International Review of Research in Mental Retardation: v. 6

International Review of RESEARCH IN MENTAL RETARDATION VOLUME 6 Consulting Editors for This Volume John M. Belmont UN...

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International Review of RESEARCH IN MENTAL RETARDATION VOLUME 6

Consulting Editors for This Volume John M. Belmont UNIVERSITI OF KANSAS

Paul S . Siege1 UNIVERSITY OF ALABAMA

LAWRENCE, KANSAS

UNIVERSITY, ALABAMA

Joseph W. Gallagher

Herman H . Spitz

UNIVERSITY OF ALABAMA UNIVERSITY, ALABAMA

Philip Roos NATIONAL ASSOCIATION

FOR RETARDED CHILDREN DALLAS, TEXAS

E. R. JOHNSTONE TRAINING A N D RESEARCH CENTER BORDENTOWN, NEW JERSEY

Dennis Runcie UNIVERSITY OF ALABAMA UNIVERSITY, ALABAMA

International Review of RESEARCH IN MENTAL RETARDATION

EDITED BY

NORMAN R. ELLIS D E P A R T M E N T OF PSYCHOLOGY U N I V E R S I T Y OF A L A B A M A UNIVERSITY. A L A B A M A

VOLUME 6

1973

ACADEMIC PRESS New York and London A Subsidiary of Harcourt Brace Jovanovich, Publishers

COPYRIGHT 0 1973, BY ACADEMIC PRESS, INC. ALL RIGHTS RESERVED. NO PART OF THIS PUBLICATION MAY B E REPRODUCED OR TRANSMITTED IN ANY FORM OR BY ANY MEANS, ELECTRONIC OR MECHANICAL, INCLUDING PHOTOCOPY, RECORDING, OR ANY INFORMATION STORAGE AND RETRIEVAL SYSTEM, WITHOUT PERMISSION IN WRITING FROM THE PUBLISHER.

ACADEMIC PRESS, INC.

111 Fifth Avenue, New York, New York 10003

United Kingdom Edition published by ACADEMIC PRESS, INC. (LONDON)LTD. 24/28 Oval Road, London N W I

LIBRARY OF

CONQRESS CATALOO CARD

NUMBER:65-28627

PRINTED IN THE UNITED STATES OF AMERICA

Contents

List of Contributors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Prefuce

ix

..............................................................................

xi

.........................................................

XIII

Contents of Previous Volumes

...

Cultural Deprivation and Cognitive Competence

J. P. DAS ......................................

I . Introduction .......

ce .............. A Cross-Cultural Look at Cultural Deprivation .............. ....................................... IQ. SES, and Cognitive Competence Ethnicity, Personality, and Cognitive Competence: Results of Three Parallel ............................................................. Studies Structure of Cognitive Abilities . . . . . . . . . . Summary ............................... .................... References .....................

11. Cultural Deprivation:

Ill. IV. V.

VI. VII.

2 3 22 31

35 44 48 50

Stereotyped Acts

ALFRED A. BAUMEISTER A N D REX FOREHAND I. Introduction .................................................................... 11. Theoretical Formulations ................................... Ill. Research Strategies ......................................... IV. Correlational Studies ............ .............. V. Intervention Studies .............................................................

55

69

.................. ........... 90 References ...................................................................... 92 Research on the Vocational Habilitation of the Retarded: The Present, The Future

MARCW. GOLD I. Introduction ................................................................... 11. The Present .................................................................... V

97 101

vi

Contents

111 The Future .................................................................... IV. Concluding Comments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

References .....................................................................

124 140 141

Consolidating Facts into the Schematized Learning and Memory System of Educable Retardates

HERMANH . SPITZ 1. Psychology’s Frame of Reference I I . Psychology’s Forgotten Past 111. The Idealized Memory Syste IV. Discovering Redundancy . . . . V. Summary .................

..............................................

149 1.50 ...................... 151 ....................................... 158 ...................... ............ 166 .......................... 166 .............................. ......................

An Attention-Retention Theory of Retardate Discrimination Learning

MARYANNFISHER A N D DAVID ZEAMAN I . Introduction

..................................................................

.I71 I73 ..................................... I78

11. A Concise Quantitative Statement of the Theory ...

111. IV. V. VI. VII. VIII. IX. X. XI. XII. XIII. XIV.

Outline of the Data Domain of the Theory What is Learned . . . . . . . One or Two Learning Pro Strengths or Relative Stre Gradual vs. All-or-Nothin Mechanism of Learning . Generalization ............... Chaining . . . . . . . . . . . . . . Modifiability of the Links Breadth of Attention . . . Feedback ..................................................................... Retention ................ ........................

..................................................... XVI. Control Processes and Structural Features ..................................... References ....................................................................

,217 ,223 .242 ,244 ,251

Studying the Relationship of Task Performance to the Variables of Chronological Age, Mental Age, and IQ

WILLIAM E. KAPPAUF 1. Introduction ............................................ 11. A Developmental Population for Research on C 111. Two-Dimensional Maps of the CA, MA, IQ Domain ...

IV. Critique of Harter’s Interpretation of Her Data . . . . . . . . . . . . . ., 2 6 4 V. Intercorrelations and the Factor Space ........................................ ,266 VI. Response Surfaces and the Ruled Surface Model VII. Procedure for Deriving and Plotting Iso-Performance Contours . . . . . . . . . . . . . . . ..280

CONTENTS

VIII . IX . X. XI . XI1 . XI11 .

vii

Analysis of Harter’s Data Using Iso-Performance Contours Appraisal o f the Graphic Approach in the Analysis of Response Surfaces . . . . . . .293 Some Comments on the Research Literature ............ The Design of Experiments on CA. MA. and IQ ................................ 303 The Problem of Correlated Variables in Other Areas of Research ...............309 Summary and Conclusions ..................................................... 310 312 Appendix ...................................................................... ................................... ........................ 315 Author Index ................................................................... Subject Index ..................................................................

319 326

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List of Contributors Numbers in parentheses indicate the pageson whichthe authors’ contributions begin.

ALFRED A. BAUMEISTER, University of Alabama, University, Alabama ( 5 5 )

J . P. DAS,Centre for the Study of Mental Retardation, University of Alberta, Edmonton, Canada (1) MARYANNFISHER, University of Connecticut, Storrs, Connecticut (169) REXFOREHAND, University of Georgia, Athens, Georgia ( 5 5 ) MARCW . GOLD,Children’s Research Center, Universityof Illinois at UrbanaChampaign, Champaign, Illinoii (97) WILLIAM E. KAPPAUF, University of Illinois at Urbana-Champaign, Champaign, Illinois (257) HERMAN H . SPITZ,E. R. Johnstone Training and Research Center, Bordentown, New Jersey (149)

DAVID ZEAMAN, University of Connecticut. Storrs, Connecticut (169)

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Currently, emphasis in mental retardation is placed on service programs, community living, civil rights of the retarded, and similar issues. This state of affairs is reflected not only in the activities of the professional and scientific community, but also in the policies of federal, state, and other agencies providing the bulk of financial support for work in mental retardation. Research, both basic and applied, seems to have waned in comparison. Obviously, both service and research deserve the attention of scientists and professionals. Indeed, their strong interdependence should be recognized explicitly. Moreover, it should be noted that the basic human rights of the retarded can be insured only through increased knowledge of their behavioral and biological inadequacies. Service programs for the retarded in the absence of basic knowledge of behavior will ultimately prove to be custodial in nature. These serial publications are dedicated to the position that increased knowledge of the retarded through research is of central importance to the mentally retarded in their struggle to adapt to a complex society. These volumes provide current information on behavioral research and theory, both basic and applied.

NORMAN R. ELLIS University of Alabama December, I972

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Contents of Previous Volumes Volume 1

A Functional Analysis of Retarded Development W. BIJOU SIDNEY Classical Conditioning and Discrimination Learning Research with the Mentally Retarded LEONARD E. Ross The Structure of Intellect in the Mental Retardate AND C. EDWARD MEYERS HARVEY F. DINGMAN Research on Personality Structure in the Retardate EDWARD ZIGLER Experience and the Development of Adaptive Behavior H. CARLHAYWOOD AND JACK T. TAPP A Research Program on the Psychological Effects of Brain Lesions in Human Beings RALPHM. REITAN Long-Term Memory in Mental Retardation JOHNM. BELMONT The Behavior of Moderately and Severely Retarded Persons JOSEPH E. SPRADLIN AND FREDERIC L. GIRARDEAU Author Index-Subject

Index

Volume 2

A Theoretical Analysis and Its Application to Training the Mentally Retarded M. RAYDENNY The Role of Input Organization in the Learning and Memory of Mental Retardates HERMAN H. SPITZ

...

