. As such, poverty inﬂuences both ability and achievement,

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and a strong connection has been made between lower educational achievement and adult poverty. Poverty and achievement certainly are interconnected; however, the primary cause is elusive. Again, as with poverty and disability, the question of the chicken and the egg is relevant.

POVERTY MEASURES In this investigation, several deﬁnitions of poverty were employed. In addition to the federal threshold, values representing 50%, 150%, and 200% of the federal threshold were chosen (see Table 1). The federal poverty thresholds were ﬁrst developed in 1963–1964 by Mollie Orshansky, based on the low cost and economy food plan (Fisher, 1992). At that time, Orshansky found that families spent about one-third of their income on food, and she developed a detailed set of matrices of family sizes and types, took what each would need to meet the minimum dietary requirements, and multiplied it by three to get the federal poverty measure (Fisher, 1992). Since that time, no major changes have been made to the way that the federal government measures poverty, and the accuracy of the measure has long been questioned. In 1995, the National Academy of Sciences (NAS) issued a report commissioned by Congress on the federal poverty threshold. The major conclusion of the report was that the current federal measure needs to be revised (Citro & Michael, 1995). In addition to the NAS report, the Table 1. Poverty Measure Fifty percent of federal measure ‘Poverty One’ Federal poverty measure ‘Poverty Two’ One and a half times the federal poverty measure ‘Poverty Three’ Two times the federal measure ‘Poverty Four’

Alternate Deﬁnitions of Poverty. Description

Related Literature

Often described as extreme poverty

Fisher (1992)

Set by US Government, collected and published by US Census Bureau

Fisher (1992) and Citro and Michael (1995) Caldas and Bankston (1997)

Midpoint for eligibility for Free and Reduced Meals (FARMS) programs

Eligibility criteria for Children’s Health Boushey, Brocht, Insurance Programs (CHIPS) in most Gundersen, and states and is the average of all basic Bernstein (2001) family budgets

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consensus of research concludes that the current measure of poverty needs to be revised, in that it does not provide an accurate picture of who is poor in America (Boushey et al., 2001; Garner, Short, Shipp, Charles, & Paulin, 1998; Glennerster, 2002; Slesnick, 2002; Rich, 2001). For these reasons, the current investigation uses multiple deﬁnitions of poverty. Given the rise in poverty and in the numbers of students with disabilities, this investigation was concerned with examining the relationship between characteristics of individuals classiﬁed as having disabilities and various poverty measures. Speciﬁcally, the following research questions were addressed: What are the student characteristics of children with disabilities using different measures of poverty? What are the household characteristics of children with disabilities using different measures of poverty? To what extent is poverty associated with academic achievement and disability when controlling for other factors?

METHOD Data Set and Participants Secondary analyses of the Special Education Elementary Longitudinal Study (SEELS; Wagner, Marder, Blackorby, & Cardosa, 2004) data were conducted. The Ofﬁce of Special Education Programs (OSEP) funded the SEELS to be conducted by SRI International. The present investigation utilizes data from the ﬁrst wave of the SEELS, speciﬁcally from parent interview and direct assessment. The SEELS data set includes a large, nationally representative sample of students in special education, ages 6–12 years and enrolled in elementary school in 1999. SEELS selected a stratiﬁed sample of students in special education from a nationally representative sample of local education agencies (LEAs). Eligible LEAs and special schools were stratiﬁed by geographic region, district enrollment, and community wealth to enhance the representativeness of the sample. Agencies who agreed to participate in the study provided rosters of students in special education, and SRI staff randomly selected the sample from these lists. The design of SEELS takes into account the length of the data collection period (six years) and assumptions regarding attrition. In total, 12,075 students were selected for inclusion in the study. This sample size was

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Table 2.

Disability by Sample and Population Estimates.

Disability

Number in Sample

Percentage in Sample

Number in Population

Percentage in Population

LD SI MR ED HI VI OI OHI AUT TBI MD Deaf/blind

1,050 837 866 876 1,032 815 990 924 1,101 359 845 49

10.8 8.6 8.9 9 10.6 8.4 10.2 9.5 11.3 3.7 8.7 .5

1,299,277 1,042,362 281,479 189,040 38,603 14,624 42,017 146,972 48,985 6,069 58,292 1,026

41 32.9 8.9 6 1.2 .5 1.3 4.6 1.5 .2 1.8 .0

Total Missing

9,747 2

3,168,744 234

Note: Number and percent in population based on weighted estimates.

chosen with the intention of yielding a sample of sufﬁcient size and representativeness to meet the needs through the ﬁnal wave of data collection in year six, 2004–2005. This sample consists of 1,150 students in each disability category except for deaf-blind, with 200 students , and traumatic brain injury, with 375 students being selected. Fewer students were sampled from these last two disability categories because they are the least populous categories. Out of the 12,075 students selected, 9,747 parent interviews were completed and 4,912 direct assessments were done. Weights were applied to each disability category to correspond to the proportion of students in that category in the entire population. Table 2 displays number and percentages of students in the ﬁnal sample and in the population by disability category.

Data Analyses Data were recorded in ﬁve poverty categories, using the variables family income and student family size, using values representing 50%, 100%, 150%, 200%, and greater than 200% of the federal threshold (the latter representing non-poverty status). Descriptive statistics were computed in

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order to answer the ﬁrst two research questions: what are the student characteristics and what are the household characteristics of special education students by poverty level? Regression analyses were conducted to answer the third research question, and determine the extent to which poverty is associated with academic achievement and disability when controlling for other factors.

RESULTS Student Characteristics Descriptive analyses yielded some ﬁndings similar to what is widely known but also revealed some surprising ﬁndings. Findings revealed that in special education: (a) there are more boys than girls; (b) older children are more highly represented in more severe poverty levels; (c) the majority of children speak English at home; (d) ethnicity differs by poverty level, with the highest percentage of students in extreme poverty being African American; and (e) percentages of students living with both parents increase as income increases. Speciﬁc ﬁndings are described separately next. Gender In all categories of poverty, males outnumbered females in special education (see Table 3). The greatest percentage difference between boys and girls is in the non-poverty category, with boys comprising 68.9% of all special education students, compared with 31.1% for girls. It was also noted that lower income levels overall were associated with smaller proportional differences in gender, with extreme poverty consisting of 56.5% males and 43.5% females. In other words, as family income level decreases, the differences between the number of males and females receiving special education services decreases. Age SEELS data on age were collected , with the youngest students in the sample being seven years of age, to the oldest students at 14 years of age. Table 3.

Demographics: Gender Percentages by Poverty Level.

Gender

Poverty 1

Poverty 2

Poverty 3

Poverty 4

Non-Poverty

Male Female

56.5 43.5

65.8 34.2

63.8 36.2

65.6 34.4

68.9 31.1

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ELIZABETH HALLORAN TORNQUIST ET AL.

Demographics: Age Percentages by Poverty Level.

Table 4. Age

Poverty 1

Poverty 2

Poverty 3

Poverty 4

Non-Poverty

7.4 7.5 19.5 16.9 12.9 22.9 11.1 1.8

5.2 11.8 12.6 17.1 18.3 21.9 11.6 1.5

12.1 13.0 15.3 17.8 13.3 17.1 10.0 1.4

8.5 11.5 16.4 21.2 19.7 12.6 10.0 .2

8.2 12.0 16.3 15.7 20.6 15.6 11.4

7 8 9 10 11 12 13 14

Table 5. Age o10 10 or more

Demographics: Collapsed Percentages of Age-by-Age Level. Poverty 1

Poverty 2

Poverty 3

Poverty 4

Non-Poverty

34.4 65.6

29.6 70.4

40.4 59.6

36.4 63.6

36.5 63.5

Table 4 displays age data across all age and poverty categories. A higher percentage of 9-, 10-, 11-, and 12-year-olds exist in all ﬁve poverty categories, with percentages ranging from 12.6% to 22.9%. No differences were observed across the other age groups. Age categories were collapsed into less than 10, and 10 years of age and older. As can be seen in Table 5, percentages of students less than 10 range from 29.6% to 40.4% and 10 or older range from 59.6% to 70.4% across poverty levels. These data indicate that older children have more serious poverty levels.

Primary Language SEELS data were collected on the primary language spoken at home. A total of 22 languages were identiﬁed. In all categories, the overwhelming majority of students spoke English at home (89.8%), followed by Spanish (5%). English speakers were fairly evenly distributed across all poverty levels. In the non-poverty category, 97.1% of the students spoke English at home, compared with 92.1% of poverty four, 92.6% of poverty three, 91.2% of poverty two, and 90.1% of children in extreme poverty. The children in families in poverty two had the highest percentage of Spanish speakers, 7.4%, followed by poverty four with 6.5%, then poverty three with 3.2%, with the lowest proportion being the non-poverty

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Table 6. Ethnicity White Black Hispanic Asian Native American Mixed/other

Demographics: Ethnicity Percentages by Poverty Level. Poverty 1

Poverty 2

Poverty 3

Poverty 4

Non-Poverty

21 60.2 17.9 .4 .5 2.1

50.8 22.9 22.7 1.5 .1 1.5

64.3 19.4 11.6 3.2 .8 .3

68.7 14.6 11.8 4.6

83.3 6.7 6.8 2.2

.3

category, 1.7%. The highest percentage of speakers of languages other than English and Spanish (6.8%) were students from families in extreme poverty. Ethnicity SEELS ethnicity data were classiﬁed in the categories of White, Black, Hispanic, Asian/Paciﬁc Islander, Native American, or mixed/other. For the descriptive purposes of this study, the same terminology has been used that was used in the SEELS data set. Ethnicity varied by poverty level. Table 6 displays ethnicity percentages by poverty level. The percentage of White students increased as income levels increased with 21% of students in extreme poverty being White, compared with 50.8% of poverty two students, 64.3% of poverty three students, 68.7% of poverty four students, and 83.3% of non-poverty students being White. Conversely, Black students were represented in the opposite fashion with 60.2% of Black students in extreme poverty (category poverty one) and 6.7% of Black students in the non-poverty category. Hispanic students were represented the most at the federal poverty level, making up 22.7% of that group, while the lowest percentages were in the non-poverty category (6.8%). Disability Category As in the SEELS data set, disabilities were classiﬁed into the 12 categories under IDEA. Analyses revealed that the three special education categories with the highest percentages of students in all poverty categories have learning disabilities (LD), speech impairments (SI), or mental retardation (MR), with emotional disabilities (ED) and other health impairments (OHI) representing the next highest percentages of students. Table 7 displays disability percentages by poverty level. For all poverty categories except poverty three and non-poverty, LD had the highest percentage of students, poverty one 47%, poverty two 43.2%, and poverty four 39.7%. Poverty three and non-poverty had slightly higher percentages of students with SI,

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Table 7.

Demographics: Disability Percentages by Poverty Level.

Disability

Poverty 1

Poverty 2

Poverty 3

Poverty 4

Non-Poverty

LD SI MR ED HI VI OI OHI AUT TBI MD Deaf/blind

47.0 19.6 20.0 7.3 .5 .2 1.3 1.7 .7 .1 1.6

43.2 24.2 12.8 9.0 1.4 .5 1.1 4.2 1.2 .1 2.2 .1

33.6 37.0 10.5 6.8 1.1 .6 1.1 5.9 1.3 .3 1.8

39.7 34.5 7.7 5.5 1.1 .5 .9 5.8 2.0 .1 2.1

37.0 38.7 4.9 4.3 1.2 .5 1.6 7.0 2.7 .2 1.8

Table 8. Disability LD SI MR ED OHI Other

Disability Category Percentages by Ethnicity. White

Black

Hispanic

40.9 34.4 6.9 5.8 5.2 6.8

35.8 27.9 17.9 8.6 4.2 5.6

51.0 29.6 6.8 3.6 2.8 6.2

37% and 38.7%, respectively. Extreme poverty had the highest percentage of students with mental retardation (20%), followed by poverty two (12.8%), poverty three (10.5%), poverty four (7.7%), and non-poverty (4.9%). Disability by Ethnicity Additional analyses of disability by ethnicity were conducted with these data to identify special education categories represented by the three largest ethnic groups. Table 8 displays disability category percentages by ethnicity. For the ethnicity categories White, Black, and Hispanic, learning disabilities represented the highest percentages: 40.9% for Whites, 35.8% for Blacks, and 51% for Hispanics. All three ethnic groups shared speech impairment for the second highest percentages and mental retardation for the third. However, a greater percentage of mental retardation was represented in

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Black students with 17.9%, as compared with 6.9% for Whites, and 6.8% for Hispanics. These data also revealed a higher percentage of Black students in the ED category, with 8.6%, compared with 5.8% for Whites, and 3.6% for Hispanics. Living Arrangements SEELS data were collected on student living arrangements. Students were classiﬁed as living with two parents, one parent, relatives, a legal guardian, in foster care, in an institution, or other. Data from this study indicate that more than half of all students from poverty three, poverty four, and non-poverty live with both of their parents, the percentages being 68.9%, 72%, and 85.7%, respectively. However, as the poverty level increases, the percentages of students living with both their mother and father decreases, with 36% and 48.8% of students being in the lowest two poverty levels. The next highest category of living arrangement is with one parent, with the majority of students in extreme poverty (58.6%) living with one parent, 41.7% of poverty two, 24.1% of poverty three, 23% of poverty four, and 11.3% of nonpoverty. It was also found that 6.6% of students in poverty two live with a relative, as do 4.3% in poverty three and 4.1% in extreme poverty.

Household Characteristics Across 9,747 students, the characteristics of the number of people in students’ households, parent’s highest level of education, parent’s marital status, and income were analyzed according to the ﬁve categories of poverty. Students in extreme poverty are more likely to live in households with more people. Lower income families are more likely to have lower levels of parental educational attainment. Students from lower income families are more likely to have parents that were never married, while more than threequarters of non-poverty students live in a home with married parents. Considerable differences in income also exist between the wealthiest and the poorest, with over a third of students in non-poverty families coming from homes with incomes above $70,000 a year, compared with 82.8% of families in extreme poverty earning less than $5,000 a year. Family Size The SEELS parent interview data set also collected data on the number of individuals living in students’ households, which ranged from two to nine. In poverty categories two, four, and ﬁve, the highest percentage of students

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lived in households with four people, with the percentages being 28.6%, 55.4%, and 40% respectively. Poverty categories one and three had the highest percentages of students living in households with ﬁve people, 23.3% and 32.9% for those categories. Data were collapsed in order to examine the differences in poverty categories with six and fewer, and more than six people living in the household. Over 10% of poverty categories two, three, four, and non-poverty had greater than six people in the household, while 30.3% of students in extreme poverty lived in households with more than six people.

Parent’s Education SEELS parent interview data were collected on parents’ highest level of education, which ranged from less than 8th grade to Doctor of Philosophy (PhD) or Medical Doctor (MD) in 10 categories. Table 9 presents these data. Results revealed that educational attainment of the parent declined as income declined. Of all students in the poverty one category, 52.5% of their parents had not ﬁnished high school. This percentage dropped to 25.2% of students in poverty two, 12.5% of students in poverty three, 12.4% of students in poverty four, and only 3.3% of students in non-poverty. Conversely, 30.1% of students in the non-poverty category had parents who completed two or four years of college as compared to 20.5% in poverty four, 20.3% in poverty three, 10.9% in poverty two, and only .3% of poverty one.

Table 9.

Demographics: Percentages of Parents Highest Level of Education by Poverty Level.

Level W 8th grade Some high school High school or GED Some post high school 2-year college 4-year college Graduate school Masters PhD/MD Other

Poverty 1

Poverty 2

Poverty 3

Poverty 4

Non-Poverty

12.2 40.3 40.2 7.1 .2 .1

6.1 19.1 45.5 16.4 8.8 2.1 .8 .1 .1 .9

1.2 11.3 43.3 19.7 9.4 10.9 2.9 1.3 .1

2.8 9.6 46.7 19.2 12.4 8.1 .4 .8

.4 2.9 29.3 20.5 12.0 18.1 3.9 10.2 2.3 .3

.1

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Impact of Poverty

Parent’s Marital Status Data were collected in the SEELS parent interviews on the marital status of parents. A trend consistent with the other household characteristic variables occurs with this variable; lower poverty levels were associated with lower rates of parental marriage. That is, 41.2% of students living in extreme poverty were from families with parents who never married, compared with 14.3% of poverty two students, 5.6% of poverty three students, 7.7% of poverty four students, and 1.7% of non-poverty students. Conversely, 84.6% of non-poverty students are in families with married parents, compared with 71.9% of students in poverty four, 68.5% in poverty three, 50.3% in poverty two, and 35.4% in extreme poverty. Students in the poverty two category have the highest percentage of divorced parents (25.3%), followed by poverty three with 17.7%. Household Income Household income data were collected in $5,000 increments, which ranged from less than $5,000 to more than $75,000 per year. The greatest variation in this category was observed in the non-poverty group, which ranged from $25,000 to more than $75,000. In this category, .6% earned less than $30,000, 22.2% earned between $30,000 and $50,000, 41.1% earned between $50,000 and $70,000, and 36.1% earned more than $70,000 a year. Poverty level four was associated with household incomes that ranged from $20,000 to $75,000, with 83.5% of these incomes falling between $25,000 and $45,000. Poverty level three ranged from $5,000 to $40,000, with 81.9% falling between $10,000 and $25,000. The smallest variation in income was for families of students in extreme poverty, which ranged from $5,000 to $15,000 a year, with the overwhelming majority (82.8%) of these families earning less than $5,000 a year.

Extreme Poverty Because ﬁndings revealed that students in extreme poverty had different characteristics, further analyses were conducted examining student and household characteristics by extreme poverty. Tables 10, 11, and 12 present data for gender, disability category, and ethnicity for the extreme poverty group. Table 13 presents summary data comparing students in extreme poverty with the non-poverty group. Results indicate that students with disabilities in extreme poverty differ by ethnicity, while White students make up the majority of the other poverty categories. That is, 60.2% of the

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ELIZABETH HALLORAN TORNQUIST ET AL.

Table 10.

Gender by Ethnicity Category Percentages for Extreme Poverty.

Ethnicity

Male

Female

White Black Hispanic

51.5 69.7 90.3

48.5 30.3 9.7

Note: Total N ¼ 301.

Table 11.

Gender by Disability Category Percentages for Extreme Poverty.

Disability

Male

Female

LD SI MR ED OHI AUT

60.8 100 55.5 83.3 81.1 62.4

39.2 44.5 16.7 18.9 37.6

Note: Total N ¼ 301.

Table 12. Ethnicity Category by Disability Percentages for Extreme Poverty. Ethnicity

LD

SI

MR

ED

OHI

Other

White Black Hispanic

43.5 51.2 39.3

15.0 15.4 40.4

24.2 23.6 2.4

10.5 4.8 9.8

3.1 1.2 .4

3.1 2.1 4.5

Note: Total N ¼ 301.

students in extreme poverty were Black, compared to only 6.7% of students in the non-poverty category. Disability categories were also different for students in extreme poverty, with 20% of these students classiﬁed as having mental retardation, compared with 4.9% of students in the non-poverty category. The majority of students in extreme poverty live with one parent (58.6%), compared with 11.3% of students not in poverty; and 30.5% of students in extreme poverty lived in homes with more than seven people, compared with only 7.2% of non-poverty students. It was also found that

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Impact of Poverty

Table 13.

Percentage Differences between Extreme Poverty and Non-Poverty Special Education Students.

Area African American Mental retardation Lives with one parent More than seven people in home Parents never married Parent with no high school diploma Parent graduated 4-year college

Extreme Poverty

Non-Poverty

60.2 20.0 58.6 30.5 41.2 52.5 .1

6.7 4.9 11.3 4.2 1.7 3.3 34.8

41.2% of the students in extreme poverty had parents who were never married, while only 1.7% of parents of non-poverty students had never married. Education levels of parents also differ, in that 52.5% of those in extreme poverty had never ﬁnished high school and only .1% graduated from college, compared with 3.3% of non-poverty parents not having completed high school and 34.8% having graduated from a four-year college or university.

Relations among Poverty, Ethnicity, and Academic Achievement Multiple linear regression models were conducted using three variables related to disability: age of onset of disability, mental skills, and self-care. Two variables were run for academic achievement: passage comprehension and calculation. These variables were chosen because they represented key components of disability and academic achievement. Age of onset, mental skills, and self-care skills represented the level of severity of a disability and the level of personal independence of the student. Passage comprehension and calculation were chosen as representative of mathematics and reading skills. Regressions were run with poverty and ethnicity as independent variables, predicting the dependent variables, disability and academic achievement. Controlling for other factors, poverty was found to be a statistically signiﬁcant predictor for mental skills, F(10, 4) ¼ 7.13, po.001. Ethnicity, however, was not a signiﬁcant predictor for mental skills, F(10, 5) ¼ 1.23, p ¼ .44. Neither poverty, F(10, 4) ¼ .55, p ¼ .27, nor ethnicity, F(10, 5) ¼ .84, p ¼ .84, was found to be a signiﬁcant predictor of self-care skills. Poverty was not found to be a signiﬁcant predictor of age of onset,

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Table 14.

Inﬂuence of Poverty and Ethnicity.

Poverty

Age of onset Mental skills Self care Passage Calculation

df

F-Value

p-Value

5.87 7.13 .55 6.82 6.51

.06 .00 .27 .001 .01

10, 10, 10, 10, 10,

Ethnicity

4 4 4 4 4

df

F-Value

p-Value

3.84 1.23 .84 1.78 3.90

.29 .44 .84 .35 .05

10, 10, 10, 10, 10,

5 5 5 5 5

F(10, 4) ¼ 5.87, p ¼ .06; nor was ethnicity, F(10, 5) ¼ 3.84, p ¼ .29. The poverty variable, however, very nearly attained the traditional criterion for statistical signiﬁcance, so the conclusion of no relation may represent a Type II error. Poverty appeared to be a stronger predictor than ethnicity of academic achievement when using standard scores from two subtests of one achievement measure. The relation between poverty and passage comprehension was statistically signiﬁcant, F(10, 4) ¼ 6.82, po.001, while ethnicity was not statistically signiﬁcantly related to achievement, F(10, 5) ¼ 1.78, p ¼ .35. Both poverty, F(10, 5) ¼ 6.51, p ¼ .01, and ethnicity, F(10, 4) ¼ 3.90, p ¼ .05, were statistically associated with calculation. While poverty was the stronger predictor of academic achievement, ethnicity was also a signiﬁcant predictor of academic achievement on calculation. Table 14 displays the F-values and p-values for each of the regression models.

DISCUSSION Major ﬁndings from this research study suggests that lower family income is associated with less advantageous life circumstances for students with disabilities; and that poverty is a prevalent characteristic of students receiving special education services, especially when using the alternative deﬁnitions of poverty employed in this investigation. The data analyzed for this research underscores the impact poverty has on children. This research supports previous ﬁndings that children in poverty experience very different realities from students who are not poor (Benson, 2003; Moore, Vandivere, & Ehrle, 2000). This secondary analysis of the SEELS database revealed that, when combining the four poverty categories used in this research, 40.3% of all

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elementary aged children in special education are in poverty. Findings also suggest that circumstances differ even among students in poverty, with those students in extreme poverty faring the worst. Students with disabilities in extreme poverty are differentially associated with single parent households, parents who have never been married, and parents who have never graduated from high school and 20% of these students are categorized as mentally retarded. Extreme poverty for children is growing rapidly, with four out of every ﬁve children in the United States who have fallen into poverty since 2002 falling into extreme poverty (Children’s Defense Fund, 2004). This study also supports previous research that poverty is a stronger predictor of academic achievement than ethnicity (Entwisle & Alexander, 1995). Results of the present investigation revealed that poverty is a signiﬁcant predictor of academic achievement on two subtests of the WJ-R, passage comprehension and calculation. In addition, results of the present investigation revealed that lower income categories were associated with the higher percentages of minority students. Such evidence offers interesting insights on the problems of the signiﬁcant issue of disproportionate representation of different racial/ethnic groups in special education, in that such overrepresentation may be explained to a great extent by the overrepresentation of different racial/ethnic groups in categories of poverty. The evidence also suggests, given childhood poverty on the rise, that we might reasonably expect continued growth in special education enrollment. The results of this investigation are consistent with the conclusions of Berliner (2005), who concluded that poverty exerts a profound effect on virtually all aspects of schooling. The present results suggest that poverty may be the too often overlooked factor contributing to or possibly even causing the increased enrollment in special education and possibly the overrepresentation of minority students found eligible for services, a conclusion supported by other researchers (Parrish, 2000; Zhang & Katsivannis, 2002; Hebbeler & Wagner, 1998). Future research could provide further explanations of the complex relationship between poverty and disability.

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Boushey, H., Brocht, C., Gundersen, B., & Bernstein, J. (2001). Hardships in America: The real story of working families. Washington, DC: Economic Policy Institute. Bradley, R. H., Corwyn, R. F., McAdoo, H. P., & Coll, C. G. (2001). The home environments of children in the United States part one: Variations by age, ethnicity, and poverty status. Child Development, 72, 1844–1868. Brown, B., Vandivere, S., Lindberg, L. D., Boggess, S., Porter, L., & Williams, S. (1999). Trends in the well-being of America’s children and youth (4th ed.). Washington, DC: U.S. Department of Health and Human Services. Caldas, S. J., & Bankston, C., III. (1997). Effect of school population socioeconomic status on individual academic achievement. Journal of Educational Research, 90, 269–277. Center on Budget and Policy Priorities. (2003). Poverty increases and median income declines for second consecutive year. Washington, DC: Center on Budget and Policy Priorities. Children’s Defense Fund. (2004). 2003 facts on child poverty in America, October. Available at http://childrensdefense.org/familyincome/childpoverty/basicfacts.asp. Retrieved on February 7, 2005. Citro, C. F., & Michael, R. T. (1995). Measuring poverty: A new approach. Washington, DC: National Academy Press. Entwisle, D. R., & Alexander, K. L. (1995). A parent’s economic shadow: Family structure versus family resources as inﬂuences on early school achievement. Journal of Marriage and the Family, 57, 399–409. Fisher, G. M. (1992). The development and history of the poverty thresholds. Social Security Bulletin, 55, 3–14. Garner, T. I., Short, K., Shipp, S., Charles, N., & Paulin, G. (1998). Experimental poverty measurement for the 1990s. Monthly Labor Review, 121, 39–61. Glennerster, H. (2002). United States poverty studies and poverty measurement: The past twenty-ﬁve years. The Social Service Review Chicago, 76, 83–107. Guo, G. (1998). The timing of the inﬂuences of cumulative poverty on children’s cognitive ability and achievement. Social Forces, 77, 257–288. Hebbeler, K., & Wagner, M. (1998). Representation of minorities and children of poverty among those receiving early intervention and special education services: Findings from two national longitudinal studies. Menlo Park, CA: SRI International. Kruse, D. L. (1998). Demographic, income, and health characteristics, 1993. Monthly Labor Review, 121(9), 13–23. Lee, S., Sills, M., & Gi-Taik, O. (2002). Disabilities among children and mothers in low income families. Washington, DC: The Institute for Women’s Policy Research. Moore, K. A., Vandivere, S., & Ehrle, J. (2000). Socioeconomic risk and child well being (ERIC Document Reproduction Services No. ED442885). Washington, DC: Urban Institute and Child Trends. National Organization on Disability. (2004, June 25). Landmark disability survey ﬁnds pervasive disadvantages. Available at http://www.nod.org/content.cfm?id ¼ 1537. Retrieved on July 30, 2004. Park, J., Turnbull, A. P., & Turnbull, H. R. (2002). Impacts of poverty on quality of life in families of children with disabilities. Exceptional Children, 68, 151–171. Parrish, T. (2000). Disparities in the identiﬁcation, funding, and provisions of special education. Paper submitted to The Civil Rights Project for The Conference on Minority Issues in Special Education in Public Schools, November, Cambridge, MA. Rich, S. (2001). Poverty, by the numbers. National Journal, 33, 694–695.

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Seelman, K., & Sweeney, S. (1995). The changing universe of disability. American Rehabilitation, 21, 2–16. Slesnick, D. T. (2002). Prices and regional variation in welfare. Journal of Urban Economics, 51, 446–468. U.S. Census Bureau. (2000). Poverty in the United States: 2000 (Current population reports, series P60-214). Washington, DC: Dalaker, J. Wagner, M., Marder, C., Blackorby, J., & Cardosa, D. (2004). Special education longitudinal study. Unpublished raw data from http://www.seels.net Zhang, D., & Katsivannis, A. (2002). Minority representation in special education: A persistent challenge. Remedial and Special Education, 23, 180–187.

INCREASING ACCESS TO HIGHER EDUCATION FOR STUDENTS WITH DISABILITIES AND STRENGTHENING THE PREPARATION OF PROFESSIONALS WHO INSTRUCT THEM: THE HIGHER EDUCATION OPPORTUNITY ACT OF 2008 Jane E. West ABSTRACT Enacted in August 2008, the Higher Education Opportunity Act (HEOA), PL 110-315, represents a landmark public policy effort on behalf of students with disabilities and a natural outgrowth of the impact of Individuals with Disabilities Education Act (IDEA) and No Child Left Behind (NCLB). This chapter examines the myriad new provisions in HEOA intended to improve access to higher education for students with disabilities as well as HEOA’s provisions related to preparing teachers to effectively instruct students with disabilities in the K-12 environment. Policy and Practice Advances in Learning and Behavioral Disabilities, Volume 22, 189–225 Copyright r 2009 by Emerald Group Publishing Limited All rights of reproduction in any form reserved ISSN: 0735-004X/doi:10.1108/S0735-004X(2009)0000022009

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Multiple new provisions reﬂect an invigorated commitment to developing a workforce for today’s schools – schools with unprecedented diversity – and to addressing the critical teacher shortages, including special education. This chapter is organized around three themes: access to higher education for students with disabilities, investing in the capacity of higher education to serve students with disabilities, and strengthening the preparation of teachers of students with disabilities, including accountability for this preparation. People with disabilities are one of the poorest and least employed minorities in our nation. The employment rate of working-age people with disabilities is only half the rate of people without disabilities – 38% compared to 78% in 2005 (National Council on Disability, 2007). Further, working-age Americans with disabilities are more than twice as likely to live in poverty as other Americans and only half as likely to be employed (Stapleton, O’Day, Livermore, & Imparato, 2005). The dire consequences of these long-term high unemployment and poverty rates leave people with disabilities at risk of becoming a long-term underclass. Higher education is a much-overlooked avenue that could be effective in ameliorating these chronic conditions. Data from the National Center for Education Statistics (1999) indicate that students with disabilities who do manage to graduate from college exhibit similar labor market outcomes as their peers without disabilities. Despite these promising data, students with disabilities may be the most marginalized of all subgroups in terms of access to higher education. While numerous initiatives in higher education have existed for some time to promote access for other underrepresented groups (African American students, Hispanic students, Native American students, ﬁrst-generation college goers), those for students with disabilities have been few and far between. In fact, students with disabilities are generally not considered in conversations and policies about diversity in higher education.

THE HIGHER EDUCATION OPPORTUNITY ACT OF 2008: WHY NOW? After over 30 years of a guaranteed free appropriate public education in K-12, students with disabilities, like their peers without disabilities,

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seek to take the next step into higher education and are pushing the boundaries of higher education. Policies and practices to support their participation are developing and improving. During that time, over 130 programs for students with intellectual disabilities in higher education were developed (Thinkcollege.net, 2008). Implementation of Section 504 of the Vocational Rehabilitation Act and the Americans with Disabilities Act (ADA) (1990) matured and is addressing issues such as campus accessibility, accommodation for students during instruction, access to instructional materials and accommodations in college, and graduate school entrance exams. And it is now more the norm than the exception to have a disability services ofﬁce on the campus (AHEAD, 2008). The last reauthorization of the Higher Education Act took place in 1998 – a decade ago. This reauthorization predated the enactment of No Child Left Behind (NCLB) (2001) and the Individuals with Disabilities Education Act (IDEA) (2004) reauthorization. The 1998 reauthorization of the Higher Education Act authorized the ﬁrst program exclusively targeted to increasing access to higher education for students with disabilities by investing in the capacity of higher education faculty and administrators to better meet the needs of students with disabilities on campus through demonstration projects (Higher Education Act Amendments, 1998, Section 761–765). This modest initiative (never funded beyond $6.8 million per year) created a platform for further investment and expansion. The 2008 reauthorization of the Higher Education Act represents a signiﬁcant acknowledgment that students with disabilities are part of higher education. Just as barriers are acknowledged for other underrepresented groups (Hispanic students, minority students, ﬁrst-generation college goers), so too are those for students with disabilities. The enactment of the Higher Education Opportunity Act (HEOA) in 2008 represents a great leap forward in policy for access to higher education for students with disabilities and toward strengthening the preparation of those who instruct them. New provisions in the law related to students with disabilities and the preparation of educators who instruct them are reviewed later. The provisions are organized into three sections: access to higher education for students with disabilities, investing in the capacity of higher education to serve students with disabilities, and strengthening the preparation of teachers of students with disabilities.

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ACCESS TO HIGHER EDUCATION FOR STUDENTS WITH DISABILITIES Who are Students with Disabilities? The population of students with disabilities in K-12 education includes those served under the IDEA and those served under Section 504 of the Rehabilitation Act. IDEA serves students with autism, deafness– blindness, deafness, emotional disturbance, hearing impairments, mental retardation, multiple disabilities, orthopedic impairment, other health impairment, speciﬁc learning disability, speech or language impairment, traumatic brain injury, and visual impairments. These students receive special education services under the direction of an individualized education program (IEP) developed by a team that includes the parents of the student, sometimes the student, and the professionals who work with the student. All students eligible under IDEA are also protected by Section 504 of the Rehabilitation Act, which deﬁnes disability as physical or mental impairments that substantially limit a major life activity. Students eligible under Section 504 (but not IDEA) include not only students whose disabilities do not require specially designed instruction as provided under IDEA, but also those who do need reasonable accommodations such as extended time for test taking, materials or other auxiliary aids and services, such as qualiﬁed sign language interpreters, note takers, readers, accessible materials, and adaptive equipment. How Many Students with Disabilities Participate in Higher Education? The two key federal sources of data on people with disabilities are census data and federal program data. Both are problematic. Census data are selfreported and thus subjective. Federal program data revolve around the deﬁnition of disability for a particular program, and are limited to the purpose of the program (e.g., income maintenance, welfare, antidiscrimination, employment and training, education). No single disability program applies to the more than 50 million Americans who are generally considered to have disabilities (National Council on Disability, 2008). The number of students served by special education who exit from high school – either by graduating with a diploma or certiﬁcate, or by reaching maximum age – was approximately 300,000 in 2005–2006 (U.S. Department

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of Education, 2007). A U.S. Government Accountability Ofﬁce (GAO, 2003) study for the 2000–2001 school year indicated that 56% of young people with disabilities graduate from high school with a standard diploma. The number of students exiting high school who were served under Section 504 and those who had disabilities but did not seek services is difﬁcult to determine. It appears certain that several hundred thousand students with disabilities may be in a position to pursue higher education every year – and this only includes those who are newly exited from high school. Some may pursue higher education at a later stage in their lives. Of those who may be eligible, only a small portion attend and graduate. The number of students with disabilities who participate in postsecondary education is more difﬁcult to determine. First, some students with disabilities who graduate from high school, even with a regular diploma, are not eligible to attend college. Second, some high school graduates with a disability delay entry to college and may be missed in data collection efforts. Finally, some students with disabilities do not indicate a disability on a survey and are thus missing from data. Further, some college students with disabilities choose not to seek disability services (Wolanin & Steele, 2004) and, therefore, elude being included in data collection. Available data indicate that the number of students with disabilities in higher education has been climbing regularly from 2.6% in 1978 to 9.2% in 1994 to 18% in 1996. (Blackorby & Wagner, 1996). Still, however, the enrollment of people with disabilities in postsecondary institutions is 50% lower than that among the general population (Getzel, Stodden, & Briel, 2001). To help meet this need for information, the Government Accountability Ofﬁce has undertaken a study to examine and analyze the status of students with disabilities in higher education. Requested by Congressman George Miller (D-CA), Chairman of the U.S. House of Representatives Committee on Education and Labor, the study was initiated in the spring of 2008 and will: 1. Examine the extent and manner in which students with disabilities are applying to, being accepted in, enrolling in, and graduating from different types of institutions of higher education. 2. Determine the factors that inﬂuence the physical, academic, social, and economic access for students with intellectual, emotional, and physical disabilities in higher education. 3. Collect and identify the rates of requests for, and access to, accommodations on college and graduate admissions tests.

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4. Examine the effectiveness and capacity of disability support service ofﬁces in institutions of higher education. 5. Determine the extent to which institutions of higher education partner and coordinate services with other programs to assist students with disabilities. 6. Examine program characteristics of institutions of higher education that have been effective in recruiting and graduating students with all types of disabilities. (Miller, 2008). This comprehensive request is a reﬂection of the very limited data available about students with disabilities and higher education. Policy Nexus Supporting Access to Higher Education for Students with Disabilities The worlds of K-12 education and higher education are fundamentally different in relation to serving students with disabilities. Whereas in K-12 universal access is a mandate with a zero rejection policy, in higher education entry is competitive and all students (those with and without disabilities) are routinely rejected because they do not meet standards set by higher education. This fundamentally different approach to education by the two sectors represents a signiﬁcant challenge for students with disabilities who leave a K-12 system where they are universally served to enter a system that, by design, excludes on the basis of merit.

The Individuals with Disabilities Education Act – Transition Services The key K-12 federal education program for students with disabilities, IDEA, requires planning for transition from high school to the adult world, be it work, higher education, or other activities. This planning is required to begin no later than when the student is aged 16. Planning, via the IEP process, must focus on the services that will be needed for an effective transition out of secondary education. Students are required to be involved in this planning process. Effective transition has been a concern for policymakers over the life of IDEA, as many students with disabilities continue to experience difﬁculties in moving into employment or postsecondary education after high school. Speciﬁcally, a recent National Council on Disability (2007) report indicates that much transition planning lacks relevance or is ineffective or poorly

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implemented and that students with disabilities who leave K-12 education often face fragmented services or services targeted to training for low-paying jobs. Vocational Rehabilitation Vocational Rehabilitation (VR) is a federal program intended to promote employment and independent living for people with disabilities. States receive block grants from the federal government to provide services. Because participation in higher education is a route to employment, VR provides assistance to some people with disabilities in higher education when deemed appropriate. A 2000 study indicated that approximately 300,000–400,000 people with disabilities annually receive postsecondary education services through VR. This represents approximately one quarter of all undergraduate students with disabilities in higher education (Wolanin & Steele, 2004). VR services vary and may last for one or more years. Services may include counseling, paying for assessments to document a student’s disability, and paying direct expenses such as tuition, fees, books and supplies, room and board costs. One study found that for those receiving ‘‘college only’’ services, the average length of time was nearly four years and the average cost for purchased services was $5,538 (Hart, Gilmore, & Zafft, 2000). Clearly, VR is a signiﬁcant source of support for students with disabilities in higher education. The Americans with Disabilities Act and Section 504 The nation’s two key anti-discrimination laws for people with disabilities – Section 504 of the Rehabilitation Act and ADA – apply to higher education, where they prohibit discrimination on the basis of disability. Within the realm of postsecondary education, these laws require the provision of auxiliary aids and services and the modiﬁcation of policies and procedures that are necessary to afford a student with a disability an equal opportunity. Such aids and services may include taped texts, note takers, interpreters, readers, and specialized computer equipment, and modiﬁcations may include course substitution, additional time to complete academic requirements, and adaptation of the manner in which courses are conducted. In addition, the laws require physical accessibility on campuses. To date, enforcement of these provisions has tended to focus on the physical

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accessibility rather than programmatic accessibility (National Council on Disability, 2008) to higher education, probably because programmatic accessibility is more complex and more challenging. Amendments to the ADA, enacted into law in September, 2008 (Americans with Disabilities Amendment Act (ADAA)) reinforce an existing provision in the law, indicating that institutions of higher education are not required to provide accommodations or modiﬁcations that would require a ‘‘fundamental alteration of the program.’’ Higher education institutions sought this language, which re-states an existing provision of the ADA (Section 302(b)(2)(A)(ii)), in an effort to reiterate that modiﬁcations to academic requirements are not mandated if the institution can demonstrate that such modiﬁcations would fundamentally alter the program. The courts will be the ﬁnal arbiters as to whether a requested accommodation or modiﬁcation would require an inappropriate alteration to a program or course, or whether the denial of such a request is discriminatory. Other provisions in the ADAA seek to overturn several Supreme Court decisions and make a number of additional changes to broaden the interpretation of the deﬁnition of disability. One provision clariﬁes that ‘‘mitigating measures’’ are not to be considered when determining if a person has a disability. In other words, if a person with epilepsy is taking medication to control seizures, that person is still considered to have a disability even though the medication may reduce or eliminate the seizures. Additionally, the ADAA clariﬁes that ‘‘learning, reading, concentrating, thinking, communicating’’ are examples of major life activities that may be substantially limited by an impairment, constituting a disability. The ADAA also ensures that the agencies with regulatory authority will promulgate new rules related to the amendments. These new provisions are likely to have an impact on students with disabilities in higher education. Once again, the courts will ultimately be the arbiters.

New Provisions in HEOA Five key sets of provisions in the new law are targeted at increasing access to higher education for students with disabilities: data collection, universal design for learning (UDL), access to federal ﬁnancial student aid for students with intellectual disabilities, revision of the Free Application for Federal Student Aid (FAFSA), and additions to TRIO and Gaining Early Awareness and Readiness for Undergraduate Programs (GEAR UP) programs.

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Data Collection Data are essential ingredients of policy deliberations. Without accurate data, policymakers struggle to determine the scope and impact of policies. Because of the paucity and the lack of reliability of data currently available about students with disabilities in higher education, a provision was added in an effort to create a reliable data set. These data will provide policymakers and others with indicators of the extent to which students with disabilities are participating in higher education. A new section of the law, ‘‘Transparency in College Tuition for Consumers,’’ (Section 132 of HEOA) includes a set of information that institutions of higher education must provide for potential students and their families to be fully informed. These data include descriptors of the student population, such as how many males/females attend the school; how many full- vs. part-time students attend the school; what percentage of students complete their degrees on time, and so on. One new set of data required is the percentage of undergraduate students who are registered with the ofﬁce of disability services or its equivalent (Section 132 I (1) (I)). If 3% of less of the student population is students with disabilities, the institution is to report ‘‘3% or less.’’ While this provision will be helpful in providing a new data set, it is not without limitations. While every institution of higher education has a disability ofﬁce which, at a minimum, determines eligibility under Section 504 and ADA, some students with disabilities who may be eligible for services elect not to utilize them. They would be left out of the data set. While the new data set offers a more objective and reliable measure than self-report through sample surveys – which is currently the way data are reported – it is likely to be an underreporting of students with disabilities in higher education.

Universal Design and Universal Design for Learning The notion of UDL was built on the notion of universal design, which is an architectural term connoting design for use by the maximum number of people regardless of physical or mental needs.1 One analogy is the idea of a curb cut for learning. In other words, it takes a curb cut to make a sidewalk accessible for a person using a wheelchair, but people pushing strollers or dragging wheeled suitcases may also beneﬁt. In terms of UDL, it takes the instructional version of a curb cut to make learning accessible for some students.

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HEOA infuses the notion of universal design and UDL throughout the law, thereby sending a clear message about the intended access to instruction for students with disabilities in higher education. In Section 103 of the statute, UDL is deﬁned as follows: UNIVERSAL DESIGN FOR LEARNING – The term ‘‘universal design for learning’’ means a scientiﬁcally valid framework for guiding educational practice that – (A) Provides ﬂexibility in the ways information is presented, in the ways students respond or demonstrate knowledge and skills, and in the ways students are engaged (B) Reduces barriers in instruction, provides appropriate accommodations, supports, and challenges, and maintains high achievement expectations for all students, including students with disabilities and students who are limited in English proﬁciency. (HEOA Section 103 (a)(24). Universal design and UDL are referenced several places in the statute, including in the Teacher Quality Partnership Grants (HEOA Sections 202 (d)(1)(A)(i) and 204 (a)(G)) accountability for programs that prepare teachers (HEOA Sections 205(a)(1)(F) and 205 (b)(1)(K)), Preparing Teachers for Digital Age Learners (HEOA Sections 231(a)(3), 232(a)(2), (b)(2), 233(1)(B)), Teach to Reach Grants (HEOA Section 251(c)), Demonstration Projects to Support Postsecondary Faculty, Staff and Administrators in Educating Students with Disabilities (HEOA Section 762(b)(2)(A)and (G)), the Advisory Commission on Accessible Instructional Materials in Postsecondary Education for Students with Disabilities (HEOA Section 772(b)(C)(ii)(V)), Model Demonstration Programs to Support Improved Access to Postsecondary Instructional Materials for Students with Disabilities (HEOA Section 733(f )(1)(G), and the National Technical Assistance Center (HEOA Section 444(4)(B)). Access to Federal Financial Aid for Students with Intellectual Disabilities In one of the most potentially far-reaching new provisions in the law for students with disabilities, students with intellectual disabilities are, for the ﬁrst time, provided access to student federal ﬁnancial aid. While an increasing number of students with intellectual disabilities are participating in higher education (thinkcollege.net) they are not participating in standard matriculation programs and, thus, have not been eligible for federal ﬁnancial aid. For the students who do manage to ﬁnd appropriate higher education programs, the tuition is often the same or sometimes higher than for students in traditional programs. Without access to ﬁnancial

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aid, the burden for payment falls completely on the family, thereby excluding any students and their families who cannot afford to foot the entire bill.2 Students with intellectual disabilities are deﬁned in the legislation as follows: STUDENT WITH AN INTELLECTUAL DISABILITY – The term ‘‘student with an intellectual disability’’ means a student — (A) With mental retardation or a cognitive impairment, characterized by signiﬁcant limitations in i. Intellectual and cognitive functioning and ii. Adaptive behavior as expressed in conceptual, social, and practical adaptive skills; and (B) Who is currently, or was formerly, eligible for a free appropriate public education under the Individuals with Disabilities Education Act (Section 760). Title IV of HEOA (HEOA Section 485(s)) provides that students with intellectual disabilities may be eligible for Pell Grants,3 Supplemental Educational Opportunity Grants (SEOGs),4 and Work Study funds.5 In order to be eligible for these funds, students with intellectual disabilities must be enrolled or accepted for enrollment in a comprehensive transition and postsecondary program for students with intellectual disabilities at an institution of higher education. Students must maintain satisfactory progress in the program as determined by the institution based on standards established by the institution. A comprehensive transition and postsecondary program for students with intellectual disabilities is deﬁned in the statute in Section 760 as follows: 1. Comprehensive Transition and Postsecondary Program for students with intellectual disabilities – The term ‘‘comprehensive transition and postsecondary program for students with intellectual disabilities’’ means a degree, certiﬁcate, or non-degree program that is – (A) Offered by an institution of higher education; (B) Designed to support students with intellectual disabilities who are seeking to continue academic, career and technical, and independent living instruction at an institution of higher education in order to prepare for gainful employment; (C) Includes an advising and curriculum structure; and (D) Requires students with intellectual disabilities to participate on not less than a half-time basis, as determined by the institution, with

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such participation focusing on academic components and occurring through one or more of the following activities: i. Regular enrollment in credit-bearing courses with non-disabled students offered by the institution. ii. Auditing or participating in courses with non-disabled students offered by the institution for which the students does not receive regular academic credit. iii. Enrollment in non-credit-bearing, non-degree courses with nondisabled students. iv. Participation in internships or work-based training in settings with non-disabled individuals. The Secretary of Education is authorized to waive statutory provisions relevant to eligibility for student ﬁnancial aid or institutional eligibility requirements if she determines that this is necessary in order to ensure that students with intellectual disabilities in comprehensive transition and postsecondary programs are eligible for ﬁnancial aid. The Secretary is required to promulgate regulations allowing programs for students with intellectual disabilities to be eligible for federal student aid. These regulations will be critical for implementation of this program, as they will put forward a process and standards for determining which programs meet the deﬁnition of a ‘‘comprehensive transition and postsecondary program.’’ Until this determination is made, ﬁnancial aid will not be available to students with intellectual disabilities. The Free Application for Federal Student Aid (FAFSA) The FAFSA is the form students and families use to apply for ﬁnancial aid. The HEOA requires the Secretary to lead an effort to make the FAFSA more consumer friendly and to ensure that it is ‘‘available in formats accessible to individuals with disabilities’’ (HEOA Section, 483 (a) (1)). HEOA also requires the formation of a study group which will consult with the Comptroller General who will undertake an analysis and issue a report with recommendations on how to improve and simplify the FAFSA (HEOA Section 483(f )(3)). TRIO and GEAR UP programs These two long-standing programs in HEOA are intended to support at-risk students in high school in pursuing higher education. The HEOA underscores that both programs are intended to serve students with disabilities. In the conference report, the conferees note that they encourage both

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TRIO and GEAR UP to offer programs and activities that are ‘‘specially designed to address the unique challenges these students face as they work to achieve a college degree’’ (U.S. House of Representatives, 2008 – Conference Report for HEOA to accompany HR 4137, report 110-803, pp. 506 and 513).

INVESTING IN THE CAPACITY OF HIGHER EDUCATION TO SERVE STUDENTS WITH DISABILITIES Institutions of higher education are gradually developing the capacity to effectively serve and instruct students with disabilities; however, more progress is needed. Higher education does not always embrace the mission of serving students with disabilities and sometimes believes that they represent a challenge to the authority to determine academic standards. When students are successful academically and request accommodations, universities may believe that they are not really disabled because, the logic goes, otherwise, ‘‘how would they be successful academically?’’ Indeed, several court cases have supported this line of thinking (Price v. National Board of Medical Examiners [966 F. Supp. 419,427; S.D. W. Va. 1997]; Gonzales v. National Board of Medical Examiners [225 F. 3d 620; 6th Cir. 2000]; and Wong v. Regents of University of California [379 F. 3d.1097; 9th Cir. 2004]). The U.S. House of Representatives Committee on Education and Labor Report that accompanied HR 3195, the ADAAA, argues that a careful analysis is required when considering whether or not a high-achieving person has a disability. The committee notes that while the basic mechanics of reading and writing do not pose extraordinary lifelong challenges for a person without a learning disability, they do for a person with a learning disability. Additionally, the legislative record makes it clear that Congress believes that an individual who performs well academically may still be considered an individual with a disability.6 A letter published to the editor of the Chronicle of Higher Education exempliﬁes a less-than-welcoming environment for students with disabilities in higher education: Giving a ‘learning disabled’ student extra time on exams is like letting a blind person qualify for a pilot’s license with the aid of a Seeing Eye dog in the cockpit. I don’t think any of us want to ﬂy in an airplane with such a pilot, or to ﬁnd in the emergency room a doctor who owes his medical-school admission to extra time on exams. (Katz, 1998, p. B10)

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The 1997 Guckenberger v. Boston University class action lawsuit is one of the most notorious cases related to the provision of accommodations. Jon Westling, the president of Boston University, believed that students were manufacturing disabilities to get accommodations that provided them with unfair advantages over other students. Westling created a ﬁctional story about a student with a disability, dubbed ‘‘Somnolent Samantha,’’ who requested the accommodation of the professor ﬁlling her in on material she missed if she slept in class. He took over the disability services ofﬁces at Boston University and made himself the arbiter of determinations about accommodations (Lewin, 1997). Boston University lost this case and was required to improve the accommodation process. Beyond such blatant cases, evidence suggests that faculty at institutions of higher education are uninformed about the nature of disability and unaware of the needs of students with disabilities (Greenbaum, Graham, & Scales, 1995). The reauthorization of the Higher Education Act appears to reﬂect the understanding that there is a signiﬁcant need to invest in the capacity of higher education to become equipped to more effectively meet the needs of students with disabilities. Thus, HEOA includes reauthorization of the one program addressing access to students with disabilities that was initiated in the 1998 reauthorization of the Higher Education Act, as well as four new programs as outlined below.

Demonstration Projects to Support Postsecondary Faculty, Staff and Administrators in Educating Students with Disabilities (HEOA Part D, Subpart I, Sections 760–765) Although the name has been changed, this program was initially authorized in the Higher Education Act in 1998. The purpose of the program, which remains the same, is to provide technical assistance or professional development for postsecondary faculty, staff, and administrators in higher education to enable them to provide students with disabilities a quality postsecondary education. Grants, contracts, and cooperative agreements are authorized, and not less than two must be targeted to support for students with learning disabilities. Grants are awarded for three to ﬁve years and must address one or more of the following activities: The development of teaching methods and strategies consistent with the principles of UDL to provide faculty, staff, and administrators with

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the skills and supports necessary to teach and meet the academic and programmatic needs of students with disabilities in order to improve their retention and completion of postsecondary education programs. The development of effective transition practices to ensure the smooth transition from secondary school to postsecondary education. A synthesis of research and information related to the provision of postsecondary education for students with disabilities including data on the impact of a postsecondary education on subsequent employment. The development of innovative teaching methods for providing accessible distance education programs and classes. The provision of assistance to faculty, staff, and administrators that would promote student interest and participation in preparation for disability-related careers. The provision of professional development and training. Increasing the accessibility of postsecondary education through curriculum development consistent with the principles of UDL.

The law requires an evaluation of the grant and dissemination of results to other institutions of higher education. Factors to be considered in awarding grants include geographic distribution, urban and rural awards, the range and type of institution, and prior experience or exceptional programs. Not later than a year after the enactment of the law (August 2009), the Secretary of Education is required to submit a report to the authorizing committees of the Congress and the public on all projects awarded grants from 1999 to 2008, including a review of the activities and program performance of the projects.7 The program is authorized for six years at a ‘‘such sums’’ level. The program is currently funded at the $6.7 million level. Funding has remained close to that level since the inception of the program in 1998. This program has been routinely recommended for elimination in President Bush’s annual budget submissions to Congress. However, every year Congress restored the funds.

Model Comprehensive Transition and Postsecondary Programs for Students with Intellectual Disabilities Students with intellectual disabilities are increasingly seeking to participate in postsecondary education. An estimated 2,000–3,000 students with intellectual disabilities annually are eligible for postsecondary programs.

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About 130 programs are in existence (thinkcollege.net), most of them supporting students who are dually enrolled in high school and college. Early research indicates that students with intellectual disabilities who had some type of postsecondary education experience are more likely to obtain competitive employment than those who did not (Hart, Grigal, Sax, Martinez, & Will, 2006). The HEOA reﬂects this growing need for higher education to include students with intellectual disabilities. Grants are authorized to institutions of higher education to create or expand high quality inclusive model programs for students with intellectual disabilities. The program is to be administered in the Ofﬁce of Postsecondary Education in the U.S. Department of Education. Grants are to be awarded for a ﬁve-year period. Geographic distribution is to be taken into account in awarding the grants in areas which are underserved by such programs as these. Preference is to be given to applicants who offer one or more of the following elements: formation of a partnership with any relevant agency, such as a VR agency; integration of students with intellectual disabilities into the housing offered to students without disabilities; the involvement of students studying special education, general education, vocational rehabilitation, or related ﬁelds in the model program. Funds may be used to provide individual support and services for the academic and social inclusion of students with intellectual disabilities in academic courses, extracurricular activities and other aspects of the college’s regular postsecondary program. The program should focus on academic enrichment, socialization, independent living skills (including self-advocacy) and integrated work experiences, and career skills that will lead to gainful employment. Person-centered planning is to be integrated in the development of the course of study for each participating student. The program must participate in the coordinating center (see later) and partner with one or more local education agencies to support students who are still eligible for services under IDEA, including the use of funds from Part B of that act to support the participation of students in the postsecondary program. The grant recipient must plan for the sustainability of the program after the end of the grant and most create and offer a meaningful credential upon completion of the program. The institution receiving the grant must provide matching funds toward the cost of the program (in cash or in-kind) equaling no less than 25% of the amount of costs. No later than ﬁve years after the date of the ﬁrst award, the Secretary of Education must submit a report that reviews the activities of the model programs and provides guidance and recommendations on how effective model programs can be replicated.

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‘‘Such sums’’ are authorized for the program for six years. A portion of the funds must be set aside to fund a cooperative agreement to establish the coordinating center described below. Coordinating Center (HEOA Section 777 (b)) This center is intended to provide coordinating services for institutions of higher education that offer inclusive comprehensive transition and postsecondary programs for students with intellectual disabilities – both those funded by the model grants described earlier and others. Entities eligible for these funds must have expertise in higher education, the education of students with intellectual disabilities, the development of comprehensive transition and postsecondary programs for students with intellectual disabilities, and evaluation and technical assistance. The Coordinating Center shall: (a) Serve as the technical assistance entity for all comprehensive transition and postsecondary programs for students with intellectual disabilities. (b) Provide technical assistance regarding the development, evaluation, and improvement of such programs. (c) Develop an evaluation protocol for such programs. (d) Assist model programs in awarding meaningful credentials to students completing programs. (e) Develop recommendations for necessary components of such programs including academic, vocational, social and independent living skills, evaluation of student progress, program administration and evaluation, student eligibility and issues regarding the equivalency of a student’s participation in such programs to semester, trimester, quarter, credit, or clock hours at an institution. (f ) Analyze and recommend possible funding streams for such programs. (g) Develop model memoranda of agreement for use between or among institutions of higher education and state and local agencies providing funding for such programs. (h) Develop mechanisms for regular communication, outreach, and dissemination of information among programs and to parents and prospective students. (i) Host a meeting of all grant recipients not less than once a year. ( j) Convene a workgroup to develop and recommend model criteria, standards, and components of programs that are appropriate for the development of accreditation standards.

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National Center for Information and Technical Support for Postsecondary Students with Disabilities (Sections 777–778, HEOA) This new center is authorized to provide technical assistance and information on best and promising practices to students with disabilities, their families and higher education entities to improve recruitment, transition, retention, and completion rates of students with disabilities in postsecondary education. The Secretary is authorized to provide funding to an institution of higher education, a non-proﬁt organization, or a partnership of two or more such institutions or organizations with expertise in supporting students with disabilities in postsecondary education, technical knowledge necessary for the dissemination of information in accessible formats, working with diverse types of institutions of higher education, and the subjects supported by grants and contracts in other parts of the law for students with disabilities. The National Center is required to provide or carry out the following activities: Assistance to students and families, including information to assist prospective students with disabilities in planning for postsecondary education while they are in secondary school. Information and technical assistance to IEP teams and early outreach to student services programs to support students with disabilities with a successful transition to postsecondary education. Research-based supports, services, and accommodations that are available in postsecondary settings. Information on student mentoring and networking opportunities for students with disabilities. Effective recruitment and transition programs at postsecondary institutions. Assistance to institutions of higher education to improve the services provided to, the accommodations for, the retention rates of, and the completion rates of, students with disabilities in higher education settings, which may include the collection and dissemination of best and promising practices, the development and provision of training modules for higher education faculty, and development of technology-based tutorials for higher education faculty and staff. Information collection and dissemination, including building, maintaining, and updating a database of disability-support services, and information related to institutions of higher education.

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Collaboration with organizations and individuals with expertise to evaluate, improve, and disseminate information related to the delivery of high-quality disability-support services at institutions of higher education. Prepare and disseminate reports to the Secretary of Education and authorizing committees analyzing the condition of postsecondary success for students with disabilities. ‘‘Such sums’’ are authorized for the National Center for six years.

Advisory Commission on Accessible Instructional Materials in Postsecondary Education for Students with Disabilities (Section 772) One of the commonly noted barriers to higher education for some students with disabilities is access to instructional materials. For example, students who are blind may need a textbook on tape, in Braille, or in electronic format. Securing instructional materials in these specialized formats can be challenging for students – both in terms of ﬁnding them and in securing them in a timely manner (e.g., at the time during the course when all other students are using the materials). Copyright protections present challenges in providing specialized formats and must be addressed in order to improve access. Students who are print disabled may include students with learning disabilities, who may be able to process information more efﬁciently when it is offered orally rather than when it is offered in print. HEOA includes two new authorizations intended to address these access challenges. The Commission is authorized to conduct a comprehensive study and develop recommendations related to instructional materials for students with print disabilities in higher education. The Commission is to assess the barriers, systemic issues, and technical solutions available that may affect or improve the timely delivery and quality of accessible instructional materials for postsecondary students with print disabilities, as well as the effective use of such materials by faculty and staff. The Commission is to make recommendations related to the development of a comprehensive approach to improve the opportunities for postsecondary education for students with print disabilities to access instructional materials in specialized formats in a time frame comparable to the availability of standards instructional materials for students without disabilities.

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Recommendations should: Inform federal regulations and legislation. Support model demonstration programs to support improved access to postsecondary instructional materials for students with print disabilities (described later). Identify best practices for collecting, maintaining, processing, and disseminating materials in specialized formats to students with print disabilities at costs comparable to instructional materials for postsecondary non-disabled students. Improve the effective use of such materials by faculty and staff while complying with relevant copyright law. Modify the deﬁnitions of instructional materials, authorized entities and eligible students, as such terms are used in applicable federal law, for the purpose of improving services to students with disabilities. The following should be considered by the Commission in developing recommendations: How students with print disabilities may obtain accessible instructional materials in a time frame comparable to the availability of instructional materials for non-disabled students and to the maximum extent practicable, at costs comparable to the costs of such materials for nondisabled students. The feasibility and technical parameters of establishing standardized electronic ﬁle formats, such as the National Instructional Materials Accessibility Standards as deﬁned in IDEA, to be provided by publishers of instructional materials to producers of materials in specialized formats, institutions of higher education, and eligible students. The feasibility of establishing a national clearinghouse, repository, or ﬁlesharing network for electronic ﬁles in specialized formats and ﬁles used in producing instructional materials in specialized formats, and a list of possible entities qualiﬁed to administer such a clearinghouse, repository, or network. The feasibility of establishing market-based solutions involving collaborations among publishers of instructional materials, producers of materials in specialized formats, and institutions of higher education. Solutions utilizing universal design. Solutions for low-incidence, high-cost requests for instructional materials in specialized formats.

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Members of the Commission shall not be more than 19, should be appointed by the Secretary, and should include one representative from each of the following categories: The Ofﬁce of Postsecondary Education in the Department. The Ofﬁce of Special Education and Rehabilitative Services in the Department. The Ofﬁce for Civil Rights in the Department. The Library of Congress National Digital Information and Infrastructure Preservation Program Copyright Working Group. The Association of Higher Education and Disability. The Association of American Publishers. The Association of American University Presses. The National Council on Disability. Recording for the Blind and Dyslexic. National organizations representing individuals with visual impairments. National organizations representing individuals with learning disabilities. The Commission is required to submit a report to the Secretary and the authorizing committees detailing the ﬁndings and recommendations of the Commission no later than one year after the Commission’s ﬁrst meeting. The Commission is terminated 90 days after the report is submitted.

Model Demonstration Programs to Support Improved Access to Postsecondary Instructional Materials for Students with Print Disabilities (Higher Education Opportunity Act, Sections 773–775) The purpose of this new program is to support model demonstration programs in developing systems to improve the quality of postsecondary instructional materials in specialized formats and such materials’ timely delivery to postsecondary students with print disabilities. Eligible partnerships for the programs include an institution of higher education with expertise in meeting the needs of print disabilities and a public or private entity with demonstrated expertise in developing accessible instructional materials in specialized formats for postsecondary students with print disabilities and the technical development expertise needed to disseminate such materials including procedures to protect against copyright infringement.

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Required activities for the partnerships include supporting the development and implementation of the following: Processes and systems to help identify and verify the eligibility of postsecondary students with print disabilities in need of instructional materials in specialized formats. Procedures and systems to facilitate and simplify request methods for accessible instructional materials from students with print disabilities. Procedures and systems to coordinate among institutions of higher education, publishers of instructional materials and entities that produce materials in specialized formats to facilitate requests for such materials, responses to such requests, and the delivery of such materials. Delivery systems that will ensure the timely provision of instructional materials in specialized formats to eligible students, which may include electronic ﬁle distribution. Systems to reduce duplicative conversions and improve sharing of the same instructional materials in specialized formats for multiple eligible students at multiple institutions of higher education. Procedures to protect against copyright infringement with respect to the development, use, and distribution of instructional materials in specialized formats while maintaining accessibility for eligible students. Awareness, outreach, and training activities for faculty, staff, and students related to the acquisition and dissemination of instructional materials in specialized formats and instructional materials utilizing universal design. The partnership should also provide recommendations on how effective procedures and systems described earlier may be disseminated and implemented on a national basis. ‘‘Such sums’’ are authorized for this program.

STRENGTHENING THE PREPARATION OF TEACHERS OF STUDENTS WITH DISABILITIES The enactment of NCLB in 2001 focused a spotlight on the issue of teacher quality. With a federal deﬁnition of a ‘‘highly qualiﬁed teacher’’ and compelling research about the signiﬁcance of the effect of teacher quality on student learning, policymakers sought levers to increase the quality of

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teachers. As Congress moved its attention from NCLB to HEA, the opportunity to address pre-service preparation was paramount. NCLB generated two speciﬁc policy concerns in relation to preparing teachers for students with disabilities. The ﬁrst was ensuring that special education teachers have curricular content knowledge. The IDEA requires that students with disabilities receive access to the general education curriculum. This provision was included in the law in response to concerns that the curriculum offered to students with disabilities was watered down or unrelated to the curriculum for general education students. The signiﬁcance of this requirement became paramount with the implementation of NCLB. For the ﬁrst time students with disabilities were being assessed with the same assessments that were used for general education students. Their lack of exposure to the general education curriculum yielded low test scores and cries for reform in the preparation of special education teachers. In particular, the deﬁnition of a highly qualiﬁed special education teacher (which was enacted as a part of the 2004 amendments to IDEA, Section 602(10)) required acquisition of curricular knowledge in addition to special education certiﬁcation. If school districts were being held accountable for the achievement of students with disabilities in the general education curriculum, the teachers who were instructing them needed to be knowledgeable in that content, it was argued. The second policy concern relates to ensuring that general education teachers are effective in instructing students with disabilities. As a result of increased inclusion of students with disabilities in general education classrooms, general education teachers are increasingly expected to be proﬁcient in instructing students with disabilities. According to the Department of Education (U.S. Department of Education, 2006), 48% of students who are served under IDEA are taught in general education classrooms for 80% of the day. It is rare to ﬁnd a general education classroom in 2008 that does not include students with disabilities. Surveys of general education teachers document dissatisfaction with their skills and knowledge in instructing students with disabilities. The outcry of concern from general educators, principals, and superintendents in relation to accountability for the achievement of students with disabilities under NCLB has increased the pressure to ensure that general educators are skilled in instructing students with disabilities. In response to this concern Representative Ruben Hinojosa (D-TX), Chairman of the U.S. House of Representatives’ Subcommittee on Higher Education, Lifelong Learning and Competitiveness of the Committee on

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Education and Labor, requested a study by the General Accountability Ofﬁce. The questions that Representative Hinojosa requested the GAO to address are: 1. Which federal grant programs support the preparation of general education teachers to work with English language learners and students with disabilities? 2. To what extent do teacher preparation programs provide preparation for general education teachers to work with these two student subgroups? 3. How do selected states and school districts inﬂuence the preparation of general education teachers to work with these subgroups? 4. What challenges do teacher preparation programs, states, and school districts face in preparing these teachers and what assistance does education provide? (personal communication, ofﬁce of Representative Hinojosa, September 10, 2008) The results of this study should serve to inform ongoing policy and practice dimensions of efforts to improve preparation of teachers to effectively instruct diverse populations. The new HEOA includes numerous new provisions related to the preparation of teachers to education students with disabilities in the following sections of the law: Teacher Quality Partnership Grants, Accountability for Programs That Prepare Teachers, Teach to Reach Grants, Graduate Fellowships to Prepare Faculty in High Need Areas at Colleges of Education, New Loan Forgiveness Programs, TEACH Grants, and a Study on Teaching Students with Reading Disabilities.

Teacher Quality Partnership Grants (HEOA, Sections 201–204) The previous authorization allowed for three sub-grant programs under the previous Teacher Quality Enhancement Grant program (now called the Teacher Quality Partnership Grant program). These were State Grants, Partnership Grants, and Teacher Recruitment Grants. The new Teacher Quality Partnership Grant program provides for competitive grants to eligible partnerships to improve preparation at the undergraduate and graduate levels. Funds may also be used to prepare school leaders in rural areas, early childhood educators, and for a partnership with digital education content developers. The purposes of the grants are to (a) improve student achievement, (b) improve the quality of preparation of prospective teachers and enhance professional development for new teachers, (c) hold teacher preparation

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programs at institutions of higher education accountable for preparing highly qualiﬁed teachers, and (d) recruit highly qualiﬁed individuals, including minorities and individuals from other occupations, into the teaching force. Eligible Partnership While numerous entities may be included in an eligible partnership, the following are required:

A high-need local educational agency. A high-need school or consortium of high need schools. As applicable, a high-need early childhood education program. A partner institution of higher education. A school, department, or program of education within a partner institution of higher education. A school or department of arts and sciences within a partner institution of higher education. Grant funds may be used to carry out a program for the prebaccalaureate preparation of teachers, a teaching residency program (master’s degree level), a combination of the two, and leadership development programs. Matching requirements for the partnership grants are up from 25% to 50% to 100%. Funds are authorized for three years for this program, with $300 million authorized for Financial Year (FY) 2009 and ‘‘such sums’’ authorized for the remaining two years. Pre-Baccalaureate Preparation of Teachers Grants for these programs must prepare new or prospective teachers to be highly qualiﬁed; such teachers and, as applicable, early childhood educators, must be taught to understand empirically based practice and scientiﬁcally valid research related to teaching and learning and the applicability of such practice and research, including through effective use of technology, instructional techniques, and strategies consistent with the principles of UDL and through positive behavioral interventions and support strategies to improve student achievement. Programs must promote strong teaching skills and techniques for early childhood educators, as appropriate, to improve children’s cognitive, social, emotional, and physical development. Sustained and high-quality clinical preparation with the duration of at least one year must be offered. An induction program for new teachers, or in the case of early childhood educators mentoring and coaching, must be

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provided. Teacher recruitment mechanisms must be part of the grant as well as literacy training. Teacher Residency Programs Another possible use of these funds is to develop or enhance teacher residency programs. Teacher residency programs have gained considerable visibility and popularity with policymakers in that they are viewed as a promising practice for meeting the teacher shortage in high-need schools and school districts. Inspired by the teacher residency program in Chicago, the Academy for Urban School Leadership (AUSL), Senator Barack Obama (D-IL) introduced legislation in the Senate to authorize the development of more of these programs. The genesis of these provisions regarding teacher residency programs in HEOA is Senator Obama’s original bill. (S. 1574, Teaching Residency Act, Obama, 2007). The two best known such programs, the Boston Teacher Residency program and the AUSL program in Chicago, offer promising early results, with retention rates as high as 95% ﬁve years out (Barry et al., 2008). Studies are underway to examine the impact of residency-prepared teachers on student learning. A residency program is deﬁned in HEOA as a school-based preparation program for a prospective teacher with the following features: The candidate teaches alongside a mentor teacher, who is the teacher of record, for one year. The candidate receives concurrent instruction during the year from the partner institution; courses may be taught by local educational agency personnel or residency program faculty in the teaching of the content area in which the teacher will become certiﬁed. The candidate acquires effective teaching skills. Prior to completion of the program, the candidate earns a master’s degree, attains full state teacher certiﬁcation or licensure, and becomes highly qualiﬁed. Grants for residency programs are required to develop criteria for the selection of mentor teachers and to ensure that they are relieved of teaching duties to perform additional responsibilities required of them. Teaching residents are grouped in cohorts to facilitate professional collaboration. When candidates complete the program, they are to be supported for their ﬁrst two years of teaching with induction services. Candidates in residency programs must be supported with a one-year living stipend or salary. Graduates of residency programs must serve for no less than three years as full-time teachers in a high-need school in the

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high-need local education agency that is part of the partnership. Further, the graduate must teach in a high-need subject area. If the graduate does not complete the service obligation, he/she must repay the stipend or salary to the partnership with interest. Rural Leadership Development Programs Partnerships that receive grants to carry out either the pre-baccalaureate or residency programs may also undertake a leadership development program for rural areas. These initiatives must prepare individuals enrolled or preparing to enroll in school leadership programs for careers as superintendents, principals, early childhood education program directors, or other school leaders. These programs must include clinical components that are at least a year in duration as well as induction programs for new school leaders.

Accountability for Programs that Prepare Teachers HEOA continues and expands the requirements for institutions, states, and the Secretary of Education to collect data and issue reports on teacher quality. Several new provisions require data related to the effective preparation of teachers to instruct students with disabilities – both general and special education teachers. Institutions of higher education must issue annual report cards outlining the performance of both their traditional and alternate route preparation programs. These report cards must reﬂect whether or not the institution has met its self-determined teacher development goals and describe the activities undertaken to do so. In addition, for the students who have taken state licensing or certiﬁcation exams, the report must also provide data on (a) the percentage of students who have completed 100% of their non-clinical coursework and taken the assessment who pass; (b) the percentage of all students who pass such assessment; (c) the percentage of students who have taken such assessment who enrolled in and completed the traditional teacher preparation program or alternative routes to state certiﬁcation or licensure; (d) the average scaled score for all students who took such assessment; (e) a comparison of the program’s pass rates with the average pass rates for programs in the State; and (f ) a comparison of the program’s average scaled scores with the average scaled scores for other programs in the state. The report cards must include a description of activities, including activities consistent with principles of universal design, that prepare teachers

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to effectively integrate technology into their instruction; and activities that prepare general education and special education teachers to teach students with disabilities effectively. States, in turn, must issue annual report cards on the quality of teacher preparation in their individual state for both traditional teacher preparation programs and for alternate route programs – both those within institutions of higher education and those outside. Speciﬁcally, these reports must include: A description of the reliability and validity of the teacher certiﬁcation and licensure assessments and any other certiﬁcation requirements used by the state. The percentage of students at each institution of higher education in the state who have completed 100% of their non-clinical coursework and taken the assessment and passed it; the percentage of all such students at all institutions and entities who have taken the assessments who pass the assessments; the percentage of students who have taken the assessment who enrolled in and completed a teacher preparation program and the average scaled score of individuals participating in such a program or who have completed such a program. A description of alternate routes to teacher certiﬁcation as well as pass rates and average scaled scores for individuals in each. A description of the state’s criteria for assessing the performance of teacher preparation programs. The number of teachers prepared as a whole and by area of certiﬁcation, academic major, and subject. A description of the extent to which preparation programs are addressing shortages of highly qualiﬁed teachers. The extent to which teacher preparation programs prepare teachers, including general education and special education teachers, to teach students with disabilities effectively including training related to participation as a member of an IEP team. Finally, the Secretary of Education must issue an annual report on teacher quality that includes all of the information provided by the states. The report card must compare states’ efforts to improve the teaching force; compare partnerships’ efforts to improve the quality of the teaching force; and report the national mean and median scaled scores and pass rate on any standardized test that is used in more than one state for teacher certiﬁcation. The Secretary is prohibited from creating a national list or ranking of states, institutions, or schools using the scaled scores provided.

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The HEOA establishes new teacher development requirements. These provisions are based on a recommendation made by the Commission on NCLB, a bipartisan Commission which produced numerous recommendations for policymakers intended to improve NCLB (The Commission on NCLB, 2007). The new provision requires each IHE with a teacher preparation program to set annual quantiﬁable goals for increasing the number of prospective teachers trained in teacher shortage areas designated by the Secretary or by the State, including mathematics, science, special education, and instruction of limited-English proﬁcient students. In addition, each IHE with a teacher preparation program must provide the following assurances to the Secretary of Education: That training to prospective teachers responds to the identiﬁed needs of the local educational agencies or states where the institution’s graduates are likely to teach. That training provided to prospective teachers is closely linked with the needs of schools and instructional decisions new teachers face in the classroom. That prospective special education teachers receive coursework in core academic subjects and training in providing instruction in core academic subjects. That general education teachers receive training in providing instructions to diverse populations, including children with disabilities, limitedEnglish proﬁcient students, and children from low-income families. That prospective teachers receive training in how to effectively teach in urban and rural schools, as applicable.

Release of Data to Teacher Preparation Programs This new provision, requested by the American Association of Colleges of Teacher Education (AACTE), requires states to provide data to teacher preparation programs upon their request when the data may enable teacher preparation programs to evaluate the effectiveness of the program’s graduates or the program itself. Such information is to include an identiﬁcation of speciﬁc individuals who graduated from the teacher preparation program and may include K-12 academic achievement and demographic data about students who have been taught by graduates of the program as well as teacher effectiveness evaluations for teachers who graduated from the program. Many schools and colleges of education are eager to follow their graduates and assess their performance but experience difﬁculty

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securing the data needed to make such assessments. This provision is attended to facilitate access to such data. Teach to Reach Grants (HEOA, Section 251) Initiated by Representative John Yarmuth (D-KY), this new program authorizes grants to prepare general education teachers to effectively educate students with disabilities. Grants are to be awarded to partnerships that include: One or more departments or programs at an institution that prepare general education teachers. A department or program of special education at an institution of higher education. A department or program at an institution that provides degrees in core academic subject areas A high need local educational agency. The following activities are required by a partnership: Develop or strengthen an undergraduate, post-baccalaureate, or master’s teacher preparation program by integrating special education strategies into the general education curriculum and academic content. Provide teacher candidates with skills related to response to intervention, positive behavioral interventions and supports, differentiated instruction, data-driven instruction, UDL, determining and utilizing accommodations for instruction and assessments, collaborating with special educators, related services providers, and parents, including participation in IEP development and implementation and appropriate use of technology and assistive technology. Provide extensive clinical experience with mentoring and induction that continues through the ﬁrst two years of full-time teaching. The program is authorized for ‘‘such sums’’ for six years. Graduate Fellowships to Prepare Faculty in High-Need Areas at Colleges of Education (HEOA, Section 258) This new program in HEOA was championed by Representative Ruben Hinojosa (D-TX). It is intended to address the shortage of higher education faculty in areas of teacher shortages. The shortage of special education faculty in institutions of higher learning has been well documented (Smith, Pion, Tyler, Sindelar, & Rosenberg, 2001) and clearly linked to the shortage of special education teachers.

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This new program authorizes grants to institutions to provide graduate fellowships to individuals who are preparing for the professoriate in order to prepare highly qualiﬁed elementary school and secondary school mathematics and science teachers, special education teachers, and teachers for limited-English proﬁcient students. The fellowships are stipends to be provided at the same level as that for fellowships granted by the National Science Foundation. Individuals who receive these fellowships must be teacher educators at IHEs one year for every year in which they have received a fellowship. If individuals do not comply with this service obligation, the fellowship amount they received will be converted to a direct loan and must be repaid with interest. New Loan Forgiveness Programs (HEOA, Section 428K) HEOA adds 17 new categories of areas of national need that are eligible for loan forgiveness of up to $2,000 per year for a ﬁve-year period for a total of $10,000. Many of these categories are relevant to the education of students with disabilities and are intended to incentivize the retention of these professionals in their respective ﬁelds. The following are some of the individuals eligible for this loan forgiveness program: early childhood educators, nurses, speech-language pathologists and audiologists, school counselors, public-sector employees, nutrition professionals, mental health professionals, physical therapists, superintendents, principals and other administrators, and occupational therapists. The loan forgiveness is dependent upon the availability of appropriations. TEACH Grants Originally authorized in 2007 in the College Cost Reduction and Access Act, the Teacher Education Assistance for College and Higher Education (TEACH) Grant Program provides scholarships for students in higher education studying to become teachers in high-need ﬁelds. Up to $4,000 per year for a total of $16,000 is available for undergraduate students and up to $8,000 ($4,000 per year) is available for students pursuing master’s degrees. Those accepting grants must complete a four-year service obligation in a high-need ﬁeld in a low-income school within eight years following completion of their preparation program. If the service obligation is not completed, funds received from TEACH grants will be converted into an unsubsidized student loan and must be repaid with interest. High-need ﬁelds include mathematics, science, foreign languages, bilingual education, special

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education, reading specialist, and any other ﬁeld documented as high need by the federal government or state or local education agencies. Funds available for TEACH grants are ‘‘mandatory spending,’’ which means the funds are not subject to annual Congressional appropriations processes, and thus are unlimited in the sense that all students and programs that are eligible would receive funding. This remarkable investment by the Congress in teacher preparation is intended to address the signiﬁcant teacher shortages in low-income schools, including special education. As of September 2008, the ﬁrst semester of availability of TEACH grants, over 400 colleges and universities had signed up to participate (U.S. Department of Education website). HEOA amended the TEACH grants to allow students who began their preparation in an area designated by the state as a ‘‘shortage area’’ that subsequently is not a ‘‘shortage area’’ to complete their service obligation in that area nonetheless. The amendments require a program report on the status of the implementation of the TEACH grants. Study on Teaching Students with Reading Disabilities (HEOA, Section 1116) The Secretary of Education is directed to fund the Center for Education of the National Academies to study the quality of teacher preparation programs to determine if teachers are adequately prepared to meet the needs of students with reading and language processing disabilities, including dyslexia, and to determine the extent to which teacher education programs are based on the essential components for reading instruction and scientiﬁcally valid research.

CONCLUSIONS With the reauthorization of HEOA, the Congress has identiﬁed higher education as a new frontier for students with disabilities. The promise of higher education for students with disabilities is signiﬁcant as greater education is generally linked to increased employment and decreased poverty. But the challenges remain signiﬁcant, not the least of which is changing the culture of higher education. Beilke (1999) captured the dilemma like this: Similar to debates about afﬁrmative action, the arguments over the participation of students with disabilities in higher education represent a fundamental schism between

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those who believe that, in a democratic society, all citizens deserve the opportunity to obtain a college degree and those who believe that hard work and merit should determine who reaps the beneﬁt of postsecondary education. Until faculty can be assured that opportunity does not come at the expense of academic integrity, it is likely that students with disabilities will continue to encounter chilly classrooms in higher education. (p. 5)

While Congress has set forward a promise for increased inclusion of students with disabilities in higher education with the passage of the HEOA, the realization of the promise will depend on the advocacy of the disability community and its allies. While the disability community has never held increased access to higher education as a top priority,8 this may be changing as the expectations of students with disabilities and their families who leave the K-12 system increase. The disability community, primarily through the involvement of the Consortium for Citizens with Disabilities’ Education Task Force (see www.c-c-d.org), was active and vocal in advocating for changes in the Higher Education Act. This is the ﬁrst reauthorization of the Higher Education Act where that was the case. Led by organizations like the Higher Education Consortium for Special Education, the National Council on Learning Disabilities, the National Down Syndrome Society, the Association for University Centers on Disabilities, the Teacher Education Division of the Council for Exceptional Children, the Consortium for Citizens with Disabilities (CCD) was in regular communication with Congressional ofﬁces as the legislation was developed and considered. Two key areas where advocacy is critical are in securing appropriations to fund the many new programs and a new investment in capacity of the U.S. Department of Education. In its Transition Document to the Obama and McCain campaigns for President, CCD Education Task Force (2008) recommended funding the new programs in the Higher Education Act and investing more in the preparation of teachers for students with disabilities. As there are over 50 newly authorized programs in the HEOA, competition for funds will be intense and a concerted effort will be required. Yet, there are many champions for students with disabilities in the Congress and their leadership will make a signiﬁcant difference. For example, Senator Tom Harkin (D-IA), a long time champion of the disability community, chairs the Appropriations Subcommittee on Labor/HHS/Education and Related Agencies in the U.S. Senate, where the funding could be made available. Congressman George Miller (D-CA), Chairman of the Committee on Education and Labor, who crafted many of the new provisions in the bill, is also a champion for students with disabilities and his advocacy

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could have a signiﬁcant impact on funding. The ﬁrst opportunity for funding is likely to be the FY 2010 appropriations bill, as decisions about new funding in the FY 2009 appropriations bill are well underway and unlikely to be revisited. Activity for the FY 2010 appropriations bill will begin ofﬁcially in February 2009 when the President releases his budget proposal. The HEOA envisions a new leadership role for the U.S. Department of Education in relation to ensuring access for students with disabilities to higher education and preparing teachers to effectively instruct students with disabilities. All the programs described in this chapter are administered by the Department of Education’s Ofﬁce of Postsecondary Education (OPE). Until this time, OPE has administered only the one small discretionary program targeted to facilitate access to higher education for students with disabilities – demonstration projects to ensure students with disabilities receive a higher quality education. The OPE will need to expand its vision, capacity, and expertise in disability in order to implement the multiple new provisions effectively. With the enactment of HEOA, policymakers have come one step closer to embracing students with disabilities as one of many subgroups of Americans who are underrepresented in higher education and for whom the federal government must play a unique role in enhancing access. Indeed, federal policy has taken one more step forward in meeting the nation’s goals for people with disabilities as articulated by the Americans with Disabilities Act (1990): equality of opportunity, full participation, independent living, and economic self-sufﬁciency.

NOTES 1. The term ‘‘universal design’’ means a concept or philosophy for designing and delivering products and services that are usable by people with the widest possible range of functional capabilities, which include products and services that are directly accessible (without requiring assistive technologies) and products and services that are interoperable with assistive technologies (Assistive Technology Act, 29 USC 3002). 2. Students with disabilities who are eligible for admissions to higher education programs are eligible for federal ﬁnancial aid, just as any other students. However, students must be enrolled at least half-time and this requirement is sometimes a barrier for a student whose disability prevents them from a half-time level of enrollment.