Xlll

Contents of Previous Volumes

xiv

Autonomic Nervous System Functions and Behavior. A Review of Experimental Studies with Mental Defectives RATHE KARRER Learning and Transfer of Mediating Responses in Discriminative Learning BRYANE. SHEPPA N D FRANK D. TURRISI A Review of Research on Learning Sets and Transfer ofTraining in Mental Defectives MELVIN E. KAUFMAN AND HERBERT J. PREHM Programming Perception and Learning for Retarded Children MURRAY SIDMAN AND LAWRENCE T. STODDARD Programmed Instruction Techniques for the Mentally Retarded FRANCES M. GREENE Some Aspects of the Research on Mental Retardation in Norway I V A RARNLJOT BJORGEN Research on Mental Deficiency During the Last Decade in France R. LAFONAND J. CHABANIER Psychotherapeutic Procedures with the Retarded STEKNLICHT MANNY Author Index-Subject

Index

Volume 3

Incentive Motivation in the Mental Retardate PAULS. SIEGEL Development of Lateral and Choice-Sequence Preferences I R M A R. GERJUOY A N D JOHNJ. WINTERS, JR. Studies in the Experimental Development of Left-Right Concepts in Retarded Children Using Fading Techniques SIDNEY w. B1Jou Verbal Learning and Memory Research with Retardates: An Attempt to Assess Developmental Trends L. R. GOULET Research and Theory in Short-Term Memory KEITHG. SCOTTA N D MARCIA STRONG SCOTT Reaction Time and Mental Retardation ALFRED A. BAUMEISTER A N D GEORGE KELLAS

CONTENTS OF PREVIOUS VOLUMES

xv

Mental Retardation in India: A Review of Care, Training, Research, and Rehabilitation Programs J. P. DAS Educational Research in Mental Retardation SAMUEL L. GUSKIN A N D HOWARD H. SPICKER Author Index-Subject

Index

Volume 4

Memory Processes in Retardates and Normals NORMAL R. ELI-IS A Theory of Primary and Secondary Familial Mental Retardation ARTHUR R. JENSEN

Inhibition Deficits in Retardate Learning and Attention LAIRD W. HEALA N D JOHNT. JOHNSON, JR. Growth and Decline of Retardate Intelligence MARYANNFISHER A N D DAVID ZEAMAN The Measurement of Intelligence A. B. SILVERSTEIN Social Psychology and Mental Retardation WARNER WILSON Mental Retardation in Animals GILBERT W. MEIER Audiologic Aspects of Mental Retardation LYLEL. LLOYD Author Index-Subject

Index

Volume 5

Medical-Behavioral Research in Retardation JOHNM. BELMONT Recognition Memory: A Research Strategy and a Summary of Initial Findings KEITHG. SCOTT

xvi

Contents of Previous Volumes

Operant Procedures with the Retardate: An Overview of Laboratory Research PAULWEISBERG Methodology of Psychopharmacological Studies with the Retarded A N D JOHNS. WERRY ROBERTL. SPRAGUE Process Variables in the Paired-Associate Learning of Retardates AND GEORGE KELLAS ALFRED A. BAUMEISTER Sequential Dot Presentation Measures of Stimulus Trace in Retardates and Normals EDWARD A. HOLDEN, JR. Cultural-Familial Retardation FREDERIC L. GIRARDEAU German Theory and Research on Mental Retardation: Emphasis on Structure A N D PAUL B. BALTES LOTHAR R. SCHMIDT Author Index-Subject

Index

International Review of RESEARCH IN MENTAL RETARDATION VOLUME 6

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Cultural Deprivation and Cognitive Competence J. P. DAS CENTRE FOR THE STUDY OF MENTAL RETARDATION, UNIVERSITY OF ALBERTA, EDMONTON. CANADA

I. Introduction . . . . . . .

...............

....

m and Essence ................................ A. The Concept of Cultural Deprivation ...................................... ............................ B. Socioeconomic Status and Language C. Early Experience and Cognitive Funct ............................ D. Poverty, Nutrition, and Cognitive Ability .......................... E. Compensatory Education for the Disadvantaged Child ...................... F.. An Overview ............. ....................... 111. A Cross-Cultural Look at Cultural Deprivation ................................ A. The Effect of Schooling .................................................... B. Modes of Information Processing .......................................... C. Intelligence: A Cross-Cultural Definition ................. D. Cultural vs. Economic Prosperity: Experi Influence of Caste and SES on Cognitive Ability ........................... 11. Cultural Deprivation:

2 3 3 5 8 16 20 22 22 25 21

29

................... 31

..........................................

31

Retarded Children

.............................. ..................

32

A. Hypotheses .......................... .................... B. Tests and Experiments ............................................ C. White and Canadian Indian Comparisons ......

35

1

2

J, P. Das I. INTRODUCTION

The disadvantaged or culturally deprived child is characterized by his failure in the academic situation. In determining the causes of his failure, several antecedents have been suggested. Lack of proper intellectual stimulation, as well as social-personality factors such as poverty, broken home, absence of a male model, and language disability are often blamed for the child’s cognitive incompetence. A genetic explanation is usually not popular. Early intervention and compensatory education programs, as we shall see in subsequent sections, almost ignore the possibility that genetic factors partially contribute to the child’s academic failure. An environmental approach, therefore, recommends as early an intervention as practicable to reverse the trend of intellectual retardation found in disadvantaged children at a later stage. A strong influence in fixing the age before which intervention should take place is Bloom’s prophecy-50% of a child’s IQ is developed by age 4 (Bloom, 1964). The percentage is based on the correlation of 0.70 between IQ at age 4 and at 17 for the same individual. Bloom notes that IQ at birth has azero correlation with IQ at age 17, but this rises to 0.70 at 4, and to 0.90 between 4 and 11 years of age. But even if the observation that 50% of IQ is developed by age4 were statistically valid, does it follow that the consequence of increasing the IQ before age 4 will be a higher IQ at age 17? In fact, as Jensen (1969b) points out, the child’s IQ before he is born is predictable from the IQ of his parents, because of its heritability. Bloom’s correlations may merely reaffirm the course of the development of IQ reaching a genetically predicted level at age 17. Compensatory education for the early school age child is discussed later. But compensatory education should have a strong theoretical base. It is not defensible to launch a program for improving cognitive competence without aproven theory. In addition, if the programs are concerned with intelligence and not achievement, the underlying assumptions are: (1) intelligence can be improved, and (2) the weakness of the disadvantaged child lies in his intellectual capacity rather than in his performance. The first has qualified support from research. The second is doubtful. Perhaps, requirements for some kind of school performance are alien to a child from a specific subculture, and a judicious change in these would reveal an adequate capacity. Finally, the general orientation in this chapter towards intelligence and its measurement in different subpopulations is presented. One should give up the idea of constructing culture-fair tests for the disadvantaged, or devising tests entirely made up of skills found in a subculture. It may be quite true that a ghetto child learns to survive in the jungle of ghetto life, but as long as these skills do not help him in taking advantage of the educational opportunity which would guarantee him some degree of upward social mobility in the North American culture, such skills are of no consequence.

CULTURAL DEPRIVATION A N D COGNITIVE COMPETENCE

3

Vernon (1969) advocates that the intelligence which we measure through standard instruments including the so-called culture-free ones can never be separated from the biases of the majority culture in the Western countries. In all of these countries, reasoning and verbal abilities are emphasized, and the education system selectively reinforces children who demonstrate these abilities. If genotypic endowment enables a child to develop his phenotypic intelligence in interaction with his environment, its measurement will be colored by the nature of the cultural milieu in which the child has developed. The environmental that fosters skills for academic success is the one to be desired, and provided. Because the school experience is an integral part of the growth of the child, it minimizes differences in home background, helps social learning, and transmits the values of the majority culture. In other words, it is the great leveler. Perhaps because of some commonality in school environment, the blacks and the whites in the United States perform more similarly in culture-loaded tests than in culture-free ones. In the course of the review, it became apparent that the cognitive competence of disadvantaged children should be examined in the general context of cognitive growth. Cognitive abilities are products of underlying psychological processes, mostly related to the reception, analysis, and integration of information. An explanation of cognitive competence or incompetence has to be in terms of a psychological theory, and not through “circumstantial evidence.” As Bruner advocates (Bruner, Olver, & Greenfield, 1966): A child does not perform a certain act in a certain way at a certain age because the culture he lives in exhibits a certain pattern, because it is inherent in the evolution of primates.. . because his language has or does not have an easy or obligatory way of making a significant distinction or because the child’s act exhibits a certain underlying logical structure . . . what is needed for a psychological explanation is a psychological theory [P.2-31,

In the present chapter, the two main divisions consist of a review of some issues and their contents in the area of cultural disadvantage, followed by reports of a series of the author’s investigations aimed at clarifying the nature of cultural deprivation in different settings. The latter provides evidence for suggesting a structure for cognitive abilities.

II. CULTURAL DEPRIVATION: EUPHEMISM AND ESSENCE A. The Concept of Cultural Deprivation

Cultural deprivation refers to a complex set of conditions which favor intellectual subnormality in a child. Some of these conditions are attributed to unstimulating environment, lack of verbal commerce with adults, poor

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sensory experience, and other deleterious environmental factors generally associated with poverty. The impetus for work on cultural deprivation has come from the research on early experience and sensory deprivation in comparative psychology (Wood-Gush, 1963). Hebb (1949) demonstrated that animals raised in restricted environment showed defects in sensory and perceptual development. Hunt (1961) extended the implications of this to humans and pointed out the importance of early experience in intellectual growth: lack of proper stimulation may hinder the development of the inherited constitutional apparatus such as the eye. As Haywood and Tapp (1966) have concluded in their review, an enriched early environment increases intelligence, whereas impoverished environment may lower intelligence level. Often it is presumed that enrichment of early environment should be introduced at a “critical period” in the organism’s development in order to have the optimum effect on learning a specific response or skill. However, the critical period hypothesis, based on the imprinting studies by Lorenz (1952), may not be too useful in enrichment programs for children, as the evidence for its existence in early childhood is still inconclusive. In recent years there has been some re-examination of the animal data on restricted environment and their application or extension to humans. A good review is presented in Jensen (1969a). For example, it is seen that even in animal studies when an animal is brought up in a lighted environment in contrast to a darkened one, and with all other conditions being constant, the animal typically does not show the ill effects of sensory deprivation. Secondly, animals which have been reared in a restricted environment do show initial disadvantages in discrimination learning, but such disadvantages gradually disappear with exposure to a normal environment. In other words, the gap between the sensory-deprived animals and those raised normally begins to narrow as the deprived animal is increasingly exposed to a normal environment following its early exposure to a restricted one. In the case of human children, however, the opposite is known to happen. The gap betweeen a culturally disadvantaged child and a nondisadvantaged child begins to grow with age and exposure to normal classroom leaning. The IQ tests reveal a wider and wider gap between, say, the black and the middleclass white child as they progress in school years. Such considerations lead one to question the validity of extending findings from animal research to the culturally disadvantaged child. Also, the myth that the slum child has much less stimulation than the middle-class child is no longer supported. A close examination of the typical day-by-day life of the slum child reveals, as we know now, that he might be really overstimulated and overindulged by adults. There is usually someone in the lower-class home, an aunt or a grandmother, who cuddles and fondles the slum child. So, if the slum child

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does not lack stimulation, if he does not lack maternal love, why is he disadvantaged? The neo-early experience theorists believe that it is not stimulation per se but the quality of stimulation that is important. The middle-class child most often has a superior quality of both verbal and nonverbal stimulation. These stimulations are distinct. The reinforcement systems in a middle-class home are of a delayed kind which is congruent to adult life; and certainly the verbal milieu in which the middle-class child grows up corresponds much more closely to that found in academic textbooks and in school learning. All in all, language is given a very importnat role as a determinant for the growth of intellect. However, there are even disturbing facts about this explanation. In the next two sections of this chapter we shall evaluate the relation between socioeconomic status(SES) and language, and the role of early experience. B. Socioeconomic Status and Language

If the disadvantaged child has cognitive deficiency, it should be reflected in his language. For language is the vehicle of thought, and much of our analytical capacity depends on our ability to manipulate symbols, which are generally verbal (except for special groups of children such as the deaf). The importance of the link between language and thought has gained support from theoreticians (Vygotskii and Luria,) and researchers in human ability such as Vernon and Cattell. Working within a Pavlovian framework of the second-signal system, the Soviet psychologists have invariably emphasized the role of speech. Words are regarded as representations of primary signals or perceptual stimuli, and therefore are conditioned stimuli of a higher order. Words also influence a child’s action through internal speech. Luria (196 1, 1963) has convincingly shown that speech acquires an impelling function in the young child, adequate to start a response, but not to terminate it. Then it passes through a period of regulating action, assuming a greater control on behavior as the child grows. Dissociation between speech and action disappears. Only a developmentally retarded child still shows some dissociation even beyond adolescence. Speech serves a useful purpose only if it gives the child the freedom to manipulate symbols without having to bother with actual objects or experiences. It should also guide motivation by permitting the child to plan his actions, set goals, and derive satisfaction (reinforcement) when these goals are attained. Thus, apart from facilitating information processing which is the basis of cognitive competence, a schoolchild’s verbal system helps him to develop the appropriate attitudes for scholastic achievement. For, it is well accepted that autochthonous factors (belief in self rather than chance con-

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J . P. Das

trol, parental aspiration regarding child’s education, etc.) make a major contribution in determining school success. The child from the low SES home has a poor record in school achievement. Is this exclusively due to his poor language ability as some sociolinguists (Bernstein, 1961) have suggested or because of the autochthonous factors; are they both poor in acquiring the standard language used at school, and poor in scholastic achievement? The typical example given by Bernstein as to why the lower-class child falls behind in academic performance compared to that of the middle-class child is that the language of the lower-class child is of a descriptive nature, while that of the middle-class child is of an analytic nature. Because analytic language is the key to success in academic subjects and is increasingly demanded in higher learning, the lower-class child has to assume an inferior status due to his verbal experience. It is further stated that verbal stimulation must begin and be maintained at a critical period of life, preferably around age. 4. Since the lower-class child lacks such experience or has very little of it during this critical period he remains at a lower state of verbal development throughout his life. As was said before, these statements have now been questioned. It will be fair to say that according to Bernstein (196 l), the social structure gives rise to the linguistic form or style of speech, which is used to transmit the culture of the class, constraining its behavior. The speech style of the lower class is described as restricted, and that of the middle class as elaborated. As the labels signify, a restricted linguistic code refers to concrete and descriptive language whose lexical and syntactic forms are highly predictable. It is marked by short grammatical sentences, simple and repetitive conjunctions, frequent interjections seeking the listener’s support, short commands and questions. In contrast, the elaborate code has low syntactic predictability, is discursive rather than descriptive. It is marked by complex sentence constructions, use of impersonal pronouns, and hesitations during actual speech. Thus, the social structure determines the language of a subculture, and language interacts with the mode of not only cognitive, but also affective and evaluative expressions. All three affect the educational attainment of the children in that group. Lawton (1968) has presented agood critique of Bernstein’s work and discussed his latest model of social structure-language interactions. The model describes how socialization and the transmission of culture may occur. Bernstein’s suggestion of a deficit in the lower-class language has met with criticisms. A cognitive style peculiar to the lower class seems to be an acceptable proposition as long as the lower-class English is not stigmatized. But that is seldom true. Therefore, Labov (1969) reacts to a deficit concept

CULTURAL DEPRIVATION AND COGNITIVE COMPETENCE

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unfavorably. He thinks that Bernstein’s distinction of restricted vs. elaborated codes is a stylistic distinction. It merely demonstrates the difference between nonstandard and standard English. Nonstandard dialects are used by the lower class, and the lower class may fall behind the middle class in school achievement. But the two may not be causally related. The lower class, Labov contends, has its own dialect and grammar both of which adequately serve the purpose of communication in that culture. There is no proof that they are illogical or that they are primitive or as Bernstein suggests, hardly a step removed from gestures and emotional accompaniment to action here and now. When one seriously analyzes the train of an argument as Labov demonstrates, uneducated Negro speech is as logical, but less verbose than that of the educated Negro. But the schools prefer the structure of the middle-class English. It is merely a matter of convention. In an experimental paper, Baratz (1969) has shown that when sentences were presented in nonstandard English, the Negro children could repeat these more accurately than the whites. But they did poorly when the sentences were in standard English. The error of the Negro children in reproducing standard English sentences was consistent-they translated the sentences into their own dialect. Labov’s paper is very persuasive and deplores much ofthe loose thinking in the field of educating the disadvantaged. Lack of sound empirical work without the biases of the middle-class investigators is perhaps a valid reason to suspect that Bernstein or other verbal deprivation theorists have any useful suggestions for remodeling the education for the disadvantaged. When Negro children are found to lag behind in reading, one should not go out and write a program for teaching them reading, rather one should look for the antecedents which have made them poor readers. Important antecedents could be their preference for nonstandard English, and negative attitudes of the Negro subculture toward education in general. If verbal deprivation cannot result from the environment in which a lowerclass child is raised, and if we agree with Labov that it does not exist, then one should assume that the language of the disadvantaged child is as functionally adequate as that of the middle-class child. Language development, then, takes a normal course in each subculture. Curiously enough, such an assumption is consistent with a biologically determined view of language. A biologically oriented writer, Lenneberg (1969), maintains that language development, indeed, takes a normal course if it is not severely interfered with. That is, if attempts are not made to deliberately deprive the child of verbal experience, then language development proceeds normally. The haphazard experience that characterizes most of our early verbal development is adequate enough. Lenneberg has shown, for example, that the children of deaf parents do equally well in school as the children of hearing

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parents, after only 1 year in school. Intensive and qualitatively superior verbal experience is not indispensable for academic success in later years. The language of the lower-class child at home is not the same as the language used at school; such disparity is not present in the case of the middleclass child. But this may not be an important reason why the lower-class child does not perform as well as the middle-class child. One could point out that from a cross-cultural perspective, such disparities do not seem to matter at all. In many countries, the language spoken at home is structurally different from the language used at school. The minority groups in Europe or the minority groups in certain regions in India use one language at home and read and write in another language at school. But one does find academically successful people in these groups. The poor Jewish immigrant from Europe who arrives in the English-speaking communities of the United States and who already has been exposed to more than one language soon catches up with the American school system and succeeds in it. In Japan, children may speak many kinds of dialects at home, but use one language at school. Their intellectual development is not known to be inadequate by any standard.