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3. Pell Grants are grants for low-income students, usually undergraduate students. For 2008–2009, the maximum annual award is $4,731. The maximum amount can change each year depending on federal funding. 4. Federal Supplemental Educational Opportunity Grants are administered by campuses. They are for undergraduates with exceptional ﬁnancial need. The neediest Pell Grant recipients will be the ﬁrst to receive these funds. Between $1000 and $4000 per year may be awarded. Not all schools participate in the program. 5. Federal Work-Study provides part-time jobs for undergraduate and graduate students with ﬁnancial need. 6. 153 CONG. REC. S. 8291 (September 11, 2008); 153 CONG. REC. H. 8291 (September 17, 2008). 7. Despite requests for such a report from Appropriations Committees, none has been forthcoming to date. 8. This may be explained by the multiple areas of policy need in areas which are critical to the very survival of people with disabilities, such as health insurance reform, living in the community rather than in institutions, income maintenance which supports independence rather than dependence, and access to affordable accessible housing. Indeed, access to higher education may seem like a luxury to those who do not have health insurance which may result in a threat to their ability to live at all (look at NICL website).

REFERENCES Americans with Disabilities Act. (1990). P. L. 101-336. Americans with Disabilities Amendments Act of 2008, P.L. 110-325. Association of Higher Education and Disability (AHEAD). (2008). Assessment of campus climate to enhance student success (ACCESS). Available at www.ahead.org. Retrieved on November 18. Barry, B., Montgomery, D., Curtis, C., Hernandez, M., Wurtzel, J., & Snyder, J. (2008). Creating and sustaining urban teacher residencies: A new way to recruit, prepare, and retain effective teachers in high-needs districts. Washington, DC: The Aspen Institute and the Center for Teaching Quality. Beilke, J. (1999). The chilly climate for students with disabilities in higher education. College Student Journal, 33(3), 364–371. Blackorby, J., & Wagner, M. (1996). Longitudinal postschool outcomes of youth with disabilities: Findings from the National Longitudinal Transition Study. Exceptional Children, 62, 399–414. Consortium for Citizens with Disabilities (CCD), Education Task Force. (2008). Transition document. Washington, DC: Consortium for Citizens with Disabilities, Education Task Force. Getzel, L., Stodden, R. A., & Briel, L. (2001). Pursuing postsecondary education opportunities for individuals with disabilities. In: P. Wehman (Ed.), Life beyond the classroom: Transition strategies for young people with disabilities (3rd ed.). Baltimore: Brookes.

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Greenbaum, B., Graham, S., & Scales, W. (1995). Adults with learning disabilities; educational and social experiences during college. Exceptional Children, 61, 460–472. Hart, D., Gilmore, D., & Zafft, C. (2000). The current status of postsecondary education services, individuals with disabilities and the vocational rehabilitation system. Boston: Institute for Community Inclusion. Hart, D., Grigal, M., Sax, C., Martinez, D., & Will, M. (2006). Institute for Community Inclusion, University of Massachusetts, Boston, Postsecondary education options for students with intellectual disabilities. Research to Practice, 45, 1–4. Higher Education Act Amendments of 1998, P.L. 105-244. Individuals with Disabilities Education Act. (2004). P.L. 108-446. Katz, J. (1998). Learning disabilities and true handicaps. Chronicle of Higher Education (April 17), p. B10. Lewin, T. (1997). Fictitious learning-disabled student is at center of lawsuit against college. New York Times, Health Section, April 8. Miller, G. (2008). Letter to Gene Dodaro, Acting Comptroller General, U.S. Government Accountability Ofﬁce, April, Washington, DC. National Center for Education Statistics. (1999). Students with disabilities in postsecondary education: A proﬁle of preparation, participation and outcomes. NCES 1999-187. Washington, DC: U.S. Department of Education. National Council on Disability. (2007). Empowerment for Americans with disabilities: Breaking barriers to careers and full employment. Washington, DC: National Council on Disability. National Council on Disability. (2008). NCD’s national disability policy. A progress report. Washington, DC: National Council on Disability. No Child Left Behind. (2001). P. L. 107-110. Obama, B. (2007). Teaching Residency Act, S. 1574. Washington, DC: U.S. Senate. Smith, D., Pion, G., Tyler, N. C., Sindelar, P., & Rosenberg, M. (2001). The study of special education leadership personnel with particular attention to the professoriate (Project Number: H920T970006-00A), April. Washington, DC: U.S. Department of Education, Ofﬁce of Special Education and Rehabilitation Service. Stapleton, D. C., O’Day, B., Livermore, G. A., & Imparato, A. J. (2005). Dismantling the poverty trap: Disability policy for the 21st century. Policy brief. Paper posted at http:// digitalcommons.ilr.cornell.edu/edicollect/124 The Commission on NCLB. (2007). Beyond NCLB: Fulﬁlling the promise to our nation’s children. Washington, DC: The Aspen Institute. Thinkcollege.net. (2008). References related to postsecondary education. Available at http:// www.thinkcollege.net/resources/index.php?page ¼ references. Retrieved on November 18, 2008. U.S. Department of Education. (2006). 26th Annual report to Congress on the implementation of the individuals with disabilities act of 2004. Washington, DC: U.S. Department of Education. U.S. Department of Education, Ofﬁce of Special Education Programs, Data Analysis System (DANS). (2007). OMB #1820-0521: Children with Disabilities Exiting Special Education, 2005–2006. Data updated as of July 15.

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U.S. Government Accountability Ofﬁce. (2003). Special education: Federal actions can assist states in improving postsecondary outcomes for youth. Washington, DC: U.S. Government Accountability Ofﬁce. U.S. House of Representatives. (2008). Report 110-730 Part I, Committee on Education and Labor. Washington, DC: U.S. House of Representatives. Vocational Rehabilitation Act, Section 504. P. L. 93-510. Wolanin, T., & Steele, P. (2004). Higher education opportunities for students with disabilities. Washington, DC: The Institute for Higher Education Policy.

INTERVENTION WITH STUDENTS WITH ADHD: ANALYSIS OF THE EFFECTS OF A MULTI-COMPONENT AND MULTI-CONTEXTUALIZED PROGRAM ON ACADEMIC AND SOCIO-EMOTIONAL ADJUSTMENT Ana Miranda, Marı´ a Jesu´s Presentacio´n, Rosa Garcı´ a and Rebeca Siegenthaler ABSTRACT Recent research suggests that multi-component and contextualized interventions are a good option for the treatment of children with ADHD. The primary goal of the present investigation was to examine the efﬁcacy of a multi-component psychosocial intervention involving children, with ADHD, their parents and their teachers. Forty-two children with ADHD were distributed in two groups: one with 27 children who received the Policy and Practice Advances in Learning and Behavioral Disabilities, Volume 22, 227–263 Copyright r 2009 by Emerald Group Publishing Limited All rights of reproduction in any form reserved ISSN: 0735-004X/doi:10.1108/S0735-004X(2009)0000022010

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intervention (experimental group) and the other with 15 children who received no intervention (control group). The effects of the intervention program were evaluated in three basic developmental areas: school learning, emotional adjustment and social adjustment. Once the intervention was over, the learning problems of children with ADHD who participated in the intervention were signiﬁcantly reduced, based on the observations of both parents and teachers. Furthermore, social adjustment of the treated group improved signiﬁcantly at the posttest evaluation. In contrast, in the group of children with ADHD who did not receive treatment, the learning and social problems remained stable.

The past few years have witnessed a considerable increase in the number of studies designed to clarify the efﬁcacy of the different intervention procedures available for treating children with ADHD. In general, the results conﬁrm that pharmacological treatment continues to be the most widely used, although it also has important limitations. Pharmacological intervention has been shown to be effective in only about 80% of the children and young people with ADHD. Furthermore, side effects can appear, including sleep, appetite and growth problems (Faraone, Biederman, Spencer, & Aleardi, 2006; Swanson et al., 2008a, 2008b). In addition, although its effectiveness with the essential symptoms of the disorder is signiﬁcant, various studies show that the same thing does not occur with school performance (Raggi & Chronis, 2006), family dysfunction (Johnston & Mash, 2001) or social relationships with peers (Hoza et al., 2005). As an alternative or complement to the pharmacological interventions, psychosocial interventions constitute useful treatment options for managing the main symptoms of the disorder and for dealing with the many associated problems children with ADHD present. Traditionally, together with the direct intervention with the child, programs for parents have been the most widely used intervention modalities. Nevertheless, despite the crucial mediating role played by the teachers in the optimal development of children with ADHD, very few teachers have received preparation that would enable them to adequately respond to this challenge. Ghanizadeh, Bahredar, and Moeini (2006) have reviewed the literature on ADHD interventions focusing on the role of the teachers, and they conclude that training in this area should be a required subject in university teacher training programs. Various reviews have been carried out in the past few years with the purpose of determining the most effective components of psychosocial

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interventions (Antshel & Barkley, 2008; Barkley, 2002; Brown, 2000; Chronis, Jones, & Raggi, 2006; Chronis, Chacko, Fabiano, Wymbs, & Pelham, 2004; DuPaul & Weyandt, 2006; Miranda, Jarque, & Ta´rrega, 2006). In general, the majority of the studies carried out coincide in the validated empirical efﬁcacy of behavior training for parents and teachers. Parent training in behavior modiﬁcation techniques improves not only the child’s behavior at home but also the parent/child relationships, and even the marital problems that can arise. In the school setting, programs for teachers make it possible to increase their knowledge about the disorder and take the necessary steps to improve their students’ behavior in the classroom. Another intervention approach is cognitive-behavior modiﬁcation, which is based on teaching self-regulation strategies. Promise has also been shown by social skills training with generalization components, intensive summer training programs and academic interventions. Next, a review is presented of the empirical evidence supporting each of these investigation procedures.

BEHAVIOR MODIFICATION TECHNIQUES Behavior modiﬁcation combines a set of strategies that use reward and punishment to establish or increase positive behaviors and reduce or eliminate inappropriate behaviors. These techniques are easily applied and widely accepted among parents and teachers, as the study by Stormont and Stebbins (2001) shows. These authors analyzed the preferences of Early Childhood Education teachers about 43 speciﬁc behavioral intervention modalities for students with ADHD. The teachers surveyed rated the majority of the techniques from quite important to extremely important. They seem to prefer the use of strategies to increase positive behaviors, although procedures that include only positive reinforcement are not usually effective in managing disturbing behaviors, especially in the school context. The implementation of the response cost technique in the classroom has been shown to be effective on many occasions for signiﬁcantly reducing the main ADHD symptoms and increasing academic productivity (Carlson & Mann, 2000; DuPaul, Guevremont, & Barkley, 1992), as well as reducing disruptive behaviors (Gordon, Thomason, Cooper, & Ivers, 1991). Also in the context of the classroom, the OuLeary team (Pﬁffner & OuLeary, 1987) described the necessary characteristics for producing more effective reprimands – the system most widely used by teachers in classrooms – such

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as making prior eye contact and making the reprimands speciﬁc, slow, deliberate, clear and, ideally, private. For parents of children with ADHD, various programs have been developed, such as the Community Parent Education Program (Cunningham, Cunningham, & Martorelli, 1997), the programs included in the Incredible Years packet (Webster-Stratton, 1992), the Triple P-Positive Parent Program (Sanders, Markie-Dadds, Tully, & Bor, 2000) for children with behavior problems or the program developed by Barkley (1987, 1997) in which the parents learn a broad spectrum of techniques for managing the behavior. There are fewer behavioral programs developed speciﬁcally for their implementation in the school context. One that stands out is the ADHD Classroom Kit (Anhalt, McNeil, & Bahl, 1998), which is designed to improve the behaviors of ADHD children in academic, behavioral and social aspects within the classroom by using an adaptation of the strategy of actively teaching the class norms (DuPaul & Stoner, 2003). This program is based on the teacher’s management of consequences of the behavior, but it adds the novelty of introducing the classmates as essential ﬁgures in the intervention. Within the classroom, the work is carried out in groups with the goal of respecting the class rules. The leader of the group, who varies from one day to another, is responsible for motivating the members and reminding them that they must follow the rules. Depending on their behavior, the groups obtain happy or sad faces. One aspect researchers agree on is the need to establish close relationships of collaboration between parents and teachers in achieving behavioral improvements. With this objective in mind, the majority of the intervention programs use the home–school card, whose efﬁcacy has been shown in many studies (Atkinson & Forehand, 1979; Chronis et al., 2001; Fabiano & Pelham, 2003). Speciﬁcally, at ﬁrst the teachers establish the target behaviors, both academic and behavioral. They provide daily quantitative ratings (e.g., between 1 ‘‘did not perform the behavior’’ and 5 ‘‘performed it completely’’) for each target behavior established, which already provides an initial reinforcement in the classroom. Later, the teachers’ ratings are transformed into points in the family context and exchanged for reinforcements provided by the parents. The parent training programs do not only produce changes in the children’s behavior; in some cases, they also improve important aspects such as general family functioning, reductions in parental stress and increases in the parents’ self-esteem (Chronis et al., 2004). Nevertheless, the behavioral programs have also received criticism. The most frequent ones refer to their short duration and the fact that they produce more improvements in the

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behavior problems than in the speciﬁc ADHD symptoms (Anastopoulus, Shelton, DuPaul, & Guevremont, 1993; Antshel & Barkley, 2008). Furthermore, there is very little evidence that the improvements achieved are maintained once the treatment has been withdrawn or that there is a generalization of the behavior learned to other school situations where the intervention procedures are not operative. This important limitation of the behavioral treatments is explained by Barkley (1997) by means of the concept of ‘‘environmental interventions,’’ ways of artiﬁcially reorganizing the environment in order to achieve successful performances.

COGNITIVE-BEHAVIOR MODIFICATION Cognitive-behavior modiﬁcation includes a series of techniques whose purpose is to provide subjects with the necessary tools to direct their own behavior (Reid, Trout, & Schartz, 2005). The intention is to maintain and generalize the effects over time and in different contexts, by teaching selfcontrol strategies based on the subject’s ability to observe his/her own behavior, direct it and evaluate it according to the behavior norms. In this process, private language plays an essential role. One of the cognitive-behavioral techniques that has shown the greatest efﬁcacy with ADHD children uses self-instruction (self-talk) to foster sequential thinking, facilitate the comprehension of situations, spontaneously generate strategies and mediators and use these mediators in guiding and controlling their behavior (Meichenbaum & Goodman, 1971). There are also programs such as ‘‘Thinking aloud’’ (Camp & Bash, 1980) or ‘‘Stop and think’’ (Kendall, Padever, & Zupan, 1980), in which the self-instructional technique is combined with problem-solving and contingency management. They include various personal and impersonal activities, which the children have to resolve by applying the self-instructional technique. For interpersonal situations, the problem-solving strategies help to analyze feelings and their causes, thus deﬁning the problem; look for different solutions and analyze the consequences of each; select the most appropriate solutions; put a chosen plan into practice and evaluate the results. Miranda and Presentacio´n (2000) analyzed the effects of a program combining self-regulation and anger management in two groups of children with ADHD (aggressive and non-aggressive). For this purpose, they compared the effects of three intervention modalities: (1) intervention in self-regulation; (2) intervention in self-regulation and anger management; and (3) control without intervention. The results showed signiﬁcant

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improvements in the two treated groups in the basic characteristics of the disorder and the associated symptomatology (social skills, aggressiveness and learning problems), in the opinions of both the parents and the teachers. Moreover, the improvements were especially important for the subgroup of non-aggressive hyperactive children. However, the subgroup of aggressive ADHD children improved signiﬁcantly more, according to the parents, in the combined treatment condition. As Boo and Prins (2006) point out, the importance of this study lies in the fact that speciﬁc components focusing on the particular characteristics of the children are included in the intervention programs, in this case the externalizing symptomatology that often accompanies ADHD. Self-evaluation is another cognitive-behavioral technique used by children with ADHD whose effectiveness has repeatedly been shown (Ardoin & Martens, 2004; Hinshaw & Melnick, 1992; Shapiro, DuPaul, & BradleyKlug, 1998). The intention is to adjust the self-ratings of children with ADHD about their behavior and/or task performance to standard norms. In the application developed by DuPaul and Hoff (1998), the teachers begin by training ADHD students in the use of self-evaluation following three steps (the teacher’s evaluation, training in reaching an agreement and progressive withdrawal). After using this program, the authors observed a decrease in disruptive behavior and an increase in attention paid to tasks and performance on school activities. Although they state that contingency management represents a good alternative, the authors point out that these improvements cannot be attributed to the self-evaluation alone, as they could also be because a token economy program had previously been applied but extinguished when the self-evaluation began. We coincide with Miranda, Jarque, and Ta´rraga (2006) in that, although there is certainly a lack of studies that analyze the differential efﬁcacy of the two techniques, the results are promising at the least, as the students maintained the changes in the absence of feedback from the teacher. Although, in theory, the cognitive-behavioral techniques are ideal procedures for treating children with ADHD, they have been questioned in some studies (Abikoff, 1991; Bloomquist, August, & Ostrander, 1991; Ialongo et al., 1993; Robinson, Smith, Miller, & Brownell, 1999) and meta-analyses (Baer & Nietzel, 1991) that were not able to conﬁrm their beneﬁcial effects. However, other studies have obtained signiﬁcant improvements after their implementation (Branswell, 1993; DuPaul & Weyandt, 2006; Hinshaw & Melnick, 1992; Miranda & Presentacio´n, 2000; Miranda, Presentacio´n, & Soriano, 2002b). For Pelham, Wheeler, and Chronis (1998), the cognitivebehavioral techniques are important for maintaining and generalizing

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appropriate behaviors, as long as they are combined with an intensive behavioral intervention, although no studies supporting this premise have been carried out. Some studies indicate that combining self-control and self-reinforcement strategies is effective in improving various behaviors such as attention paid to the task, academic precision and interactions with parents (Barkley, Copeland, & Sivage, 1980). In this sense, Pizarro and Valenzuela (2005) analyze the effectiveness of a cognitive-behavioral program (adapted from Branswell & Bloomquist, 1991) with a group of school-age Chilean children, comparing it to a control group (with standard pharmacological treatment). The results show that the multi-component program was not demonstrated to be superior in the management of the main ADHD symptoms, but it was for the associated symptoms (depression, self-esteem, relationship with parents and attitude toward teachers, among others).

ACADEMIC INTERVENTIONS The purpose of academic interventions for children with ADHD is to reduce problematic behaviors and increase learning by means of curricular modiﬁcations in the normal dynamics of the class. They include a whole series of instructional procedures and environmental and organizational accommodations. One of the most frequently recommended steps for teachers in classrooms with ADHD children is to manipulate the events that precede the behaviors in an attempt to prevent problems before they occur. Some of the antecedent manipulation strategies that have received the greatest experimental support are choosing the task, reducing its duration (or dividing it into parts) and actively teaching the class rules (DuPaul & Weyandt, 2006). The study by Powell and Nelson (1997), for example, showed that allowing the students to choose among three different tasks that could form a part of the academic curriculum reduces inappropriate behaviors of disobedience, getting out of their seats, bothering others and not working. Ridgway, Northup, Pellegrin, LaRue, and Hightsoe (2003) concluded that providing rest periods during the performance of an activity signiﬁcantly reduces ‘‘off-task’’ behaviors such as inappropriate talking, disobedience or playing with objects. The teachers can also modify the instructions provided to students with ADHD, for example, by using direct instruction or individualized curricular adaptations for acquiring skills in speciﬁc learning areas such as mathematics (Skinner, Johnson, Larkin, Lessley, & Glowacki, 1995). Thus,

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the children are more likely to pay attention and complete tasks when they contain the basic motivational stimuli, and the secondary stimuli are minimized (e.g., the margins) (Zentall, 1989). Finally, the importance of the role of the classmates in the intervention programs has also been pointed out in different studies. Among the most interesting programs, for students both with and without school-related problems, two programs stand out: the aforementioned ADHD Classroom Kit (Anhalt et al., 1998), which uses cooperative learning in groups to perform activities, and Classwide Peer Tutoring (CWPT) (Greenwood, Delquadri, & Carta, 1988). Plumer and Stoner (2005) have applied the latter program, showing its efﬁcacy in improving academic performance and signiﬁcantly reducing the disruptive behaviors of children with ADHD. In these cooperative programs, both teachers and students demonstrate a high level of satisfaction with these intervention procedures. Environmental and curricular modiﬁcations, together with behavioral procedures and training in self-regulation strategies, constitute the main components of the intervention program for ADHD children designed by Miranda et al. (1999). On the basis of the idea that the classroom is the ideal context for fostering the children’s self-regulation, the program is directed toward classroom teachers who have children with ADHD in their classes. Designed as a theoretical/practical training course for teachers, the program includes an initial session to make contact with the participants and seven training sessions in the following thematic areas: (1) general knowledge about ADHD; (2) training in behavior modiﬁcation techniques (praise, reward, contingency contract and token economy program, extinction, response cost, time-out); (3) self-instructions; (4) instructional, spatial and organizational adaptations in the classroom (physical set-up of the classroom, presentation of explanations, activity planning, doing work and exams and organization); and (5) reinforced self-evaluation technique (adapted by the authors for the classroom context in three phases: establishment of class norms; training in self-evaluation skills and introduction of the token economy system). As in the rest of the program’s components, it includes an initial period of application to the entire group leading to a second moment of individualized application with the ADHD student or students. In order to investigate the efﬁcacy of this teacher training program, a study was carried out in which 50 children with ADHD participated during one academic school year (Miranda et al., 2002b). According to the results, the children with ADHD whose teachers took the training course showed, after the intervention and in the follow-up evaluation three months later, signiﬁcant improvements on both the primary symptoms and the

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behavioral difﬁculties usually associated with the disorder. The parents detected improvements in the basic symptomology of the disorder and in behavioral problems and anxiety. The teachers reported improvements in the hyperactive and impulsive behaviors and in self-control, as well as reductions in the learning problems. The academic grades also improved, as well as the behavioral observations in class. An improvement was also observed in the teachers’ beliefs, attributions and knowledge about strategies for responding to children with ADHD. Complementary analyses of the effects of the study found that the majority of the children had improved clinically and/or had recovered after the treatment in the opinions of both the parents and the teachers (Miranda, Garcı´ a, & Presentacio´n, 2002a).

SOCIAL SKILLS TRAINING Given the difﬁculties children with ADHD often have in their social lives, social skills training has become a widely accepted form of intervention in clinical practice. This training is based on the teaching and practice, through role-playing, of a broad range of skills such as conversation skills (greetings, introducing oneself, interrupting correctly, etc.), friendship (making friends, giving compliments, initiating and joining group activities, etc.) and/or resolving difﬁcult situations (accepting ‘‘no’’ and criticism, reacting to jokes, apologizing, etc.). As a prototype, we will highlight the ADHD Classroom Kit, which teaches social skills in a natural context and provides children with the opportunity to practice them every day in cooperative learning activities carried out in class (Anhalt et al., 1998). Another approach is that of Hoza, Mrug, Pelham, Greiner, and Gnagy (2003), where the children are put into pairs according to their sociometric, sports or academic preferences, which fosters cooperation and develops friendships. For some authors such as Antshel and Barkley (2008), children with ADHD have problems relating to their peers, but they do not have deﬁcits in social skills, so that this type of therapy is not useful for them. They consider that the problem is one of performance and not knowledge. For DuPaul and Weyandt (2006), the studies that have done training in social skills have not achieved the generalization of the results to the ‘‘real world.’’ Despite being effective during the social skills, problem-solving and anger management training sessions, the improvements are rarely maintained once the intervention is over (DuPaul & Eckert, 1994; Gresham, 2002). However, many other studies support the efﬁcacy of social skills training, to the extent

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that it has been selected as a basic component of the most important ADHD intervention packets developed in the past few years (see review by Boo & Prins, 2006).

MULTI-CONTEXTUAL AND MULTIMODAL INTERVENTIONS Although all the authors defend the need for multi-contextual interventions in ADHD, in reality very few studies have included interventions for both parents and teachers. In an attempt to determine the contributions of an intervention that includes both the home and the school, Barkley et al. (2000) compared three different intervention conditions in a group of pre-school children. One condition was carried out only at school, the second with the parents, and the third was a combined intervention. Furthermore, there was a ﬁnal control condition without any type of intervention. The participants in the study were 158 pre-school children with high levels of aggressiveness, hyperactivity, impulsivity and inattentive behavior. The behavioral interventions implemented in class included behavior modiﬁcation techniques (token economy, response cost, time-out and over-correction), social skills training and cognitive-behavioral self-control and anger management techniques. With the parents, an adaptation of the program elaborated by Barkley (1987) was developed, also lasting the entire school year. This parent training program included the techniques of praise, reinforcement, token economy system, time-out and response cost. Thinking aloud strategies were used to manage disobedient behaviors outside the home. The results showed that the two school intervention conditions, with and without intervention with parents, produced similar signiﬁcant improvements in multiple domains. Speciﬁcally, the evaluations by the parents improved with regard to the adaptive behavior of their children, as did the teacher evaluations of aggressiveness, attention, self-control and social skills. The parent treatment did not produce signiﬁcant improvements, which could be due to their low participation and involvement in the intervention. In fact, a follow-up study carried out two years later showed that the improvements achieved after the treatment had disappeared (Shelton et al., 2000). The results suggest that early interventions in class with disruptive children are effective, but they may not produce lasting effects when the treatment is short-term and the parents are not completely involved.

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Other more successful programs have also been prepared with the purpose of combining different performance procedures in the distinct developmental contexts of the child with ADHD. One especially interesting program is an intensive intervention program carried out during the summer vacation period. The Summer Treatment Program (STP) by Pelham and Hoza (1996), which lasts 8 weeks, includes ﬁve of the main components of ADHD interventions: (1) parent training in managing their children’s behavior; (2) use in class of behavior modiﬁcation techniques (social reinforcement, token economy system with weekly rewards, response cost); (3) tutoring in and practice of academic and sports skills); (4) training in social skills and problem-solving (normally during sports activities and (5) stimulant medication. The program is applied by special education teachers when the children perform academic, artistic and computer activities and by monitors when the children participate in recreational activities such as swimming and football. In order to maintain the advances made with the STP and extend them to natural settings, the program includes group training for the parents, where they are provided with information about the disorder and treatments. In this way, a continuous communication system is established with them. When necessary, the program also introduces psychostimulant medication. Owing to widespread evidence about the efﬁcacy of this program, it was included in the most important study on ADHD intervention carried out to date (MTA Cooperative Group, 1999).

Multimodal Treatment Study of Children with ADHD (MTA) Co-ﬁnanced by the U.S. National Health Institute and the Department of Education, the Multimodal Study of Children with Attention Deﬁcit/ Hyperactivity Disorder (MTA Cooperative Group, 1999) was designed to test the long-term efﬁcacy of different unimodal and multimodal interventions in the many areas where children with ADHD have difﬁculties. In this study, 576 children with combined ADHD participated. Their ages ranged from 7 to 9.9 years, and they were randomly assigned to one of the following treatment conditions for 14 months: pharmacological treatment; intensive behavioral treatment; a combined modality of these two intervention approaches; and community treatment, in which the subjects received general community care. The pharmacological treatment began with a trial of methylphenidate for 28 days, using ﬁve different doses according to the children’s weight. For the children who did not have a positive response to the methylphenidate,

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alternative medications were tried until the right one was found for each subject, in the following order: dextroamphetamine, pemoline, imipramine and other medications. The intensive behavioral intervention consisted parent training in behavior modiﬁcation techniques, an intervention at school, and a STP. The combined treatment included all the aforementioned interventions (behavioral and pharmacological). Finally, in the community treatment the subjects did not follow any of the interventions described earlier, although they did receive general community care (different medications and psychotherapeutic treatments without data). The results provided by the MTA study concluded that, after 14 months of intervention, the four groups of children experienced marked improvement, with signiﬁcant differences among them with regard to the amount of change achieved (MTA Cooperative Group, 1999). The combined and pharmacological treatments, signiﬁcantly superior to the behavioral and community treatments in reducing the symptoms of the disorder, were equally effective, as there were no signiﬁcant differences between these two intervention modalities. It is important to mention that the subjects who participated in the combined modality intervention received a lower daily dose of methylphenidate than the subjects who were in the pharmacological treatment only condition (at the posttest, the average daily dosage was 31.2 mg in the combined group and 37.7 mg in the pharmacological intervention group). These results support the advisability of using lower doses of medication when performing a combined intervention over a long period of time, which undoubtedly would beneﬁt the children, as it would reduce the possible side effects of the medication. There were no signiﬁcant differences on the main symptoms between the behavioral and community groups, probably, among other things, because the community group was not a real control group (68% of the children in this group received an average daily dosage of 22.6 mg of medication). The authors also provided additional information comparing the number of times each treatment appears in ﬁrst place for its effectiveness in the 19 dependent variables included in the study. They found that the combined group was ﬁrst 12 times, the pharmacological group 4 times, the behavioral group 2, and the community group 1. Although the comparisons among the groups do not suggest differences between the medicated modality and the combined modality, secondary

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studies that have used complementary methodological approaches point to some advantages of the combined condition. Idiographic studies, which combine the ratings of parents and teachers on the symptomatology of ADHD and negativism/deﬁance, conclude that the greatest percentage of improvement occurs in the children who follow the combined treatment (68%), followed by stimulant medication (56%), behavioral intervention (34%) and community care (25%) (Swanson et al., 2001). The studies carried out 24 months after initiating the intervention present a pattern of results similar to the one obtained after the treatment but less conclusive (MTA Cooperative Group, 2004). Speciﬁcally, the decline in the improvements obtained at the posttest evaluation was more important in the groups that had been medicated (pharmacological and combined) than in the children whose treatments had initially been less effective (behavioral and community). Finally, in the analyses performed at 36 months, the groups were not signiﬁcantly different on any of the variables analyzed (Jensen et al., 2007). The superiority of the pharmacological and combined treatments had disappeared. For Swanson et al. (2008a, 2008b), this temporary effectiveness of the medication for the majority of the children, even if it continued to be used, could be explained by a lack of control on the part of community services. They point out that this reduction in the differences between the intervention modalities could be due to the way the drugs were used once the intervention was over. Thus, although some of the children from the modalities that included drugs abandoned them, others in the behavioral and community conditions began to take them, following the advice of the researchers. Undoubtedly, the scope of the MTA marks a point of inﬂection in ADHD intervention. However, the study has also received some criticisms, due to both the characteristics of the treatments and the implicit model that supports them (Barkley, 2000; Greene & Ablon, 2001). Some examples are the lack of a control group without treatment, differences in the doses of medication for the two modalities that used it, the fact that the behavioral program was not as individualized as the pharmacological one, or the different treatment conditions in the evaluations, where some modalities continued while others had already concluded. It is also important to highlight that the psychosocial intervention left out some important components. For example, the behavioral packet did not include any essential contents related to psycho-educational intervention for students with ADHD, such as making educational accommodations in the classroom and in the teaching–learning process.

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The Academic and Behavioral Competences Program The effectiveness of psycho-educational intervention in ADHD has been supported by The Academic and Behavioral Competences Program’’ (ABC) (Pelham et al., 2005), which involves the entire school. It includes positive teacher–student interactions with a high level of feedback (social reinforcement, precise instructions, effective attention); establishment of norms (desserts, prizes and contingent negative consequences); time-out; tasks to do at home (with parent participation); a home–school card; consistent weekly rewards in the form of enrichment activities (Fun Friday); honor privileges (desired roles or badges); lunch and free time with points or privileges for good behavior; group contingencies; social skills (every day a different skill is analyzed and practiced), and individualized programs for children with associated behavior problems (problem-solving with parent participation). The program was implemented in a school in Ohio (371 children from ﬁrst to ﬁfth grades of elementary school and the entire team of teachers and aides in the school) and later improved and replicated in three schools in New York from the year 2002 on. The results indicate that the teachers and parents considered the program to be effective. Speciﬁcally, the visits of the most problematic children to the director (for inappropriate behavior) were substantially reduced from 1,200 the year before beginning the intervention to 178, 373, 525 and 290 in the four following years. Task performance went from 25% before the program to 85%, 92%, 95% and 95%, respectively. The number of failing grades fell from 75 previously to 11 in the ﬁrst year of the intervention (there are no data for the three following years). In summary, we can conclude that the review of the studies carried out on ADHD intervention clearly show the beneﬁts of the psychosocial interventions, including the behavioral training of parents and teachers, cognitive-behavior modiﬁcation, school interventions, social skills training and summer programs. There were no studies found that mention harmful side effects of the psychosocial interventions. Another clear result is the effort made in the past few years to combine different intervention modalities and apply them in the contexts where the children develop. Keeping in mind the teachers’ limitations and lack of resources in trying to do a good job with ADHD children, which they themselves recognize, teacher training programs have been designed that combine different intervention strategies presented in this chapter. In the same way, programs have also been elaborated that help the parents interact with their children

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with ADHD. The results obtained are very encouraging, as are those from the few studies that have incorporated coordinated interventions with parents and teachers.

THE PRESENT INVESTIGATION As we have shown, the majority of the psychosocial interventions with children with ADHD are based on behavioral techniques, with very few of them including other components. There is a striking lack of instructional modiﬁcations to foster learning or social skills training. Furthermore, the majority focus on the efﬁcacy on the basic symptomatology of the disorder, and few of them really evaluate the beneﬁts in other domains where these children usually have problems functioning (such as learning, grades, anxiety, shyness, social status) or provide the point of view of different informants who can provide a truer panoramic view of the efﬁcacy of the intervention program (parents, teachers, classmates, educational psychologists, brothers and sisters, etc.). Finally, another common aspect in the majority of the programs is that the child is not considered the direct target of the intervention, with the parents and/or teachers (rarely both) directly applying the techniques to the children. In this framework, the purpose of our study was to analyze the possible beneﬁts of a contextualized multi-component intervention involving children with ADHD, their parents and their teachers. A mixed experimental design was used (between-group/within-group) with pre- and post-treatment measures for the treated and untreated ADHD groups. The effects of the intervention program were evaluated in three basic developmental areas: school learning, emotional adjustment and social adjustment. Furthermore, in order to better capture the possible effects of the intervention, information was gathered from different informants: parent, teachers and classmates.

METHOD Participants Participants in this study were 42 children with ADHD who were enrolled in elementary education in the province of Castello´n. The criteria used to determine the presence of ADHD were (a) meeting six or more of the criteria

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in each of the sections (inattention-disorganization and hyperactivityimpulsivity) of the diagnosis for combined subtype ADHD, according to the DSM-IV-TR (APA, 2000); (b) symptoms lasting more than one year; (c) appearance of the problem before the age of 7; (d) absence of mental handicaps and (e) absence of psychosis, neurological damage, and sensorial or motor deﬁcits. The children with ADHD had to meet two additional requirements. They could not be presently undergoing treatment of any kind, and they had to have an IQ of 80 or above on the WISC-R (Wechsler, 1993). The children were distributed into two groups: one with 27 children who received the intervention (experimental); and the other with 15 children who received no intervention (control). For ethical reasons, after the posttest evaluation the parents of the children in the latter group participated in a 3-hour session in which they were given information about the disorder and procedures to control their children’s behavior. The experimental group was composed of 23 boys (85.2%) and 4 girls (14.8%). The same tendency in the proportion of sexes was observed in the control group, which was made up of 86.7% boys and 13.3% girls. The age range of the participants was from 7 to 10 years, although the majority of them (63% of the experimental group and 66.7% of the control group) were between 7 and 8 years old. Regarding IQ, the mean IQ of the experimental group was 102.4 (standard deviation 7.1), and the mean IQ of the control group was 97.4 (standard deviation 10.0). There were no signiﬁcant differences between the two groups on any of the aforementioned variables. The majority of the parents of the participants were actively working professionals with a medium socio-economic status.

Measures The evaluation battery used included different instruments designed to obtain information in the distinct contexts in which the child carries out his/ her daily life. For this purpose, both parents and teachers evaluated developmental aspects that can be associated with ADHD, speciﬁcally social adjustment, emotional adjustment and learning. Information was also collected from the classmates about the social reality of these children in their classrooms. Screening Instruments ADHD questionnaire for parents adapted from the DSM-IV-TR (APA, 2000). This questionnaire consists of 18 items corresponding to the

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DSM-IV-TR criteria (APA, 2000) for the diagnosis of the Attention Deﬁcit Disorder with Hyperactivity. These items are statements about observable behaviors that demonstrate (a) attention deﬁcit (items 1–9) and (b) hyperactivity (items 10–15) and impulsivity (items 16–18). The parents must respond using 4 possible response alternatives (‘‘never’’ and ‘‘sometimes’’ ¼ 0 points, ‘‘often’’ and ‘‘quite frequently’’ ¼ 1 point). Thus, the total number of possible points on each of the scales is 9. This questionnaire, together with the one for the teachers, was used as a test for selecting the sample. ADHD Questionnaire for teachers adapted from the DSM-IV-TR (APA, 2000). This questionnaire makes it possible to gather information from the teachers about the basic symptoms of ADHD. It is exactly the same as the one for parents described earlier. Revised Wechsler Intelligence Scale for Children, WISC-R (Wechsler, 1993). The blocks design and vocabulary subtests were selected, in order to obtain an equivalent IQ (Sattler, 1982). Behavioral Measures Scale of Behavior Problems for Parents, EPC (Navarro, Peiro´, Lla´cer, & Silva, 1993). This scale includes 99 statements referring to behaviors that describe ways of being of children and adolescents. The parents must respond by indicating how their child usually is, according to three possible response alternatives: ‘‘no’’ (0), ‘‘sometimes’’ (1) and ‘‘often’’ (2). The scale includes the following subscales: (a) problems at school (e.g., ‘‘his/ her schoolwork is low quality,’’ ‘‘s/he has trouble learning in school’’); (b) antisocial behavior (e.g., ‘‘s/he argues a lot,’’ ‘‘s/he participates in ﬁghts a lot,’’ ‘‘s/he physically attacks people’’); (c) shyness, withdrawal (‘‘others’ jokes affect him/her,’’ ‘‘s/he is a loner’’); (d) anxiety problems (e.g., ‘‘s/he is very fearful or anxious’’) and (e) social adjustment (e.g., ‘‘s/he gets along with others,’’ ‘‘s/he asks permission to use others’ things’’). Inventory of Problems in School for Teachers, IPE (Miranda, Martorell, Lla´cer, Peiro´, & Silva, 1993). This questionnaire is ﬁlled out by the teachers, and it analyzes the behavior the students may present within the school context. It consists of 92 items that are rated on a 3-point scale: ‘‘no’’ 0 points, ‘‘sometimes’’ 1 point and ‘‘often’’ 2 points. The questionnaire’s factorial scales analyze (a) learning problems (‘‘his/her reading is poor,’’ ‘‘s/he has problems with arithmetic’’); (b) antisocial behavior (‘‘s/he has temper tantrums,’’ ‘‘s/he destroys others’ things’’); (c) shyness and anxiety (‘‘s/he is easily embarrassed,’’ ‘‘s/he is scared by any type of unimportant noise’’); (d) withdrawal (‘‘s/he prefers to play alone,’’ ‘‘s/he does not

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participate in class activities’’) and (e) school maladaptation (‘‘s/he complains about being in school’’). IOWA Hyperactivity and Aggressiveness Questionnaire (Loney & Milich, 1982). Aggressiveness/oppositionism subscale, with ﬁve items (e.g., ‘‘s/he is argumentative, looks for ﬁghts,’’ ‘‘s/he behaves in a violent manner’’) with four response alternatives rated from 0 to 3 points. Sociometrics This test (Gonza´lez, 1991) makes it possible to determine the level of social acceptance or rejection within a group (sociometric status), discover the relationships between the individuals and reveal the structure of the group. This test is based on the responses that all the students in a class give to four questions about their preferences and rejections of the other students, as well as the perceptions they have about themselves, that is, whether they feel accepted by their classmates or not. The computer analysis provides information on (a) positive choices or the number of times his/her classmates choose the student to sit, play or work with; (b) negative choices or the number of times his/her classmates choose him/her negatively, that is, not wanting to sit, play or work with him/her and (c) sociometric status, which makes it possible to obtain the relative position each subject holds in the group from a sociometric point of view, with ﬁve possible categories: rejected, the child has a signiﬁcantly high negative status; controversial, the positive and negative statuses are signiﬁcantly high; popular, the subject has a signiﬁcantly high positive status; isolated, the child has signiﬁcantly low positive and negative statuses and medium, with medium positive and negative statuses. Intervention Programs The multi-contextual and multi-component approach used in this study integrated three different programs, depending on the context in which each was implemented: directly with the children, with the parents and with the teachers. The intervention lasted 10 weeks. There were 16 sessions with the children (approximately two per week), whereas the parents and teachers each attended 10 sessions, one per week. The basis of this intervention packet was the communication between the participants, so that both the parents and the teachers were aware at all times of the techniques that were being worked on with the children, in order to facilitate the generalization of what was learned. Furthermore, the therapist was in contact with the children, parents and teachers at

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the weekly meetings and through permanent telephone contact. Likewise, the parents and teachers kept in contact daily by using the home–school card. Intervention program for the children. This program consisted of a set of behavioral-cognitive techniques, which were introduced in small groups by a specialist. The main nucleus of the program was teaching the selfinstructional technique, adapted from the program ‘‘Thinking Aloud’’ (Camp & Bash, 1980), with the purpose of fostering inhibitory control. In order to work on the interpersonal plane, the self-instruction was combined with problem-solving and anger management techniques and with the teaching of social skills (adapted from Miranda & Presentacio´n, 2000; Hugues, 1988; Michelson, Sugai, Wood, & Kazdin, 1987; Monjas, 1996). The program was complemented with token economy system. The techniques were introduced in a successive manner, with each of them being practiced in various sessions. Speciﬁcally, the ﬁrst six sessions were dedicated to the self-instructional technique, although it continued to be practiced in all the remaining sessions as applied to diverse content matter. The token economy was introduced in the third session, and it was also maintained until the end of the intervention. The next six sessions were dedicated to problem-solving and anger management techniques, to conclude with social skills training in the last four sessions. The methodology for implementing these techniques included dialogue, debate, exposure, modeling (of mastery, conﬂict and correction), role playing and dramatization. To orient them in their performance, feedback and reinforcement were applied (external and self-reinforcement), and to maintain and generalize what had been learned, tasks and work were provided. Intervention program for the parents. This program was adapted from Barkley (1997). It includes 10 sessions carried out over a period of 10 weeks. It consists of a set of behavior modiﬁcation techniques, through which the parents learn to apply simple procedures for contingency management, promoting attention and obedience within the family context. Before beginning with the techniques, information was provided about the disorder (ﬁrst and second sessions), so that the parents would not focus the responsibility for the problem exclusively on their children and to make them aware of the enriching aspects of parent–child interactions. The parents received a home–school card, which had been prepared, so that the parents and teachers could keep in contact every day. On this card, the teachers had to rate the behaviors of the children in class that had been

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identiﬁed as targets. Sessions 3–6 were dedicated to behavior modiﬁcation techniques: praise, rewards, extinction, time-out, token economy, response cost and contingency contracts. During these sessions, the parents also acquired knowledge about the cognitive-behavioral techniques of selfinstruction and reinforced self-evaluation. Session 7 focused on orienting the parents about how to support their children’s academic learning at home. Sessions 8 and 9 were directed toward improving the parents’ emotional health. By means of diverse strategies and techniques (anger management, relaxation and problem-solving), the parents learned to deal with the complex situations that arise in bringing up their children. The program ended with one follow-up session. To teach the parents the various techniques, debate, exposure and modeling (of mastery and conﬂict) were used, and they were practiced using role-play, dramatization and vignettes. Intervention program for the teachers. A post-graduate course was prepared for the teachers. In it, they received up-to-date information about managing children with ADHD in the classroom, and about their academic and social performance. The teachers attended 10 sessions lasting 4 hours each over a period of 10 weeks. The course consisted of an adaptation of the Miranda et al. (1999) program. In the ﬁrst three sessions, the teachers were provided general knowledge about ADHD: diachronic evolution, basic symptomology, associated disorders, prevalence, prognosis, developmental manifestations, diagnosis and subtypes. Session 4 was dedicated to implementing the behavior modiﬁcation techniques in the classrooms. The teachers were asked to motivate the child’s use of the self-instructional technique that s/he was practicing with the specialist. In sessions 5 and 6, training was provided in self-evaluation with reinforcement in order to develop the children’s evaluation and regulation skills in following the class norms and doing the required tasks. The teachers were also informed about how their students were applying the problem-solving and anger management techniques, and the need to generalize them to the classroom context was emphasized. Sessions 7–9 dealt with physical and organizational classroom adaptations for children with ADHD, along with instructional modiﬁcation according to the subject matter. The teachers also received information about social skills training. The last session focused on following-up on the application of the program techniques. The activities for transmitting the techniques to the teachers involved debate, exposition, modeling, role-playing, vignettes and ﬁlling out observation and activity-planning sheets.