C. Early Experience and Cognitive Functions

1. IMPLICATION OF CULTURAL DISADVANTAGE The role of early experience in cognitive development has become a muchdiscussed topic mainly because of our interest in early and compensatory education. There are three excellent books in which our present state of knowledge in this field has been reviewed and criticized (Ambrose, 1969; Denenberg, 1970; White, 1971). Some of the points covered in these books will be highlighted and evaluated along with other materials. The implications of cultural deprivation seem to vary widely depending on the author’s predilections. For Kagan (1970), it is essentially a feeling of impotence to alter one’s life or the future of one’s children. The remedy is improvement of mother-infant relationship so that the children develop a sense of mastery. But is it not apparent that many privileged people believe in determinism? Another view holds that meaningful mother-child interaction is lacking in underprivileged homes. Thus, Hess and Shipman( 1968) suggest that “The meaning of deprivation would thus seem to be deprivation of meaning in the early cognitive relationships between mother and child.” Here, they are concerned only with cognitive rather than the total relationship. On the other hand, its effect is seen in personality-according to them, this produces a child who relates to authority and is not rational. One may ask if this

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characteristic is exclusive to children from the poor families or subpopulations which are economically disadvantaged. Assuming that this is true only of the disadvantaged children, Hess and Shipman recommend that early education should prepare children to deal with information rather than to aim at merely transmitting to the children a supply of concepts and skills. But do the teaching institutions usually discourage regard for authority and encourage the child to think rather than acquire information? Silberman’s (1970) widely noticed book, Crisis in the Classroom, mentions that the opposite seems to be practiced-classrooms are oriented toward maintaining discipline by the authority figure, and curricula aim at transmission rather than creation of knowledge. When psychologists look at the culturally disadvantaged child, they may forget how a nondeprived child is handled in the educational system. As a result, their recommendations for cultural stimulation often appear to be too idealistic in the context of current practices in childhood education. An example of this is found in Fowler (1968) who describes the goals of cultural stimulation as follows: “I would like to believe it possible for us to plant the seeds of logic in early childhood in ways which foster the interplay of creative imagination and logical reasoning throughout the course of life. . . [p. 361.” Riessman (1962) observes that the disadvantaged child is antiintellectual, and externally controlled. As a cure, we have to show the child that ideas and theories have practical merit. The method is to highlight intellectual heroes such as Pasteur, Darwin, and Salk. But d o anti-intellectuals appear only among the disadvantaged children? When it comes to parents, most of the privileged adults are not known particularly for their intellectualism. The purpose of pointing out these impractical suggestions here is to show that although academic psychologists and educationists mean well, their recommendations are neither realistic nor specific enough to guide the practitioner in the field. Sometimes, the orientation of intervention programs is toward cure and remedy. This assumes the child to be apassive agent who stands to gain from exposure to the good things in middle-class life. A further assumption is that the effect of such exposures may be limited to a certain “critical period” during which the passive child is most susceptible. Thus, Deutsch and associates (1967) point out that taking children to museums and art galleries may not help if the children have passed that stage of development. But how do we know if the child has passed that stage? It is doubtful that anything like a critical period exists for the human child. There is some evidence that it operates at the embryonic stage; beyond that it is merely a figure of speech (Ambrose, 1969, pp. 39-43). The concept of a passive child is also untenable. Children gather knowledge by operating on objects. They construct images of reality through a constant chain of

J. P. Das actions and feedback. An enriched environment can be enriching only when it allows the child to respond in a variety of ways, thereby helping him to know the nature of things and acquire skills. Moreover, there is some doubt that this is best achieved by putting children through specific programs solely aimed at developing a particular skill. Kohlberg (l968), for instance, supports a liberal preschool experience, unstructured opportunities for play and esthetic, and social activities, rather than narrow cognitive training. One should not, however, reject some structure in preschool activities, and cognitive experience need not be narrow and insulated from the rest of the child’s experience. Reports on some British preschool and early education programs suggest that everything from sensory training to number concepts can be provided in a liberal, playful atmosphere. EFFICACY O F EARLY EDUCATION From a biological perspective, we have enough data to support the hypothesis that sensory deprivation may hamper the development of the sensory apparatus, and hence perception and discrimination (Denenberg, 1970; Haywood & Tapp, 1966; White, 1971). Mason (1970) lists the effects of deprivation in animals as the breakdown of primitive functions, such as biochemical and structural changes in the retina of animals raised in darkness, lack of environmental tuning, inappropriate behavior, excessive arousal effects, and deficiency in problem-solving skills and other higher nervous activities. But he concludes that a biological perspective cannot guide us to predict deprivation effects on humans. In fact, as many have noted (see Jensen, 1969a), the extent of sensory deprivation which produces these deleterious effects can hardly be duplicated in human real-life situations. Kohlberg (l968), who advocates a cognitive-developmental point of view, the interaction between nature and nurture in the development of intellectual abilities, dismisses the relevance for humans of deprivation studies on animals. He points out that deaf or blind children, who miss a substantial part of sensory experience, nevertheless develop normal cognitive abilities, such as conversation. Complete social and sensory deprivation perhaps seldom occurs in humans, and when deprivation occurs naturally, as in the deaf or the blind, its effects are not irreversible. The last portion of the statement goes against a critical period hypothesis. Children make up for deficiencies, at least as late as adolescence. Feuerstein’s work with the Jewish adolescents from North Africa provides convincing evidence in this regard (Feuerstein, 1970; Feuerstein & Hamburger, 1965). Therefore, one need not take seriously such prophecies as half of the IQ is developed by age 4, and hence half of the battle forimprovement ofcognitive abilities has been lost if we did not start a child on a cultural stimulation

2.

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program earlier than that age. Many experimental child psychologists including White (1971), and Cole and Bruner (1971) are critical of such prophecies. Our lack of knowledge as to what in the environment contributes to rapid intellectual development in different subpopulations and across cultures makes it hard to manipulate the environment appropriately at certain critical periods of development, if these do exist. As Bruner notes, in a child’s cognitive development, there are no monumental milestones or memorable crossings. Skills are acquired gradually, their use in new situations gives the child a sense of mastery, helps him to acquire a successstriving orientation, and prevents the development of a failure-set, as is typically found in disadvantaged children (Gollin, 1968). A connected issue here is whether or not early stimulation accelerates mental development. More seriously, does it improve genotypic intelligence, variously called intelligence A by Hebb, and fluid intelligence by Cattell? Piaget and many non-piagetians such as Jensen and Cattell would answer negatively. Most environments are adequate for developing the intellectual potential of the child. However, Jensen may concede that when there is an unusually severe deprivation condition, early stimulation may be needed, and become effective. H e proposes something close t o this in assuming an environmental threshold hypothesis (Jensen, 1969a). Cattell (1971), on the other hand, doubts that any environmental stimulation results in improvement in fluid intelligence. Crystallized intelligence can be improved through training, because it measures attainment. But the tests of fluid intelligence, asVernon (1969) remarks, are essentially characterized by spatial-reasoning ability, and those for crystallized intelligence are measuring verbal-educational. Unlike Hebb’s or Vernon’s genotypic intelligence which cannot be measured, Cattell’s fluid intelligence is measurable by tests resembling the Progressive Matrices. This test is believed to resist the effects of practice or training. Jensen too regards the Progressive Matrices as a good test of inherited intelligence. Despite its high heritability, Progressive Matrices scores have been shown to improve with training. Guinagh (1971) selected low-SES white and black children whose scores were at least 1 SD below the norm in Progressive Matrices, and further divided these groups as high and low scores in a digit span test. Thus, four groups were formed-the two white groups, high or low on digit span, and the two corresponding black groups. The white and black children came from Grade Three classes, but were attending separate schools. Children in the experimental groups were given seven half-hour training sessions on the concepts involved in Progressive Matrices, and then retested. Results showed substantial improvement for three of the four groups; only the black children with low digit span did not show significant gain over their control group.

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Besides demonstrating that Progressive Matrices scores are vulnerable to training, the results ironically support a different Jensen (1970) hypothesis regarding primary and secondary retardation. The low-SES black group with low digit span is probably made up of mostly primarily retarded children whose associative abilities are defective due to organic causes. Their IQs do not belong to the normal distribution of intellectual abilities. Thus, their reasoning cannot be improved. For the other groups in Guinagh‘s experiment, one suspects that the training program consisted of repeated associations between a problem and the method for its solution in largely overlapping samples of problems. Thus it may be argued from Jensen’s position that the associative ability of the high digit span groups was advantageously used in getting at the reasoning tasks. However, the improvement of the low digit span white group is contrary to Jensen’s hypothesis-he holds that adefect in associative ability is usually a sign of primary retardation. Hence the low digit span white group, like the black, is primarily retarded and not merely culturally disadvantaged. The data in Guinagh’s study are from only 10 experimental subjects who are compared with 10 controls. It will be of interest to see ifthe same results can be obtained with a larger sample. A future study following from Guinagh should also try the effect of training on verbal reasoning tasks, and categorize subjects on additional associative tasks such as serial recall. Later in this article we shall describe a research project in South Africa which demonstrated that performance on Progressive Matrices varied with years of schooling rather than the age of the child in a community where children enter school at different ages. The rationale for attempting compensatory training should not depend on whether ability is environmental or hereditary. One should be aware of a simplistic fallacy that if intellectual inadequacy is genetically determined, it cannot be removed. Prosthetic devices, such as eyeglasses, remove myopia, and many such devices mark a civilized society. It is in this light that environmental stimulations are justified. Taking seriously the existence of an environmental threshold below which stimulation will improve intellectual ability, one should find out what the threshold could be. Children brought up in the abnormal condition of a poor orphanage as those in Skeels and Dye’s (1939) sample, certainly were below this threshold. According to Bereiter (1970), their environment may be as much as 4 SDs below that of a hypothetical normal environment. The only real issue, then, is not whether early education is efficacious, but at what level of deprived environment should it be useful. Add to this the observation that a hereditary “fault” may not be manifested if the environment does not support it-a genetic proneness to a certain disease such as tuberculosis needs an unsanitary environment and poor health for its manifestation.

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3. A MODIFIED THRESHOLD HYPOTHESIS The antidote to environmental deprivation may not be intensive stimulation geared to achieve special cognitive abilities-it may be simply the restoration of the environmental conditions prevailing for the majority of nondeprived children, allowing the potpourri of experience which exists for a child of that age, Such a view is essentially similar to those held by Lenneberg regarding language development. Provided that a child has normal intelligence, (above IQ 85) an enriched environment beyond the usual one may not be useful; but below this IQ threshold, enrichment would have a beneficial effect on intellectual development. All that a child from an extremely disadvantaged home needs is his removal to an ordinary environment. This could be provided by schooling, teacher’s encouragement, and the positive attitude of parents toward the child‘s education. Thus, we are here proposing an intellectual threshold which under certain conditions interacts positively with environmental stimulation. The range of IQ most sensitive to early stimulation could be 70-85. Liberal programs aimed at developing a broad basis for cognitive abilities may be essential for disadvantaged children in this range. Between IQs of 85 and 100, the disadvantaged child does not need or benefit from “cultural stimulation.” Probably, autochthonous traits such as diffidence, failure-set, and lack of a feeling of mastery need to be removed through appropriate school experience and positive evaluation by teachers and other “elders” whom the child loves and admires. This IQ-environment interaction hypothesis is described further in another article (Das, 1971). The threshold hypothesis advocates that if the child is born with a certain level of intelligence which could be defined as above a normal threshold then the usual amount of disadvantageous experiences does not destroy his capacity. If we accept this, what do we say about the programs for enhancing the quality of early experience? One may still support them for those who are below the threshold. In these cases there is perhaps a certain danger that unless the inherent capacities are adequately stimulated they may deteriorate further and hide the actual potentiality. Thus Project Headstart programs should be limited to those who have intelligence below this threshold. One may assume that if the programs are appropriate and adequate the performance of these culturally disadvantaged children may be boosted to the level of a normal child. In the case of those bright children who belong to the disadvantaged class, one would do well simply to remove the barriers against scholastic achievement. What we are pleading here is not for an enriched intellectual program to be forced upon them. In fact, such a step will be not only unnecessary but may slow down the normal intellectual growth of the bright child. We are merely asking to let this child acquire knowledge in his own way by providing him with physical facilities such as a library or a place to study, and psycho-

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logical conditions conductive to higher learning. The latter would include appropriate teacher expectancy and to some extent encouragement from parents for higher education. D. Poverty, Nutrition, and Cognitive Ability

We have been concerned with psychological handicaps of the underprivileged child. But poverty itself may affect intellectual development through physical conditions such as malnutrition and sickness. The evidence in this regard is quite definitive, as summarized in Scrimshaw and Gordon (1968). Severe malnutrition, referred to as a marasmic condition occurring between the last 2 months before birth and 6 months after birth, has a high probability of causing intellectual retardation. Its effect on the child’s intellect is irreversible. But after the age of 6 months, the same degree of severity does not leave any permanent trace, even if the child had been so seriously affected that he needed hospitalization. This is quite expected from our knowledge of brain development and intelligence. The important period of development seems to be from the seventh month of gestation, reaching its maximum shortly before birth. But the brain continues to grow, although at a decelerating rate, until 20 weeks after birth. At this period, it is most vulnerable to nutritional deficiencies. Attempts to improve the nutritional intake of the expectant mother if she is severely malnourished, and of her young infant, have generally resisted developmental deficiencies. However, the underprivileged infant seems to be protected from the ill effects of malnutrition if he or she is breast-fed. In astudy in India, Rajalaxmi (Baroda University, 1967) found that rich and poor mothers have equally healthy babies before the babies are weaned at around 6 months. The babies of poor mothers do not show any developmental lag. Often the poor mother is superior in lactation to the rich mother whose baby has to be put on supplementary diet even after the first 2 months. But from then onward, as the mother’s milk supply becomes inadequate and the baby has to depend on additional food, developmental retardation becomes increasingly apparent. It is sometimes seen that not all children from a poor family demonstrate low intellectual ability; only some do. Perhaps a major factor would be the inability of the mother to breast-feed the baby (poor lactation caused by illness, etc.). Where malnutrition in childhood has been associated with cognitive deficiency, it is hard to isolate malnutrition from the physical, social, and family conditions under which it occurs. Interaction between malnutrition and infectious diseases results in developmental retardation in disadvantaged communities. Rafalski and Mackiewicz (1968) from Poland demon-

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strate the complexity of the interactions between socioeconomic factors, only one of which is diet, and the child’s development. According to them, “A child’s development depends on its genotype, the quality and quantity of food, measures of prevention and treatment of diseases, and other physiological and environmental factors. The crux of the matter is to find a set of socioeconomic variables, for a given population at a given time, which best distinguishes children of accelerated physical development from those retarded [Pp. 79-80].” Their emphasis is a practical one-how to locate children who may need help in school, and whose families should be included in intervention programs. This seems to be more relevant than considering if or to what extent malnutrition, in isolation, causes cognitive deficiencies. The work of Birch, Cravioto, and their associates provides reliable data on cognitive competence in malnourished children (Birch & Belmont, 1964; Cravioto, Gaona, & Birch, 1967). These children were not only physically small, of short height and stunted growth, but also were found to be below normal in reaciil,g ability and auditory-visual integration. The latter was tested by a simple task where the subject listened to patterns of pencil taps on a table, and was required, later, to identify the pattern he had heard from three visually presented dot patterns. We have found (Das, 1972) that this cross-modal task has a high factor loading on a Progressive Matrices factor when normal children were used as subjects, Birch et al. suggest that early malnutrition might have caused a structural deficit in the central nervous system which particularly affects “neurointegrative” development. Although there is little doubt that children showing severe symptoms of malnutrition such as kwashiorkor perform poorly in motor and language development, and that severe malnutrition can depress IQ by 20 points, how many children like these are found in North America? Jensen (1972) discusses this in some detail. He remarks that of the 15 studies usually cited, only one was done in the United States. This was the Harrell, Woodyard, and Gates (1955) study on underprivileged children, who before birth, were put under a nutritional enrichment program for their mothers, and continuously afterward were given vitamins and polynutrients. At age 3, their IQ gains over the controls were between 2.5 and 5 points. But there will always be the question regarding the permanence of this gain; in evaluating so many intervention programs this has been a difficult question to answer. Incidentally, Jensen asked Birch to estimate what percentage of American children suffer from malnutrition equal in magnitude to those found abroad on which the majority of studies were based-the estimate was 1% (Jensen, 1972). Birch seems to be now less convinced of a central nervous system deficit in malnourished children except for a small number who had extraordinarily severe malnourished conditions. Even in those cases, the data cannot be interpreted as demonstrating conclusively that malnutrition

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directly affects either nervous system development or intellectual growth (Birch & Gussow, 1970, p. 194). As we have mentioned earlier in this section, undernourished children are also poverty stricken, prone to infections, brought up in uneducated families, and in some established societies, belong to the lowest caste. Since the evidence is not clear that poverty and malnutrition cause permanent damage to the intellectual ability of the child, what could be the relevance of these for education? A humanistic answer to this would be that poor children are unhappy human beings, posssessing no desire for selfactualization. I n practical terms, they are apathetic, distracted, and have low self-confidence and low achievement motivation. Improvement of the social conditions of the underprivileged may not lead to an improvement in their intellectual ability; it gives back to them their self-respect as they grow up. It seems that our past emphasis on intellectual improvement as a consequence of removing poverty should be abandoned. There is a need to return to commonsense and observe what chronic poverty does to children. Most of them drop out of school, even when, in some countries as in India, they are given special bursaries by the government to study. And those who finish high school have much less ambition than the privileged person of their age and education. They do not use their intellectual capacity. The problem, therefore, is a social one. E. Compensatory Education for the Disadvantaged Child

1. RATIONALE AND BACKGROUND

In advocating a comparative psychology of cognition, Cole and Bruner (1971) dismiss the possibility that the minority child has any cognitive deficit; he may have some differences. This is an important orientation for any crosscultural research, and to some extent, research in cultural deprivation. But if the low-SES child’s difference is disadvantageous, some intervention becomes necessary. Such a child is disadvantaged in relation to only two aspects: (a) his achievement in a standard academic program is poor and (b) his potential for employment beyond school is low. Both of these are quite important and the cause of concern among social planners and educators. Consequently, emphasis on compensatory education has assumed priority. Now, faced with the task of making the child from low SES benefit from school instruction and bringing him to a level comparable with the level of the advantaged child so that he might have almost the same opportunity for employment in adult life, what can one do? Two approaches to altering

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the performance of the disadvantaged child in school suggest themselves. The ideal thing to do is to banish the poverty and inequality that exist between social classes and living conditions. This would require the poor and the underprivileged class to be elevated in physical-social environment to the level of the average middle class. Although this is very desirable and should be done ultimately, it is not very practical at this point unless one is thinking in terms of drastic social changes equivalent in extent to social revolution. The other alternative, almost a reactionary one, would be to change the goals, beliefs, and expectations in the disadvantaged group to make these consonant with those of the parents and children from the advantaged class. Both the Plowden (1967) report and the Coleman (1966) report mention the overriding role of parental attitudes on the child's school achievement. Plowden observes that this was more important than SES of parents and variation in schools. Coleman summarizes the effect of school environment and achievement. The report makes the following points.