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Procedure The study was carried out in four differentiated stages: (1) sample selection; (2) pre-treatment evaluation; (3) the intervention with parents, teachers and children and (4) post-treatment evaluation. In order to select the sample of children with ADHD, the Educational Psychology Service of Castellon was asked to collaborate. Visits were also made to different schools and parents associations, which yielded 136 cases distributed in 24 schools in Castello´n. Of these 136, once the preliminary evaluation had been made, only 42 met the diagnostic criteria for ADHD. After obtaining the parents’ informed consent and performing the pretreatment evaluation, the 42 children were randomly assigned to two groups: 27 children were assigned to the treatment group and 15 to the group without treatment. This asymmetrical distribution was designed to offer the intervention to the greatest number of children possible while maintaining a large enough control group to carry out the proposed statistical analyses. The intervention program with the children was applied to seven groups of four children after school at Jaime I University in Castello´n, achieving a mean attendance percentage of 88.4%. Meanwhile, in the parent program at Jaime I University, 27 couples participated who were divided into two groups. The attendance was noteworthy (76.4%), although in 59.7% of the cases only one member of the couple attended, usually the mother. The postgraduate course for teachers involved 70 hours of theory-practice, which was carried out in 10 training sessions with 93.1% attendance. Once the three intervention programs had ended, the post-treatment evaluation was performed on both the group of children who had received the treatment and the students without ADHD treatment.

Analysis After analyzing the data and verifying that the supposition of normality was not met, and keeping in mind that the sample size was small, the decision was made to look for appropriate contrasts. In these cases, the most appropriate contrasts are the non-parametric ones, given that they do not require making distribution suppositions on the population data. Nonparametric tests are less efﬁcient than parametric ones, and they also have a greater probability of not rejecting a false null hypothesis (resulting in a type II error). However, they have been shown to be very useful as an alternative when parametric tests are not considered appropriate (Conover, 1999).

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In the ﬁrst place, a calculation was made of the factors or general values resulting from combining the speciﬁc measures for each of the variables. Then, after calculating the corresponding descriptive statistics, nonparametric tests were used to analyze the within-group comparisons. Speciﬁcally, the Wilcoxon test was used to make the pre–post test comparison. For the comparisons between the treatment and non-treatment groups, the Mann–Whitney U statistic was applied. Percentage analyses were also performed on the dichotomous and nominal variables.

RESULTS For greater clarity, the results will be presented according to the three functioning domains evaluated in this study: learning, emotional adjustment and social adjustment. Within each of them, ﬁrst the results will be presented for the general factor and then the results related to the parents and teachers on the variables of interest. Thus, after the results of the school learning general factor, the results of the school problems variables as estimated by the parents (IPE) and the learning problems as estimated by the teachers (EPC) are presented. After the results on general emotional adjustment, the speciﬁc variables of shyness-withdrawal and anxiety problems appear as rated by the parents (EPC) and the variables of withdrawal and shynessanxiety as rated by the teachers (IPE). The social adjustment results rated by the antisocial behavior and social adjustment variables, ﬁlled out by the parents (EPC), and the measures of antisocial behavior and social maladjustment (IPE) and the IOWA Aggressiveness Questionnaire (Loney & Milich, 1982), ﬁlled out by the children’s teachers, are also presented. Finally, the sociometric data provided by the classmates are presented.

Effects of the Intervention on School Learning on Children with ADHD The general measure of school learning (see Table 1) showed changes in the experimental group, with the improvements being signiﬁcant (z ¼ 4.493; p ¼ .000) once the intervention had ended. In the control group, however, there were no signiﬁcant improvements at the second evaluation. Comparing the two groups, we did not ﬁnd signiﬁcant differences on the pretest, whereas they did appear on the posttest (U ¼ 93.000; p ¼ .004), due to the improvements in the group that had received the intervention.

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Table 1. Results on Academic Progress before and after the Treatment for Treated and Untreated ADHD Groups. Treated

Untreated

Treated

Untreated

z

z

Median/IQR Pretest

Posttest

Pretest

Posttest

7.04 3.42

4.61 2.57

7.04 2.80

6.67 3.55

– 4.493***

ns

EPC: problems in schoola

19.00 9.00

12.00 5.00

19.00 7.00

17.50 6.00

– 4.379***

ns

IPE: learning problemsa

25.00 25.00

21.00 23.00

30.00 18.00

31.00 20.00

School learninga

2.562*

ns

*po.050; **po.010; ***po.001. a Inverse variable: a higher score indicates less school learning.

The parents’ ratings of the school problems variable conﬁrms that the children with ADHD who had received the treatment presented problems in school in the initial evaluation performed. Nevertheless, after the intervention the experimental group clearly reduced its median, going from 19.00 on the pretest to 12.00 on the posttest, with this improvement being signiﬁcant (z ¼ 4.379; p ¼ .000). The control group, however, maintained the same median at the two points in time. In addition, the comparative results between the two groups of children with ADHD, treated and not treated, support the inﬂuence of the treatment, as there were no differences found between them in the ﬁrst evaluation, but there were on the posttest (U ¼ 44.000; p ¼ .001). Similar results were found with regard to the information provided by the teachers. Thus, in the learning problems variable, when comparing the two evaluation times, there was a signiﬁcant improvement in the experimental group at post-treatment (z ¼ 2.562; p ¼ .010). The control group maintains the initial median on the posttest, which indicates that there was no signiﬁcant change. In the comparisons between the two groups, there are no signiﬁcant differences on the pretest, whereas on the posttest the improvement experienced by the treated group reached statistical signiﬁcance (U ¼ 84.500; p ¼ .021). The teachers were also asked to provide information about the children’s grades (pass/making progress and fail/needs to improve) at the two

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evaluation times: (1) before the intervention, coinciding with the ﬁrst school evaluation (December); and (2) once the intervention was over, coinciding with the last school report card (June). Fig. 1 displays the percentage of failures (NM) of the children in three basic areas of learning, mathematics, Spanish language and environmental sciences. As the graph shows, 60.9% of the children in the experimental group and 60.0% of the control group did not pass mathematics in the month of December. Once the academic year was over in June, the percentage of failures in this area was 50.0% in the children with ADHD who had participated in the intervention. In the control group, however, there are 6.7% more failures in this evaluation, which represents 66.7% of the children. In the area of Spanish language, the same tendency is observed as in mathematics in the experimental group. Speciﬁcally, 69.6% of the children with ADHD who were going to participate in the intervention had failed Spanish language in the ﬁrst school evaluation in December, while six months later the percentage of failures was 50.0%. The children in the control group maintained the same number of failures as in the ﬁrst evaluation (66.7%). Finally, in the subject environmental sciences, 34.8% of the treated group failed in December and 18.7% in June (16.1% less). In this subject, the control group also experienced a reduction in the number of failures, although not as pronounced (6.7% less).

70

pretest

60

posttest

50 % 40 30 20 10 0 mat.

len. Treated

Fig. 1.

c.med.

mat.

len.

c.med,

Untreated

Percentage of Children with ADHD-C Who Failed Mathematics, Spanish Language and Environmental Sciences on the Pretest and Posttest.

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Effects of the Intervention on the Emotional Adjustment on the Children with ADHD The general emotional adjustment factor did not experience signiﬁcant changes in any of the groups analyzed in the second evaluation. Nor did signiﬁcant differences appear in the comparison of the groups on the pretest or the posttest (see Table 2). An analysis of each variable individually showed that the parents did perceive emotional changes in shyness-withdrawal after the intervention. These changes affect both the experimental group (z ¼ 2.299; p ¼ .022) and the control group (z ¼ 2.263; p ¼ .024). There were no signiﬁcant differences when comparing the groups at any of the evaluation times. Regarding anxiety problems, the changes detected in both groups after the intervention are only signiﬁcant for the experimental group (z ¼ 2.782; p ¼ .005). In this case, there were no signiﬁcant differences in the comparisons of the groups either. The teachers’ perceptions about the emotional modiﬁcations are less marked than those of the parents. On the two variables analyzed, withdrawal and shyness-anxiety, neither of the groups showed signiﬁcant changes. The group comparisons did not show signiﬁcant differences either.

Table 2.

Results on Emotional Adjustment before and after Treatment in Treated and Untreated ADHD Groups. Treated

Untreated

Treated

Untreated

z

z

ns

ns

2.299*

2.263*

2.782**

ns

ns

ns

ns

ns

Median/IQR

Emotional adjustmenta EPC: shyness-withdrawala Anxiety problemsa IPE: withdrawala Shyness-anxietya

Pretest

Posttest

Pretest

Posttest

3.54 2.12 7.00 4.00 9.00 6.00 4.00 7.00 11.50 12.00

3.11 2.05 6.00 5.00 6.00 4.00 5.50 6.00 10.00 6.00

4.14 3.59 7.50 7.00 10.50 10.00 6.00 16.00 12.00 16.00

4.37 4.83 6.50 9.00 8.50 10.00 6.00 8.00 10.00 9.00

*po.050; **po.010; ***po.001. Inverse variable: a higher score indicated less emotional adjustment.

a

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Effects of the Intervention on the Social Adjustment on Children with ADHD The results obtained on the general adaptation factor show an improvement in the children in the treated group between the pretest and the posttest (see Table 3). Thus, in the experimental group signiﬁcant improvements were observed (z ¼ 3.975; p ¼ .000) once the intervention was over, whereas the control group did not show any signiﬁcant improvement. There were no signiﬁcant differences in the comparisons of the groups at the pretest or the posttest either. On antisocial behavior, as rated by the parents, in the experimental group there was a signiﬁcant improvement between the pretest and the posttest (z ¼ 2.924; p ¼ .003). The control group, however, did not modify its initial score signiﬁcantly. In the between-group comparisons, there were no signiﬁcant differences on the pretest or on the posttest. The social adjustment Table 3.

Results on Social Adjustment before and after Treatment in the Treated and Untreated ADHD Groups. Treated

Untreated

Treated

Untreated

z

z

3.975***

ns

2.924**

ns

ns

ns

Median/IQR

a

Social adjustment

EPC: antisocial behaviora Social adjustment IOWA: aggressivenessa IPE: antisocial behaviora School maladjustmenta Sociogram: positive choicesb Negative choicesa,b

Pretest

Posttest

Pretest

Posttest

4.55 2.00 17.00 7.00 18.00 5.00 5.00 6.00 29.50 14.00 4.00 4.00 5.00 5.00 11.00 10.00

3.64 1.50 12.00 9.00 20.00 6.00 3.00 3.00 18.00 13.00 4.00 4.00 4.00 6.00 8.50 13.00

4.40 3.07 16.50 9.00 16.00 6.00 4.00 6.00 23.00 22.00 4.00 4.00

4.38 2.43 15.00 3.00 16.00 9.00 3.00 7.00 24.00 17.00 4.00 6.00

– –

2.324*

ns

3.941***

ns

ns

ns

–

ns

–

–

2.983**

–

*po.050; **po.010; ***po.001. a Inverse variable: a higher score indicates less social adjustment. b Variable not included in the general social adjustment factor.

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variable rated by the parents showed a positive tendency in the experimental group, but without reaching a signiﬁcance of .05. There were no signiﬁcant differences in the within-group or between-groups comparisons on either of the evaluations. Similar results are provided by the information from the teachers. Regarding aggressiveness (IOWA: Loney & Milich, 1982), a positive tendency can be seen in the two groups on the posttest, although only the improvement in the experimental group is statistically signiﬁcant (z ¼ 2.324; p ¼ .020). In the comparisons of the two groups with ADHD, there were no signiﬁcant differences at either of the evaluation times. For the antisocial behavior variable, it can also be observed that the experimental group clearly improved between the two evaluation times (z ¼ 3.941; p ¼ .000), although there are no signiﬁcant differences between the two groups with ADHD at either of the evaluation times. Finally, the school maladaptation variable did not present signiﬁcant changes in either of the groups. Nor were there differences between the groups at either of the evaluation times. The results of the information provided by the classmates on the sociogram show that the positive choices variable experienced small modiﬁcations between the two evaluation times, although they did not reach statistical signiﬁcance. However, on the negative choices variable, the treated group experienced signiﬁcant changes between the pretest and the posttest (z ¼ 2.983; p ¼ .003). Fig. 2 shows the percentages of the children included in the various sociometric categories of the test. As can be seen, the social status derived

80

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60 50 40 30 20 10 0 medium

Fig. 2.

rejected

controv.

popular

isolated

Percentage of Treated Children with ADHD-C in Different Sociometric Categories on the Pretest and Posttest.

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from the response produced in their classmates, in terms of acceptance, rejection or indifference, experienced important modiﬁcations. Speciﬁcally, in the pretest phase, the treated children with ADHD were generally rejected. However, these children clearly improved their sociometric status between the two evaluations. There was a considerable decrease in rejected children, with an increase in popular and controversial ones. In fact, the high percentage of children who had been rejected by their classmates initially (75%) decreased by 20% after the intervention. The number of children with a controversial status increased, going from 5% initially to 15% on the posttest. Likewise, 10% of the children had the status of popular at the posttest evaluation, whereas there were no children included in this category on the pretest. Finally, no modiﬁcations occurred in the categories of medium or isolated. The percentage of children with a medium status was maintained at 20% at the two evaluation times, and the isolated category remained stable at 0%.

DISCUSSION The main purpose of this study was to analyze the effectiveness of applying a multi-component intervention program directly to a group of ADHD children along with guidance for parents and teachers. The possible effects of the program were tested in three main domains: school learning, emotional adjustment and social adjustment. In general, the results support the efﬁcacy of the intervention, especially in the academic and social areas in which these children show the greatest difﬁculties. With regard to academic performance, the children with ADHD who participated in the intervention initially presented many school learning problems, which were reﬂected in the ratings of both the parents and the teachers (medians that coincide with the 90th and 80th percentiles, respectively). Once the intervention was over, at the posttest evaluation, the learning problems were signiﬁcantly reduced in the observations of parents and teachers (70th percentile in both cases). In contrast, in the group of children with ADHD who did not receive treatment the learning problems remained stable. The comparisons between the two groups showed signiﬁcant differences on the posttest, in the opinions of both the parents and the teachers, due to the improvement experienced by the ADHD group. Moreover, although the percentage analyses of school grades are not usually sensitive enough to detect the changes produced by an intervention, improvements were noted in all the areas evaluated. In the treatment group,

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the number of failing grades fell by 10.9% in mathematics, 19.6% in Spanish language and 16.1% in environmental sciences. The difﬁculty of reducing learning problems and modifying school grades should be highlighted. The majority of children with ADHD have an adverse school trajectory with important gaps in knowledge and deﬁcits in academic skills, which are difﬁcult to compensate for in the brief time period of the intervention. Despite this fact, it is likely that the inclusion of instructional and organizational modiﬁcations in the programs, as well as speciﬁc adaptations in the areas of mathematics and language, has contributed to the slight improvement in the children’s academic situation. It would be interesting to carry out studies replicating our study and extend their duration in order to test the effectiveness of the program in overcoming learning problems. In this sense, our results are similar to those obtained by Pelham et al. (2005) and Miranda et al. (2002b). Although their contents and lengths vary to some extent, one basic element of these programs is speciﬁc instruction for teachers about classroom modiﬁcations and instructional adaptations as a way of achieving signiﬁcant improvements in school performance. As mentioned earlier, the lack of this component may also be one of the possible limitations of the intensive behavioral treatment used in the MTA. In general, the children with ADHD who participated in this research had scores within the normal range on the aspects of emotional functioning, with the exception of anxiety problems (whose median coincides with the 75th percentile on the pretest). Probably for this reason, there was no signiﬁcant improvement on the general factor of emotional adjustment in either of the two groups. There were, however, modiﬁcations in its mean scores, according to the parents, highlighting a signiﬁcant improvement until reaching normal values in the group treated for anxiety problems (45th percentile on the posttest). Our results coincide with those obtained in numerous studies that emphasize that the most important associated problems presented by combined subtype ADHD children are of an externalizing nature and related to social adjustment (percentile 90 in antisocial behavior, for parents and teachers). After analyzing the social variables rated by the parents, teachers and classmates, it is possible to conclude that, in the opinions of all the observers, the experimental group improved between one evaluation and the other, with the change being signiﬁcant in the general factor of social adjustment and on four of the seven variables analyzed (antisocial behavior rated by parents and teachers, aggressiveness and negative choices). The control group, however, remained stable between the two evaluations, with

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not signiﬁcant modiﬁcations in any of the cases. Our results coincide with those obtained by Miranda and Presentacio´n (2000) and Barkley et al. (2000). Both intervention programs achieved improvements too in antisocial behaviors and aggressiveness by combining behavior modiﬁcation and cognitive-behavioral techniques. In our opinion, some important complementary information is provided by the results of the sociometric test. This test is not usually included in the research on ADHD intervention and other problems, probably because of the well-documented difﬁculty of positively modifying the perceptions the children in class have about one of their classmates. An extended period is needed in order for the classmates to begin to perceive the different behaviors the child is exhibiting and change the stereotypes they have about him/her. This situation, which is true for all children, is especially difﬁcult in the case of children with ADHD, who are usually involved in negative relationships in their classrooms. However, after the implementation of the multi-component packet used in this study, the sociometric test shows important differences in the relationships between the treated ADHD children and their classmates, increasing the number of positive choices and signiﬁcantly reducing the number of negative ones. In fact, after the intervention, the number of rejected children dropped by 20%. In the MTA study, however, the relationships between the classmates did not improve in any of the treatment conditions and remained signiﬁcantly impaired (Hoza et al., 2005). The great weight given in our study to instruction in cognitive strategies for dealing with conﬂicts is one of the variables that could explain this difference. Without a doubt, applying studies like the one described in this chapter is quite complex, although not as complex as the MTA (in the words of Antshel & Barkley, 2008, impossible to replicate). However, despite its difﬁculty, it is easier to apply on a daily basis, thus improving the quality of life of children with ADHD. Among the main contributions of our study, the coordination of three parallel programs in the child’s two closest developmental contexts stands out. As in the study by Barkley et al. (2000), our intervention includes coordinated programs for parents and teachers, but it also provides direct intervention with the children. Some programs have included direct actions with the child (STP, MTA), but they did not apply an intensive packet. Another noteworthy aspect of our study is the design of a multicomponent packet that combines the main treatments that have been shown to be effective with ADHD children in the basic symptomology and associated academic, social and emotional manifestations. The program

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included behavior modiﬁcation techniques, training in cognitive strategies of self-control, problem-solving and anger management, social skills training and academic modiﬁcations. In this sense, our work goes beyond the use of interventions that tend to emphasize the behavioral control of the ADHD child, omitting important aspects like school learning and socio-emotional adjustment. Furthermore, an attempt was made to offer a comprehensive view of the effects of the intervention, while analyzing variables related to the basic symptomology of the disorder. Thus, in our study an evaluation was made of the efﬁcacy of the functioning in different domains, including learning problems, grades and emotional and social adjustment. The points of view of different informants are also provided in order to offer a more global view of the reality of the child. Some limitations must also be mentioned. In the ﬁrst place, we do not have any information about the improvement obtained in the follow-up of these children. Given that the intervention was multi-component and applied in a natural setting (home–school) and that it encouraged coordination between the participants, it is more likely that the long-term beneﬁts would be maintained. Second, the lack of a control group in the sociometric analyses also limits the interpretation of the results. Nevertheless, it is unlikely that the passing of time alone would produce such important improvements in the interpersonal relationships. One last limitation is related to the sample size. Its low number recommends the use of nonparametric statistical analyses, which have less discriminatory power. To conclude, our ﬁndings, together with those from other previous studies, indicate that multi-component, multi-contextualized interventions can reduce the many problems of the child with ADHD and foster his/her socio-personal adjustment. However, it would be advisable to try to increase the efﬁcacy of the ADHD treatment as much as possible, reﬂecting on the conditions that would make up an ‘‘Ideal’’ intervention. Thus, interventions in the school context must focus on multiple objectives in all the areas in which these children present problems and involve mediators other than just the teachers themselves. We clearly believe in a close clinic–home–school collaboration that includes the family, the formal and informal educational institutions and society in general. In this same sense, Chronis et al. (2006) defend the need to overcome reductionist and partial proposals and take on a contextualized and multi-component approach with an emphasis on prevention, the active role of parents and teachers and a multimodal intervention, maintaining these over time so the desired generalization can occur. The teachers should take into account the strategies that can be

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implemented in the classes throughout the school years. The educational teams in the schools should meet periodically to change or alter the strategies depending on the results. It is also important to keep in mind the coordination of interventions in the school with other types of treatment (like medication) and the interaction between them.

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NONVERBAL LEARNING DISABILITIES AND ARITHMETIC PROBLEMS: THE EFFECTIVENESS OF AN EXPLICIT VERBAL INSTRUCTION MODEL Johannes E. H. Van Luit ABSTRACT In recent years, there has been a growing interest in nonverbal learning disabilities (NLD). Based on the description of this syndrome, the literature offers some guidelines for the intervention of children with NLD. However, studies on the effectiveness of these guidelines are rare. This study examined the inﬂuence of explicit verbal instruction on the arithmetic skills of ﬁve children with NLD in a pedagogical center in the Netherlands. The children were given direct verbal instruction twice a week for 10 weeks. The aim of this instruction was to teach them to multiply and divide. Additionally, the consequences of the direct verbal instruction on their strategy use and verbal problem-solving skills were investigated. The inﬂuence of the given instruction on the task orientation of the children was also assessed using a behavior observation scale. The results showed both, that is, the children took advantage of the direct verbal instruction and demonstrated quantitative and qualitative progress. Policy and Practice Advances in Learning and Behavioral Disabilities, Volume 22, 265–289 Copyright r 2009 by Emerald Group Publishing Limited All rights of reproduction in any form reserved ISSN: 0735-004X/doi:10.1108/S0735-004X(2009)0000022011

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Nonverbal learning disabilities (NLD) is a neuropsychological developmental disorder, characterized by a proﬁle of skills and deﬁcits in neuropsychological, socio-emotional and academic areas (Antshel & Khan, 2008). The neuropsychological skills are in the auditory–verbal area. As a result of good auditory perception, children with NLD develop strong attention and have a relatively good memory for verbal and auditory material. Because of this they prefer verbally presented material and in the long term develop good linguistic skills. They are good at learning simple verbal material by heart; and after enough practice, they master simple motor actions as well. Rourke (1989, 1995) published several articles about the implications of this disorder. The neuropsychological deﬁcits he discussed concern tactile and visual perception, complex psychomotor functions and the processing of new and complex information. Children with NLD experience difﬁculties in tactile and visual attention and memory, exploratory behavior and tactile– perceptual and visual–spatial organization. Therefore, they have problems with nonverbal skills, concept formation, problem-solving and testing hypotheses (Rourke, 1995). In spite of good verbal skills, deﬁcits have also been observed in semantics during spoken and written language. Their speech is characterized by many repetitions, disturbed prosody (intonation, accents and pitch) and they have a tendency to take everything literally and have a limited sense of humor (Serlier-Van den Bergh, 2002). Rourke (1995) suggested that there were causal relationships among these neuropsychological skills and deﬁcits and skills in the socio-emotional and academic areas. The socio-emotional deﬁcits concern adjustment to new situations, social competence and emotional stability. Children with NLD have difﬁculties with social perception, social judgment and social interaction skills (Serlier-Van den Bergh, 2002). In the academic area, with frequent practice (technical) reading and spelling develop well. According to Rourke (1989, 1995), it is from the 2nd grade that arithmetic skills and reading comprehension lag behind early reading skills and spelling. Such outcomes are a result of visual–spatial deﬁcits, deﬁcient concept formation and problem solving. According to Rourke (1989), the NLD syndrome should be thought as an aspect of the ﬁeld of learning disabilities. However, this syndrome is not included in recent classiﬁcation systems like the DSM-IV-TRt (APA, 2000). According to Ruijssenaars, Van Luit and Van Lieshout (2004), this is because the NLD syndrome is described as a series of causes and effects; in order to speak about a learning disorder, the various hypothesized causes and the resulting weaknesses need to be conceptually disentangled. Danckaerts (2001) criticized the NLD concept and stated, among other

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things, that there was a need for empirical evidence of the NLD syndrome. Deﬁcits in the white matter of the brain or a dysfunction of the right hemisphere in children with NLD have not yet been proven in neurological investigations. There is also not enough evidence that the characteristics of NLD occur in combination with each other and are mutually reinforcing (Kinsbourne, 1997). The characteristics of NLD also overlap with those of other disorders such as ADHD and Asperger (Drummond, Ahmad, & Rourke, 2005). NLD cannot be clearly differentiated from these disorders using objective criteria (Danckaerts, 2001). Moreover, it is not possible to diagnose NLD univocally and because it is clear how many distinct characteristics have to be present in order to make a diagnosis. The criteria are equivocal and appropriate test instruments are lacking. Although the NLD syndrome has been severely criticized and its existence has been questioned (Danckaerts, 2001; Van Luit, Kroesbergen, Den Engelsman, & Van den Berg, 2003), NLD is increasingly being identiﬁed in clinical practice. Especially in practice it is often recognized in the academic domain, such as arithmetic.

ARITHMETIC PROBLEMS IN CHILDREN WITH NLD Arithmetic problems seem to occur in children with NLD. These problems are related to understanding arithmetic concepts, changes to operations, generalization of problem-solving strategies, application of procedures (partly as a result of the poor ability to visualize arithmetic procedures) and reasoning. According to Strang and Rourke (1985), visual–spatial deﬁcits cause problems with spatial organization (e.g., arranging numbers correctly one under another) and problems with distinguishing visual details (e.g., numbers and operations signs). Strang and Rourke (1985) acknowledge that these arithmetic problems and a number of the aforementioned errors have also been observed in children with other neuropsychological problems. Nevertheless, according to the authors, children with NLD can be distinguished from those with other neurological problems, because they make (1) a greater diversity in mistakes; (2) more mistakes than other poorly achieving children and (3) predominantly mental arithmetic mistakes, which are directly related to their poor understanding judgment and reasoning. Typically mental arithmetic can be acquired after much practice, but the deﬁcits in concept formation and problem solving and these students’ inability to visualize arithmetic procedures cause obvious weaknesses in arithmetic skills (Serlier-Van den Bergh, 2002).

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INTERVENTIONS FOR CHILDREN WITH NLD With respect to treating children with NLD, general guidelines for teachers are most common. These guidelines (see Bachot & Ko¨nig, 2001; Rourke, 1989, 1995; Thompson, 1997) can be organized into suggestions for (1) adapting the environment (e.g., predictability, structure, logical step-bystep instruction and avoiding visual–spatial material), (2) making use of the students’ strengths (e.g., using verbalizations for teaching knowledge and skills) and (3) training those skills that have been poorly developed (e.g., by learning conversation techniques, nonverbal behaviors, problem-solving skills and generalization skills). These guidelines, however, are mainly based on the known weaknesses of children with NLD. Suggestions for instruction are mainly concerned with emphasizing well-organized, logical, step-by-step verbal instructions, in which problemsolving strategies are explicitly taught (Strang & Rourke, 1985). Step-bystep instruction provides support within the learning process (Thompson, 1997). By describing the steps verbally, the hypothesized verbal skills of the children with NLD are involved (Strang & Rourke, 1985). Because of their weak automaticity and their inability to generalize spontaneously, repeated practice and explicit teaching of generalization skills are also considered important as part of the intervention (Thompson, 1997). In addition, lack of visual reﬂection and poor motor production worsen their difﬁculties in learning arithmetic (Bachot & Ko¨nig, 2001). That is why there should be changes to the instructional materials, such as avoiding visual materials (i.e., drawings, diagrams, tables, busy or complex story) and ensuring the students have enough space on the page for writing. The students’ comprehension problems and their weak problem solving mean that irrelevant information in story problems should be removed. Finally, because of their poor visualization abilities children with NLD need to work with material for a longer time (Thompson, 1997). These suggestions for assisting children with NLD to learn arithmetic correspond strongly with the general principles of instruction that should be used with children with speciﬁc arithmetic problems (Ruijssenaars et al., 2004). These researchers described the following instructional principles: direct instruction, structuring, isolating partial steps, activities to develop generalization and practice activities to develop automaticity. The advice for teachers with respect to teaching arithmetic to children with NLD is therefore not very speciﬁc. According to Ruijssenaars (2001), the description of NLD provides little information about an intervention for those with NLD. He stated that an analysis at the level of the individual student is

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necessary to determine what should occur with respect to content. To date there is little or no empirical evidence indicating that the suggested guidelines for instruction for children with NLD are effective. They are merely based on the proﬁle of skills and deﬁcits of the NLD syndrome. In the current study, the quantitative and qualitative effects of explicit direct verbal instructions on the arithmetic skills of children with NLD areassessed. Based on the hypothesis that verbalization is an important component of intervention for children with NLD (Bachot & Ko¨nig, 2001; Rourke, 1989; Strang & Rourke, 1985), an improvement in the arithmetic skills of these children can be expected.

SPECIAL EDUCATION IN THE NETHERLANDS In the Netherlands, school attendance is compulsory for all children between the ages of 5 and 16. From the age of 16 there is a 2-year, part-time compulsory education phase (Min. O.C.&W., 2006). Children generally start attending primary school at the age of 4, and continue until 11 or 12 years. In the ﬁrst grade children receive some 800 h of education annually, whereas in the higher grades 1000 h of education are given. A week consists of ﬁve school days. The Dutch educational system is characterized by homogeneous grouping. Children who do not master the educational matter may have to repeat a year. In this year–group system children have to deal with a set amount of educational material throughout the year. Generally, children (and their parents) receive a progress report several times a year, which may also serve as the basis for the decision for a child to repeat a year. The end of primary school is marked by tests (national examinations) in which the majority of schools participate. This assessment procedure is important in the process of choosing the best type of secondary education placement. After a relatively short transition period (1 or 2 years) in a secondary school, the pupils have to choose among the different types of secondary education. Special education refers to a separate system of special provision. This includes the peripatetic supervision of pupils in mainstream education. Separate primary- and secondary special education is provided for children for whom it has been established that a special approach is most appropriate. Special educational provision currently has 10 different categories, including schools for students with hearing impairments, visual impairments, physical handicaps, severe mental retardation and pupils with serious behavior problems. These 10 types of provision are in separate

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schools. There are also specialist departments located within particular types of special education schools (e.g., a department for children with severe speech disorders in a school for hearing impaired children or a pedagogical day care institute for children with co-morbid difﬁculties like behavior problems and NLD). Pupils returning from special to mainstream education are entitled to certain facilities, as are pupils with sensory, physical or multiple handicaps, who although are eligible for special education have not been referred to a special school. These facilities in the form of the so-called preventive ambulant teaching are used to an increasing extent. The participation rate in special education varies according to handicap and age group. Overall, approximately 1.8% of all children of primary- and secondary school age participate in separate special education. There has been a remarkable growth in pupils attending separate special schools over the past decades. The growth has not been equally evident in each type of school.

METHOD Participants The study was conducted in one school, which is part of a pedagogical day care institute. In order to participate in the study, the pupils had to meet the following criteria: demonstrate most of the characteristics of the NLD syndrome, be at least 8 years, have a signiﬁcant deﬁcit in arithmetic when their level of reading and/or spelling. In this study, the children had to have problems in multiplication and division, but have adequate skills in addition and subtraction. Based on an analysis of the ﬁles of all the children at the school, seven children were selected who met the criteria and who had been diagnosed as having NLD by a psychiatrist from the pedagogical day care institute. Next a national test of arithmetic basic skills was administered, ﬁve out of seven pupils who met the requirements with respect to these arithmetic skills were selected. The ﬁve pupils came from three classes. The parents of these ﬁve pupils agreed to their child’s participation in the study. The pupils’ names are pseudonyms to protect their privacy. Based on neuropsychological investigations three of the ﬁve children (Bart, Joris and Pim) had been diagnosed with NLD. The other two children (Carmen and Simon) could be described as ‘probably having NLD’. All pupils met the following NLD characteristics: a VIQ-PIQ discrepancy of at least 10 points, visual–spatial deﬁcits, motor problems, problems in

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Table 1. Name Bart Joris Simon Carmen Pim

IQ-Scores and Ages of the Five Children.

Total IQ-Score

Verbal IQ-Score

Performance IQ-Score

Age (Years)

90 73 88 63 81

98 89 95 71 89

83 64 82 61 77

9.4 10.2 9.7 9.8 12.3

arithmetic compared to their achievements in reading and/or spelling, social–emotional problems and difﬁculty with adjusting to new or unexpected situations. Bart also had deﬁcits in visual and tactile perception, problems with organization and planning and problems in the area of concept formation and problem solving. Joris also showed relatively weak visual attention and problems with organization and planning. Pim also had difﬁculty with recognizing emotions and showed deﬁcits in cognitive ﬂexibility. Table 1 shows some of the characteristics of the children at the start of the intervention. Three of the ﬁve children had below average IQ-scores. Carmen’s Total IQ-score was more than two standard deviations below the mean. Thus, it seems that she had an intellectual disability. Nevertheless, the psychiatrist diagnosed both Carmen and Joris as children with NLD.

Design This study investigated the effects of a direct verbal instruction model by using of a N ¼ 1 design. In such a design, children are considered to be separate research groups and there is no control group. The study comprised three periods: the baseline period, the intervention period and the post-test period. During the baseline period of three weeks, the children had no instruction focusing on the topic and six arithmetic tests were administered. These assessments indicated the pupils’ baseline level. The children received 45 min of intervention, twice a week, for a period of 10 weeks. Each time 35 min was spent on instruction and 10 min on a test administration. During the post-test period of 3 weeks, 6 tests were administered. At the end of the baseline period and at the start of the post-test period, the pupils’ strategy use was assessed. Especially children’s verbalizations during problem solving were videotaped in order to examine their strategy

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use. After each intervention session, a behavior questionnaire, which examined children’s task orientation, was completed by a research assistant. The three class teachers also completed this questionnaire concerning the task orientation during the regular arithmetic lessons at the start and end of the intervention period.

Test Instruments Parallel arithmetic tests were administered during the baseline, after each intervention session and in the post-test period. Each test consisted of 25 items: 5 multiplication items (tables 0 up to and including 10), 5 multiplication items (speciﬁcally, a(r10) b(W10 and r20)), 5 division items (division tables 1 up to and including 10), 5 division items with remainders (up to and including the 10 times table and double digits) and 5 story problems involving multiplication and division. The story problems were simple and all the irrelevant information had been removed. The aim of the story problems was to examine whether the pupils were able to generalize the strategies they had learned to other situations. In order to take account of the pupils’ poor motor control functioning and their visual–spatial deﬁcits, the items were spread over three A4-size pages. The ﬁrst page comprised the 10 multiplication items, the second 10 division items and the third page the story problems. The assessment of strategy use at the start and end of the intervention consisted of similar problems. As they solved the problems, the pupils were asked to explain their actions. These verbalizations were examined to determine whether the pupils could justify their actions and whether or not they were aware of possible problem-solving strategies for speciﬁc types of arithmetic problems.

Other Material Worksheets from the ‘MASTER program’ (Van Luit & Naglieri, 1999) were also used. These sheets contained a limited number of items. The 24 worksheets were similar to those typically used in teaching arithmetic in this school. Different worksheets were completed one at a time during the sessions. That is, on completion of a worksheet the pupils received a new one. This way children’s progress and their speed in completing each sheet could be mentioned. The number of ﬁnished worksheets varied per child and so did time and the number of problems completed.

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An existing curriculum-based ﬂashcard program was used to develop children’s automaticity of the multiplication and division tables. In class they used the same computer program. Children’s motivation was stimulated by means of several reward systems. An individual table diploma could be gained and in addition each pupil could earn stickers. When the pupils had earned six stickers they could choose to trade them for postcards or little toys.

Verbal Instruction The intervention used the direct instruction model (see Van Luit & Naglieri, 1999). The model consists of six stages: (1) daily review, (2) presentation of new material, (3) scaffolding learning activities, (4) individual independent practice, (5) feedback and (6) periodic review. During the stage of scaffold learning there is a gradual release of the teacher’s responsibility for a learning task and an increase in the pupil’s responsibility. The material is presented in small steps. During the intervention three types of instruction can be offered. Each type reﬂects an increase in the intensity of instruction. The type of instruction that is used is dependent on the pupil’s individual needs; thus one, two or even three types can be offered to one pupil depending on one’s need: 1. A brief explanation of the indications is provided and examples are discussed. Attention is also paid to connecting existing knowledge to the new concepts that need to be learned. 2. Possible problem-solving strategies are discussed with the pupils. The processes or strategies for solving the problems are verbalized. Explanations are kept brief and to the point. 3. Instruction is offered by means of a procedure known as ‘model learning’. This procedure encompasses ‘demonstrating–doing it together– imitating’ learning task and can be subdivided into ﬁve stages: Demonstrate: The teacher demonstrates the task, talking aloud. The pupil observes. Do it ‘together’: The teacher and the pupil jointly undertake the task while seated next to each other. Both of them verbalize the problemsolving strategy aloud. The pupil follows the teacher’s example. Do it ‘separately’: The pupil works on the arithmetic task by performing the actions and verbalizing the problem-solving strategy.

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During this time the pupil can still use the support of the teacher. At the same time the teacher completes the steps independently as well. Imitate audibly: The pupil ﬁnishes the task independently, whispering the problem-solving strategy audibly. These verbalizations are limited to the core steps. The actions become less detailed and the verbalizations increasingly pithier. Imitate inaudibly: The pupil ﬁnishes the task, repeating the instructions inaudibly. The instruction has now changed into self-instruction. At this point, it is assumed that the pupil has mastered the core aspects of the problem-solving strategy. In all three types of instruction, the actions and partial steps were offered verbally, alongside a written action plan. Teachers have the option of using concrete material. During the intervention in this study, the instructional materials were provided. Concrete materials such as marbles, rubbers, pencils and rulers (number lines) were provided as support. All materials were selected keeping the pupils’ interests and needs in mind.

Procedure The study began in January 2008 and lasted 16 weeks in total. Based on the results of assessment undertaken during the baseline period, the children were divided into two groups: group A and group B. The class programs, the pupils’ baseline levels and their characteristics were taken into account. Group A consisted of Bart, Joris and Simon and group B consisted of Carmen and Pim. In the ﬁrst 10 weeks the pupils worked under the supervision of a research assistant, an experienced remedial teacher, twice a week for 45 min each time. The intervention was offered by the same person. Both groups started the intervention by learning to automatize their knowledge of the times tables and the approach strategy of those times tables that they did not know automatically. Group A began with easier times tables (tables 1, 5 and 10) and group B started with more difﬁcult times tables (tables 7, 8 and 9). Carmen and Pim appeared to have reasonably good control of their times tables, but they did not know how to apply a problemsolving strategy when they were not able to immediately answer a table task item. This is why they received instruction in one times table. The instruction attempted to ﬁt the pupils’ individual instructional needs as appropriately as possible. Group instruction and individual instruction were alternated in both groups. This was dependant on the pupils’ speed. Both

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groups started with group instruction, but the pace in the groups soon differed for each pupil. Simon (group A) and Pim (group B) appeared to be quicker than the other pupils on the uptake of the context. Therefore in both groups two ‘instruction moments’ were introduced. In group A, Simon received individual instruction, while separately Bart and Joris received joint instruction. In group B Carmen and Pim received mostly individual instruction. The intensity of instruction was dependant on the pupil and the type of problem. For Pim and Simon short explanations were sometimes enough, but they (Simon to a greater extent) also needed support with respect to working through the problem-solving strategies. A written action plan offered Simon a great deal of support with respect to his actions. With this support he was able to work well on his own. Bart, Joris and Carmen appeared to need more support. The brief time during which the ﬁxed problem-solving strategy was used plus a written action plan was not enough for them. These pupils needed a more simpliﬁed type of model learning. The demonstration, doing it together and imitating occurred as planned in the stages of model learning, but with less intensity. Stages 2 and 3 (do it ‘together’ and do it ‘separately’) were also not applied as described. Doing it together consisted of jointly going through the steps, but the research assistant constantly had to give feedback to the pupil when they completed each partial step. The problem-solving strategies also had to be undertaken in small partial steps. These steps were discussed a couple of times together with the pupils ﬁrst, before they were understood and could the pupils could apply them on their own. At the start, instruction made use of concrete materials. Bart, Joris and Carmen needed the instruction to be repeated several times and they also needed repeated practice. All three of them took advantage of a written action plan. They often also looked for support from the use of concrete materials. However, they did not always know how to use these materials adequately and correctly. After a period of instruction, Bart and Joris appeared to be sufﬁciently competent in applying the problem-solving strategies to the times table items, but they had a great deal of difﬁculty with automatizing their knowledge of the times tables. In order to progress to the next type of problem, they received a card that was placed on the desk for support in learning new problem-solving strategies. In addition, during each session attention was paid to automatizing the times tables. Carmen appeared to have a great deal of difﬁculties understanding how to solve the story problems. During the intervention this was practiced many times, often with the use of concrete materials. At the end of the intervention period she still needed a lot of support. Simon and Pim completed all of the worksheets

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in a short time and so after consulting their teachers, they were given extra arithmetic worksheets. These were used to support their learning of arithmetic in their classrooms. In this way they continued to participate in the intervention sessions. During the entire intervention period, the children did not receive instruction in multiplication and division in their classes. However, they did have the opportunity to practice the automatization of the tables on their own on the computer in their classrooms. The extent to which they practiced on the computer in the classrooms depended on the class schedule and the opportunities given by the teacher. After a few sessions, it was clear that Bart and Carmen had difﬁculty with the rules and expectations with regard to their behavior. They especially found it difﬁcult when they had to work on their own, or in silence. Both children were offered the rewards for showing good behavior. This had a positive effect on the children’s attitude to work and their behavior.