I . The achievement of low-SES children depends more on the schools they attend than does the achievement of middle-SES children. Low-quality schools affect the achievement of low-SES children much more adversely compared to high-SES children. Improvement in school quality will bring about most of the improvement in their scholastic ability. 2. Achievement is strongly related to the educational backgrounds and aspirations of the other students in the school. The report shows that the principal way in which the school environments of low- and middle-SES children differ is in the composition of their student bodies; the latter has a strong (.80)correlation with the achievement of low-SES students. 3. The amount of variation in achievement that school characteristics account for depends much more on students and teachers than on facilities and curricula. 4. A pupil attitude factor which appears to have a stronger relationship to achievement than do all the school factors together is the extent to which an individual feels that he has some control over his destiny. Low-SES students have far less conviction than middle-SES ones that they can affect their own environments and futures. When they do, however, their achievement is higher than that of middle-SES students who lack that conviction. Those low-SES students in schools with a higher proportion of middle-SES students have a greater sense of control than their counterparts in predominantly low-SES schools. This again suggests that the direction such an attitude takes may be associated with the pupil's school experience. In a later section of this review, the results of an experiment where school environment was the same for the disadvantaged and the nondisadvantaged

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children will be presented. Perhaps the rationale of compensatory education for the disadvantaged child can be found in the following quotation. When cultures are in competition for resources, as they are today, the psychologist’s task is to analyze the source of cultural difference so that those of the minority, the less powerful group, may quickly acquire the intellectual instruments necessary for success of the dominant culture, should they so choose [Cole & Bruner, 1971, p. 8751.

2. STRATEGIES FOR COMPENSATORY EDUCATION What are the cultural skills that are necessary to be successful in the dominant culture? What should be taught and to whom? These are the basic questions in compensatory education. The compensatory program has been directed exclusively at culturally disadvantaged children. Thus the approach has been to teach them to overcome handicaps in learning, teaching things in which the children lag behind their middle-class counterparts. The emphasis here, then, is in the cognitive domain rather than in the affective or conative domains. A general strategy adopted in education programs such as Headstart seems to be a more-of-the-same strategy. Most directors of Headstart programs, for example, agreed that it is through organized and systematic stimulation, through a structured and articulated learning program that a child is best prepared for the demands of school (White, 1970). Thus, if the child is deficient in language, he needs more intensive training for language skills. If he is deficient in numerical concepts, he is given more drilling on the same. In other words, all that the deprived child needs is an intensification of the same kind of training that a middle-class child receives. We have pointed out elsewhere (Das, 197 1) that there might be a fallacy in such a strategy. As an analogy, let us examine the methods adopted to fight malnutrition in poverty-striken children. Very often it is found that the so-called poor or lower-class child may be given a higher quality of nutrition than the middle-class child, but the gain in weight and height is not the same as that of the middle-class child. In other words, better nutrition per se does not improve the physical growth of the lower class. One of the apparent reasons for such disparity is the fact that we are here neglecting the total environment in which the lower class child lives. Instead we are concentrating merely on the nutritional aspect of his environment. As we have pointed out before, he lives in unsanitary conditions where infections and epidemics are chronic. Thus the higher quality of food cannot be assimilated properly and does not contribute to the growth of the lower-class child. Obviously, the more-of-the-same strategy here is quite inadequate. It is now common knowledge that most Headstart programs have a shortlived effect. A critical evaluation by White (1970) of the effects of Headstart has the following points.

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The official Westinghouse-Ohio report mentions that only when a child has been through a full year of Headstart program did he perform somewhat better in a standard test given at Grade One level, compared to his controls who had not had Headstart experience. But the effects of having been in a Headstart program decreased in Grade Two and GradeThree. Even though some initial improvement due to Headstart was noticed, in an absolute sense it was very little. The test used was the Metropolitan Readiness Test generally given to first graders. In this test, the positive effect of Headstart did not improve the child’s performance even as much as f SD. Thus the child’s academic prospects do not seem to have improved by the Headstart experience. White concludes that it will take up to a decade before the fundamental idea of Headstart can be given a reasonable test. Thus, any evaluation of Headstart and its subsequent rejection could be quite premature. As to what kind of educational program should be encouraged White is not very definitive. The answers are found in Jensen (1969a) and in Bereiter’s curriculum (Bereiter & Engelman, 1966). Suggestions in these reports are at variance with the existing approach in compensatory education. Jensen advocates that one should take into account the possibility of finding different patterns of abilities in the low- and high-SES children as well as in the distinct ethnic groups that exist in the country. H e presents some data and a theory(Jensen, 1970), as was mentioned earlier, implying that social class differences are chiefly found in reasoning ability. In associative learning ability the lowand high-SES groups do not differ, but reasoning favors the high-SES group. The program for education should be diversified, taking advantage of the strength of the ability found in a specific group or subpopulation. We should teach the low-SES and the black children to optimize their memory rather than reasoning skills in learning the 3 R s . Many people have reacted emotionally to this suggestion because, in their view, this amounts to an admission of inferiority for certain subpopulations in cognitive ability. Bereiter (1970), in partial support of Jensen, suggests that the emphasis in early childhood education, especially for the deprived, should be on learning rather than on thinking. In the context of Bereiter’s programs, attention is directed at facilitating the acquisition of particular skills. Claims of success of the programs need not be based on global improvement in cognitive ability. One can claim an improvement only in those skills which have been taught to the children. A program for preschool education that preceded Headstart was initiated by Susan Gray (see Gray, Klaus, Miller, & Forrester, 1966).An evaluation of that program and of early educational intervention in general is provided by Miller (1970), who concludes that we must approach these interventions with a spirit of cautious optimism because until now the mass compensatory programs have failed to produce evidence of their effectiveness. He repeats

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what has been said before, that early intervention at a preschool level has only a marked short-term effect on children. Gray (1970) does not argue with this conclusion, but notes a quite interesting secondary effect of early intervention. Her research has been entirely concentrated on poor black families in Tennessee around Nashville. Some of the children in that area were in a major intervention program during the summer. Their progress was followed for 9 months afterward. During these months when the children were not in the early intervention sessions, home visitors were sent to work with mothers, providing some continuity between one summer program and the next. Quite by chance, the home visitors noted that the younger brothers and sisters of the experimental children showed accelerated development. This was actually confirmed by testing the siblings of the experimental child on the Stanford Binet, and comparing their scores with the siblings of the control child. The former had about 13-14 points more than the latter in Stanford Binet IQ. Thus, the results of the intervention seem to have spread to the family. Gray calls it “vertical diffusion.” It underscores the role of the mother in improving the educability of all her young children. She has initiated a large scale investigation into the role ofthe mother with the following assumptions: (1) The mother is the chief source of stimulation in the early years for the children as well as the agent who influences the child’s development of competence and control. (2) The mother assists in sustaining developed skills and in motivating the child to develop more complex abilities. We seem to have come back to the role of the mother and her interaction with the child in shaping cognitive development which we had discussed in an earlier section citing the work of White, Hess, and Shipman. It was noted before that if cultural deprivation leading t o cognitive incompetence is a psychological matter, it should be explained through psychological processes backed by theory. The field work of Susan Gray seems to have reiterated this point serendipitously. In evaluating the effects of compensatory education, one moves a step backward and considers what variables lead to cognitive improvement, and in considering these, one moves further backward to well-controlled laboratory investigations and accurate observations which emphasize the role of parent-child interactions in cognitive development. F. An Overview

The present section on cultural deprivation can be concluded as follows. The essence of cultural deprivation is academic failure and reduced potentiality for employment after finishing school. Language of the lower-class

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child might appear to be an impediment in his scholastic progress, but it is not his grammar which prevents him from doing well in school. Rather, it is the total attitude of the lower class child or of the disadvantaged communities toward education in particular, and toward their chance of being successful in the existing social system in general. These are the salient variables in determining the child’s success in school. The failure of the lowSES child cannot be very effectively traced back to lack of early stimulation. The animal model largely based on sensory deprivation seems to be a tenuous one. Malnutrition, which is often associated with poverty, and all its deleterious effects cannot be viewed as a serious cause for the subnormal performance of the economically poor child in scholastic tests. Wherever additional nutrition in preschool or early school children has proved to be effective in improving his intellectual performance, the cause is not in food but in the social conditions that facilitate intellectual growth when a certain community or school is singled out for nutritional intervention. Strodtbeck has labeled it “sociomins,” analogous to vitamins (in Scrimshaw & Gordon, 1968, p. 363). Poverty perhaps has a deleterious influence on affect and personality rather than on cognition. Since it is impossible to display one’s cognitive capacity without the facilitating motivational and personality characteristics that are associated with it, the role of poverty in depressing cognitive competence should not be minimized. One cannot ignore hereditary mechanisms that limit scholastic achievement. Instead of denying their existence, one should work around them. Finally, a general question about what compensatory education or early intervention should do. Does it really improve the genotypic intelligence or does it merely facilitate the growth of phenotypic intelligence which interacts with the cultural milieu of the child? In terms of Cattell’s fluid (genotypic) and crystalized (phenotypic) intelligence, the answer is the latter. But to what extent is an IQ score an artifact of the specific IQ test? Vernon (1969) suggests that in addition to the genotypic A and phenotypic B intelligence, a third kind, C, is the intelligence that we observe through the artifacts of the test which measures it. Since it seems more plausible to assume that genotypic intelligence cannot be directly measured, and phenotypic intelligence which is culture-bound cannot also be measured as such, it is impossible to escape the influence of the instrument on the phenomenon which we are measuring. What is the purpose of intelligence measurement? If it is, as it was when Binet constructed the first intelligence test, to predict school achievement, then the measurement of intelligence has to be relevant to the culture. Relevance here would mean that it should gauge the prospect of the child

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succeeding in the culture in which he lives. A wide variety of psychologists of different persuasion seem t o agree on this point. Ethnographic psychologists such as Cole, hereditarian psychologists such as Jensen, and those of a cross-cultural persuasion such as Vernon would all recommend that if the disadvantaged child is going to succeed in the culture of the advantaged class, he should acquire skills that would enable him to do so. 111. A CROSS-CULTURAL LOOK AT CULTURAL DEPRIVATION

“If he is smart, why isn’t he rich” suggests an antecedent-consequent relationship between intelligence and wealth. If one does not take this seriously, cultural disadvantage should not be equated with poverty and low IQ. It is possible that “culture” may have a definition with no reference to economic prosperity. A cross-cultural look helps us in realizing this. First of all, one should distinguish cognitive capacity and cognitive performance as Bortner and Birch (1970) have done-performance does not necessarily reflect all of one’s capacity. Existing demands for a certain behavior relevant to the culture may develop one aspect of the child’s capacity but not another. Therefore, intercultural differences in cognitive development are observed; and within the same global cultures, subpopulations may demonstrate a diversity of cognitive abilities which are typical of that subculture. In comparing these abilities across subpopulations and cultures, tasks with a wide variety of content should be given in different contexts. As efficient design will include variations between groups and between task dimensions. Where possible, developmental hierarchies within each group for each cognitive ability should be considered. Patterns of culture may coexist with patterns of abilities which develop at different rates and reach different levels. Many instances of these are given in the incisive studies reported by Cole, Gay, Glick, and Sharp (1971). A. The Effect of Schooling

Attendance at Western-type schools helps the development of problemsolving skills (Bruner et al., 1966). In the school, children learn to deal with symbols rather than objects and events existing here and now. Schoolchildren also learn to read and write. Similarly, Schmidt (1966) concludes from his studies in South Africa that schooling, and not SES, determines IQ and scholastic attainment. That study was done on school students who entered first grade at different ages because of the lack of accommodation in the beginning classes. In that study, it is clear that SES does not universally predict IQ or achievement; it may do so in Western communities because schools are compulsory and everyone can get into them. What seems universally impor-

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tant is the attitude of the community in general and of the child’s family in particular toward schooling. We mentioned this in the preceding section, and we shall present some of our own data supporting this in a later section. The support given by the child’s family need not be in the form of assistance in home work. Nonintellectual support, such as encouragement and pressure for scholastic achievement, is quite adequate for children coming from the homes of uneducated Indian residents of Natal. Schmidt (1960) mentions this as an instance of “families whose attitudes and orientations are congruent with the demands and aims of the school.” In our earlierdiscussion on cultural deprivation and the black child’s poor performance at school, the absence of such an orientation seems to be an overriding factor. Culture in that context may stand for congruence with schooling. Schooling can be broadly interpreted as learning under instruction. Vygotskii (1962) mentions the role of instruction in concept acquisition, and has generally influenced our belief that what is not spontaneously acquired, can be learned through instruction, and a learned concept is more accurate. Can instruction and coaching improve performance on problem-solving tasks and therefore in tests of intelligence? Guinagh (1971), as we have seen, demonstrated its possibility in regard to Progressive Matrices. Lloyd and Pidgeon (1961) examine this in three hierarchical ethnic groups in South Africa-the Europeans, the Indians, and the Bantus. Lloyd and Pidgeon used two parallel forms of a nonverbal group intelligence test (Lee and Jenkins test published by the National Foundation of Educational Research in England and Wales) on 300 children, ages 10-12 year, from each ethnic background. These children were further assigned to a practice and a coaching group. The practice group took the two alternate forms of the test, 3 weeks apart, while the coachinggroup was given explanation and rationale behind the correct answers of that form of the test which they had already taken, and were subsequently tested on the alternate form after 3 weeks. Each group was counterbalanced on the form of the test it was given on the first and the second test session. It was hypothesized that both practice and coaching groups would improve their performance on the second test, but the coaching group would excel the practice-only group. Further, among the three ethnic samples, the Europeans would show the lowest gain because of their superior home background, followed by the children of Indian origin. The largest gain was expected among the Bantu children who came from the most disadvantaged homes. The results are noteworthy in many ways. The test-retest (parallel form) gains were evident for all ethnic samples, and were more or less equal. Between the samples, the Europeans showed an increase of 11 IQ points, the Bantus 14.5, and the Indians did not improve after coaching when compared to their practiceonly counterparts.

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Schmidt (1960) commenting on these results rightly points out that the validity of the first test scores of all three samples was low; the test did not show the potential of the children. One may also add that excellent home background such as that of European children did not guarantee the child’s optimal performance on the test. Familiarity with the test itself without any feedback or coaching leads to improvement. The study also sheds new light on the relation between SES and IQ. In SES, the three groups were hierarchical-Europeans, Indians, Bantus. But in actual performance after coaching, the mean scores of Indians (92.5) were actually lower than those of the Bantus (103.30), who were lower than those of the Europeans ( 1 15.66).The authors did not expect this, and speculate that nonverbal tests, like all manual work, may produce a negative attitude in the Indian culture. Western-style schooling not only improves the development of some cognitive skills, but seems to influence the child’s orientation to self and his environment. Bruner (197 1) notes that the Wolof schoolchildren in Senegal who attend Westernized schools develop self-consciousness, a distinction “between their own thought or statement about something and the thing itself.” Schmidt and Nzimande (1970) observed that the Western type of schooling favors an earlier transition from color to form preference. In fact, without any schooling, the Zulu children do not shift to form preference from 5-14 years of age whereas, in contrast, those educated even in ill-equipped bush schools use form, number, and size, moving away from color as a criterion for categorization. Dart and Pradhan (1967), in an extremely interesting article which will be discussed later, observe that the Nepalese child (Nonwestern school) constructs a sequential map, whereas an American child constructs a spatial one, when both groups of children are asked to show the way from “your house to school.” We wish to reflect on Bruner’s self-consciousness concept before moving to a discussion of the Dart and Pradhan study. Bruner found that the Wolof children did not comprehend the question “why do you say that this glass has more water than this one”; but when this was changed to “why is it that . . .,” they could answer it. He suggests that “the relativistic notion that events can vary according to point of view” may be less acceptable in the Wolof culture but it could be realized with school education. One should not infer from this that the uneducated child is at a lower stage of development, and that the ability to classify into a number of alternative categories may reflect a relativistic orientation which is not necessarily superior. In many cultures where literacy is not widespread, as in Nepal and India, the nature of things is fixed; the task is to discover their nature. True knowledge is therefore unequivocal, and it has to be attained through perception, inference, and testimony (books and authorities). A person can have apoint

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of view only when he is predicting a future or uncertain event or when knowledge is not self-evident. Under those two conditions, there may be scope for arguments, which sometimes take the form of complex philosophical discussions. But in case of knowledge available in textbooks regarded as authoritative, the Nepalese child behaves as though human knowledge about nature is a closed body which should be acquired through schooling, and that it is passed on from teacher to student (Dart& Pradhan, 1967).The child depends on rote memory for learning school subjects; his strategy is adaptive. Thus in the broader context of cross-cultural considerations, the so-called disadvantaged child’s preference for memory rather than reasoning in school work may be based on the notion that knowledge is fixed and is to be acquired from books and teachers. On the other hand, if reasoning and abstraction are required to fit in with the dominant culture, the schools should provide for it. B. Modes of Information Processing