RESULTS Quantitative and qualitative data were examined to determine whether direct verbal instruction had positive effect on the children’s arithmetic skills.

Quantitative Results The pupils’ test results were converted into the percentage of correct answers for each test (see Fig. 1). A visual examination of this ﬁgure shows the test scores at baseline, intervention and at post-test. The criteria for mastery was 80%. This is shown on the graphs by means of a horizontal line. When a pupil obtained a score equal to or more than 80%, this meant that the pupil had sufﬁcient skill in multiplication and division. After tests 12 and 28, the pupils went on 1 or 2 weeks holiday (see the double vertical lines in Fig. 1). By means of a time series analysis (Blumberg, 1984; Tryon, 1982, 1984), the trend that can be visually observed was tested for statistic signiﬁcance. Speciﬁcally z-scores are presented in Table 2 for each period. The visual trend noted in the baseline period for Bart, Joris and Carmen points to a plateau. The statistical analysis conﬁrms this view. Simon and Pim seemed to make little progress during the baseline period. The statistical analysis showed that these trends were stable and thus not meaningful. Therefore, none of the children showed signiﬁcant growth during the baseline period.

Nonverbal Learning Disabilities and Arithmetic Problems

Fig. 1.

Test Scores (%) per Participant.

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Table 2. Name

Bart Joris Simon Carmen Pim

z-Values for the Three Research Periods per Pupil.

Baseline Period

Intervention Period

Post-Test Period

n

z

n

z

n

z

6 6 6 6 6

1.630 0.609 1.876 0.432 0.740

20 20 20 20 20

3.816* 3.920* 4.117* 3.646* 2.242*

6 6 6 6 6

0.497 1.402 0.108 0.053 0.174

Note: n ¼ number of parallel tests; * signiﬁcant when ao.01.

This means that their arithmetic skills stayed stable during this period and were not changed by regular education. The signiﬁcant scores that were derived during the intervention period conﬁrm the positive trends found in Fig. 1. All pupils showed progress in their arithmetic skills. The 80% mastery level was obtained by three pupils: Carmen, Simon and Pim. Bart and Joris achieved mastery levels between 50% and 60%. This indicates that these students had inadequate skills in multiplication and division with remainders. The trends shown by the children during the post-test period seem reasonably stable. The z-scores from the different measurements conﬁrm this stability. This means that after the intervention, children do not revert to previous achievements. Qualitative Research Results The foci of the process assessments are the pupils’ verbalizations and the strategy use. Two observers independently scored the verbalizations. The interobserver reliability was between .79 and .87 and therefore was moderately strong. In addition, a behavior observation scale was used to examine whether or not the intervention led to improvement in the pupils’ task orientation. Again, two observers independently observed the children’s behavior. The proportion of agreement was between .81 and .86, which again can be viewed as moderately high. The following sections disuss the results pupil by pupil. Bart During the ﬁrst process assessment, the baseline period, Bart appeared to have almost no knowledge of multiplication and division items. He correctly completed only the simple multiplication items (times tables 0, 1, 2 and 10)

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and one division task (6:3 ¼ ). He did not master the items above 10 and the division items (with a remainder) at all. Bart had many problems with verbalizing his actions and he indicated that the questions were very difﬁcult. He was not able to explain how he had solved the tasks. Moreover, he was not able to understand relationships between multiplication and division and addition and subtraction. In the case of the story problems, he verbalized the actions that should have been completed in order to solve the problems reasonably well. However, when he used the concrete materials he became entangled in his own actions. At the end of the intervention period, Bart was able to solve all times table items. Bart had not yet automatized all tables, but for those times table items that were not automatized he consistently used a splitting strategy, which involved chunking the multiplication task into two (7 4 ¼ 5 4 and 2 4). In addition, he used the splitting strategy with 10 (13 7 ¼ 10 7 and 3 7). As a consequence of his slow processing and his poor automatization skills he only began to tackle division in the last stage of the intervention. Therefore, division items were not mastered by the end of the intervention period. Bart was able to successfully complete division items using his automatized times tables. Bart was not able to solve more difﬁcult division problems. He was not able to complete these problems with the help of partial steps nor was he able to say which strategy could be applied in these situations. At post-test Bart could answer most of the story problems correctly, but he was not always able to describe clearly how he had executed particular steps. During the secondprocess assessment, Bart was more able to verbalize his actions when solving multiplication items. However, the verbalization of actions remained difﬁcult. Bart was also not able to verbalize and explain the relationship between division and multiplication items, nor was he always able to explain why he took particular actions. Furthermore, he was unable to create stories in situations where multiplication and division items were assessed. The result of Bart’s performance on the behavior observation scale revealed that his concentration and motivation were variable during the intervention. There was a small decrease in his continuous seeking of conﬁrmation. Bart had a lot of difﬁculty with asking for help especially with respect to the content, and he showed little change with regard to this aspect of learning. In class, Bart showed greater concentration and a more positive attitude. At the end of the intervention period, Bart was less quickly distracted during instruction, assessment moments and the completion of the group tasks. Bart was also better able to work on his own in the classroom lessons. He needed less encouragement and he was less inclined to immediately ask for help without ﬁrst trying the task himself.

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Joris During the ﬁrst measurement, Joris was able to answer the simple table items (0, 1, 2 and 10) and verbalize them correctly. It was remarkable that he was able to formulate an addition task in the case of a simple task (2 3 ¼ ), but not in the case of more difﬁcult items (4 5 ¼ , 8 9 ¼ ). Joris did not master the multiplication items above 10 (type a (r10) b (W 10 and r20)) and the division items at all. He was able to answer a few story problems correctly, but he could not explain his actions verbally. Learning to automatize the tables and the partial steps of the learned strategies took Joris much effort and energy. This development was going very slow, which resulted in not having automatized all of the tables during the second-process measurement. He was better able to verbalize his actions and he handled different problemsolving strategies: reversing the task (5 4 ¼ 4 5), searching for a near task (10 8 ¼ 80, so 9 8 ¼ 808 ¼ 72) and the splitting strategy with 10 (2 14 ¼ 2 10 and 2 4). During the second-process measurement, Joris was better able to make the division items, due to which he knew the matching multiplication task immediately. He also could make a few division items with remainder. When he could not answer division items directly, he could not verbalize the accompanying possible strategy as well. Answering the story problems went better than during the ﬁrst process measurement, but he kept having difﬁculty explaining these items verbally. He was, for example, not able to explain why he applied a multiplication task in the case of a particular story problem. At the end of the intervention period, Joris had acquired a good insight in division and multiplication, although he did not master the relation between multiplication and addition completely. Especially in the case of story problems he kept having difﬁculties in applying this relation. During the entire intervention period, Joris showed a sufﬁciently stable concentration. With regard to motivation Joris showed a clear growth, especially as a consequence of showing more interest and less aversion, by doing better his best when answering questions, showing more perseverance and less need to be stimulated. Nevertheless, in class changes in task orientation were observed.

Simon During the ﬁrst process measurement, Simon appeared to be able to answer the simple table items (1, 2, 3, 5 and 10) reasonably well, but these were not

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automatized yet. He did already use a few simple strategies, such as reversing the task and splitting the task in several partial steps; in the case of items he recognized immediately (7 4 ¼ , 7 2 ¼ 14, 14þ14 ¼ 28). Simon did not master the multiplication and division items above 10. He did show a reasonably good mastery of the story problems. He could verbalize his actions reasonably good based on the content of the story. In the case of the ‘bare’ items, Simon had difﬁculty with the relation between multiplication and addition and between multiplication and division. During the second process measurement, Simon showed a mastery of the table items. He also mastered the multiplication items above 10, the division items and the division items with remainder. Simon showed little progress in his verbalizations, except in the case of the division items. During the ﬁrst process measurement he could not explain these items at all, but during the second measurement he could explain his actions well and he understood the relation between division and multiplication. However, he was not able to explain a task by means of a story. During the intervention period, Simon had a moderate concentration and this did not improve during the instruction period. With regard to motivation and independence Simon showed a strongly varying attitude as well; during one session he could concentrate himself well and he showed a good motivation, but during the next session he could be very distracted and unmotivated. His attitude toward work seemed also to be dependant of the day on which he was picked up; at the start of the week he was often hard to handle, whereas at the end of the week he showed a better attitude toward work. In class, Simon did show an improved attitude toward work. His concentration was developed better and he was not so soon distracted any more. He also showed some progress in his independence: he showed less aversion, he hesitated less often to ask for help with respect to content, he needed stimulation less often and he had less need for constant conﬁrmation. Simon did not show progress in his perseverance.

Carmen Carmen appeared to have disposal of automatized table knowledge already before the intervention period. Tables 4, 6, 7 and 8 were however not yet mastered completely. The multiplication items above 10, as well as the division items (with remainder), were not mastered. She solved all of the story problems incorrectly: she did not read the story well with respect to content, and added all of the numbers she saw immediately. In spite of

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stimulation to read a story well, Carmen remained unable to understand what was standing there and which actions were asked of her. During the second process measurement, Carmen mastered all of the table items and the multiplication items above 10. These last items were solved on paper in two partial steps. She could explain the steps well. The division items were mastered for the greater part as well, by searching the correct accompanying table task. The division items with remainder were yet too difﬁcult for Carmen: she solved these items by searching for the nearest multiplication task. She would become confused doing this and she seemed to have insufﬁcient insight in the concept ‘remainder’ in the sense of what exactly was the rest in a task. The story problems were almost all made correctly, but Carmen was not able to verbalize her actions adequately. She made the task without reading the story problems well; after reading she was not able to explain the problem. Carmen was also not able to make up a story herself in the case of a simple multiplication task (2 3 ¼ 6). It did work in the case of one or two simple division items (6:3 ¼ ). In the case of items with a bit larger numbers she still became confused frequently. During the intervention period, Carmen showed a varying picture concerning her concentration, motivation and attitude toward working on tasks. In general Carmen was quickly distracted, she often did something different from the assigned task and she needed much stimulation. She was strongly inclined to ask for help immediately, without trying the task herself ﬁrst. Yet she did show increasingly more effort: she did her best when answering questions and she often started a task smoothly. She did not show changes in her attitude toward working on tasks. In class, her distraction was also noticed. At the start of the intervention period, Carmen showed a weak attitude toward working on tasks, and during the research period she did not show progress with regard to this. The teacher observed at the start as well as at the end of the intervention period a weak perseverance, a strong need for stimulation and a very strong distraction. In class, Carmen did not start a task quickly, in contrast to the intervention.

Pim During the ﬁrst process measurement, Pim showed a sufﬁcient mastery of the tables and the multiplication items. He could verbally explain his actions concerning multiplication items reasonably well. Pim did not master the division tables and division items with remainder for the greater part and his

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arithmetic verbalizations were insufﬁcient. He made the story problems correctly already during the ﬁrst process measurement and he could also explain these reasonably well. During the second measurement, Pim showed mastery in all areas: the tables and division tables were by then automatized. In his verbalizations, he showed progress mainly in the case of the division items. Pim was better able to verbalize his actions and to explain the relation between division and multiplication. He did, however, show little progress in verbalizing his actions clearly in the case of multiplication items and story problems. He still was not able to make up stories himself in the case of simple multiplication and division items. At the start of the intervention period, Pim had a good attitude toward working on tasks; concentrated, sufﬁcient effort, sufﬁcient independence and perseverance. During the intervention period some decline concerning his task orientation was observable: he concentrated less during the individual processing, he showed more often task-avoidant behavior, he showed more aversion against tasks and he had to be stimulated more often. He did remain doing his best during the instruction and while answering questions. In class, Pim showed a slight progress in his concentration, but his task orientation decreased somewhat here as well. He showed more aversion to learning tasks, he started a task less smoothly and he had to be stimulated more frequently.

SUMMARY AND DISCUSSION The results show that all of the children have reached a clear growth in the extent of mastery of multiplication and division. At the end of the intervention period Pim, Carmen and Simon dispose of automatized table knowledge. Moreover Pim and Simon master the division items completely. At the end of the intervention period, Bart and Joris master sufﬁcient strategies to use a correct solving strategy in the case of table items and multiplication items above 10 (a (r 10) b (W 10 and r 20)). Solving table items (tables 4, 6, 7, 8 and 9) and multiplication items above 10 took most of the time yet several halfway steps. During the second process measurement, the division items were not completely mastered by both of them: only the items, in case of which they know immediately the matching multiplication task, they can answer correctly. In addition, they do not handle other solving strategies yet.

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The pupils’ working speed has possibly been of inﬂuence on the extent of mastery at the end of the intervention period. Bart and Joris had a slower working speed and weaker automatization skills than the other three children, because of which they have completed comparatively less practicing matter. The results show this as well: Bart and Joris show, compared to Pim, Carmen and Simon, less mastery of multiplication and division. The positive development in the test results goes together with qualitative improvements in the use of solving strategies. All of the children show progress in handling strategies. At the end of the intervention, the children were able to handle different strategies in the case of the multiplication items. When solving the division items, Pim and Simon were able to apply several strategies. Carmen, Bart and Joris had knowledge of the relation between division and multiplication, but they were not able to also apply other strategies in the case of division items. The verbalizations of all the pupils show, indeed in different areas, a slight growth. Bart, Joris and Carmen are better able to formulate their solving strategies in the case of multiplication items clearly. Simon and Pim show little growth in the area of multiplication, but at the end of the intervention they can explain the actions in the area of division with increased clarity. It is remarkable that at the end of the intervention period all of the children still have difﬁculty with making up a story (context) for a task. Besides, Bart, Joris and Carmen have great difﬁculty with verbalizing their actions in the case of story problems. Simon and Pim do not show any progress with regard to this. On the behavioral level few changes are observable. Bart, Simon and Carmen show a varying concentration and motivation. Pim shows a slight decline in his task orientation as a consequence of a smaller motivation and concentration. Only Joris shows an improvement in his task orientation as a consequence of an increasing motivation. In class, Bart and Simon show an improved attitude toward working: they are more concentrated, less quickly distracted and need less stimulation. Joris and Carmen do not show any changes in their attitude toward working. In the case of Pim, the task orientation in class had somewhat decreased. Based on these, results can be concluded that a verbal step-by-step instruction appeared to be effective for teaching multiplication and division to children with NLD in a little treatment group. The children have come to a better mastery of the tables of multiplication and the division tables. Moreover, they are able to use and explain several solving strategies. The verbal instruction has nevertheless not led to demonstrable changes in attitude toward working.

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This study examined the effect of a verbal instruction on the arithmetic skills of children with NLD in a pedagogical day care institute. A distinction is made between a quantitative and qualitative component of the arithmetic skills. All of the children in the study show progress in multiplication and division. Considering quality, an increase can be seen in the use of adequate solving strategies and in the verbalizing of actions. The described research has nevertheless a couple of limitations. First of all generalizing the conclusions is not completely possible because of the limited sample size. The research has used a N ¼ 1 design, which means that the obtained results of the children cannot be compared to children in a comparable control group. Another limitation is the length of the intervention. Teaching new solving strategies in combination with the weak automatization skills of children with NLD, asks probably for a longer instruction period. Because of this limitation, in the case of two of the ﬁve children not, all of the learning matter could be treated. The question remains whether the children develop more insight in the mutual relations between multiplication, division, addition and subtraction and in the interpretations of story problems after a longer instruction period. Longitudinal research can possibly point this out. Another limitation of this research concerns the robustness of the diagnosis NLD. One of the criteria handled by Rourke (1998) for the diagnosis of NLD is a discrepancy between the verbal and performance IQ-score of at least 10 points at the expense of the performance IQ-score. Although all of the children in this research among others meet these criteria, the value of this can be disputed. Ruijssenaars (2001) states that discrepancies between the verbal and performance IQ-score are a normal phenomenon. A discrepancy of 10 points can be accidental. The greater part of the research population does not or hardly meets the assumption of Roman (1998) that in the case of children with NLD a discrepancy of at least 15 points can be expected. In our opinion it can even be discussed that distinguishing between two scales (verbal and performance), with each having a considerable standard deviation is especially disputable because the margin of error merely shall increase as a result of this. The danger of an incorrect interpretation of the discrepancy becomes only greater because of that. The importance of the discrepancy of 10 points as one of the criteria for the diagnosis of NLD is clearly disputed with this. Moreover, the criticism mentioned in the introduction leads to doubt about the diagnosis of NLD in the case of the children in this study. Although Rourke (1989) states that the VIQ-PIQ discrepancy in the case of older children (9–14 years) is of greater importance for the learning

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disorder than the general intelligence level, Serlier-Van den Bergh (1999) notices that the discrepancies seem to be smaller in the case of less able children. This is conﬁrmed in her research (Serlier-Van den Bergh, 2002), which shows that in the case of older children (9–12 years) a signiﬁcant discrepancy only can be found in children with a general IQ-score above 85. In children with a general IQ-score below 85, they do not or hardly ﬁnd signiﬁcant differences. Because of this, the question arises as to what extent the diagnosis of NLD is possible in the case of children with intelligence below average and what the diagnosis of NLD means for the children in this study who have below average scores in the intelligence test. With regard to the research population, it is thus notable that three of the ﬁve children have an intelligence score below average. This is possibly related to the sample selection from a population of children of a school connected to the Pedagogical Day Care Institute. In a school like this, an intelligence score below average is not an unknown phenomenon. Nevertheless it is remarkable that the instruction needs of the children in this research strongly seem to correspond to the instruction needs of other children with an intelligence score below average. Keogh, Whitman, and Maxwell (1988) conclude based on research that children with a mild retardation proﬁt more by a verbal self-instruction procedure than children without any retardation. Children with a low IQ-score have furthermore more often to contend with arithmetic problems than children with least average IQ-score. Because of the corresponding instruction needs and the relation between an IQ-score below average and arithmetic problems, the question can be asked whether the arithmetic problems of the children in this research are NLD-speciﬁc and do not primarily stem from limited intellectual capacities. Critical research on the relations between intelligence, arithmetic problems and the NLD syndrome is therefore considered necessary. Whether children with the probability diagnosis of NLD show similar arithmetic problems as children with mild mental retardation has to be investigated as well. Possibly, the arithmetic problems correspond and no distinction can be made in type of errors like Strang and Rourke (1985) mention. Regardless of the children’s intelligence level the diagnosis of NLD is anyhow under discussion, because the necessary elements for science-based diagnosis are missing (Van Luit et al., 2003). There is no clear deﬁnition of the number of characteristics that should be present for the diagnosis; there are insufﬁcient appropriate testing instruments and no clearly formulated criteria and procedures. As a result of this, in the case of the children in this research, NLD is diagnosed in different ways. Owing to generalization,

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the conclusions become especially difﬁcult. Being assigned to a NLD research group is dependant on the presupposed criteria and research instruments. Some of the children shall end in an NLD research group in one research but not in another research. As long as NLD is diagnosed in different ways, effect studies on intervention forms are difﬁcult to compare. Children in this study were found in a school for special education. Because of the Dutch school system, children with severe difﬁculties, in this study – among children with other handicaps – behavioral problems and NLD are placed in this special school. For adequate education a specialized teacher can give these children support in group sessions using their strong points and adaptation to their weak characteristics. When these children were in regular education they would be educated in different classes and would not have a specialized teacher. In this school of a pedagogical day care institute, these children receive the educational and instructional support they need. For research purposes, we were happy to ﬁnd these children with more or less the same handicap in one institution. Such a homogeneous group makes it possible to educate these children at the same time at a comparable level. This means that economically it is interesting to give group instruction instead of individual instruction when these children were not in an institution but in a regular primary school. As a result of the research ﬁndings and the critical notes made concerning the NLD syndrome, further research on the validity of the NLD concept is necessary. In this study, doubt is expressed about the diagnosis of NLD of the participating children, which gives rise to the question whether the research results can univocally be linked to intervention possibilities for children with NLD. At the same time, there is a need in clinical practice for handling advice for the intervention of children with NLD problems. The clinical practice therefore beneﬁts from effect studies on different intervention forms. The ﬁndings of this research show that a verbal instruction has a positive effect on the arithmetic skills of children, considered to be children with NLD by means of the current criteria. Further research shall have to reveal whether children with NLD proﬁt more by the verbal instruction handled in this study or by any another (verbal) instruction form.

REFERENCES American Psychiatric Association (APA). (2000). Diagnostic and Statistical Manual of mental disorders, DSM-IV-TRt (4th ed). Washington, DC: American Psychiatric Association.

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Antshel, K. M., & Khan, F. M. (2008). Is there an increased familial prevalence of psychopathology in children with nonverbal learning disorders? Journal of Learning Disabilities, 41, 208–217. Bachot, J., & Ko¨nig, C. (2001). Behandeling van het kind met nonverbal learning disabilities [Treatment of children with nonverbal learning disorders]. Tijdschrift voor Orthopedagogiek, Kinderpsychiatrie en Klinische Kinderpsychologie, 26, 78–89. Blumberg, C. F. (1984). Comments on a simpliﬁed timeseries analyses for evaluating intervention interventions. Journal of Applied Behavior Analyses, 17, 539–542. Danckaerts, M. (2001). NLD: Een (minder) valide concept? [NLD: A (less) valid concept?]. Tijdschrift voor Orthopedagogiek, Kinderpsychiatrie en Klinische Kinderpsychologie, 26, 114–118. Drummond, C. R., Ahmad, S. A., & Rourke, B. P. (2005). Rules for the classiﬁcation of younger children with nonverbal learning disabilities and basic phonological processing disabilities. Archives of Clinical Neuropsychology, 20, 171–182. Keogh, D. A., Whitman, T. L., & Maxwell, S. E. (1988). Self-instruction versus external instruction: Individual differences and training effectiveness. Cognitive Therapy and Research, 12, 591–610. Kinsbourne, M. (1997). Nonverbal learning disability. In: T. E. Feinberg & M. J. Farah (Eds), Behavioral neurology and neuropsychology (pp. 789–794). New York: McGraw-Hill. Min. O.C.&W. (2006). Primair onderwijs 2006–2007 [Primary education 2006–2007]. Den Haag, The Netherlands: Ministerie van Onderwijs, Cultuur en Wetenschap. Roman, M. A. (1998). The syndrome of nonverbal learning disabilities: Clinical description and applied aspects. Current Issues in Education, On-line: http://cie.ed.asu.edu/volume1/ number7/ Rourke, B. P. (1989). Nonverbal learning disabilities: The syndrome and the model. New York: Guilford Press. Rourke, B. P. (1995). Syndrome of nonverbal learning disabilities. Neurodevelopmental manifestation. New York: Guilford Press. Rourke, B. P. (1998). Frequently posed questions about the syndrome of NLD. Ontario, Canada: University of Windsor & Yale University (internal report). Ruijssenaars, A. J. J. M. (2001). NLD: Is het geheel meer dan de som der delen? [NLD: Is the whole more than the sum of the parts?]. Tijdschrift voor Orthopedagogiek, Kinderpsychiatrie en Klinische Kinderpsychologie, 26, 109–113. Ruijssenaars, A. J. J. M., Van Luit, J. E. H., & Van Lieshout, E. C. D. M. (2004). Rekenproblemen en dyscalculie: Theorie, onderzoek, diagnostiek, behandeling. [Arithmetic difﬁculties and dyscalculia. Theory, research, assessment and treatment]. Rotterdam, The Netherlands: Lemniscaat. Serlier-van den Bergh, A. (2002). Development and validation of the Dutch Nonverbal Learning Disabilities Scale and Dutch Preschool Nonverbal Learning Disabilities Scale. Waalre, The Netherlands: Praktijk Kinderneuropsychologie. Strang, J. D., & Rourke, B. P. (1985). Arithmetic disability subtypes: The neuropsychological signiﬁcance of speciﬁc arithmetical impairment in childhood. In: B. P. Rourke (Ed.), Neuropsychology of learning disabilities: Essentials of subtype analysis (pp. 167–183). New York: The Guilford Press. Thompson, S. (1997). The source for nonverbal learning disorders. East Moline, IL: LinguiSystems.

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Tryon, W. W. (1982). A simpliﬁed time-series analyses for evaluating intervention interventions. Journal of Applied Behavior Analyses, 15, 423–429. Tryon, W. W. (1984). A simpliﬁed time-series analyses for evaluating intervention interventions: A rejoinder to Blumberg. Journal of Applied Behavior Analyses, 17, 543–544. Van Luit, J. E. H., Kroesbergen, E. H., Den Engelsman, M. J., & Van den Berg, A. E. M. (2003). Prevalentie van NLD in een rekenzwakke populatie en CAS-proﬁelen van NLD [Prevalence of NLD in a population with arithmetic deﬁcits and CAS proﬁles of NLD]. Tijdschrift voor Orthopedagogiek, 42, 447–455. Van Luit, J. E. H., & Naglieri, J. A. (1999). Effectiveness of the MASTER program for teaching special children multiplication and division. Journal of Learning Disabilities, 32, 98–107.

IMPLEMENTING RESPONSE TO INTERVENTION: THE SYNERGY OF BEGINNING READING INSTRUCTION AND EARLY INTERVENING SERVICES Stephanie Al Otaiba, Carol MacDonald Connor, Barbara Foorman, Luana Greulich and Jessica S. Folsom ABSTRACT The primary purpose of this chapter is to describe a synergistic ‘‘hybrid’’ model of Response to Intervention (RtI) that combines individualized effective Tier 1 classroom instruction with powerful early intervening services. First, we provide an overview and explain how RtI traditionally has been conceptualized. Next, we illustrate how to implement a hybrid model that focuses on beginning reading instruction and also incorporates additional school-level resources. Finally, we will discuss implementation issues related to identifying children who need additional intervention and propose directions for future research.

Policy and Practice Advances in Learning and Behavioral Disabilities, Volume 22, 291–316 Copyright r 2009 by Emerald Group Publishing Limited All rights of reproduction in any form reserved ISSN: 0735-004X/doi:10.1108/S0735-004X(2009)0000022012

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Synergy refers to the combined impact of two things – in this case beginning reading combined with early reading interventions – being greater than the sum of their individual effects. The purpose of this chapter is to describe a synergistic or ‘‘hybrid’’ model of Response to Intervention (RtI) that emphasizes early prevention of reading difﬁculties by focusing on the nexus of primary instruction and secondary interventions for beginning readers in kindergarten and ﬁrst grade. We provide an overview and explain how RtI traditionally has been conceptualized. Next, we illustrate how to implement a hybrid model that focuses on beginning reading instruction and also incorporates additional school-level resources. Finally, we will discuss implementation issues related to identifying children who need additional intervention and propose directions for future research. Understanding how to implement RtI in the early grades is important because of a recent shift in federal policy. Previously, to qualify for special reading intervention, students had to demonstrate a relatively severe and unexpected discrepancy relative to their intelligence. New RtI policies promote a more preventative model that supports interventions for struggling readers before they fail to meet grade-level achievement standards. Speciﬁcally, in 2004 the Individuals with Disabilities Educational Improvement Act was passed that allowed school districts to use up to 15% of special education funds for preventing reading problems using RtI approaches. RtI approaches allow schools to ‘‘use a process that determines if the child responds to scientiﬁc, research-based intervention as a part of the evaluation procedures’’ for learning disabilities (Pub. L. No. 108-446 y 614 [b][6][A]; y 614 [b] [2 & 3]). Thus, RtI has largely been conceptualized as a general education initiative. The goal is to reduce the incidence of students identiﬁed as learning disabled (LD) by focusing on prevention through providing children who are at-risk for reading difﬁculties with evidencebased instructional services immediately, rather than waiting for children to fall far enough behind to qualify to receive remedial special education services. Shifting toward a policy of prevention is vital because poor early reading instruction explains poor reading achievement for far too many students (Snow, Burns, & Grifﬁn, 1998; Vellutino et al., 1996). Currently, over a third of American fourth graders perform below ‘‘basic’’ on the reading comprehension section of the National Assessment of Educational Progress (NAEP, 2007, National Center for Educational Statistics) and reading performance is markedly lower for minority students (e.g., 53% of Blacks and 50% of Hispanics at fourth grade performed below basic). Moreover, the modal age at which children qualify for services as ‘‘learning disabled,’’

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under ‘‘discrepancy’’ policies, is 11 years. By this age, reading difﬁculties become very difﬁcult to remediate (Fletcher & Foorman, 1994; Kennedy, Birman, & Demaline, 1986). Such issues and ﬁndings led researchers to question the validity of using the traditional IQ-achievement discrepancy to identify students with reading disabilities (RD) (e.g., Donovan & Cross, 2002; Fletcher & Foorman, 1994; Stanovich & Siegel, 1994; Stuebing et al., 2002; Vaughn & Fuchs, 2003). The IQ-achievement discrepancy model required that, to receive special services, students must demonstrate a difference (typically 1–2 standard deviations in standard scores) between their assessed cognitive ability (i.e., IQ) and their assessed reading ability. Proponents of RtI have criticized this discrepancy approach for several reasons: (1) the large increase in the numbers of students with RD and variability in state-to-state prevalence ﬁgures (U.S. Department of Education, 2004), (2) the disproportionate representation of diverse students among those labeled LD (Donovan & Cross, 2002), (3) that instructional needs of students labeled RD are not reliably different from poor readers without the label (Fletcher & Foorman, 1994; Stuebing et al., 2002), and ﬁnally (4) that without the label, many children who need early literacy intervention, especially children from high poverty backgrounds, do not receive it (Scruggs & Mastropieri, 2003).

CONCEPTUALIZING RtI Presently, there is no universally accepted model of RtI, but broadly speaking all RtI models include a multi-layer or multi-tier process that typically involves extensive school reform (cf. Jimerson, Burns, & Van der Heyden, 2007). Fig. 1, adapted from Batsche et al. (2005) represents this model. An important aspect of this process is accountability for reading growth (ideally 90% of students on grade level) and identiﬁcation of students who are not making adequate progress early to provide them with additional interventions that are increasingly intensive (and therefore increasingly costly to schools). Thus, RtI models incorporate universal screening measures and ongoing progress-monitoring measures (1) to assess all students’ reading growth toward benchmark skills; (2) to identify students who are not making ‘‘adequate’’ growth; and (3) to provide data about how to differentiate interventions. Because RtI is a general education initiative, it requires that general education teachers receive professional development, which precedes or coincides with implementation of RtI, and that aims to support instructional

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Tier 3

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1-5% of students

se rea

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Tier 3 Students still not making adequate progress in Tier 2 receive: • Very intensive interventions up to one hour a day in very small groups (1-3) by experts • Intervention is responsive to individual children needs • Mix of general and special education or purely special education

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Tier 1

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Tier 1 All students receive: • Universal screening and ongoing progress monitoring • Evidence-based classroom core reading instruction provided by general education classroom teacher for minimum of 90 minutes per day

Tier 2

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Tier 2 Students not making adequate progress in Tier 1 receive: • More intensive 3-5 days per week for 15-20 minutes, supplemental small group intervention • More frequent progress monitoring

80-90% of students

Fig. 1. Response to Intervention Model. Adapted from ‘‘A Three-Tiered Intervention Model.’’ Adapted from the National Association of Directors of Special Education (NADSE), Batsche et al. (2005).

effectiveness. Then during Tier 1, or classroom instruction, all students receive evidence-based classroom core reading instruction provided by their general education classroom teacher for a minimum of about 90 minutes per day. Next, students not making adequate progress receive Tier 2, which is more intensive (3–5 days per week for 15–30 minutes), supplemental small group intervention. Depending on the existing resources, these interventions might be delivered by classroom teachers, reading specialists, other interventionists, or well-trained and supervised paraprofessionals or community tutors. Within Tier 2, student progress is monitored more frequently (weekly or biweekly) than in Tier 1 in order to differentiate intervention based on individual needs. Then, students still not making adequate progress receive Tier 3 interventions, provided in even smaller groups (1–3) by a skilled intervention specialist. Tier 3 sessions may be thought of as a mix of general and special education or, in many schools as purely special education, with the criteria that intervention be responsive to individual childrens’ needs and very intensive (an hour or more extra intervention per day provided in very

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small group or individual sessions by experts) (see for example, Fuchs & Fuchs, 1998; Fuchs, Mock, Morgan, & Young, 2003; O’Connor, Fulmer, Harty, & Bell, 2005; Vaughn, Linan-Thompson, & Hickman, 2003). Before continuing the chapter, it is important to explain some historical differences in how RtI has been conceptualized and operationalized in a number of markedly different ways. At one end of the continuum of current RtI models, the standard treatment model begins with giving students with similar reading deﬁcits evidence-based intervention that have been shown to ‘‘work’’ for other students with the same deﬁcits. Teachers or interventionists are then expected to follow a standardized treatment protocol and to implement intervention with ﬁdelity (Fuchs, Fuchs, & Compton, 2004; Mathes et al., 2005; McMaster, Fuchs, Fuchs, & Compton, 2005; Torgesen et al., 1999, 2001). At the opposite end of the continuum, a problem-solving model addresses reading deﬁcits by incrementally individualizing instruction (Deno, 2002; Deno et al., 2002; Marston, Muyskens, Lau, & Canter, 2002; Tilly, Reschly, & Grimes, 1999). Between the two ends of the continuum are models that provide a combination of standardized and individualized intervention – often beginning with standard protocols and increasingly tailoring instruction based on progress monitoring (Case, Speece, & Molloy, 2003; O’Connor, 2000; Speece & Case, 2001; Vaughn et al., 2003). It is also important that we clarify that our operational deﬁnition of ‘‘What works,’’ with regard to the standard protocols, stems from converging ﬁndings from three inﬂuential reports, Teaching Children to Read (National Reading Panel [NRP], 2000), Preventing Reading Difﬁculties in Young Children (Snow et al., 1998), and Reading for Understanding: Toward an R&D Program in Reading Comprehension (Snow, 2002). These ﬁndings provide convincing evidence that early literacy intervention should include explicit and systematic instruction in code- (phonemic awareness, phonics, and ﬂuency) and meaning-focused (vocabulary and comprehension) instruction. Explicit instruction, in contrast with implicit or incidental teaching, follows a conscious and logical sequence from easier to more difﬁcult. For example, teaching children to blend syllables such as ‘‘bat’’ and ‘‘man’’ to make ‘‘batman’’ would happen before teaching that ‘‘bat’’ is made up of three sounds: /b/ /a/ and /t/. Systematic code-based instruction aims to teach the alphabetic code, which is the system or the relationship between sounds in speech and letters. Findings from these reports known collectively as either ‘‘ScientiﬁcallyBased Reading Research’’ (SBRR) or ‘‘evidence-based instruction’’ are cited throughout No Child Left Behind Act of 2001 (2002, PL 107-110), especially in Part B, known as Reading First. To achieve the stated goal of all children

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reading by third grade, all schools receiving funding through Reading First were required to provide SBRR instruction and more intensive intervention that include all ﬁve core training components (phonological awareness, phonics, vocabulary, ﬂuency, and comprehension) in order to reduce the proportion of students inappropriately identiﬁed for special education. In other words, good classroom instruction is necessary, but may not be sufﬁcient, for all students. Even with sustained individualized intervention, or treatment, beyond classroom reading instruction many students catch up to their peers. Some have questioned whether such ‘‘heroic’’ interventions can be delivered in general education or in special education classrooms (see Fuchs & Fuchs, 1998; O’Connor, 2000). Unfortunately, special education programs are often unable to provide intensive and individualized reading intervention for a number of reasons (Vaughn, Moody, & Schumm, 1998). In special education, teachers’ caseloads are high because many children placed in special education are not truly reading disabled but rather may not have received appropriate instruction or early intervention (Simmons, Fuchs, & Fuchs, 1991). In addition, the context of special education is changing. Beginning with the last iteration of Individuals with Disabilities Education Act (IDEA, 2004), an increasing number of students with RD are served primarily in their general education classrooms. There has also been considerable convergence in ﬁndings from metaanalyses and research syntheses of the special education literature regarding which intervention components lead to improved academic outcomes speciﬁcally for students with LD (Cavanaugh, Kim, Wanzek, & Vaughn, 2004; Gersten et al., 1998; Elbaum, Vaughn, Hughes, & Moody, 2000; Mastropieri & Scruggs, 1996; Swanson, 1999b; Swanson & Hoskyn, 1998; Vaughn, Gersten, & Chard, 2000). As Vaughn et al. explained, critical components producing the strongest results include small group interactive instruction, extended practice and feedback, sequenced tasks presented in order of difﬁculty to ensure student success, and instruction that showed students how to be meta-cognitive (think aloud, self-question, or problemsolve) while reading text. In the research base on teaching comprehension to older students with LD, this later component, metacognition strategy instruction was associated with the highest average effect size of 1.19 (Swanson, 1999a). There is less convergence about the speciﬁc operational deﬁnitions of ‘‘adequate’’ response to instruction and intervention (Al Otaiba, 2003). This issue is problematic because it informs who gets extra help and who does not. In a thoughtful paper, titled ‘‘What We Need to Know about

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Responsiveness to Intervention (and Shouldn’t Be Afraid to Ask),’’ Fuchs and Deshler (2007) described ﬁve ways that researchers have deﬁned unresponsiveness: (1) median split in reading slope (e.g., Vellutino et al., 1996, calculated slopes of growth during treatment and students whose slope was below the median were considered unresponsive); (2) normalization (e.g., standard scores below 85 on letter word identiﬁcation after treatment, as suggested by Torgesen, 2000); (3) below cut-points or end of year benchmarks (e.g., scores associated with ‘‘risk’’ on a criterion referenced progress monitoring measures such as the Dynamic Indicators of Basic Early Literacy Skills or DIBELS measures used by Good & Kaminski, 2002); (4) dual discrepancy (e.g., scores that are initially below a normative cut-point and a treatment slope that is below that of a peer group as proposed by Fuchs & Fuchs, 1998); and (5) slope discrepancy (e.g., treatment slope below that of peer group used in Fuchs et al., 2004). Disturbingly, researchers have begun to warn that these different models identify different children as needing help (Al Otaiba et al., 2008; Schatschneider, Wagner, & Crawford, in press). Because no clear consensus about RtI methods for RD identiﬁcation exists, we argue it is vital to provide the most effective beginning reading instruction possible during Tier 1 and propose utilizing resources to create a hybrid Tier 1/Tier 2 model that serves as a broader safety net across the beginning reading stage.

HOW TO IMPLEMENT RtI: BEGINNING WITH THE FOUNDATION OF TIER 1 One of the advantages of RtI is that the speciﬁc procedures protocols that comprise RtI may be tailored by districts and schools to best meet the needs of their students and to take into account the resources (staff, facilities, etc.) available to them. What we describe here are key elements of RtI and some of the decision points. The ﬁrst step in a successful RtI program is implementing effective Tier 1 General Education instruction for all children. Without a solid foundation of effective instruction, too many children will be referred for more expensive Tier 2 interventions. Furthermore, since Tier 2 is a supplement to Tier 1, effective Tier 1 is truly the foundation of RtI. Throughout this chapter, we use the term ‘‘effective instruction’’ to include not only instructional recommendations of the NRP (2000) but, in essence, any combination of instructional strategies that leads to stronger

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student learning of key concepts and skills. Thus, ‘‘effective instruction’’ is deﬁned in terms of student outcomes so that effective Tier 1 literacy instruction results in virtually all of the students – from struggling to able – showing a year or more growth in literacy skills. Effective Tier 1 instruction includes dynamic use of whole class, differentiated small group instruction, and time for students to practice skills independently. Research shows that such instruction can reduce the percentage of children who do not perform on grade level to about 5–7% (Al Otaiba & Fuchs, 2006; Foorman, Brier, & Fletcher, 2003; Mathes et al., 2005).

A Strong Foundation: An Evidence-Based Core Literacy Curriculum Tier 1 instruction begins with an evidence-based core literacy curriculum (Foorman, Francis, Fletcher, Schatschneider, & Mehta, 1998; Mathes et al., 2005). An evidence-based core literacy curriculum is based on a solid foundation of research evidence. Although the curriculum itself may not have undergone rigorous research trials, there should be strong evidence that the components of the core have been tested (Al Otaiba, KosanovichGrek, Torgesen, Hassler, & Wahl, 2005). There are a number of resources that describe the components of an evidence-based core literacy curriculum including the What Works Clearinghouse and the National Reading Panel Report (NRP, 2000). Generally, a well-designed core curriculum includes time for explicit instruction in phonological awareness, phonics, and decoding strategies (NRP, 2000), especially in the early grades. But it also provides guidelines for improving students’ ﬂuency (NRP, 2000), oral language (Beck, McKeown, & Kucan, 2005), and reading comprehension skills (Snow, 2002). Writing is also important (Foorman et al., 2006; Graham, Harris, & Larsen, 2001). Because no one core curriculum ﬁts the needs of all children, teachers may need to augment or supplement with additional materials that are consistent with classroom instruction and are evidence-based. Differentiate core reading instruction based on formative progressmonitoring data. A good core literacy curriculum is necessary but not sufﬁcient: The key to effective Tier 1 is how teachers use data to create more dynamic, differentiated instruction in their classrooms. Differentiated instruction has been deﬁned in a number of ways. Splitting the class into three reading groups based on ability, the teaching approach used about 20 years ago, is not what we mean by differentiated

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instruction. Differentiated or individualized instruction includes all of the following: (a) The expectation is for all children to become proﬁcient readers. (b) Decisions about students’ proﬁciency and the progress they are making are based on assessment data. (c) Students participate in some aspects of the core curriculum as a class. However, students also receive additional targeted instruction in small groups along with time for independent practice individually or with peers on activities that are matched to their current proﬁciency levels and interests. (d) Groups may be fairly homogeneous but they are also ﬂexible, changing as children’s skills and learning need change. Provide a daily dedicated and uninterrupted time for literacy instruction. Descriptive and correlational research suggests that providing a dedicated and uninterrupted block of time lasting between 45 and 120 minutes each day, with much of that time dedicated to differentiated instruction using small groups, is associated with stronger student reading achievement (Connor, Morrison, Fishman, & Schatschneider, 2009c; Connor, Morrison, Fishman, Schatschneider, & Underwood, 2007; Connor et al., 2009d; Pressley et al., 2001; Taylor & Pearson, 2004; Wharton-McDonald, Pressley, & Hampston, 1998). School- or district-level leaders utilize a number of strategies for providing a dedicated uninterrupted block of time for literacy instruction. Some schools have a grade level designated time for literacy so that, for example, all ﬁrst grade classrooms have literacy at the same time. In most schools, students stay with their homeroom teacher, but in others, students go to a different teacher for reading. In the latter example, students are assigned to reading classes based on their reading skills. In other schools, the dedicated block of time is staggered so that reading specialists and other professionals can help during the reading blocks (Taylor & Pearson, 2002). For example, a ﬁrst grade classroom might have the reading block from 9:00 to 10:00 with all the reading professionals helping during centers or stations. Then classroom B’s reading block would be from 10:00 to 11:00 and the specialists would help in that class (Taylor, Pearson, Clark, & Walpole, 2000; Wharton-McDonald et al., 1998). Right now, there is no evidence that one scheduling strategy is more effective than another nor is there evidence that there is an ideal length of time for the

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literacy block. However, there is good evidence that the amount of time students spend in meaningful instruction is strongly related to how much they learn (Algozzine & Algozzine, 2007; Connor, Son, Hindman, & Morrison, 2005). There is also correlational evidence that small group instruction is more effective minute for minute than is whole class instruction (Connor, Morrison, & Slominski, 2006) even though many teachers report that teaching to the whole class is easier. Although the teacher works with small groups of children, the rest of the students will learn more if they are involved in high-quality learning activities (Elbaum et al., 2000; Foorman & Torgesen, 2001). By conceptualizing instruction across multiple dimensions, including the level of scaffolding and explicitness, group size, and content, teachers are able to ﬁne-tune the activities they provide to individual students (Connor et al., 2009c; Connor et al., 2007; Connor et al., 2009d). Finally, there is accumulating evidence that teachers who plan their instruction time carefully (Borko & Niles, 1987; Connor et al., 2007; Connor et al., 2009e; Fuchs, Fuchs, & Phillips, 1994) and explicitly teach their students classroom routines such as how to move from one center activity to another, spend more time in meaningful instruction, and have fewer classroom disruptions and discipline problems than do teachers who do not plan and organize (Connor et al., 2009e). Deﬁne differentiated literacy instruction activities speciﬁcally and multidimensionally when planning instruction. Thinking about literacy instruction multi-dimensionally allows teachers more precision and ﬂexibility when they plan and implement instructional activities with their students. In the past, literacy instruction has been described globally as either skill-based or meaning-based (Ravitch, 2001). However, research shows that literacy is a complex skill that includes both decoding (understanding that letter sounds are blended into words) and comprehension (understanding the meaning of what is spoken and read) (Hoover & Gough, 1990) and that literacy instruction can be described across several dimensions (Connor, Morrison, & Katch, 2004). Salient dimensions include (1) the level of scaffolding; in other words, whether the teacher is actively working with students (teacher/child managed) or whether students are working independently or with peers (child managed); (2) the content of the instruction, which can be either code-focused (phonological awareness, phonics, letter and word ﬂuency) or meaning-focused (language, vocabulary, comprehension, text ﬂuency, writing, reading); and (3) the size of the group, whole class, small group, and individual. These dimensions operate simultaneously (see Table 1), and hence, any literacy activity can be deﬁned multi-dimensionally.

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Table 1.

Selected Language Arts Instruction Activity within the Dimensions of Instruction. Teacher Managed

Code-focused Alphabet activity Grapheme-phoneme correspondence Onset-rime Word segmentation Phonics activities Phonological awareness activities Sight word reading Meaningfocused

Vocabulary Teacher read aloud Student read aloud, choral Group writing, writing instruction, model writing Listening comprehension Discussion Repeated reading of text Timed reading Comprehension strategies

Child Managed

Spelling Independent repeated reading of words Phonics activities Phonological awareness activities Non-word reading activities Computer activities code-focused

Student read aloud, individual Buddy reading Sustained silent reading Reading comprehension worksheets Student individual writing

Multiple dimensions make it easier to match students’ learning needs with activities provided in the core reading curriculum and with other literacy activities. For example, children who struggle with reading will generally make more progress when they spend more time in teacher/child-managed (i.e., highly interactive with the teacher actively working with the child), small group, explicit code-focused instruction (Connor et al., 2009d; Foorman et al., 1998). This is a more precise way of thinking about instruction than just saying the child needs more phonics instruction and therefore assigning phonics seatwork for extra practice. Work with children in homogeneous skill-based groups that are based on their progress monitoring results and their speciﬁc learning needs and vary in time, content, and degree of scaffolding. Flexible learning groups differ from old-fashioned tracking because the groups change as students’ skills and learning objectives change. For example, rather than assigning children to a group based on their skills at the beginning of the year, reformulate the groups frequently based on progress monitoring and informal assessment results. By working with students who have similar learning needs, teachers can more effectively tailor instruction by providing more time for children

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who struggle, providing different content based on students’ reading skills, and by monitoring the level of support and direct instruction needed for children to master key skills. Most teachers seem to use three to four groups, depending on how large their class is and the range of students’ skills. Providing instruction in small groups, although important, is not enough. For truly effective Tier 1 general education, research gives us guidelines on how to match students’ skills with the content and activities that will be most effective for them (Connor et al., 2009d; Taylor et al., 2000; Wharton-McDonald et al., 1998). This is important because of converging correlational evidence that the effect of particular instructional strategies depends on students’ language and literacy skills (child-by-instruction interactions) from preschool through third grade using different samples of children, conducted by different researchers, and with different outcomes (e.g., word reading, reading comprehension, and vocabulary) (Connor, Jakobsons, Crowe, & Meadows, 2009b; Connor et al., 2004; Connor et al., 2004; Connor et al., 2006; Connor, Morrison, & Underwood, 2007; Foorman et al., 1998; Foorman et al., 2006; Juel & Minden-Cupp, 2000; Mathes et al., 2005; Torgesen, 2000). We can think of children as falling into three or four general skill levels: (1) the majority of the children who are working at grade level and for whom general education is typically most effective; (2) students who are very proﬁcient readers (well above grade level); and (3) students who are truly struggling (well below grade level) and who will most likely need Tier 2 or Tier 3 interventions as well as students who are having some difﬁculty (slightly below grade level, colloquially termed on the ‘‘bubble’’). For children who are reading right around grade level. The core curriculum is generally effective for these students when it provides a balance of code and meaning-focused activities, time with the teacher in small groups, and time to work independently. Most teachers have no difﬁculty meeting the needs of children in this group. Children with average grade level skills usually make the most progress with a balance of instructional types (Connor et al., 2007; Connor et al., 2009d). For example, children who begin the school year with average to weaker reading comprehension skills may make more progress when they receive extra instruction in explicit reading comprehension strategies, such as making inferences and summarizing what they have just read (Guthrie, Schafer, & Huang, 2001; NRP, 2000; Snow, 2002). Such activities appear to be less important for students with very strong reading comprehension skills. For children who are reading above grade expectations. One group that seems to be underserved in many classrooms, especially in schools that

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serve children from low income families, are students with above grade level skills (Connor et al., 2009a; Connor et al., 2009d; Neal & Schanzenbach, 2007; Viadero, 2007). Research shows that, in general, children who start ﬁrst grade with stronger skills make less progress than do their peers, that they are less likely to receive the amounts and types of instruction that research says will be most effective for them, and instruction is less effective (i.e., leads to weaker growth) than it is for their peers. It may be that teachers and administrators are assuming they are doing just ﬁne and do not need any additional help. One danger of an over-reliance on whole class instruction is that these children are not learning the new skills they need because they have already mastered the material being covered. Not surprisingly, more challenging activities are more effective for these children. Research suggests that children who are reading well above grade expectations show greater gains in ﬁrst grade when provided substantial amounts of time in child- and peer-managed meaning-focused literacy activities. Suggested activities include writing in journals, buddy reading with peers, tutoring younger children or peers who are less proﬁcient, reading independently, and more advanced learning activities. For students whose skills are slightly below or well below grade expectations. As children fall below grade expectations, research shows that more time in teacher/child-managed code- and meaning-focused instruction in small groups is critical to bring their skills to grade level. Moreover, this instruction is most effective when focused on the explicit skills with which children are struggling. For example, if the child is having difﬁculty sounding out words, then speciﬁc help with letter–sound associations, blending sounds, and segmenting words will likely be more effective than listening to the child read and giving feedback. Childmanaged activities are important but should be introduced gradually and activities should focus on skills children have mastered and need to practice. Many of the activities we will describe for Tier 2 instruction are also useful when provided in general education classrooms. In this instance, Tier 2 interventions would be used as part of and to supplement Tier 1 general education. For example, students who begin ﬁrst grade with reading and vocabulary skills well below grade level usually make more progress when they have substantial amounts of time to work directly with their teacher or other adult specialist as on phonological awareness, phonics, and other decoding activities (teacher/child-managed code-focused activities). Meaning-focused activities are important as well including building oral language skills

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through read alouds, discussion, and introducing comprehension strategies. Time in child-managed meaning-focused activities such as independent silent reading is more effective when the time is gradually increased over the course of the school year as their reading skills improve. Teachers can use adult volunteers as a supplement. Another way school leaders facilitate individualization of Tier 1 is to provide teachers with paraprofessionals or even adult volunteers (e.g., community members, college students) (Al Otaiba & Foorman, 2008; Elbaum, Vaughn, Hughes, & Moody, 1999; Foorman & Al Otaiba, in press; Juel, 1994, 1996; Morrow & Woo, 2001; Wasik, 1998a, 1998b). The evidence supporting the efﬁcacy of such programs is growing. Two initial meta-analyses of tutoring found similar overall average effect sizes of .40 (Cohen, Kulik, & Kulik, 1982; Elbaum et al., 2000) but reported that the average effect size within the subset of interventions implemented by volunteers was smaller (.26) and variable (ranging from –.25 to .98). Wasik (1998a, 1998b) conducted a narrative review of volunteer tutoring programs. Although she highlighted the need for more robust empirical studies, she also described features associated with effective programs: (1) a reading specialist or expert provided training and supervision to tutors, (2) the tutoring program was consistent with the classroom instruction, (3) the program included high quality materials and engaging books, and (4) students’ progress was monitored. Findings from a growing body of empirical studies support the salience of Wasik’s recommended features (cf. reviews by Al Otaiba & Foorman, in press; Foorman & Al Otaiba, in press). One of the most thoroughly researched commercially available programs is Sound Partners, which has been tested in a series of experimental and quasi-experimental studies over the past 10 years (Jenkins, Vadasy, Firebaugh, & Proﬁlet, 2000; Vadasy, Jenkins, Antil, Wayne, & O’Connor, 1997; Vadasy, Jenkins, & Pool, 2000). Sound Partners was designed as a structured standard treatment tutoring program spanning K-2 (training letter–sound correspondence, decoding words, reading sight words, and ﬂuency training in decodable texts). The program includes 100 scripted lessons and suggests tutoring be conducted at least four days a week for a half an hour. Working mostly in high poverty schools, Vadasy and her colleagues reported a consistent trend favoring tutored over control students on an array of reading, phonological awareness, and spelling measures with effect sizes ranging from a small effect of .10 for comprehension to large effect of 1.24 for nonword decoding. Importantly, Vadasy and colleagues tested the importance of supervision as it relates to the ﬁdelity of tutoring; (1) larger effects were found for students whose tutors maintained higher ﬁdelity of

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implementation (Vadasy et al., 2000) and (2) when research support was withdrawn, there were no longer any meaningful differences between treatment and untutored controls, but when research staff resumed their support, effect sizes once again favored treatment students (Jenkins et al., 2000). The question of dosage, or how often struggling kindergarteners needed volunteer-conducted tutoring, was addressed in a randomized control trial by Al Otaiba, Schatschneider, and Silverman (2005). Tutor-Assisted Intensive Learning Strategies (TAILS) was investigated through a randomized ﬁeld trial conducted in four high-poverty schools. Following screening of all 243 kindergarteners in 12 classrooms, 73 children were selected who started school with very low letter naming (o2 letters correct per minute) or letter-sound naming scores (o3 letter-sounds). Nearly all the children (over 80%) were African American and received free and reduced lunch. Students were randomly assigned within classrooms to receive tutoring for two or four days a week or to a control condition that provided small-group storybook reading two days a week. TAILS is similar to Sound Partners: it is scripted, follows a direct instruction format that was consistent with the core reading program, and was conducted four days a week for a half an hour per day. TAILS, however, also incorporated dialogic reading strategies to build language and listening comprehension (Beck at al., 2005; Lonigan, Anthony, Bloomﬁeld, Dyer, & Samwel, 1999). The training provided to TAILS tutors was somewhat longer than training for Sound Partners, but supervision was similar (weekly visits and modeling or coaching by research staff ). Fidelity of TAILS implementation was consistently above 85%. Dosage was important; students in the four-day TAILS condition showed greater growth on word reading, word attack, and passage comprehension than students in either the two-day or control condition on three reading measures. (Effect sizes favoring students in the four-day vs. control condition were .79, .90, and .83 on word identiﬁcation, passage comprehension, and basic reading skills, respectively.) In contrast, another program, Start Making a Reader Today (SMART) was effective even though it was less scripted and tutors were provided with very minimal training and supervision. Notably ﬁdelity was not addressed, and there was no way of knowing whether tutoring was consistent with classroom instruction. SMART volunteers follow more of a mentoring model and meet with students twice a week for a half an hour and listen to or read with the students, depending on their age and ability. SMART was evaluated using a randomized control trial (RCT) involving 43 SMART students and 41 controls who received two full years of tutoring

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(Baker, Gersten, & Keating, 2000). SMART students showed signiﬁcantly greater improvement than controls on word identiﬁcation (ES ¼ .44) and reading ﬂuency (ES ¼ .48 at end of ﬁrst grade and .53 at end of second grade), but there were no differences between groups on comprehension.

ADDITIONAL TIERS OF MORE INTENSIVE EARLY INTERVENTIONS THAT CAN BE PROVIDED BY TEACHERS AND WELL-TRAINED PARAPROFESSIONALS Many students who are well below grade level will need additional Tiers of intervention beyond what even the most effective classroom teacher can deliver. A small and growing number of studies have examined the efﬁcacy of multi-tier models, but most have been implemented by research teachers rather than classroom teachers and paraprofessionals (for a review, see Al Otaiba & Torgesen, 2007). A thorough review is beyond the scope of this chapter, so we focus on two relatively robust studies that allow a demonstration of the percentage of children who would still be signiﬁcantly below grade level if they were to receive effective Tier 1 instruction combined with either a standard or an individualized intervention. The ﬁrst study, implemented by Mathes et al. (2005), involved a large RCT in six non-Title 1 schools. The purpose of the study was to compare the efﬁcacy of enhanced Tier 1 classroom reading instruction with enhanced Tier 1 instruction plus one of two types of supplemental intervention (one a scripted standard treatment protocol and the other was slightly more problem-solving in nature). Using a screening instrument (the Texas Primary Reading Instrument; TPRI; Texas Education Agency, 2000) the researchers identiﬁed students at the end of kindergarten who were on grade level (n ¼ 100 normally developing kindergarteners) and who were wellbelow grade level (n ¼ 292 kindergarteners designated as at-risk (i.e., below the 20th percentile). Then, in ﬁrst grade, students were randomly assigned to conditions. In the ‘‘enhanced’’ Tier 1 condition, researchers provided teachers with feedback about student progress in oral reading ﬂuency and delivered professional development about using data to differentiate instruction. The standard protocol intervention (Early Interventions in Reading, Mathes, Torgesen, Menchetti, Wahl, & Grek, 2004) provided code-focused instruction that followed a prescriptive scope and sequence of lessons that were

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standard for all children. In contrast, the second intervention (Responsive Reading Instruction, Denton & Hocker, 2005) followed a more problemsolving approach. Although a scope and sequence was provided to teachers, teachers were trained to follow a problem solving approach while responding to individual student’s strengths and weaknesses. Time was allocated differently, with more of an emphasis on phonemic decoding accuracy in Early Interventions whereas and on text reading and writing in Responsive. Each intervention group received the same amount of intervention (40 min a day for 30 weeks in small groups of three children) by well-trained certiﬁed teachers who were not the childrens’ classroom teacher. The ﬁndings from the study were encouraging; all three treated groups scored in the average range at the end of the year on reading and spelling measures. Not surprisingly, the two intervention groups outperformed the enhanced Tier 1 classroom group and the two intervention groups performed similarly to each other. Extrapolating to the general population, roughly 3% of students in the enhanced Tier 1 condition remained below grade level in word reading, compared to 0.2% in the Early Interventions in Reading condition and 1.5% in the Responsive condition. This study shows that either intervention, combined with enhanced Tier 1 classroom instruction, resulted in signiﬁcant increases in children reading at grade level and fewer children well below grade level. The second study, conducted by Torgesen et al. (1999), is notable because it provided evidence that paraprofessionals can supplement research-trained teachers in providing a prescriptive standard intervention without adversely impacting intervention ﬁdelity. The majority of kindergarten students in this RCT study came from minority backgrounds (53%) and had low letter-naming and phonological awareness scores. Children were randomly assigned to a no-treatment control condition or to one of three one-to-one tutoring conditions that were conducted 20 min daily, four days a week starting in the second half of kindergarten and lasting through second grade (roughly 47 total hours provided by teachers and 41 by paraprofessionals). These three tutoring conditions varied in the explicitness with which phonics was taught. The most explicit program provided phonological awareness training plus synthetic phonics (PASP), which consisted of explicit instruction in phonological awareness using articulatory cues plus extensive practice in decontextualized phonetic decoding. The second, embedded phonics (EP) also consisted of instruction in explicit phonics but placed more emphasis on practice in reading and writing connected text and on acquisition of sight words. The third, regular classroom support (RCS)

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consisted of tutorial assistance for the reading instruction provided in the regular classroom. The study ended as children ﬁnished second grade, by which time children who had received the most explicit phonics instruction (PASP group) signiﬁcantly outperformed the other groups on phonemic decoding and signiﬁcantly outperformed the control group and the RCS group on word reading. However, no differences among conditions were reported for reading comprehension. Extrapolating to a general population, if all kindergartners starting school similarly behind in reading received this intensive explicit phonics intervention, all but about 2.4% could reach grade level word level reading by the end of second grade. The success of these protocols should be considered in contrast to the dismal statistics we described at the beginning of this chapter: that about half of the American fourth graders who are from minority backgrounds can not read with comprehension at even a ‘‘basic’’ level (NAEP, 2007). That is not to say that if these fourth graders received similar intervention early, then we could guarantee that 98% would read ﬂuently and with comprehension. However, starting off with a strong trajectory of word reading and mastering the basics of the alphabetic principle could increases chances of future reading success.

CAUTIONARY ISSUES AND NEED FOR FURTHER RESEARCH Consider how difﬁcult school reform and scaling up RtI could be in schools where currently 50% or more students are not reading on grade level. Although we have described scientiﬁcally validated protocols for a hybrid of Tier 1 and Tier 2 that differentiates instruction on a child-by-child basis, we realize that implementing successful RtI includes many school and district level decisions. These decisions include selecting the core literacy curriculum and other materials, scheduling the uninterrupted block of time for literacy instruction, deciding how to use specialists and paraprofessionals, and other decisions that affect the entire schools or district. In turn, school leaders’ ability to make these decisions effectively is limited not only by resource issues but also by the lack of agreement about deﬁning responsiveness. In this chapter, we have argued that in lieu of a clear consensus about RtI methods for RD identiﬁcation, it is vital to provide the most effective

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beginning reading instruction possible during Tier 1. Therefore, we have proposed utilizing resources to create a hybrid Tier 1/Tier 2 model that would serve as a broader safety net across the beginning reading stage. This model could save schools from using more expensive resources to serve children who might appear ‘‘at risk’’ based on results of a beginning of year screening test who in fact respond well to differentiated instruction (so-called false positives). This model would ensure that children who appear not to be at risk, but who really do need extra help (so-called false negatives or students ‘‘on the bubble’’) would receive support at an early point of their reading development. RtI models must be sensitive enough to help children who need additional help and speciﬁc enough not to overidentify children and tax the system. As Fuchs and Deshler (2007) described, in RtI models, student response is tested against effective instruction. ‘‘Without validated instruction (implemented with ﬁdelity by practioners), RtI cannot be a valid method of disability identiﬁcation or early intervention’’ (p. 134). Clearly the magnitude of RtI efforts will be constrained by resources and the number of children who need Tier 2 and Tier 3 supports. This is critical because the effectiveness of Tier 2 and Tier 3 interventions will be impacted by factors related to the resources needed to implement the intervention (the explicitness of intervention, group size, length of instructional sessions, frequency of delivery, and duration of the intervention) and the interventionist (the training and experience of the interventionist, the ﬁdelity of intervention implementation). One ﬁnal caution stems from research that has identiﬁed characteristics of children who are likely to be less responsive with RtI models (Al Otaiba & Fuchs, 2002; Nelson, Benner, & Gonzalez, 2003; Torgesen, 2000). These students may have the most intractable phonological deﬁcits, relatively limited depth and breadth of vocabulary, poor memory, inattention or problem behaviors. Our hybrid model considered vocabulary and letter– word knowledge when recommending amounts and types of beginning reading instruction/intervention, but it does not yet incorporate behavioral recommendations. Nevertheless, additional research is needed to support special educators who will be facing a challenge to meet the intervention needs of children who have not learned to read despite receiving the most effective instruction we know how to deliver. Researchers need to design Tier 3 interventions based on what has and has not worked for these students that also uses frequent and ongoing assessment to judge success, or to ﬁne tune intervention protocols in a problem-solving formative fashion.

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ACKNOWLEDGMENTS This work was supported by (a) a Multidisciplinary Learning Disabilities Center Grant P50HD052120 from the National Institute of Child Health and Human Development, (b) a Predoctoral Interdisciplinary Research Training Grant R305B04074 from the Institute for Education Science, (c) grants R305H04013 and R305B070074, ‘‘Child by Instruction Interactions: Effects of Individualizing Instruction’’ from the U.S. Department of Education, Institute for Education Sciences, and (d) by grant R01HD48539 from the National Institute for Child Health and Human Development.

REFERENCES Algozzine, K., & Algozzine, B. (2007). Classroom instructional ecology and school-wide positive behavior support. Journal of Applied School Psychology, 24(1), 29–47. Al Otaiba, S. (2003). Identiﬁcation of nonresponders: Are the children ‘‘left behind’’ by early literacy intervention the ‘‘truly’’ reading disabled? In: T. E. Scruggs & M. A. Mastropieri (Eds), Identiﬁcation and assessment: Advances in learning and behavioral disabilities (Vol. 16, pp. 51–81). Oxford, UK: Elsevier Science/JAI Press. Al Otaiba, S., Connor, C., Petscher, Y., Greulich, L., Folsom, J., & Meadows, J. (2008, February). Response to kindergarten reading instruction. Paper presented at the annual Society for the Scientiﬁc Study of Reading Conference, Asheville, NC. Al Otaiba, S., & Foorman, B. (2008). Early literacy instruction and intervention. Community Literacy Journal, 5.1, 21–37. Al Otaiba, S., & Fuchs, D. (2002). Characteristics of children who are unresponsive to early literacy intervention: A review of the literature. Remedial and Special Education, 23, 300–316. Al Otaiba, S., & Fuchs, D. (2006). Who are the young children for whom best practices in reading are ineffective? An experimental and longitudinal study. Journal of Learning Disabilities, 39, 414(418). Al Otaiba, S., Kosanovich-Grek, M. L., Torgesen, J. K., Hassler, L., & Wahl, M. (2005). Reviewing core kindergarten and ﬁrst grade reading programs in light of no child left behind: an exploratory study. Reading and Writing Quarterly, 21, 377–400. Al Otaiba, S., Schatschneider, C., & Silverman, E. (2005). Tutor assisted intensive learning strategies in kindergarten: How much is enough? Exceptionality, 13, 195–208. Al Otaiba, S., & Torgesen, J. (2007). Effects from intensive standardized kindergarten and ﬁrst grade interventions for the prevention of reading difﬁculties. In: S. R. Jimerson, M. K. Burns & A. M. Van der Heyden (Eds), The handbook of response to intervention: The science and practice of assessment and intervention (pp. 212–222). New York, NY: Springer. Baker, S., Gersten, R., & Keating, T. (2000). When less may be more: A 2-year longitudinal evaluation of a volunteer tutoring program requiring minimal training. Reading Research Quarterly, 35, 494–519.

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ADVANCES IN LITERACY PRACTICES FOR STUDENTS WITH EMOTIONAL AND BEHAVIORAL DISABILITIES Kelley S. Regan, Thomas E. Scruggs and Margo A. Mastropieri ABSTRACT This chapter provides a descriptive review of recent intervention research practices intended to improve the literacy skills of students with emotional or behavioral disabilities (EBD). A systematic search procedure identiﬁed 21 investigations that had been published in the past ﬁve years. These studies are described within the categories of peer-mediated literacy interventions, reading interventions, and writing interventions. Generally, it has been found that such practices as peer mediation, direct instruction (DI), cognitive text mapping, and writing strategy instruction including the Self-Regulated Strategy Development (SRSD) model have led to substantial improvement in the literacy skills of students with EBD. These strategies were apparently successful because they served generally to focus student attention and to provide cognitive models for executing literacy tasks. Implications for practice and future research are provided.

Policy and Practice Advances in Learning and Behavioral Disabilities, Volume 22, 317–339 Copyright r 2009 by Emerald Group Publishing Limited All rights of reproduction in any form reserved ISSN: 0735-004X/doi:10.1108/S0735-004X(2009)0000022013

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Issues challenging the ﬁeld of emotional and behavioral disabilities (EBD) include a population whose academic and social outcomes are among the worst of any disability group (Bradley, Henderson, & Monfore, 2004), including moderate to large achievement deﬁcits in mathematics, reading, and written language (Trout, Nordness, Pierce, & Epstein, 2003). These trends are associated with a worsening with age (Nelson, Benner, Lane, & Smith, 2004) – a large proportion of that population are placed in juvenile correctional facilities (Quinn, Rutherford, Leone, Osher, & Poirier, 2005) – and poor employment outcomes (Bullis & Yovanoff, 2006). Despite the alarmingly negative proﬁle of this population, dedicated educators and practitioners continue to provide instruction for these students across inclusive settings, self-contained settings, and in supportive resource roles. These individuals on the frontline interact daily with students with EBD who often exhibit internalizing (i.e., depression, sadness, withdrawal, school refusal, lack of motivation) and/or externalizing patterns of behavior (i.e., aggression, passive aggression, uncooperative, noncompliance) which signiﬁcantly impede the learning process. Given the palpable need to assist these learners and to effectively equip teachers to serve this population, researchers must identify promising evidence-based practices to employ with students with EBD in order to improve their academic and behavioral outcomes (Kauffman & Landrum, 2008). Although the special education ﬁeld, both in the United States and internationally (Gulchak & Lopes, 2007), has been unable to collectively agree on what precisely constitutes quality research resulting in the identiﬁcation of evidence-based practices, the following general indicators can be offered: the practices result in signiﬁcant learning outcomes and/or are deemed to have potential via empirical investigations; the practices are extensively replicated (Gulchak & Lopes, 2007; Horner et al., 2005) and employed across a variety of settings, grade levels, and disabilities; the participants who demonstrate positive outcomes as well as the descriptions of the intervention (including ﬁdelity of implementation procedures) are thoroughly detailed and described (Gersten, Fuchs, Compton, & Coyne, 2005); and the evidence-based practices are accessible, usable, and trustworthy (Lewis, Hudson, Richter, & Johnson, 2004). Given selected criteria, literature reviews and special education organizations, such as the national organization, Council for Exceptional Children (CEC), have identiﬁed effective evidence-based practices to employ with students with EBD. However, the literature in the ﬁeld of EBD has primarily focused on how to manage behaviors and improve social/ emotional functioning of these individual, and provided far less guidance

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in the area of academic achievement. For example, a 2003 review of research for improving the academic status of students with EBD highlighted the type, focus, and length of interventions investigated over a 28-year span (Mooney, Epstein, Reid, & Nelson, 2003). A gradual increase in research investigations exclusively involving students with EBD was observed over time with the areas of reading and mathematics dominating the focus areas. However, despite these advances, the areas of writing, science, social studies, and strategy instruction were among those almost untouched over the years. It has been argued that students with EBD may beneﬁt not so much from speciﬁc interventions tailored exclusively for them, but rather that evidencebased practices identiﬁed for other students who display similar academic skill deﬁcits, for example, learning disabilities, may prove similarly effective (Landrum, Tankersley, & Kauffman, 2003). After all, a large portion of students with EBD meet the criteria of one or more other disabilities including learning disabilities (LD) and speciﬁc language impairments (SLI). However, it has also been argued that students with EBD can exhibit a combination of social challenges, behavioral struggles, and academic challenges in contrast to their peers with and without disabilities. Those with behavioral disorders may even have a more adverse impact on academic achievement over time than students with learning disabilities (Nelson, Stage, Epstein, & Pierce, 2005). The effects of evidence-based practices for students who are not identiﬁed as having EBD may contrast on several levels from the length of implementation of the intervention, to the motivational attributes embedded in the strategy instruction. Furthermore, the current negative proﬁle of this group of learners has charged the ﬁeld of EBD to focus on this population exclusively in order to determine what works.

PURPOSE Kauffman (2008) recently remarked that ‘‘one indication of progress [in special education] would be ﬁnding out just what makes it [special education] work better’’ (p. 134). The purpose of this chapter is to present research in literacy learning for students with EBD over the past ﬁve years. What instructional elements make the literacy learning of students with EBD ‘‘better’’? For this discussion, literacy is deﬁned as the ability to read and write. The average students with EBD read nearly two grade levels below their same-age peers and writing is a subject area that students with EBD show much aversion to, given the complex skills entailed and the selfregulatory skills required (Lane, 2004). When there are signiﬁcant areas of

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need in both reading and writing, all content area learning can be affected. However, individuals with EBD could be expected to beneﬁt greatly from the increased exposure to the outside world afforded by reading skill, and from the increased ability to systematically formulate thought and opinion in writing. Acknowledging a need for additional high-quality reading research, the National Reading Panel (NRP, 2000) described the most effective approaches for teaching students to read. In 2002, the Institute of Educational Science (IES) opened to promote rigorous studies on various topics including literacy and practices speciﬁcally for students with severe emotional and behavioral concerns. Since 2000, reading research has increased for students with EBD. Topics of phonemic awareness and oral reading ﬂuency have been targeted, while reading comprehension and investigations in the primary grades remain scant (Kostewicz & Kubina, 2008). Writing instructions for students with EBD has been comparatively absent in the literature (Lane, 2004). There is clearly a need for more research in the area of literacy learning for students with EBD; however, the past ﬁve years have provided some direction for further examination. This chapter provides a brief narrative review of published investigations conducted on topics of literacy for students with EBD during the years 2003–2008.

LITERATURE SEARCH PROCEDURES Multiple procedures were used to identify relevant studies which inform literacy acquisition among children with EBD. Firstly, computer-assisted searches for relevant literature between 2003 and 2008 were conducted using Educational Resources Information Center (ERIC) and PsycINFO with the descriptors EBD and behavioral disorders individually paired with the following indicators representing ‘‘literacy’’: literacy, reading, writing, comprehension, phonics, ﬂuency, and vocabulary. This search initially yielded 93 articles. These articles were further delimited with the following criteria: (a) subjects/participants were to be individuals identiﬁed primarily with EBD and/or severe EBD, (b) the articles described an academic intervention or a literature review with a focus on academic literacy instruction (i.e., reading, writing) for students with EBD, (c) the article described a research investigation or major literature review from an accessible peer-reviewed journal, and (d) the article was published between 2003 and 2008. Given the criteria for inclusion, and accounting for the redundancy of articles from

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each search, a total of 13 articles were identiﬁed from the initial pool. Among the 13 articles, 8 were targeted for reading instruction, 3 for writing instruction, and 2 were relevant literature reviews. Secondly, a hand search of the leading journal in the ﬁeld of behavioral disorders, Behavioral Disorders, was conducted from 2003 to 2008 for articles meeting the criteria. This step identiﬁed an additional article regarding reading instructions for students with EBD. Thirdly, an ancestry search matching the criteria was conducted from the 14 identiﬁed articles. Given the latter steps, a total of 7 additional articles which matched the criteria were identiﬁed.

RESULTS A total of 21 articles were included in this descriptive review of literacy instruction for students with EBD in the last ﬁve years. This research is described in the following three categories: (a) peer-mediated literacy interventions, (b) reading interventions, and (c) writing interventions.

Peer-Mediated Literacy Interventions Mooney et al. (2003) provided a descriptive review of 53 investigations of academic interventions for students with EBD, analyzed for type, focus, and length of intervention. The authors identiﬁed four types of academic interventions for students with EBD: child-mediated (e.g., self-management, strategy instruction), teacher-mediated (e.g., curriculum modiﬁcation, choice making), peer-mediated (e.g., peer tutoring, cooperative learning), and a combination of categories. Teacher-mediated interventions dominated in frequency, followed by peer-mediated and child-mediated interventions. Since the 2003 review, Ryan, Pierce, and Mooney (2008) have continued to summarize the efﬁcacy of these three types of academic interventions. A review of peer-mediated interventions speciﬁcally had not been addressed since the review of Scruggs, Mastropieri, and Richter (1985) over two decades ago. For the present review, only those interventions supporting the reading and writing of students with EBD were considered. The review of Ryan, Reid, and Epstein (2004), ﬁve empirical investigations and a synthesis of peer-mediated interventions were included to identify peer-mediated literacy interventions for students with EBD. Peer-mediated interventions have

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strongly demonstrated positive outcomes for the literacy learning of students with EBD (Coleman & Vaughn, 2000; Scruggs et al., 1985). The four sub-types of peer-mediated interventions identiﬁed for this review include cross-age tutoring, peer tutoring, class-wide peer tutoring (CWPT), and peer-assisted learning strategies (PALS). In cross-age tutoring, older students with an ‘‘expertise area’’ are matched with younger students to deliver instructions. A difference of at least two years is typical in this type of intervention (Ryan et al., 2004). In same-age tutoring, a dyad of the similar age and ability level work together to receive and/or provide tutoring in a content area (sometimes higher and lower functioning students are paired). The tutoring can involve an interchangeable role of tutor and tutee, referred to as reciprocal or reverse-role tutoring (Spencer, 2006). In CWPT, the entire class simultaneously participates in tutoring dyads; tutors/tutees may or may not assume reciprocal roles (Ryan et al., 2004). PALS is a form of CWPT in which higher performing and lower-performing students in pairs take turns as ‘‘coach’’ and ‘‘player.’’ Students are provided with scripts to teach and reinforce their partners’ reading, ﬂuency, and comprehension skills. Points are awarded for positive cooperation between the pairs (Barton-Arwood, Wehby, & Falk, 2005; Fuchs et al., 2001). Research trends. The reviews of peer-mediated interventions included research from 1970 to 2002 (Ryan et al., 2004) and from 1972 to 2002 (Spencer, 2006). Although the selection criteria for the two reviews varied, both reviews consistently indicated large effect sizes across a variety of categories (i.e., academic subject areas, cross-age versus same-age peer tutoring, role of student, and age group). Over three decades, peer-mediated interventions for students with EBD have been investigated across the elementary, middle, and high school levels in the literacy areas of reading, spelling, writing, and most recently, social studies/history. In contrast to the review of Ryan et al. (2004), Spencer (2006) concluded that the interventions were primarily cross-age peer tutoring with reciprocal roles between tutor and tutee. While the frequency of investigations was relatively equal at the elementary and high school level, there is a need for more investigations at the middle school level. In addition, and consistent with the review of Ryan et al. (2004), Spencer found that peer-mediated instruction in the content area of science has yet to be studied. PALS has recently been investigated in the primary grades, an age group which has long since been neglected, particularly with respect to reading instruction and students with EBD. The effectiveness of PALS on the academic achievement of students with disabilities has been extensively validated throughout the literature; however, relatively less research has been conducted with students

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identiﬁed as EBD and those students in the upper elementary and/or high school levels. Student outcomes. Peer-mediated literacy interventions among students with EBD generally have produced positive results across most reading measures, and a high level of consumer satisfaction (Ryan et al., 2008; Sutherland & Snyder, 2008). Results have been less consistently positive on measures of self-concept and attitude (Spencer, 2006). However, participants generally reported satisfaction with school and even positive perceptions of their own literacy abilities. For example, middle school students in Sutherland and Snyder’s (2008) investigation of PALS indicated that the students preferred PALS to the traditional methods of instruction; however, rather than participating every day, the students thought 1–3 times a week would be better. Academic outcomes for peer-mediated literacy interventions have included the following measures: correct words read per minute, recall of content, oral reading ﬂuency, rate of strategy use, reading comprehension, spelling tests, and content test scores. For example, the number of words read correctly per minute was recorded in an investigation using PALS instruction (Sutherland & Snyder, 2008). Paired students took turns reading aloud a passage called ‘‘partner reading,’’ then with scripted questions, they took turns prompting each other to identify the main idea, in a PALS procedure referred to as ‘‘paragraph shrinking.’’ Finally, the pair used the ﬁnal 20 min session for ‘‘prediction relay’’ in which one student ﬁrst makes a prediction, the other student then reads ahead, and then they both evaluate the prediction. Recollection of content, a form of reading comprehension, was primarily assessed across the studies with weekly tests and/or standardized measures of reading performance. A recent investigation of student use of strategy instruction (e.g., summarization of the paragraph) in conjunction with peer-mediated interventions is a recent advancement for study of peer-mediated interventions for students with EBD. For outcomes at the primary grade levels, measures of phoneme blending (number of words correct per minute), phoneme segmentation, and nonsense word ﬂuency revealed moderately strong responses after the implementation of composite interventions of PALS and a reading program (Barton-Arwood et al., 2005; Wehby, Falk, Barton-Arwood, Lane, & Cooley, 2003a). The kindergartners and 1st graders from the Wehby, Lane, and Falk (2003b) investigation also demonstrated an improvement in time spent attending to instruction. Social and behavioral outcomes, which may suggest potential collateral beneﬁts for students, were collected in many of the studies of peer-mediated interventions including time on task, and a

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frequency count of active student responses (Sutherland & Snyder, 2008). Social validity measures (e.g., student surveys, teacher interviews, selfconcept scales, attitude questionnaires, etc.) were also collected, and, other than self-concept scales, were generally positive. Future directions. Earlier models of instruction for students with EBD emphasized token economies and individual seat work (e.g., Hewitt, 1968), a model far removed from the socially interactive process of peer tutoring. However, research has demonstrated that students with EBD can be taught to work effectively in tutoring pairs to improve the literacy functioning of both tutors and tutees. Literacy outcomes for students with EBD may be enhanced when peer-mediated interventions are combined with explicit strategy instruction and/or with comprehensive reading programs. For example, the use of same-age, reciprocal peer tutoring during social studies content learning resulted in gains in weekly multiple choice test scores among 30 students with EBD at the middle school level (Spencer, Scruggs, & Mastropieri, 2003). In this same study, students were provided explicit instructions in the use of summarization strategies in order to aid in the comprehension of the dense reading material. Although students did not display a signiﬁcant increase in the use of this strategy at the middle school level, a similar study utilizing CWPT conducted with a heterogeneous group of high school students with disabilities demonstrated strong gains for those with behavioral disabilities (BD) on chapter tests and in the use of summarization strategies to enhance recall of world history content (Mastropieri, Scruggs, Spencer, & Fontana, 2003). The incorporation of strategy instruction, such as the summarization strategy, in conjunction with peer-mediated instruction, may support student recall of content. Incorporating peer-mediated instruction and strategy instruction in the content area of science has yet to be explored. In addition to explicit strategy instruction, the use of peer-mediated instruction may advance student learning if combined with a comprehensive reading program. For example, for primary level (K-3) students with EBD, PALS was used to complement the slightly modiﬁed comprehensive reading programs of Open Court Reading (Wehby et al., 2003b) and Horizons Fast Track A-B reading program (Barton-Arwood et al., 2005). Both curriculums, depending on the grade level, address instruction of phonemic awareness, blending sounds, word attack skills, reading, letter printing, spelling, and writing. During the Horizons reading study, 3rd grade students with the highest performing scores were paired with the highest performing among the low performing students. A total of 3.5 h a day (30 min/4 days per Horizons and 30 min/3 days per PALS) for approximately 27 weeks of

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baseline and intervention led to an increase in phoneme blending, phoneme segmentation, and word reading. The composite intervention of the modiﬁed Open Court Reading curriculum and PALS for kindergarteners and 1st graders deemed moderate results in a relatively short time span for probes of nonsense words, sound naming, sight words, blending, and segmenting. Finally, as noted by multiple authors from this review, there is a need for future investigations of peer-mediated interventions to explicitly focus on the measure of oral reading ﬂuency. Comprehension is signiﬁcantly affected when students read text in a belaboring, choppy, and interrupted manner. Despite the progress in their reading skills, minimal progress was made for oral reading ﬂuency among the 3rd graders exposed to PALS and Horizons Fast Track A-B reading program, and no maintenance data were collected to determine the extent of student learning (Barton-Arwood et al., 2005). In addition, a slow rate of progress, variability in performance, and a limited transfer of skills continue to slow the progress of students with EBD in the area of reading achievement.

Reading Interventions In 2000, a review of eight reading investigations for elementary students with EBD from 1975 to 1998 was unable to identify particular instructional strategies with promise outside of peer-mediated strategies and direct instruction (DI) (Coleman & Vaughn, 2000). A subsequent focus group with eight experienced teachers of children with EBD, revealed the following themes to consider when teaching children with EBD to read: emotional variability of students with EBD, a fear of failure and trust issues, keeping students engaged, instructional practices, assessment and monitoring, and daily reading. The strategies experienced teachers used to troubleshoot these trends were not necessarily evidence-based, yet worthy of investigation. Following Coleman and Vaughn’s study, which notably, was conducted prior to No Child Left Behind (NCLB) legislation, reading studies supporting students with EBD have doubled in number and have included multiple reading outcomes (Kostewicz & Kubina, 2008). This review identiﬁed three reading investigations with elementary aged students, seven investigations at the secondary level, one review of overall reading research, and one review of reading research for the primary grades. Among these articles, ﬁve reading interventions were represented: repeated reading, two comprehensive reading programs of phonological awareness,

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the Corrective Reading program, and cognitive text maps. These interventions are included in the discussions later detailing the general trends of reading intervention research, student outcomes, and the advancements guiding the direction of future research in this area. Trends of research. Reading interventions in the past ﬁve years in the ﬁeld of EBD are characterized by multiple outcomes and a combination of strategies; for example, Open Court Reading combined with PALS (Wehby et al., 2003b) and Scott Forsman Reading curriculum paired with Phonological Awareness Training for Reading (PATR) (Wehby, Lane, & Falk, 2005). Outcome measures have progressed from singular aspects of reading like phonics and sight word recall to multiple outcomes including phonemic awareness skills (segmenting and blending phonemes), oral reading ﬂuency, letter sound correspondence, and nonsense word ﬂuency (Kostewicz & Kubina, 2008). A recent review of reading interventions for students in the primary grades was conducted to summarize the needed insights for this age group. Rivera, Al-Otaiba, and Koorland (2006) identiﬁed 11 studies (students at risk for antisocial behaviors were included to widen the pool of studies) published between 1975 and 2004. Among the studies, the ﬁve domains of reading instruction from the National Reading Panel were not addressed entirely. Although phonics was emphasized in over half of the studies, more emphasis on phonemic awareness would appear appropriate, particularly for the primary years. Surprisingly, only one study addressed reading comprehension, and none addressed vocabulary instructions. Further explorations with reading interventions among the primary grades are clearly needed. Presently, most reading research for students with EBD has been conducted at the secondary level, employing predominately ﬂuency and comprehension outcome measures. In addition, most of the reading interventions for students with EBD across grade levels have been conducted primarily in self-contained environments and in small groups and/or 1:1 peer/instructor tutoring conditions. Student outcomes. Gains in reading achievement (e.g., Woodcock Reading Mastery Test-Revised, Gray Oral Reading Test), reading ﬂuency (e.g., words correct per minute, error rates), and comprehension have been demonstrated by students with EBD at the secondary level, who read on average at the 4th grade level. Corrective Reading, Repeated Reading, cognitive text maps, and a combination of interventions demonstrate promise for students at the middle school and high school level. Corrective Reading. Three investigations using the phonics-based SRA Corrective Reading program (Engelmann et al., 2008) demonstrated substantial gains for students’ oral reading ﬂuency and comprehension

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levels. Corrective Reading employs a DI method of instruction including explicit, intense, and teacher-directed procedures for decoding words and comprehending text. The program places students at their instructional level and maintains a scripted, quick-paced teaching sequence designed for high engagement. After 11 lessons, 45 min daily over 3 months, seven 6th graders with EBD excelled with high rates of words correct per minute (WCPM) for the Corrective Reading passages (Lingo, Slaton, & Jolivette, 2006). Skills of ﬂuency even generalized to grade-level reading passages for these students as well, and a social validation survey indicated an overall positive student perception of the Corrective Reading program. Similar results were reported with middle school students receiving a class-wide Corrective Reading program, 20–30 min a day, four days of the week (Strong, Wehby, Falk, & Lane, 2004). Again, reading gains for ﬂuency as well as for reading achievement were observed on the pre-/post test measures. Strong’s study, however, had an additive effect on student progress with an additional intervention of repeated reading. Repeated reading. Repeated reading is a practice entailing a student rereading a passage of text independently, with a partner, or with an instructor. With moderate growth observed from the use of the Corrective Reading intervention in Strong’s (2004) study, the repeated reading practice increased the reading measures for four out of six participants in the intervention phase as well as in the generalization phase (i.e., passages from the grade level Basal reader). Corrective Reading has also demonstrated positive effects for students with EBD in a juvenile correctional facility who received the intervention 1:1 for 30 min a day for 22 sessions (Allen-Deboer, Malmgren, & Glass, 2006). The quick, structured, and explicitness of D I, as exhibited with Corrective Reading seems appropriate for the population of students with EBD, as previously suggested by Landrum et al. (2003). Similar supports for repeated reading have been reported for upper elementary students. In 2005, Staubitz, Cartledge, Yurick, and Lu extended Strong’s study involving repeated reading by combining this promising practice within a peer-mediated condition and adding an outcome measure of comprehension. Six students were trained and given scripts to work with alternating partners in order to provide feedback, correction, and reinforcement when reading passages. Students were paired with students or the experimenter over 123 intervention sessions. As a result, student reading rates (WPM) increased with accuracy and substantial improvements were demonstrated in the assessments of comprehension (i.e., cloze procedures following each passage) when compared to the baseline condition of silent sustained reading (SSR).

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These results were extended recently with an added systematic error correction and performance feedback procedure on the reading ﬂuency and comprehension of four middle school students in a self-contained day treatment classroom (Alber-Morgan, Ramp, Anderson, & Martin, 2007). Passages were extracted from the student’s basal readers and eight literal and inferential reading comprehension questions were developed per passage. If students made an error, the instructor would provide the correct word, the student would reread this word, and then reread the sentence. Corrections made by the student and/or correct responses were praised by the teacher. A review of each miscued word was conducted at the completion of the student’s reading. After 11 weeks, robust results were interpreted from the visual analysis of repeated readings with error correction and feedback on WCPM for three of the four students and modest results were made with the comprehension questions. Cognitive text maps. In addition to Corrective Reading programs, repeated readings, and a combination of interventions, one recent investigation has revealed promising results for students at the high school level. Blankenship, Ayres, and Langone (2005) employed cognitive mapping to support student comprehension of text material. Comprehension is the essential goal of reading at all levels; however, this task is particularly relevant for secondary students who are exposed to dense content areas and heavy text-driven instructions such as social studies, world history, and science. Following teacher modeling through a teacher-led text map, three freshmen with EBD were encouraged to use the computer-based Inspiration software to map out their learning of the key concepts found after reading two to ﬁve pages from the world history text (Blankenship et al., 2005). The concept maps were to support student comprehension during and after reading and although they were not evaluated, students did complete chapter quizzes in order to proceed to the next chapter. In comparison to the low levels of knowledge prior to reading the text, an increase in comprehension levels were observed across all students. The strategy of cognitive mapping may be attributed to this progress. Phonological awareness programs. As stated previously, very few reading interventions have been conducted with primary age students identiﬁed with EBD. For these K-3 learners, reading instruction requires explicit instruction in the area of phonological awareness. The NRP asserts that phonological awareness may be the key predictor of student reading success. Skills consisting of rhyme, sound ﬂuency, and letter identiﬁcation are a part of phonological awareness. This domain of reading may be assessed using probes from the Dynamic Indicators of Basic Early Literacy Skills

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(DIBELS) including nonsense word ﬂuency, initial sound ﬂuency, and letter naming ﬂuency. A study with four kindergarten students with EBD implemented the PATR program (Torgesen & Bryant, 1994) to supplement the school district’s literacy instruction approach, the Scott Foresman Reading Program (2000) (Wehby et al., 2005). The four focus areas of PATR are rhyming, sound blending, sound segmenting, and reading/ spelling. The students of a general education classroom received PATR in groups of four, for 20 min daily, a total of 32 sessions, over the course of nine weeks. Positive reading outcomes were demonstrated from the DIBELS measures and teachers regarded the program as having positive effects on student learning albeit not on behavior. Similarly, recognizing phonemic awareness as a pivotal skill, Nelson and colleagues developed a preventative pre-reading intervention program titled Stepping Stones to Literacy. In 2005, this scripted reading program with 10–20 min lessons focusing on phonemic awareness and letter identiﬁcation was experimentally evaluated among 36 kindergarten students (Nelson, Benner, & Gonzalez, 2005). This program, in its developing stages, uniquely includes a rapid naming skills component which evaluates a child’s ability to retrieve phonemes from long-term memory. Given the substantial improvement documented with the experimental group receiving Stepping Stones to Literacy, rapid naming skills may be suggestive of further inquiry for K-3 learners with EBD who struggle with early literacy skills. Future directions. Reading interventions with promise have included the Corrective Reading program, phonological awareness intervention reading programs, repeated readings, and text mapping. Although the investigations included relatively few participants, a number of investigations have been extended and/or replicated. The promising effects of peer-mediated instruction and DI for youth with EBD were echoed once again among the reading investigations. Given their unique learning environment, the inclusion of incarcerated youth with EBD has also advanced this body of reading research. In addition, this collection of intervention reading research for students with EBD demonstrates that when combined, explicit strategic instruction can strengthen student achievement. For example, when peermediated instruction and speciﬁc reading programs are coupled with repeated reading interventions, student reading ﬂuency and reading comprehension outcomes may improve. In addition, self-monitoring, a practice often observed to support the behavioral attributes of students with EBD is inferred in many of the academic studies discussed (i.e., the graphing of oral reading ﬂuency rates).

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Finally, although only two middle school students with EBD demonstrated modest results, a recent investigation which lends itself for further exploration, targeted the motivational variables which may inﬂuence student reading performance. Daly et al. (2006) incorporated choices for students during reading ﬂuency instruction. Given a passage to read aloud for ﬂuency accuracy and a criterion goal to reach, students could choose to be instructed or not and then choose how to be instructed (i.e., antecedent instruction like modeling and practice) or error correction (i.e., practice, feedback). Rewards were incorporated as a motivator for students to reach the criterion goals established per passage. Students favored practice foremost and error correction second. Determining what motivates this population may not only advance our approach to reading instruction for students with EBD, but also our approach for minimizing the intrusive behaviors during reading instruction, as well.

Writing Interventions Among the challenges faced by students with EBD in schools is developing proﬁcient expressive writing skills. However, the research evidence supporting interventions in written expression is presently very limited. In a review of academic instructional interventions for students with EBD, Lane (2004) stated, ‘‘academic interventions targeting written expression . . . represent, by far, the least developed instructional area of the three [i.e., reading, writing, math] examined in this chapter’’ (p. 475). Lane was able to identify only a single study (McLaughlin, 1991) that met all relevant inclusion criteria; this investigation focused on spelling. More recent research in written expression for students with EBD includes the use of dialogue journals, and the Self-Regulated Strategy Development model (SRSD). These interventions are each described separately. Dialogue journals. Dialogue journals are an interactive and responsive form of writing, in which students and teachers carry on written ‘‘conversations’’ over time, sharing in writing their ideas, feelings, and concerns (Staton, 1987). Peyton and Staton (1993) provided the ﬁrst documented use of dialogue journals, in a study of 6th graders and their teacher. Used in this way, dialogue journals provide students with opportunities for social development as well as academic learning. That is, the dialogic interaction between teacher and student can facilitate the development of reading skills, modeling of correct English usage, and

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provide opportunities for writing in a less threatening and more enjoyable manner (Peyton, 1997). Deﬁcits in academic skill development and the commonly observed reluctance for self-expression of students with EBD can result in more offtask or work-avoidant behaviors (Landrum et al., 2003; Nelson et al., 2004). The use of dialogue journals may ameliorate these deﬁcits for students with EBD. Dialogue journal practice may encourage the literacy development of students with EBD, who often exhibit deﬁcits in the area of language disorders. It may be anticipated then, that improving the writing performance among students with EBD may be accomplished by providing opportunities for students to write in the more casual and consultative formats provided by the dialogue journal. Regan, Mastropieri, and Scruggs (2005) described the effects of dialogue journals on the writing quality and writing ﬂuency of 6th grade students with EBD. Five elementary students with EBD participated in this investigation, which employed a multiple baseline design across participants and a case study analysis to evaluate the effectiveness of using dialogue journals across intervention, maintenance, and generalization phases. It was anticipated that the dialogue journal would encourage more appropriate social skills by promoting a written personal discussion with the teacher centered around the individual student’s emotional and behavioral needs. Baseline data included each student’s responses to traditional writing prompts. Dependent measures included students time-on-task, the length of students’ written journal entries, the quality of writing in the student entries, and content analyses of the written comments. The following is an example of a teacher entry and a student response entry (p. 50): [Day 18] Hi, Trevor! You never said WHY you don’t like your goal at all. I noticed some positive interactions between you and [Will] yesterday. Once during recess when you were on the computer and again in the literature circle group – Sign of the Beaver. How is your relationship with Will? It seems to be very easy for you to make friendships with others. True? I remember your parents sharing that you had a really good friend last year – a girl, I think. Do you see her at all? Sincerely, Ms. [Smith] Day 18 Hi, Ms. [Smith],

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Alright, Listen. I’m going back in time to be my normal self. [Will] and I were friends in the beginning of the school year. Also, my relationships with [Will] are very well these days. No, it’s not easy to make friends with other people. People, usually, people don’t like me. They all think I’m retarded. I really don’t want to talk about friends right now. I’m having a bad day. Sincerely, [Trevor] Bye, Ms. [Smith]

Data analysis, based upon visual analysis and randomization tests, revealed an increase in time on task, length of written entries, and writing quality scores from baseline to intervention phases. Qualitative analysis suggested that participants used the dialogue journal for a variety of functions, and reported mild overall satisfaction with the journals. Overall, the results of this investigation suggested that dialogue journals may provide an important role in the instruction of students with EBD, with respect to development of written expression. Self-Regulated Strategy Development model. The SRSD model has proven successful with students with learning disabilities for improving written performance (Harris, Graham, Mason, & Friedlander, 2008). This approach provides support in self-regulation – including goal setting, self-monitoring, and self-instruction – while explicitly teaching speciﬁc strategies for improving writing performance. SRSD provides six stages of strategy instruction that takes students through understanding and application of the model, including the following: (a) develop background knowledge, (b) discuss it, (c) model it, (d) memorize it, (e) support it, and (f) independent performance (Harris et al., 2008). This approach has been shown to be very effective with typically achieving students and students with learning disabilities, and has been demonstrated to be effective in a very substantial body of research (e.g., Santangelo, Harris, & Graham, 2008). Until recently, however, little was known about whether such instructions could improve the writing performance of students with serious emotional disabilities. Mason and Shriner (2008) presented SRSD strategies in writing to six elementary aged students with EBD or at risk for EBD, and served largely in inclusive settings, and reported that their expressive writing performance improved. The SRSD strategy chosen had been developed for teaching persuasive, or opinion-based, essays, and was referred to as POW (pick my idea, organize my notes, write and say more)þTREE (topic sentence, reasons -three or more-, ending, examine). This particular strategy previously has been shown to be effective with low-achieving writers without EBD (e.g., Harris, Graham, & Mason, 2006). After intervention, students improved substantially in their abilities to write persuasive essays.

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Lane et al. (2008) investigated the effectiveness of a similar SRSD writing strategy, in teaching six elementary grade students at risk for EBD how to plan and write a story. This strategy was referred to as POWþWWW, What ¼ 2, How ¼ 2; (see Harris et al., 2008). The POW part of the acronym described the same elements as the POWþTREE strategy. In this case, the latter part of the strategy represents Who is in the story? When does the story take place? Where does the story take place? What happens in the story? What do the characters in the story do? How do the characters feel? and How does the story end? (Harris et al., 2008). Even considering this more recent research, however, writing research with students with EBD is very limited at present. It is unfortunate that more research has not addressed this issue, since students with EBD, who are frequently characterized as deﬁcient in communication skills, taking perspective, thinking reﬂectively, providing articulate self-expression, and using language in social situations (e.g., Kauffman & Landrum, 2008), could potentially beneﬁt enormously from increased written expression skills. Further, an improved ability to make a thoughtful and well-considered argument in writing – of the type taught directly with the SRSD strategies, could be of particular potential beneﬁt. Further, in previous research, students were enrolled in general education schools; however, it is unknown whether, or how, these strategies could be employed effectively with secondary students with very serious EBD. Students with very signiﬁcant EBD could conceivably beneﬁt greatly from the self-regulation and the cognitive strategy provided in SRSD strategies. However, these students also experience serious challenges in affective, behavioral, and emotional domains, and these challenges are likely to signiﬁcantly impede academic engagement. Recently, Mastropieri et al. (2009) implemented a design experiment (Brown, 1992) to determine under what circumstances previous research using SRSD could be adapted to work with nine middle school-aged students enrolled in a separate setting school for students with serious emotional disabilities. SRSD instruction was implemented approximately four days per week, over a 5-month period, during a 29 min school-wide remediation period, for a total of 55 sessions. Individual students were provided a mean of 42.2 (SD ¼ 5.8) days of instruction, with a range of 33.5–50 days. During this instructional period, teachers provided explicit, intensive instruction in the POWþTREE strategy, with many opportunities for practice and feedback. Several changes were made over the course of the instructional period, generally involving intensifying instructional procedures and increasing the teacher–student ratio. During instruction, recordings and ﬁeld notes revealed several student characteristics that interacted with the implementation of

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instruction. These student characteristics included cognitive organization, disorders of anxiety and effects thereof, disorders of perception, and aggressive behaviors. Each of these served to inhibit or slow the overall pace of instruction, reduce students’ time on-task signiﬁcantly, and required a substantial investment of teachers’ time and energy. For example, ﬁeld notes revealed the following incident (Mastropieri et al., 2009, p. 25) Alice came into the classroom, and called Maria, ‘‘little bitch.’’ Maria responded, and Richard got involved. Alice disrupted the class throughout the whole period. The teacher had to stay with Alice in the hallway while she screamed, kicked the door, and made derogatory remarks. Maria and Richard were arguing with her from inside the classroom. Tom, who was working diligently, became frustrated and angry because he could not concentrate. The same happened with Albert. Alice’s behavior was so outrageous that she got everyone off task and anxious.

At the end of the instructional period, however, post-test results revealed that students had improved signiﬁcantly in standardized measures of writing ﬂuency. Very substantial improvements were also noted in the number of words, number of essay components, number of paragraphs, number of transition words, and holistic quality scores. For example, the number of words written increased from a mean of 82.80 (SD ¼ 67.75) at pre-test to 230.78 (SD ¼ 115.78) at post-test, with a resulting effect size of 1.61. Although the amount of research investigating written expression in students with EBD is scarce, the research that does exist suggests that instructional and cognitive strategies are available that have strong promise for improving writing skills for this population. Further research could provide more insights on how interventions on written expression can help improve the social and academic outcomes for students with EBD.

SUMMARY Even the most effective evidence-based practices which support the literacy learning of students with EBD can falter if implemented ineffectively. Many contextual practices used by teachers can set the stage for either preventing or maximizing student potential (see teacher-mediated interventions review, Pierce, Reid, & Epstein, 2004). When quality practices are a part of a teacher’s daily instruction, the evidence-based strategies discussed in this chapter may produce optimal results. Lewis and colleagues (2004), for example, conducted a four-phase review of the literature to identify evidence-based practices for students with EBD. Four practices for teachers to consistently employ when teaching students with EBD include providing

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(a) high rates of praise, (b) high rates of opportunity to respond (OTR), (c) clear instructional strategies including DI, and (d) positive behavioral supports (i.e. school-wide, FBAs, etc.). School-wide behavioral supports may encourage a positive school adjustment for students with EBD; school adjustment has been correlated with higher academic achievement in both reading and writing for students with EBD in self-contained settings (Lane, Barton-Arwood, Nelson, & Wehby, 2008). Other variables which may enhance the effects of literacy instruction for students with EBD include the pacing of instruction with brief versus extended wait-time (Tincani & Crozier, 2008), student choice and reinforcement (Pierce et al., 2004), and providing students with a model for correct responses (i.e., writing, Miller, Gunter, Venn, Hummel, & Wiley, 2003). Although only a modest amount of research has been conducted to date in the area of literacy development for students with EBD, some general conclusions may still be drawn. It appears clear that behavior management techniques, taken alone, may not prove sufﬁcient to increase academic learning of EBD students. In fact, it has been demonstrated that specialized treatments can improve literacy functioning of these students, on both elementary and secondary levels. These treatments, as previously suggested by Landrum et al. (2003) include versions of those found to be effective with other low-achieving students, such as those with learning disabilities. Students with EBD appear to respond to literacy treatments that are intensive, highly structured, and carried out for longer periods of time. Treatments that maximize opportunities to respond, such as DI and peer mediation, also appear to be helpful. Finally, treatments are more likely to be successful when motivational components are built into the instruction, and when teachers modify instructions to meet the special social and emotional needs of students with EBD. Although there is clearly much to learn regarding the best way to address the needs of students with EBD in literacy instruction, there is at present a clear foundation upon which future research can be built. It is hoped that research in this area will increase in the future, so that the literacy skills of students with EBD may be maximized.

REFERENCES Alber-Morgan, S. R., Ramp, E. M., Anderson, L. L., & Martin, C. M. (2007). Effects of repeated readings, error correction, and performance feedback, on the ﬂuency and comprehension of middle school students with behavior problems. The Journal of Special Education, 41, 17–30.

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Allen-DeBoer, R., Malmgren, K. W., & Glass, M. E. (2006). Reading instruction in youth with emotional and behavioral disorders in a juvenile correctional facility. Behavioral Disorders, 32, 18–28. Barton-Arwood, S. M., Wehby, J. H., & Falk, K. B. (2005). Reading instruction for elementary-age students with emotional and behavioral disorders: Academic and behavioral outcomes. Exceptional Children, 72(1), 7–27. Blankenship, T. L., Ayres, K. M., & Langone, J. (2005). Effects of computer-based cognitive mapping on reading comprehension for students with emotional behavior disorders. Journal of Special Education Technology, 20, 15–23. Bradley, R., Henderson, K., & Monfore, D. A. (2004). A national perspective on children with emotional disorders. Behavioral Disorders, 29, 211–223. Brown, A. L. (1992). Design experiments: Theoretical and methodological challenges in creating complex interventions. Journal of the Learning Sciences, 2, 141–178. Bullis, M., & Yovanoff, P. (2006). Idle hands: Community employment experiences of formerly incarcerated youth. Journal of Emotional and Behavioral Disorders, 14, 71–85. Coleman, M., & Vaughn, S. (2000). Reading interventions for students with emotional/ behavioral disorders. Behavioral Disorders, 25, 93–104. Daly, E. J., Garbacz, S. A., Olson, S. C., Persampieri, M., & Ni, H. (2006). Improving oral reading ﬂuency by inﬂuencing students’ choice of instructional procedures: An experimental analysis with two students with behavioral disorders. Behavioral Interventions, 21, 13–30. Engelmann, S., Carnine, L., Johnson, G., Meyer, L., Becker, W., & Eisele, J. (2008). Corrective reading: Decoding strategies. Columbus, OH: McGraw Hill. Foresman, S. (2000). Scott Foresman reading. Upper Saddle River, NJ: Pearson Education. Fuchs, D., Fuchs, L. S., Thompson, A., Svenson, E., Yen, L., Otaiba, S. A., Yang, N., McMaster, K. N., Prentice, K., Kazdan, S., & Saenz, L. (2001). Peer-assisted learning strategies in reading: Extensions for kindergarten, ﬁrst grade, and high school. Remedial and Special Education, 22(1), 15–21. Gersten, R., Fuchs, L. S., Compton, D., & Coyne, M. (2005). Quality indicators for group experimental and quasi-experimental research in special education. Exceptional Children, 71, 149–164. Gulchak, D. J., & Lopes, J. A. (2007). Interventions for students with behavioral disorders: An international literature review. Behavioral Disorders, 32, 267–281. Harris, K. R., Graham, S., & Mason, L. H. (2006). Improving the writing performance, knowledge, and motivation of struggling writers in second grade: The effects of self-regulated strategy development. American Educational Research Journal, 42, 295–340. Harris, K. R., Graham, S., Mason, L. H., & Friedlander, B. (2008). Powerful writing strategies for all students. Baltimore: Brookes. Hewitt, F. (1968). The emotionally disturbed child in the classroom. Boston: Allyn & Bacon. Horner, R. H., Carr, E. G., Halle, J., Mcgee, G., Odom, S., & Wolery, M. (2005). The use of single-subject research to identify evidence-based practices in special education. Exceptional Children, 71, 165–171. Kauffman, J. M. (2008). Would we recognize progress if we saw it? A commentary. Journal of Behavioral Education, 17, 128–143. Kauffman, J. M., & Landrum, T. J. (2008). Characteristics of emotional and behavioral disorders of children and youth (9th ed.). Upper Saddle River, NJ: Prentice Hall.

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Kostewicz, D. E., & Kubina, R. M. (2008). The national reading panel guidepost: A review of reading outcome measures for students with emotional and behavioral disorders. Behavioral Disorders, 33, 62–74. Landrum, T. J., Tankersley, M., & Kauffman, J. M. (2003). What is special about special education for students with emotional or behavioral disorders? The Journal of Special Education, 37, 148–156. Lane, K. L. (2004). Academic instruction and tutoring interventions for students with emotional/behavioral disorders: 1990 to present. In: R. B. Rutherford, M. M. Quinn & S. R. Mathur (Eds), Handbook of research in emotional and behavioral disorders (pp. 462–486). New York: Guilford Press. Lane, K. L., Barton-Arwood, S. M., Nelson, J. R., & Wehby, J. (2008). Academic performance of students with emotional and behavioral disorders served in a self-contained setting. Journal of Behavioral Education, 17, 43–62. Lane, K. L., Harris, K. R., Graham, S., Weisenbach, J. L., Brindle, M., & Morphy, P. (2008). The effects of Self-Regulated Strategy Development on the writing performance of second-grade students with behavioral and writing difﬁculties. Journal of Special Education, 41, 234–253. Lewis, T. J., Hudson, S., Richter, M., & Johnson, N. (2004). Scientiﬁcally supported practices in emotional and behavioral disorders: A proposed approach and brief review of current practices. Behavioral Disorders, 29(3), 247–259. Lingo, A. S., Slaton, D. B., & Jolivette, K. (2006). Effects of corrective reading on the reading abilities and classroom behaviors of middle school students with reading deﬁcits and challenging behavior. Behavioral Disorders, 31, 265–283. Mason, L. H., & Shriner, J. G. (2008). Self-regulated strategy development instruction for writing an opinion essay: Effects for six students with emotional/behavior disorders. Reading and Writing, 21, 71–93. Mastropieri, M. A., Scruggs, T. E., Cuenca-Sanchez, Y., Irby, N., Mills, N., & Mason, L. (2009). Persuading students with emotional disabilities to write: Findings from a design experiment. Paper presented at the annual meeting of the American Educational Research Association, April, San Diego. Mastropieri, M. A., Scruggs, T. E., Spencer, V. G., & Fontana, J. (2003). Improving outcomes in high school world history: The relative effects of peer tutoring vs. guided notes. Learning Disabilities Research and Practice, 18, 52–65. McLaughlin, T. F. (1991). Use of a personalized system of instruction with and without a sameday retake contingency on spelling performance of behaviorally disordered children. Behavioral Disorders, 16(2), 127–132. Miller, K. A., Gunter, P. L., Venn, M. L., Hummel, J., & Wiley, L. P. (2003). Effects of curricular and materials modiﬁcations on academic performance and task engagement of three students with emotional and behavioral disorders. Behavioral Disorders, 28(2), 130–149. Mooney, P., Epstein, M. H., Reid, R., & Nelson, R. (2003). Status of and trends in academic intervention research for students with emotional disturbance. Remedial and Special Education, 24, 273–287. National Reading Panel. (2000). Teaching children to read: An evidence-based assessment of the scientiﬁc research literature on reading and its implications for reading instruction. Washington, DC: National Institute of Child Health and Human Development. Nelson, J. R., Benner, G. J., & Gonzalez, J. (2005). An investigation of the effects of a prereading intervention on the early literacy skills of children at risk of emotional

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disturbance and reading problems. Journal of Emotional and Behavioral Disorders, 13(1), 3–12. Nelson, J. R., Benner, G. J., Lane, K., & Smith, B. W. (2004). An investigation of the academic achievement of K-12 students with emotional and behavioral disorders in public school settings. Exceptional Children, 71, 59–73. Nelson, J. R., Stage, S. A., Epstein, M. H., & Pierce, C. D. (2005). Effects of pre-reading intervention on the literacy and social skills of children. Exceptional Children, 72(1), 29–45. Peyton, J. K. (1997). Dialogue journals: Interactive writing to develop language and literacy. Emergency Librarian, 24, 46–48. Peyton, J. K., & Staton, J. (1993). Dialogue journals in the multilingual classroom: Building language ﬂuency and writing skills through written interaction (ERIC Document Reproduction Service No.ED354789). Norwood, NJ: Ablex. Pierce, C. D., Reid, R., & Epstein, M. H. (2004). Teacher-mediated interventions for children with EBD and their academic outcomes. Remedial and Special Education, 25, 175–188. Quinn, M. M., Rutherford, R. B., Leone, P. E., Osher, D. M., & Poirier, J. M. (2005). Youth with disabilities in juvenile corrections: A national survey. Exceptional Children, 71(3), 339–345. Regan, K. S., Mastropieri, M. A., & Scruggs, T. E. (2005). Promoting expressive writing among students with emotional and behavioral disturbance via dialogue journals. Behavioral Disorders, 31(1), 33–50. Rivera, M. O., Al-Otaiba, S., & Koorland, M. A. (2006). Reading instruction for students with emotional and behavioral disorders and at risk of antisocial behaviors in primary grades: Review of literature. Behavioral Disorders, 31(3), 323–337. Ryan, J. B., Pierce, C. D., & Mooney, P. (2008). Evidence-based teaching strategies for students with EBD. Beyond Behavior, 17(3), 22–29. Ryan, J. B., Reid, R., & Epstein, M. H. (2004). Peer-mediated intervention studies on academic achievement for students with EBD: A review. Remedial and Special Education, 25(6), 330–341. Santangelo, T., Harris, K. R., & Graham, S. (2008). Using Self-Regulated Strategy Development to support students who have ‘‘trubol giting thangs into werds’’. Remedial and Special Education, 29, 78–89. Scruggs, T. E., Mastropieri, M. A., & Richter, L. (1985). Peer tutoring with behaviorally disordered students: Social and academic beneﬁts. Behavioral Disorders, 10, 283–294. Spencer, V. G. (2006). Peer tutoring and students with emotional and behavioral disorders: A review of the literature. Behavioral Disorders, 31(2), 204–222. Spencer, V. G., Scruggs, T. E., & Mastropieri, M. A. (2003). Content area learning and students with emotional or behavioral disorders: A comparison of strategies. Behavioral Disorders, 28(2), 77–93. Staton, J. (1987). The power of responding in dialogue journals. In: T. Fulwiler (Ed.), The journal book (pp. 47–63). Portsmouth, NH: Boynton/Cook. Staubitz, J. E., Cartledge, G., Yurick, A. L., & Lu, Y. (2005). Repeated reading for students with emotional or behavioral disorders: Peer and trainer mediated instruction. Behavioral Disorders, 31, 51–64. Strong, A. C., Wehby, J. H., Falk, K. B., & Lane, K. L. (2004). The impact of a structured reading curriculum and repeated reading on the performance of junior high students with emotional and behavioral disorders. School Psychology Review, 33, 561–581.

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Sutherland, K. S., & Snyder, A. (2008). Effects of reciprocal peer tutoring and self-graphing on reading ﬂuency and classroom behavior of middle school students with emotional and behavioral disorders. Journal of Emotional and Behavioral Disorders, 15, 103–118. Tincani, M., & Crozier, S. (2008). Comparing brief and extended wait-time during small group instruction for children with challenging behavior. Journal of Behavioral Education, 17, 79–92. Torgesen, J. K., & Bryant, B. R. (1994). Phonological awareness training for reading. Austin, TX: ProEd. Trout, A. L., Nordness, P. D., Pierce, C. D., & Epstein, M. H. (2003). Research on the academic status of students with emotional and behavioral disorders: A review of the literature from 1961–2000. Journal of Emotional and Behavioral Disorders, 11, 198–210. Wehby, J. H., Falk, K. B., Barton-Arwood, S., Lane, K. L., & Cooley, C. (2003a). The impact of comprehensive reading instruction on the academic and social behavior of students with emotional and behavioral disorders. Journal of Emotional and Behavioral Disorders, 11(4), 225–238. Wehby, J. H., Lane, K. L., & Falk, K. B. (2003b). Academic instruction for students with emotional and behavioral disorders. Journal of Emotional and Behavioral Disorders, 11, 194–197. Wehby, J. H., Lane, K. L., & Falk, K. B. (2005). An inclusive approach to improving early literacy skills of students with emotional and behavioral disorders. Behavioral Disorders, 30(2), 155–169.

DESIGNING FUNCTIONAL ASSESSMENT-BASED INTERVENTIONS USING A SYSTEMATIC APPROACH: A PROMISING PRACTICE FOR SUPPORTING CHALLENGING BEHAVIOR Kathleen Lynne Lane, Allison L. Bruhn, Mary E. Crnobori and Anne Louise Sewell ABSTRACT Functional assessment-based interventions are a tertiary support that have been incorporated in many three-tiered models of prevention to support students who do not respond to more global prevention efforts. Although endorsed by host of reputable organizations (e.g., National Association of School Psychologists) and mandated in Individuals with Disabilities Education Act (IDEA, 1997, 2004), concerns have been raised that this mandate may not be warranted if functional assessmentbased interventions do not meet minimum criteria to establish this as an Policy and Practice Advances in Learning and Behavioral Disabilities, Volume 22, 341–370 Copyright r 2009 by Emerald Group Publishing Limited All rights of reproduction in any form reserved ISSN: 0735-004X/doi:10.1108/S0735-004X(2009)0000022014

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evidence-based practice. One issue contributing to this concern is variability in the functional assessment process. John Umbreit and colleagues (2007) have attempted to address this concern by introducing a systematic approach that includes (a) a Function Matrix to analyze functional assessment data and identify the hypothesized function(s) of the target behavior and (b) a Function-Based Intervention Decision Model to guide intervention planning. In this chapter, we applied the core quality indicators for single-case research developed by Horner, Carr, Halle, McGee, Odom, and Wolery (2005) to studies conducted using this practice to determine the extent to which this systematic approach to functional assessment-based interventions met the standards for evidencebased practices for use in educational settings across the K-12 continuum for students with or at-risk for high incidence disabilities. If this practice is deemed to meet criteria, then this systematic approach may be particularly useful in meeting the mandate established in IDEA. Results suggest that it may be appropriate to establish this systematic method as a promising practice.

In recent years, many schools have embraced a new approach to preventing and managing problem behaviors that involves examining the school as a context for change (Horner & Sugai, 2000). Rather than viewing behavioral concerns as an indication of within child problems, schools have constructed three-tiered models of prevention such as response-to-intervention (RTI) and positive behavior support (PBS) models, as well as integrated approaches (see Lane, Kalberg, & Menzies, 2009) that focus on the school as a context for change (Sugai, 2008). These models employ data-based procedures to determine which students require more intensive levels of supports. These models traditionally involve three graduated levels of prevention ranging from: school-wide primary prevention programs (e.g., district-wide literacy program, anti-bullying programs), secondary prevention efforts (e.g., smallgroup instruction for students with common acquisition or performance deﬁcits; Gresham, 2002), and tertiary prevention efforts (e.g., highly individualized supports). Of these levels, tertiary supports offer the most intensive supports for students exposed to multiple risk factors who do not respond to more global intervention efforts (Lane, 2007; Walker & Severson, 2002). Functional assessment-based interventions are one type of tertiary prevention effort that has been widely used, particularly at the elementary level (Conroy, Dunlap, Clarke, & Alter, 2005; Kern, Hilt, & Gresham, 2004; Lane, Umbreit, & Beebe-Frankenberger, 1999).

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Function-based interventions refer to interventions constructed based on the function of the behavior rather that the form. Namely, functional assessment-based interventions are designed based on the reasons why problem behaviors occur rather than how the behavior looks (Umbreit, Ferro, Liaupsin, & Lane, 2007). The ﬁrst step in designing a functional assessment-based intervention is to identify a target behavior that if eliminated and replaced by a functionally equivalent, socially valid replacement behavior, could create meaningful, lasting changes in a student’s life (Baer, Wolf, & Risley, 1968). Once the target behavior is identiﬁed (e.g., disruption), then the motivation for this behavior is determined using descriptive (e.g., interviews, direct observations, and rating scales) and/or experimental (e.g., functional analysis) techniques. Data collected using these procedures are analyzed to determine the antecedent conditions that set the stage for the target behavior to occur as well as the maintaining consequences. In brief, behaviors serve to either obtain (positive reinforcement) or avoid (negative reinforcement) attention; activities or tasks; or tangible or sensory conditions (Umbreit et al., 2007). Results are summarized in a hypothesis statement such as the following: Mark engages in disruptive behavior to access peer attention and escape too-difﬁcult tasks. This hypothesis statement can be tested experimentally by systematically manipulating environmental conditions to conﬁrm maintaining consequences. Then, an intervention is constructed based on the function of the target behavior with the intent of teaching the student a more efﬁcient, reliable method for achieving his or her goal (e.g., escaping a too-difﬁcult or too-easy task; Umbreit, Lane, & Dejud, 2004). Such an intervention often involves three core components: (a) antecedent adjustments to prompt the replacement behavior and decrease the likelihood of the target behavior occurring, (b) increased rates of reinforcement for the replacement behavior, and (c) extinction procedures to eliminate the target behavior. At the conception, functional assessment procedures began in clinical settings to support individuals with developmental disabilities who displayed self-injurious behavior (Iwata, Dorsey, Slifer, Bauman, & Richman, 1982). However, during the past decade, functional assessment procedures have been applied in new ways. For example, functional assessment-based interventions have been designed, implemented, and evaluated in more naturalistic settings such as general education classrooms, self-contained classrooms, and alternative learning centers with students at risk for school failure (Umbreit et al., 2004), with attention difﬁculties (e.g., ADHD; Ervin, DuPaul, Kern, & Friman, 1998; Ervin et al., 2000), with

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emotional and behavioral disorders (Heckaman, Conroy, Fox, & Chait, 2000; Kern, Childs, Dunlap, Clarke, & Falk, 1994; Kern, Delaney, Clarke, Dunlap, & Childs, 2001; Smith & Sugai, 2000), as well as severe disabilities (Sasso, Reimers, Cooper, & Wacker, 1992). Thus, these procedures have moved beyond clinical settings and into more traditional educational settings to support students with a range of behavioral challenges (e.g., noncompliance, disruption, poor work completion, and low academic engagement). Functional behavioral assessments have been endorsed by a number of highly reputable organizations including the National Association of State Directors of Education (NASDE), National Association of School Psychologists (NASP), and National Institutes of Health (NIH). In fact, the Individuals with Disabilities Education Act (ﬁrst in IDEA, 1997 and again in IDEA, 2004) mandates functional behavioral assessments be conducted by school personnel under the following circumstances: (a) when a student is placed in an alternative placement for behavior determined to be a threat to the individual or others; (b) when a student is placed in an alternative setting for 45 days due to drug or weapons or drug violations; or (c) when a student’s suspension or alternative setting placement constitutes a change in placement or extends beyond 10 days (Drasgow & Yell, 2001; Kern et al., 2004). Given the success of functional assessment-based interventions present in the literature, some view this component of IDEA to be appropriate. However, some researchers contend that such a mandate may be premature if the practice is not yet supported by a strong evidence-base to suggest the efﬁcacy of functional assessment-based interventions with persons with and at risk for high incidence disabilities in more naturalistic settings (Fox, Conroy, & Heckaman, 1998; Gresham, 2004; Kern et al., 2004; Quinn et al., 2001; Sasso, Conroy, Stichter, & Fox, 2001). In short, a generalization error may have occurred if the current functional assessment procedures originally tested with adults with developmental disabilities in clinical settings have not been validated for use in K-12 educational settings with students with and at risk for high incidence disabilities (Lane, Kalberg, & Shepcaro, in press). One issue that makes it particularly challenging to determine whether functional assessment-based interventions are an evidence-based practice for this population is the fact that there is tremendous variability in how (a) data collected using traditional functional assessment tools are analyzed and (b) interventions are designed based on results of the functional assessment results. Recently John Umbreit and colleagues (2007) have attempted to

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address this concern by introducing a systematic approach to identifying the maintaining function(s) of target behaviors and developing interventions linked to the purpose of the target behavior. One feature of this systematic approach is to analyze data from all functional assessment tools (e.g., interviews, rating scales, direct observations, and functional analysis) by placing this information into a Function Matrix to identify the hypothesized function(s) of the target behavior. The Function Matrix (Umbreit et al.) is a six-celled grid used to examine whether the behavior is maintained by positive and/or negative reinforcement. Moreover, this matrix allows one to determine whether the target behavior occurs to seek (positive reinforcement) or avoid (negative reinforcement) attention, tangibles/activities, or sensory stimulation. After reviewing the data in the Function Matrix, the interventionist develops a statement describing the function(s) of the target behavior. A second feature of this systematic approach is the Function-Based Intervention Decision Model (Umbreit et al., 2007) developed to guide intervention planning using two key questions: (1) Is the replacement skill in the child’s repertoire? and (2) Does the classroom environment represent effective practices? The decision model guides involves using the answers to these two questions to focus the intervention on one of three interventions methods. Method 1: Teaching the Replacement Behavior is used when the replacement behavior is not in the student’s repertoire, such as when the student has an acquisition deﬁcit (Gresham, 2002) or when the behavior is not performed ﬂuently, and when the classroom represents effective practices. This intervention involves explicit instruction in the replacement behavior. Method 2: Improve the Environment is used when the student has the replacement behavior in his or her repertoire; yet, the antecedent conditions that precede the target behavior may not offer the most effective conditions for learning to occur (Lane, Weisenbach, Phillips, & Wehby, 2007). This intervention involves (a) eliminating or adjusting any existing aversive events and (b) providing a context that prompts the replacement behavior. Method 3: Adjust the Contingencies is used when the replacement behavior is in the students’ repertoire and when the antecedent conditions represent effective practices. This intervention method involves decreasing the rate of reinforcement for the target behavior and increasing the rate of reinforcement for the replacement behavior. Each method includes the three core components mentioned previously: teaching or modifying antecedents; reinforcing the occurrence of the replacement behavior; and withholding reinforcement (extinction) of the target behavior. Once the intervention method is selected, the interventionist designs speciﬁc plan tactics (Bergan & Kratochwill, 1990).

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The intent of this chapter is to determine whether this systematic approach to functional assessment-based practices meets the criteria posed by Horner et al. (2005) to determine the extent to which a practice is evidence-based using single case experimental investigations. This research team developed quality indicators for single case design inquiry that may be used to ascertain the degree to which a given study meets requisite criteria, thereby establishing the study as reputable. In addition, the team provided guidelines for evaluating bodies of reputable studies that meet the quality indicators to determine whether the practice is evidence-based. If the practice is evidencebased, then this systematic approach to functional assessment-based interventions may be particularly useful in meeting the mandate established in IDEA and recommended by the previously stated organizations. Consequently, the goal of this review was to ﬁeld-test these quality indicators by applying them to the body of literature exploring functional assessment-based interventions conducted using this systematic approach within educational settings with school-age students with or at risk for high incidence disabilities. Speciﬁcally, the intent was three-fold. First, we ﬁeldtested the quality indicators posed by Horner et al. (2005) to determine whether the studies using this systematic approach to functional assessmentbased interventions included the recommended quality indicators. Second, we analyzed studies meeting the recommended quality indicators to determine whether this systematic approach could be considered an evidence-based practice to functional assessment-based interventions for school-age students with or at risk for high incidence disabilities according to Horner et al.’s proposed standards. Third, we discussed the feasibility of these indicators, offering suggestions for future application of the quality indicators.

METHOD Article Selection Procedures We conducted a systematic search of psychology and educational databases (PsychInfo and ERIC) to identify function-based intervention studies conducted with school-age students across the pre-kindergarten through twelfth grade span using a systematic approach to (a) determining the hypothesized function of the target behavior and (b) designing an intervention linked to functional assessment results as developed by Umbreit et al. (2007). Search terms included all possible combinations and derivatives of the following sets of terms: functional assessment, functional

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analysis, assessment based, intervention, procedures, Function Matrix, and Function-Based Intervention Decision Model (Lane et al., in press). We examined the title and abstract of each article from the electronic search to determine whether the full article should be read to determine whether it met inclusion criteria (deﬁned below). Twelve articles were identiﬁed for possible inclusion through this electronic search. We conducted hand searches from 2004 to present of those journals that published one or more of the articles identiﬁed through the electronic search to identify other articles meeting inclusion criteria. The 2004 year was selected as the onset period given that the model was ﬁrst published during this year (Umbreit et al., 2004). Speciﬁcally, hand searchers were conducted in seven journals: Behavioral Disorders, Education and Treatment of Children, Education and Training in Developmental Disabilities, Journal of Early and Intensive Behavior Intervention, Journal of Emotional and Behavioral Disorders, Journal of Positive Behavior Interventions, and Topics in Early Childhood Education. For electronic journals (i.e., Journal of Early and Intensive Behavior Intervention), titles and abstracts of each issue were reviewed electronically to determine eligibility. The same twelve articles identiﬁed in the electronic search were identiﬁed through the hand search. Next, we contacted John Umbreit, the senior developer of the model, to inquire whether he knew of any in press studies conducted using the Function Matrix and the Function-Based Intervention Decision Model. An additional two in press articles (Turton, Umbreit, Liaupsin, & Bartley, 2007; Underwood, Umbreit, & Liaupsin, in press) were obtained during this process, the former of which appeared in print while the articles were being coded. Last, we compared our search results with other recent reviews of function-based interventions published since the model was developed in 2004 (e.g., Lane et al., in press). No additional articles were found through this process. Fourteen articles were identiﬁed through these procedures. Each article was read by the three authors to ascertain whether the article met the established inclusion criteria described below.

Inclusion Criteria The focus of this review was to examine the degree to which a systematic approach to conducting function-based intervention with students at risk and those with high incidence disabilities met the recommended indicators

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and to determine whether this model of function-based interventions is an evidence-based practice for this population. Therefore, studies were included in this review if they met the following criteria (a) the participants were diagnosed as having a high incidence disability or were at risk for school difﬁculty; (b) the participants were school-age (K-12) children and youth under the age of 18; (c) an intervention derived from a functional assessment data interpreted using the Function Matrix (Umbreit et al., 2007), with the focus of the intervention determined using the FunctionBased Intervention Decision Model (Umbreit et al.); (d) an intervention evaluated using single case methodology, with the article including a graphic display of student performance; and (e) publication in a refereed journal. Participants included students either with high incidence disabilities or at risk for school difﬁculty. This included students with (a) any of the high incidence disability categories speciﬁed in the IDEA such as speciﬁc learning disabilities (LD), emotional disturbance (ED), other health impaired, and speech and language disorders; (b) attention-related difﬁculties such as attention deﬁcit hyperactivity disorder (ADHD inattentive, hyperactive, or combined types) as speciﬁed in Diagnostic and Statistical Manual of Mental Health (DSM-IV TR, American Psychiatric Association [APA], 2001); (c) emotional or behavioral disorders, an inclusive term to describe students with behavioral concerns (Lane et al., in press); (d) emotional/behavioral disorders (EBD) and another disability speciﬁed in IDEA (e.g., LD, other heath impairment, speech and language disorder), (e) psychiatric diagnoses speciﬁed in the Diagnostic and Statistical Manual of Mental Health (DSMIV TR, APA, 2001) such as oppositional deﬁant disorder (ODD) or conduct disorder (CD); (f ) a general behavioral concern (e.g., noncompliance, disruption) that placed them at heightened risk for behavior disorders or school failure. Students were excluded if they had co-occurring cognitive impairments or developmental disabilities as the original research on functional assessment was conducted and conﬁrmed efﬁcacious for this population of students and adults. Second, all function-based interventions needed to take place with children and youth in a preschool or school setting across the pre-K through 12 continuum. Studies with persons over 18 years of age were excluded (e.g., Underwood et al., in press). Interventions implemented in noneducational settings such as day treatment centers, clinics, diagnostic centers, or residential day treatment centers were excluded as this review focused on school-based interventions. Third, functional assessment data needed to be summarized in and interpreted using the Function Matrix, presenting a hypothesis statement as

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to why the target behavior occurred. It was not necessary to include a visual graphic of the Function Matrix, provided that the information was summarized in text (Lane, Smither, Huseman, Guffey, & Fox, 2007). Articles that did not explicitly refer to the Function Matrix were excluded from the review (e.g., Blair, Liaupsin, Umbriet, & Kewon, 2006; Blair, Umbreit, Dunlap, & Jung, 2007; Lane, Thompson, Reske, Gable, & BartonArwood, 2006), with the exception of the ﬁrst application of this model (Umbreit et al., 2004). This article was retained as this was the ﬁrst formal investigation of systematic approach according to Umbreit. Functional assessment procedures such as interviews (parent, teacher, or student), direct observation of behavior using A-B-C data collection, behavior rating scales (e.g., Social Skills Rating System, Gresham & Elliott, 1990), or experimental (functional) analyses needed to be reported. At a minimum, at least one functional assessment tool must have been utilized, data must have been interpreted using the function matrix, and a hypothesis statement presented. If any of these three components were omitted, the article was excluded. Fourth, the intervention outcomes needed to be evaluated using single case methodology, although there were not speciﬁc design requirements (e.g., ABAB, multiple baseline, changing criterion, alternating treatment) for article inclusion. Furthermore, the article must have included a graph depicting student outcomes. Consistent with earlier reviews, the visual display was mandated to allow the coders to examine the accuracy of the results present in text with respect to stability, level, and trend (Lane et al., in press). Finally, articles must have appeared in peer-reviewed journals. Dissertations, chapters, and monographs were omitted as they had not been evaluated using the peer review process. Although dissertations are most often held to a high standard, they have not been through a peer review process outside of the immediate university setting. Of the 14 articles read, a total of 9 articles met these ﬁve inclusion criteria according to independent evaluations by the ﬁrst three authors. Next, these authors independently coded each article using the procedures delineated below.

Coding Procedures for Quality Indicators The nine identiﬁed articles were read and coded to determine the presence or absence of each of the 21 components constituting the seven quality indicators speciﬁed by Horner et al. (2005; see Table 1). These seven indicators included the following: describing participants and settings;

Yes (1.00) Yes (0.33) Yes (0.33) Yes (0.33) Yes (1.00) Yes (0.50) Yes (0.50) Yes (1.00) Yes (0.33) Yes (0.33) Yes (0.33) Yes (1.00) Yes (1.00) Yes (0.25) Yes (0.25) Yes (0.25) Yes (0.25)

Independent variable Independent variable description Systematically manipulated Fidelity of implementation

Baseline Repeated measurement, established pattern Description

Experimental control/Internal validity Three demonstrations – experimental effect Internal validity Pattern of results

External validity

Social validity DV is socially important Change in DV is socially important IV is practical and cost effective Use in typical contexts 6 6.67

Yes (1.00) Yes (0.20) Yes (0.20) Yes (0.20) Yes (0.20) Yes (0.20)

Dependent variable Description Quantiﬁable measurement Valid and well-described measurement Measured repeatedly Interobserver agreement

Number of Indicators: Absolute Coding Number of Indicators: Weighted Coding

No (0.67) Yes (0.33) No (0.00) Yes (0.33)

7 7.00

Yes (1.00) Yes (0.25) Yes (0.25) Yes (0.25) Yes (0.25)

Yes (1.00)

Yes (1.00) Yes (0.33) Yes (0.33) Yes (0.33)

Yes (1.00) Yes (0.50) Yes (0.50)

Yes (1.00) Yes (0.33) Yes (0.33) Yes (0.33)

Yes (1.00) Yes (0.20) Yes (0.20) Yes (0.20) Yes (0.20) Yes (0.20)

Yes (1.00) Yes (0.33) Yes (0.33) Yes (0.33)

Umbreit, Lane, and Lane, Dejud (2004) Weisenbach et al. (2006)

3 4.42

No (0.75) Yes (0.25) No (0.00) Yes (0.25) Yes (0.25)

No (0.00)

No (0.00) No (0.00) No (0.00) No (0.00)

Yes (1.00) Yes (0.50) Yes (0.50)

Yes (1.00) Yes (0.33) Yes (0.33) Yes (0.33)

Yes (1.00) Yes (0.20) Yes (0.20) Yes (0.20) Yes (0.20) Yes (0.20)

No (0.67) Yes (0.33) No (0.00) Yes (0.33)

Liaupsin, Umbreit, Ferro, Urso, and Upreti (2006)

5 6.42

No (0.75) Yes (0.25) Yes (0.25) No (0.00) Yes (0.25)

Yes (1.00)

Yes (1.00) Yes (0.33) Yes (0.33) Yes (0.33)

Yes (1.00) Yes (0.50) Yes (0.50)

Yes (1.00) Yes (0.33) Yes (0.33) Yes (0.33)

Yes (1.00) Yes (0.20) Yes (0.20) Yes (0.20) Yes (0.20) Yes (0.20)

No (0.67) No (0.00) Yes (0.33) Yes (0.33)

Stahr, Cushing, Lane, and Fox (2006)

Application of Quality Indicators Posed by Horner et al. (2005).

Describing participants and setting Participant description Participant selection Setting description

Quality Indicator

Table 1.

6 6.80

Yes (1.00) Yes (0.25) Yes (0.25) Yes (0.25) Yes (0.25)

Yes (1.00)

Yes (1.00) Yes (0.33) Yes (0.33) Yes (0.33)

Yes (1.00) Yes (0.50) Yes (0.50)

Yes (1.00) Yes (0.33) Yes (0.33) Yes (0.33)

No (0.80) Yes (0.20) Yes (0.20) Yes (0.20) Yes (0.20) No (0.00)

Yes (1.00) Yes (0.33) Yes (0.33) Yes (0.33)

Lane, Rogers et al. (2007)

350 KATHLEEN LYNNE LANE ET AL.

Yes (0.50)

Yes (1.00) Yes (0.50) Yes (0.50)

Baseline Repeated measurement, established pattern Description

7 7.00

5 5.83

Yes (1.00) Yes (0.25) Yes (0.25) Yes (0.25) Yes (0.25)

Yes (1.00)

Yes (0.33) Yes (0.33)

Yes (1.00) Yes (0.33)

No (0.00)

No (0.50) Yes (0.50)

Yes (1.00) Yes (0.33) Yes (0.33) Yes (0.33)

Yes (1.00) Yes (0.20) Yes (0.20) Yes (0.20) Yes (0.20) Yes (0.20)

No (0.33) Yes (0.33) No (0.00) No (0.00)

Turton, Umbreit, Liaupsin, and Bartley (2007)

2 3.63

Yes (1.00) Yes (0.25) Yes (0.25) Yes (0.25) Yes (0.25)

No (0.00)

Yes (0.33) No (0.00)

No (0.33) No (0.00)

Yes (0.50)

No (0.50) No (0.00)

Yes (1.00) Yes (0.33) Yes (0.33) Yes (0.33)

No (0.80) Yes (0.20) Yes (0.20) Yes (0.20) Yes (0.20) No (0.00)

No (0.00) No (0.00) No (0.00) No (0.00)

Wood, Umbreit, Liaupsin, and Gresham (2007)

Note: Subscales do not always total to 1.00 due to rounding. Numbers in parentheses refer to the weighted value of the presence of each intervention component constituting an indicator, with each component contributing an equal proportion of the quality indicator.

5 5.00

Yes (1.00)

No (0.00) Yes (1.00) Yes (0.25) Yes (0.25) Yes (0.25) Yes (0.25)

External validity

Social validity DV is socially important Change in DV is socially important IV is practical and cost effective Use in typical contexts

Number of Indicators: Absolute Coding Number of Indicators: Weighted Coding

Yes (0.33) Yes (0.33)

No (0.00) No (0.00)

Yes (1.00) Yes (0.25) Yes (0.25) Yes (0.25) Yes (0.25)

Yes (1.00) Yes (0.33)

Yes (1.00) Yes (0.33) Yes (0.33) Yes (0.33)

No (0.00) No (0.00)

Experimental control/Internal validity Three demonstrations – experimental effect Internal validity Pattern of results

Yes (1.00) Yes (0.50)

Yes (1.00) Yes (0.33) Yes (0.33) Yes (0.33)

Independent variable Independent variable description Systematically manipulated Fidelity of implementation

Yes (1.00) Yes (0.20) Yes (0.20) Yes (0.20) Yes (0.20) Yes (0.20)

Yes (1.00) Yes (0.20) Yes (0.20) Yes (0.20) Yes (0.20) Yes (0.20)

Dependent variable Description Quantiﬁable measurement Valid and well-described measurement Measured repeatedly Interobserver agreement

Yes (1.00) Yes (0.33) Yes (0.33) Yes (0.33)

Lane, Weisenbach et al. (2007)

Yes (1.00) Yes (0.33) Yes (0.33) Yes (0.33)

Lane, Smither et al. (2007)

Describing participants and setting Participant description Participant selection Setting description

Quality Indicator

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dependent variable (DV); independent variable (IV); baseline; experimental control/internal validity; external validity; and social validity. The guidelines for determining presence or absence of each component are detailed below, largely adhering to the same operational deﬁnitions speciﬁed in a review of function-based interventions conducted by Lane et al. (in press). Coding reliability was computed using an exact agreement formula in which all three raters needed to be in agreement for agreement to be present. Then, the percentage of agreement for each component as rated for each study was calculated by summing the total number of agreements, diving by 9 (the number of articles in the review), and multiplying the quantity to obtain a percentage (range: 0–100%). Any discrepancies were discussed and consensus achieved. Interrater reliability (IRR) is presented for each of the 21 components below. Describing participants and settings. According to Horner et al. (2005), this indicator contained three components: participant description, participant selection, and setting description. To meet the participant description component, participants had to be described precisely including the name of the speciﬁc disability or condition as well as the process used to determine the presence of the disability or conditions. Simply providing a general description (e.g., at risk or EBD) was considered insufﬁcient for this indicator. To meet the participant selection criteria, the authors must have deﬁned the selection procedures with sufﬁcient precision to afford replication. Examples included providing quantitative information from systematic screening procedures or a statement that the teacher reported nonresponsiveness to current educational programming. Setting description required a description of the physical setting containing sufﬁcient detail to enable other investigators to recruit comparable participants from comparable settings. Coding reliability was as follows: participant description 89%; participant selection 78%; and setting description 89%. Dependent variable. Horner et al. (2005) delineated ﬁve components to evaluate the quality of the DV. First, each DV needed to be operationally deﬁned, including examples or nonexamples. If more than one DV was reported, all DVs needed to meet these criteria in order for the component to be considered present. Second, each DV needed to be measured using a system that yielded a quantiﬁable index (e.g., percentage of time spent engaged in disruptive behavior). Third, the measurement of each DV needed to be valid and described precisely to enable replication (e.g., using a whole interval system for behaviors that the experimenter is attempting to increase or a partial interval system for behaviors that the experimenter is attempting to decrease). In brief, the question was asked: could another experimenter

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measure this same behavior using this recording system? Fourth, each DV needed to be measured repeatedly over time. We operationally deﬁned this component to require a minimum of three data points during the initial baseline phase as well as all intervention phases as this is a commonly used metric amongst single case methodology researchers (Kennedy, 2005). Fifth, data needed to be reported regarding the interobserver agreement (IOA) or reliability of each DV. Horner et al. (2005) stated that it was necessary to report IOA for each participant across each condition. They also indicated that it was insufﬁcient to report IOA only for the baseline conditions or only as one score across all measures. For purposes of this review, we operationalized this component by specifying that IOA must be reported for each individual variable, but may be reported as a mean across conditions in an ABAB design or a multiple baseline design if the authors indicated that IOA was collected during each condition. For example, two behaviors in an ABAB design should have at least two IOA mean percentages reported – one for each behavior with a reference to IOA data being collected during each condition. In instances when two more experiments were reported, both experiments had to meet criteria, otherwise the component was considered absent (e.g., Lane et al., 2007). However, the ideal would be reporting IOA for each behavior for each condition. In addition, Horner et al. indicated that IOA levels had to meet the following minimum standards: IOA ¼ 80% and Kappa ¼ 60% (if the Kappa statistic was reported). Given that some studies reported ranges as well as means, we further operationalized this component to require only the means to be at or above these criteria. Therefore, this component was considered present if the mean met criteria, independent of the reported ranges which may have had individual values below threshold. If a study reported IOA and Kappa values, then both minimum criteria had to be met for the component to be considered present. Coding reliability: DV description 78%; quantiﬁable measurement 100%; valid and well-deﬁned measurement 89%; measured repeatedly 100%; and IOA 89%. Independent variable. Horner et al. (2005) speciﬁed three required components to meet the IV quality indicator. First, the IV needed to be described with sufﬁcient precision to enable replication, inclusive of required materials and explicit procedures. General descriptions (e.g., token economy, self-monitoring) were considered insufﬁcient. Second, the IV needed to be manipulated systematically by the intervention agent (e.g., teacher, paraprofessional, researcher). Third, whereas Horner et al. considered ﬁdelity of implementation as ‘‘highly desirable’’ (p. 174), we required that ﬁdelity be measured explicitly and the data reported (Lane et al., 1999).

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Coding reliability: IV description 100%; systematically manipulated 100%; and ﬁdelity of implementation 100%. Baseline. Horner et al. (2005) stated that baseline conditions needed to include repeated measurement, with an established pattern of responding that could be used to anticipate or predict future behavior when the intervention was not in place. They quantiﬁed the required number of data points in the baseline condition as ‘‘ﬁve or more, although fewer data points are acceptable in speciﬁc cases’’ (Horner et al., p. 168). Furthermore, they indicated that the baseline condition must either provide a counter therapeutic trend or that the trend in the predicted direction of the intervention (e.g., increase in engagement) not be present. We contend that ﬁve data points in the baseline phase is too rigorous; therefore, we required a minimum of three data points given that ‘‘The goal of baseline is to establish patterns of behavior to compare to intervention. Therefore, a baseline needs only be long enough to adequately sample this pattern’’ (Kennedy, 2005, p. 38). To establish the second component, baseline description, the baseline conditions needed to be described with sufﬁcient precision to afford replication. Speciﬁcally, we required that the description include ‘‘who did what to whom, where were those actions taken, and when did those actions occur’’ (Lane, Wolery, Reichow, & Rogers, 2007, p. 226). Coding reliability: repeated measurement/established pattern 100% and description 89%. Experimental control/internal validity. Horner et al. (2005) stated that experimental control/internal validity was established when: . . . the design documents three demonstrations of the experimental effect at three different points in time with a single participant (within-subject replication), or across different participants (inter-subject replication). An experimental effect is demonstrated when predicted change in the dependent variable covaries with manipulation of the independent variable . . . (p. 168).

This indicator included three components. First, the design must have included a minimum of three demonstrations of experimental effect at three different time points. Although we required a minimum of three data points for the baseline phase, we did not necessarily require a minimum of three data points in the return to baseline condition to document an experimental effect provided that there was a clear, immediate change in level supported with two data points, with these two data points being either stable or depicting a counter therapeutic trend. If only one (AB) or two (ABA or multiple baseline across two conditions) demonstrations were evident, this component was considered absent. Second, the component of interval validity needed to be established by including an experimental design that

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controls for common threats (e.g., ABAB; BABA; changing criterion, multiple baseline with three legs, and alternating treatment). As with the Lane et al. (in press) review, we required that treatment integrity be assessed and reported given that the absence of treatment integrity poses a severe threat to internal validity (Gresham, 1989). Finally, Horner et al. required a pattern of responding that documented experimental control as determined by visual analysis techniques, which involve interpretation of level, trend, and variability of performance during each phase as well as other techniques (e.g., immediacy of effects, magnitude of change, percentage of overlapping data points, and consistency of data patterns). For our coding procedures, we determined that authors did not need to discuss each element (level, trend, variability) in text provided that (a) the study included a graph with individual student level data that allowed the reader to examine level, trend, and variability and (b) the graph suggested a functional relation between the introduction of the IV and corresponding changes in the DV. Coding reliability: three demonstrations of experimental effect 100%; internal validity 100%; and pattern of results 100%. External validity. Horner et al. (2005) recommended documenting external validity by replicating experimental effects across participants, settings, behaviors, or materials. Consistent with Tankersley and Cook (2007) and Lane et al. (in press), we determined this indicator as met if there was replication across one of the following: participants, setting, behavior, or materials. In addition, we required studies to (a) include three replications in one of those categories as recommended by Horner et al. and (b) meet all three criteria for experimental control/internal validity to be considered as possibly having external validity. We reasoned that internal validity is essential to establishing external validity (Lane, Kalberg, & Shepcaro, in press; Wolery, 2007 personal communication). Coding reliability: 89% external validity. Social validity. Social validity was the ﬁnal indicator established by Horner et al. (2005). Social validity refers to the social signiﬁcance of the goals, social acceptability of the treatment procedures, and the social importance of the effects (Baer et al., 1968). This indicator included four components. First, the DV needed to be socially important. Second, changes in the DV had to be socially important, which was deﬁned as ‘‘demonstration that the intervention produced an effect that met the deﬁned, clinical need’’ (Horner et al., p. 172). We further operationalized this component as present if (a) a functional relation was present between the intervention being introduced and changes in the DV or (b) the study included a measure of social validity, with data that suggested the rater viewed the intervention

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as producing a meaningful change. Third, the IV was practical and cost effective. Practicality was operationalized as a study conducted in a typical setting with traditional intervention agents and materials typically found in the reported setting. We operationalized cost effectiveness as being present under one of two conditions. First an intervention could be considered cost effective if the intervention was implemented with a high degree of ﬁdelity (80% or better for each introduction of the IV). Given that use is a behavioral marker for treatment integrity (which is a reﬂection of social validity; Gresham & Lopez, 1996), if the intervention agent thought the intervention was ‘‘too costly’’ (e.g., time, materials, personnel), they would not implement. Second, an intervention could be considered cost effective if formal social validity ratings reported high feasibility (practicality) either by rating scale or narrative comments. Finally, Horner et al. (2005) deﬁned use in typical contexts as follows: demonstration that typical intervention agents (a) report procedures to be acceptable, (b) report the procedures to be feasible within available resources, (c) report the procedure to be effective, and (d) choose to continue use of the intervention procedures after formal support/expectation of use is removed. (Horner et al., 2005, p. 172)

We coded this component as present if one or more of these four practices was reported. Coding reliability: social importance of DV 100%; change in DV is socially important 100%; IV is practical and cost effective 89%; and used in typical contexts 100%. In developing the coding scheme, our goal was to evaluate the studies using the least possible amount of inference by relying on the information published in the papers. The modiﬁcations and present clariﬁcations were intended to provide more clearly deﬁned criteria to promote consistency across raters and provide greater precision for the reader.

Procedures for Determining Evidence-Based Practice After coding the articles meeting the inclusion criteria, we applied the ﬁve standards for an evidence-based practice proposed by Horner et al. (2005) to the identiﬁed body of literature. Our intent was to ascertain whether the nine studies sufﬁciently documented this systematic approach to functional assessment-based interventions conducted in school settings as an evidencebased practice. The ﬁve standards are as follows: (a) the practice was deﬁned operationally in text; (b) the context and outcomes associated with the practice are deﬁned; (c) the practice was implemented as with ﬁdelity;

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(d) results suggest a functional relation between the practice and changes in DV; and (e) experimental effects are replicated across a minimum of 5 peerreviewed studies involving a minimum of 20 participants conducted by three different researchers in three different locales.

RESULTS In this chapter, we seek to address two primary questions which will serve as the organizational structure for the results section. First, we ask the question: To what extent do the studies conducted using a systematic approach to designing functional assessment-based interventions designed by Umbreit et al. (2004) adhere to the core quality indicators posed by Horner et al. (2005)? Second, we ask: To what degree do the studies that meet the quality indicators support function-based interventions for schoolage students as an evidence-based practice?

Studies Using Umbreit et al.’s (2004) Systematic Model to Design Function-Based Interventions: Findings of a Field-Test of Quality Indicators Quality Indicator 1: Describing Participants and Setting Results indicated that four of the nine studies (44%) met all three components constituting quality indicator 1: participant description, participant selection criteria, and setting description (see Table 1). Two additional studies addressed two of the three components, providing participant and setting descriptions detailed enough to enable replication (Liaupsin et al., 2006; Umbreit et al., 2004). Yet, these studies did not offer sufﬁcient precision in describing how participants were selected for participation in the study. One additional study provided explicit information on how the participant was selected as well as a replicable description of the setting; however, the participant description did not specify how the special education eligibility and mental health classiﬁcations were determined (Stahr et al., 2006). Looking across studies, participant descriptions met coding criteria in seven studies as did setting descriptions. However, only ﬁve studies described participant selection criteria with sufﬁcient detail to meet stated criteria. One study identiﬁed students for participation who were

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nonresponsive to secondary interventions according to standardized measures. For example, Nonresponsiveness to the secondary plan was deﬁned as having continued academic and behavioral concerns. . . . Speciﬁcally, Aaron was identiﬁed for participation in the current study because he had an overall GPA of 2.17 during the ﬁnal grading period (fourth quarter [March-May 2005], including one failing grade). In addition, he continued to struggle behaviorally during the same time frame as evidenced by (a) a year end (April) SRSS score of 14, and (b) nine discipline referrals. Further he had already earned three ofﬁce discipline referrals during the ﬁrst 6 weeks of the fall 2005 school year. Thus, according to schoolwide data, Aaron was the least responsive of all of the students who participated in the secondary plan and was therefore invited to participate in this study during fall 2005. (Lane, Rogers et al., 2007, p. 172)

The other four studies provided speciﬁc information on how students were identiﬁed for participation based on nonresponsiveness to the school-wide, primary prevention plan (e.g., Lane, Smither et al., 2007; Lane, Weisenbach, Little, Phillips, & Wehby, 2006; Lane, Weisenbach et al., 2007; Stahr et al., 2006). Quality Indicator 2: Dependent Variables Seven studies met the quality indicator for DV as evidenced by meeting coding criteria for the ﬁve components constituting this indicator: (a) description, (b) quantiﬁable measurement, (c) valid and well-described measurement, (d) repeated measurement, and (e) IOA. The two remaining studies met all but the IOA requirement (Lane, Rogers et al., 2007; Wood et al., 2007). In all studies, the DV were operationally deﬁned and measured using a procedure that yielded a quantiﬁable index. In addition, all studies used a valid, well-described measurement system (e.g., ‘‘30-second whole interval recording procedure. Observations lasted 15 minutes and began 5 to 10 minutes after the start of independent seat work period.’’ Umbreit et al., 2004, p. 16). Likewise, all studies involved repeated measurement of the DV. Of the two studies not meeting the IOA requirement, one study met criteria for one participant, but did not state that IOA data were collected during each phase for the second participant (Lane, Rogers et al., 2007). In the other study, the authors indicated that IOA data were collected during 31% of the sessions; however, it was not speciﬁed that IOA data were collected during each phase (Wood et al., 2007). It should be noted that in all studies, IOA met or exceeded the minimum accuracy criteria speciﬁed in the coding scheme (IOAW80%; KappaW60%).

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Quality Indicator 3: Independent Variable All studies met the quality indicator for IV as evidenced by addressing the three components constituting the indicator: IV description, systematically manipulated, and ﬁdelity of implementation. Each study provided a clear description of how the given intervention method was selected: (1) teach the replacement behavior, (2) improve the environment, or (3) adjust the contingencies (Umbreit et al., 2007). Furthermore, all studies provided a precise description of the antecedent adjustments, reinforcement procedures, and extinction procedures constituting each intervention method. In addition to providing evidence that the intervention was systematically manipulated and controlled by the experimenter, all studies monitored treatment ﬁdelity. In several studies, treatment ﬁdelity was monitored using component checklists completed by an outside observer and/or the teacher. Liaupsin et al. (2006) evaluated treatment using a 30-s whole interval procedure in which an outside observer monitored the presence (or absence) of all intervention components in place during each 30-s interval. Wood et al. (2007) used this procedure as well. Quality Indicator 4: Baseline Seven studies met the quality indicator for baseline as evidenced by addressing the two components (repeated measurement and established pattern description) constituting the quality indicator. In instances in which there were two data points in the return to baseline condition the component was met given that there was a clear change in level between the intervention and second baseline conditions (e.g., Umbreit et al., 2004). The remaining two studies met one of the two criteria for the baseline quality indicator, with one study meeting only the component of repeated measurement and established pattern (Turton et al., 2007) and another study meeting only the component of a baseline description that affords replication (Wood et al., 2007). Quality Indicator 5: Experimental Control/Internal Validity Six studies met the three components constituting this quality indicator: three demonstrations of experimental effect, internal validity, and pattern of results. One study used an appropriate design and monitored treatment integrity to satisfy coding criteria for internal validity, but did not demonstrate experimental effect or present a pattern of results that documented experimental control (Wood et al., 2007). The remaining two studies did not meet any of the three components according to the coding scheme.

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Six studies contained a minimum of three demonstrations of experimental effect. One study did not meet these criteria only because intervention was not warranted in one of the settings in the multiple baseline (Liaupsin et al., 2006). Seven studies met the internal validity component, using designs that control for common threats to internal validity such as ABAB withdrawal designs or multiple baseline across three settings, participants, or behaviors as well as meeting the requirement that treatment integrity be reported. Six studies demonstrated a pattern of results that indicated experimental control as evidenced by traditional approaches to analyzing single case design. However, some studies employed multiple baseline designs that did not afford the opportunity for the requisite number of demonstrations by intervening in fewer than three settings (e.g., Lane, Smither et al., 2007). Quality Indicator 6: External Validity Six studies established external validity according to the coding procedures. In the remaining studies, external validity was not established as we deﬁned the presence of internal validity as a prerequisite to external validity. As with previous reviews (see Lane et al., in press), the study needed to meet the full criteria for the experimental control/internal validity indicator to have the possibility of meeting the experimental control indicator. All studies that did meet the experimental control/internal validity indicator also met the external validity criteria (Lane, Rogers et al., 2007; Lane, Weisenbach et al., 2006; Lane, Weisenbach et al., 2007; Stahr et al., 2006; Turton et al., 2007; Umbreit et al., 2004). Quality Indicator 7: Social Validity Seven studies met the social validity quality indicator as evidenced by addressing the four components constituting this indicator: (a) DV is socially important; (b) change in DV is socially important; (c) IV is practical and cost effective; and (d) practice is used in typical contexts. The two remaining studies met three of the four components (Liaupsin et al., 2006; Stahr et al., 2006). One study did not meet the second component because social validity was not assessed explicitly and a functional relation was not established (Liaupsin et al., 2006). The ﬁnal study did not meet the third component (practical and cost effective), because treatment ﬁdelity was below the established 80% criteria speciﬁed in the coding procedures (Stahr et al., 2006). In this case low treatment ﬁdelity served as a behavioral marker for social validity; namely, if the intervention was implemented with low ﬁdelity it was viewed to be impractical.

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Determination of an Evidence-Based Practice Of the nine studies reviewed, two met all seven indicators. Consequently, if we apply an absolute criteria that studies must meet all seven quality indicators in entirety by adhering to all 21 components constituting these indicators, then it is not yet possible to document this systematic approach to design functional assessment-based interventions as developed by Umbreit and colleagues (2004) as an evidence-based practice for schoolage students according to Horner et al.’s (2005) standards. As a practice, the model proposed by Umbreit et al. includes (a) using function matrix to analyze functional assessment data collected using descriptive and experimental procedures; (b) an intervention decision model used to select one of three intervention methods that are linked to results of the functional assessment; (c) intervention methods that involve antecedent adjustment, reinforcement procedures, and extinction procedures; (d) use of an experimental design (e.g., ABAB, multiple baseline) that allows for experimental control to be established (Kennedy, 2005); (e) treatment ﬁdelity to ensure that all procedures are in place (Gresham, 1989); and (f ) social validity to measure the social signiﬁcance of the goals, social acceptability of the treatment procedures, and social importance of effects (Wolf, 1978). Of the studies reviewed, the number of quality indicators met in entirety ranged from 2 to 7 (see Table 1). Two studies met six indicators (Lane, Rogers et al., 2007; Umbreit et al., 2004), three met ﬁve indicators (Lane, Smither et al., 2007; Stahr et al., 2006; Turton et al., 2007), one study met three indicators (Liaupsin et al., 2006), and one met two indicators (Wood et al., 2007). However, it is possible to evaluate the indicators in other ways. For example, in a systematic review of functional assessment-based interventions conducted with adolescents with emotional and behavioral disorders, Lane et al. (in press) suggested another alternative for testing the indicators. Rather than evaluating only those studies that met all seven indicators in entirety, they suggested applying an 80% minimum criteria. Using this approach, ‘‘credit’’ or recognition of the components that were addressed in a given quality indicator are factored into an overall composite score. For example, describing participants and setting quality indicator contains three requisite components. These authors suggested weighting each component, with each component contributing an equal proportion of the quality indicator. In terms of the describing participants and setting quality indicator, each component would be weighted as contributing to 33.3% of the total score for the indicator. To illustrate, consider the article by Stahr et al. (2006). This

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study met the requirements for participant description selection and setting description. However, it did not satisfy the participant description given that the method section did not explicitly state how the participant, Shawn, received the special education label (e.g., as established by a multidisciplinary team). Rather than scoring this indicator as a zero for omitting one of the three components, a weighted scoring could be employed as follows: Describing participants and setting quality indicator ¼ ððparticipant descriptionÞð1Þð:33ÞÞ þ ððparticipant selectionÞð1Þð:33ÞÞ þ ððsetting descriptionÞð1Þð:33ÞÞ Using this approach, rather than receiving an absolute zero for not addressing all three components constituting the indicator, the study could receive ‘‘partial credit’’ for the two components that were addressed. In this case, the Stahr et al. study would receive a .67 rather than a zero for this indicator, yielding an overall score of 6.42 rather than a 5 (see Table 1 for the number of indicators present using a weighted coding system). Applying this weighted system to all studies, total scores would range from 3.63 to 7.00. If we establish a goal of requiring studies to address 80% of the indicators (80% 7 indicators), then studies with a total score of 5.60 would be rated as scientiﬁcally rigorous enough to be included in the decision-making process regarding the extent to which the given practice was evidence-based. In this review, a total of six studies would have been included for evaluating the evidence base (Lane, Rogers et al., 2007; Lane, Weisenbach et al., 2006; Lane, Weisenbach et al., 2007; Stahr et al., 2006; Turton et al., 2007; Umbreit et al., 2004). Next, these studies would be evaluated against the following ﬁve standards. First, the practice was operationally deﬁned in text. Second, the context and outcomes associated with the practice were deﬁned. Third, the practice was implemented with ﬁdelity. Fourth, the results suggest a functional relation between the practice and changes in DV. Fifth, experimental effects were replicated across more than ﬁve peer-reviewed studies with more than three different ﬁrst authors conducting these studies in three different locales (Arizona, Tennessee, and Bermuda). Yet, fewer than 20 participants were involved in the six studies meeting this 80% criteria. Thus, all but one criterion was met for establishing functional assessment-based interventions using this systematic approach with school-age participants with or at risk for high incidence disabilities.

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DISCUSSION Functional assessment-based interventions are an effective, tertiary support that have been incorporated in many three-tiered models of prevention to support students who do not respond to more global prevention efforts. This practice has been supported by a host of reputable organizations (e.g., NASDE; NASP; and NIH) and has been mandated in IDEA (1997, 2004) when certain conditions prevail (Drasgow & Yell, 2001; Kern et al., 2004). Yet, concerns have been raised that this mandate may not be warranted if functional assessment-based interventions do not meet minimum criteria to establish this as an evidence-based practice (Fox et al., 1998; Gresham, 2004; Kern et al., 2004; Quinn et al., 2001; Sasso et al., 2001). One issue that has made it difﬁcult to determine whether functional assessment-based interventions are an evidence-based practice is the fact that there is tremendous variability in how (a) data collected using traditional functional assessment tools are analyzed and (b) interventions are designed based on results of the functional assessment. John Umbreit and colleagues (2007) have attempted to address this concern by introducing a systematic approach that includes a Function Matrix to analyze functional assessment data and identify the hypothesized function(s) of the target behavior and a Function-Based Intervention Decision Model (Umbreit et al., 2007) to guide intervention planning. The intent of this chapter was to determine whether this systematic approach to functional assessment-based practices meets the criteria proposed by Horner et al. (2005) to establish this practice as evidencebased. If this practice is deemed to meet criteria, then this systematic approach to functional assessment-based interventions may be particularly useful in meeting the mandate established in IDEA (1997, 2004). Findings from this systematic review of the literature identiﬁed nine studies that met inclusion criteria by applying this systematic approach to functional assessment-based interventions with school-age student with or at risk for high incidence disabilities. Using an absolute coding criteria, two studies met all seven core indicators. However, application of an 80% criteria produced six studies that met 80% of the core quality indicators. In evaluating the six studies that met the later criteria, this practice fell slightly short of the established criteria for deﬁning a practice as evidence based, given that the six studies supported 9 participants rather than the requisite 20 participants. However, this body of literature did meet the remaining standards in that (a) the practice was operationally deﬁned; (b) the context and outcomes associated with the practice were deﬁned;

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(c) treatment ﬁdelity was established; (d) a functional relation between the practice and changes in DV was evident; and (e) experimental effects were replicated across a minimum of ﬁve peer-reviewed studies by three different researchers (ﬁrst authors) in three different locales (Arizona, Tennessee, and Bermuda). Given that all standards except for the requisite number of participants were established when evaluating this body of literature, it may be that additional studies using the same rigorous research design features are needed to establish this method as an evidence-based practice. In the interim, it may be appropriate to establish this systematic method as a promising practice (Gersten et al., 2005). While considering the appropriateness of this conclusion, we encourage the reader to consider the following three considerations.

Considerations Speciﬁcally, we encourage the reader to consider issues of variability in the functional assessment tools employed, the range of students included, and the settings in which this process was conducted. First, as with the Lane et al. (in press) review, there was variability in the functional assessment tools used, student characteristics, and instructional settings. For example, although all studies involved at least one functional assessment tool, the function matrix, a hypothesis, the intervention decision model, and an intervention linked to the functional assessment results, studies used a range of procedures to determine maintaining function of the target behavior (see Table 2). Although all studies conducted direct observations, teacher interviews, and students interviews, some also involved additional interviews with other people such as parents (Lane, Rogers et al., 2007; Lane, Weisenbach et al., 2006), paraprofessionals (Umbreit et al., 2004), or additional teachers (Turton et al., 2007). Only three studies conducted an experimental analysis of behavior (Turton et al., 2007; Umbreit et al., 2007; Wood et al., 2007). Second, the articles reviewed contained a range of students including those receiving special education services for speciﬁc learning disability (e.g., Lane, Rogers et al., 2007), at risk for negative outcomes (e.g., Lane, Rogers et al., 2007; Lane, Weisenbach et al., 2006; Lane, Weisenbach et al., 2007; Umbreit et al., 2004; Wood et al., 2007), and with co-morbid conditions (Stahr et al., 2006). Likewise the studies served students of a variety of ages ranging from kindergarten (Lane, Smither et al., 2007), to middle school (Lane, Rogers et al., 2007; Liaupsin et al., 2006) to high school (Turton et al., 2007).

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Functional Assessment Components.

Table 2. Functional Assessment Component

Direct observations Teacher interview Student interview Parent interview Other interview Rating scales Record search Functional analysis Function matrix Decision model Hypothesis statement Intervention linked to assessment data

Functional Assessment Component Direct observations Teacher interview Student interview Parent interview Other interview Rating scales Record search Functional analysis Function matrix Decision model Hypothesis statement Intervention linked to assessment data a

Umbreit, Lane, and Dejud (2004)

Lane, Weisenbach et al. (2006)

Liaupsin, Umbreit, Ferro, Urso, and Upreti (2006)

Stahr, Cushing, Lane, and Fox (2006)

Lane, Rogers et al. (2007)

1 1 1 0 1 0 0 1 0a 1 1

1 1 1 1 0 1 0 0 1 1 1

1 1 1 0 0 0 1 0 1 1 1

1 1 1 0 0 1 1 0 1 1 1

1 1 1 1 0 1 0 0 1 1 1

1

1

1

1

1

Lane, Smither et al. (2007)

Lane, Weisenbach et al. (2007)

Turton, Umbreit, Liaupsin, and Bartley (2007)

Wood, Umbreit, Liaupsin, and Gresham (2007)

1 1 1 0 0 1 1 0 1 1 1 1

1 1 1 1 0 1 0 0 1 1 1 1

1 1 1 0 1 0 0 1 1 1 1 1

1 1 1 0 0 0 0 1 1 1 1 1

This article was retained as this was the ﬁrst formal investigation of the systematic approach according to Umbreit, senior developer of the systematic approach examined.

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Finally, although all studies were conducted in school-based settings, students were served in a range of settings. For example, some studies took place in inclusive schools (e.g., Lane, Rogers et al., 2007; Lane, Weisenbach et al., 2006; Lane, Weisenbach et al., 2007), others took place in traditional general education schools (e.g., Lane, Smither et al., 2007; Umbreit et al., 2004), self-contained schools (e.g., Stahr et al., 2006), alternative high school (e.g., Turton et al., 2007), and charter schools (e.g., Liaupsin et al., 2006). In sum, there was variability with respect to the functional assessment tools employed, student participants, and instructional settings. Therefore, even if the body of literature reviewed has been found to be an evidencebased practice for school-age students, the actual efﬁcacy of the practice may have produced varied results along these three factors.

Concluding Thoughts As we conducted this systematic review of the literature, we wanted the reader to consider a few additional thoughts. First, although it is highly appropriate to have quality indicators or standards available to evaluate the current (e.g., studies in review) and future studies (e.g., grant applications), it is important to recognize that such indicators may be to some extent arbitrary or too stringent (e.g., ﬁve data points in baseline) that perhaps should not be considered absolute standards (Lane et al., in press). For example, is it always necessary or reasonable to require cost effectiveness to be explicitly stated? or the speciﬁc instrument and process used to determine the disability status to be reported? or baseline to include a minimum of ﬁve data points? In addition, it is also important to recognize the tension between scientiﬁc rigor and feasibility. As we move such applied behavior analytic techniques into more applied settings, it may not always be reasonable to address some of these standards. For example, if the return to baseline suggests immediate changes is level, is it necessary or appropriate to have an extended return to baseline condition? Second, we would also like the reader to consider that as science advances, new expectations are established. For example, all studies included in this review mentioned and reported treatment integrity data. However, had this body of literature included studies from 20 years prior such as those included in the review by Lane et al. (in press), it is highly likely that the treatment integrity component would not have been addressed given that the emphasis on the importance of treatment integrity had not yet been established (Gresham, 1989; Yeaton & Sechrest, 1981).

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Moreover, we expect standards to change over time and as they do, we must be cautious in how current standards are used to evaluate various bodies of literature that may span a greater period of time than the studies included in this review. Despite these issues, we conclude that this systematic approach to conduct functional assessment-based interventions proposed by Umbreit and colleagues is a promising practice that has yielded socially valid changes for school-age students with and at risk for high incidence disabilities. If we are permitted the latitude to speculate, we predict that in the next 5 years this approach will meet the criteria necessary to establish this as an evidencebased practice. Namely, consider that this practice has only been in place since 2004. Already six scientiﬁcally rigorous studies with nine participants suggest positive outcomes. We look forward to additional applications of this systematic approach to functional assessment in the near future so that more precise recommendations can be made regarding the application of this model.

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