Sequential and simultaneous processing of information are often considered salient for cultural and subpopulation differences. As mentioned before, the Nepalese child draws a sequential map, depicting the process of going from home to school rather than analyzing the landmarks on the way in a parallel or simultaneously presented picture. Similarly, Negro and white children show marked disparity in map analyses, but are equivalent in rote learning which is sequential (Farnham-Diggory, 1970). Rote memory requires sequential processing, whereas reasoning of the Progressive Matrices type usually needs simultaneous processing. A relevant model of the two types of information processing may be found in the work of Luria (1966a, 1966b). On the basis of his observations of cortical lesions in different brain locations, Luria has suggested these two major methods of information processing: simultaneous and successive synthesis. In simultaneous synthesis, one is required to arrange stimuli in a simultaneous manner in order to arrive at a judgment. In successive, stimuli must be arranged in a sequence to make a decision. Perhaps one can add that simultaneous synthesis will bear some relationship to a spatial-visual factor, whereas successive will be related to a temporal-auditory factor. But auditory events may need simultaneous synthesis as visual events may require successive synthesis. The two modes of processing information are available to the individual for his use according to the task demands and his past experience. No hierarchy is implied between the two modes, although some cultures may favor one over the other. Luria observed disturbances in the successive mode to be associated with frontotemporal regions of the brain. The simultaneous mode became inefficient in case of lesions in the occipito-

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parietal system. Thus, unlike memory and reasoning factors where memory is supposed to be at a lower level than reasoning (Jensen, 1970), the simultaneous and successive syntheses are on the same plane. We wish to suggest simultaneous/successive syntheses as an alternative way of categorizing cognitive ability. The usual categorization is Reasoning Memory. Reasoning is labeled as Level I1 ability, and rote memory as Level I by Jensen (1970), who distinguishes them on the number oftransformations required by the stimulus input for an appropriate response. A memory task such as digit span or short-serial learning lists requires the subject to hold the stimulus input and then “play it back” on asignal from the experimenter after a brief interval. Reasoning and abstraction, in contrast, require many transformations of the input. IQ tests are predominantly measures of Level 11. In the middle-SES group, the correlation between the two levels is higher than in the low-SES group. Some memory ability is essential for reasoning; but beyond this threshold, reasoning and memory should not be related. The relationship between SES and the two intellectual levels I and I1 is interesting. Jensen (1970) has found that in the lower IQ ranges, the low-SES child was better in rote memory scores (Level I) than his middle-SES counterpart. No prediction was made regarding the high IQ ranges. We have found, however, a crossover effect (Om, 1970; O m & Das, 1972). In the normalIQ range, the middle-SES children are higher in Level I than the low-SES children, whereas this is reversed in the low IQ range. Jensen (1970) has recently obtained a similar effect, and reports that data on some 15,000 children indicate that low-SES children have lower scores than the middle-SES ones at the upper end of the IQ scale. The regression of Level I on Level I1 is thus linear, the line being steeper for the middle-SES sample, reflecting a higher correlation between the two abilities. Jensen holds the view that the basis of the disparity in Level I1 ability between the two SES groups is genetic. Subpopulations that have not been stratified according to education and occupation would lower correlations between these two abilities. But, in other subpopulationswhere stratification exists in regard to occupation and education, assortative mating on the basis of Level I1 ability will occur (IQ correlates with occupational and educational status). Thus, according to Jensen, since spouses are selected more strongly on the basis of an intelligence match than for any other trait among North American whites, Level I1 has been genetically stratified. In contrast, since associative memory ability is needed in almost all cultural settings, Level I ability is not differentiated. In two studies we have used a variety of tests which can be classified apriori as reasoning and memory. However, their factor loadings suggest that a simultaneous vs. successive integration could be parsimonious and more meaningful (Das, 1972). We have suggested that most Level I tasks, such

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as digit span, are too easy, whereas most reasoning t&ks are difficult. Hence there is the hierarchy. But if task complexity is manipulated in each mode of information processing, the hierarchical relationship would disappear. One could design complex tasks that require successive integration, and simple tasks that need simultaneous integration. Transformation of input, or coding for subsequent retrieval and use can be a requirement in Level I memory tasks (by introducing categorization requirements, interference factors, increasing list lengths, cross-modal presentation and retrieval, etc.) as well as in reasoning. In Luria’s model, verbal comprehension depends on successive synthesis to a great extent. John is older than Jim is not equivalent to Jim is older than John-the discrimination requires sequential processing. However, it may be an item in a standard intelligence test, which measures Level I1 ability. On the other hand, a job like watch repair depends on simultaneous synthesis. Is it an instance of Level I or Level II? One could say that both tasksverbal comprhension and watch repair-need memory and reasoning. The memory is not only short-term, therefore is not covered by Level I ability; and the reasoning is not confined to perceiving spatial relationships of the kind illustrated in Progressive Matrices. Luria’s two modes have the added advantage of having identifiable areas in the cortex. Level I1 ability is almost synonymous with intelligence. But what then is intelligence in terms of the two modes of information integration? We would like to suggest that it is not the integration of information, but itsutilization in fulfilling an objective that implies intelligence. The same can be said of memory and reasoning-their effective use in solving aproblem is a mark of intelligence. How about social class differences? It is plausible that thelowSES individuals may prefer memory (which seems to have a highloadingon successive integration), and the high-SES individuals prefer reasoning (high loading on simultaneous integration). It is also conceivable that one of the classes uses information more efficiently than the other. C. Intelligence: A Cross-Cultural Definition

What qualifies as intelligence may be the ability to plan and structure one’s behavior with an end in view. The more efficient and parsimonious the plan is, the more “intelligent” the resulting behavior. Thus, even though individuals in different subpopulations and cultures may be good in simultaneous or in successive integration, or better in reasoning and verbal ability because of schooling than individuals in another ethnic or cultural group, within each group they will vary in their ability to plan and structure their purposive behavior efficiently. If one accepts this, individual differences in intelligence are admissible, while between cultural groups, there should be

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strong antecedents (genetic or environmental) for an intellectual hierarchy to operate. Most probably, subpopulation differences in reasoning vs. memory, elaborate vs. restrictive linguistic codes, parallel vs. sequential processing can be viewed as stylistic variables reflecting the group’s social history and physical environment. The argument in support of intelligence as the ability to plan and structure behavior effectively for goal attainment involves the following considerations. 1. Physiologically, the frontal lobe has been considered as the “seat of intelligence.” Its role seems to be in planning behavior. Luria (1971) reiterates this from his observation of the effects of brain damage. Injury in the frontal lobe may not seriously affect information processing nor attention, but does hamper the utilization of information for structuring future behavior. 2. Reasoning in standard intelligence tests often involves verbal mediation, although it may not demand overt verbalization in some cases. Piaget measures cognitive development through “why?” questions. But stepwise deductions are not often necessary to arrive at a solution; it is however expected in school-related tasks. Verbal articulation is not emphasized in all cultures. Intuition, a short-hand label for arriving at a solution without going through stepwise deductions, is acceptable in many cultures and subpopulations including the youth culture in America. 3. In order to plan behavior, an individual may use his immediate experience, memory, reasoning, knowledge from books and authority, and traditions. There is no need to arrange these devices in a hierarchy of superiority. 4. Intelligence, as presently measured, relates to school achievement. Its predictive value for achievement in real life beyond the school is extremely limited. Popular cases of school dropouts who have later achieved eminence in business, industry, and politics abound in many countries. 5. Our efforts at framing culture-free tests have not been too successful. If intelligence tests historically were constructed to predict school success, it is logical that culture-loaded tests should predict school achievement better than culture-free, and subpopulations in the same culture such as white and Negro who attend schools should be more similar in cultureloaded tests. Culture-free tests then become less relevant to a culture, which may not be adesirable characteristic. Thus, what is universally relevant to all cultures may not be found in spatial-reasoning ability, use of language, mechanical skills, or speed of information processing. Individuals who can give leadership and are wise are respected in every culture. They can be distinguished by an uncommon ability to plan and structure the behavior of their people to obtain desirable goals in their own culture.

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D. Cultural vs. Economic Prosperity: Experiments on the Influence of Caste and SES on Cognitive Ability

Among Hindus, “cultural” advantage is enjoyed by the children from the highest caste even when they are as poor as those from the lowest caste. We have assumed that the children from the poor Brahmin (high-caste priest) have the advantage of scholastic traditions in their caste. In contrast, the poor low-caste (Harijan-scavenger and sweeper) child has no cultural heritage of which to be proud. The general design in the two studies which are presented here is to compare school children from the same grades and schools who belong to four subcultural categories-the rich high caste, rich low caste, poor high caste, and poor low caste. It was very hard to fill in the rich low-caste category; therefore some test results on this group are incomplete, and may not be as reliable. Two experiments on the cognitive competence of the SES and caste groups will be summarized here in order to examine if belonging to the highest caste offsets some of the ill-effects of poverty. The studies are also of interest from the standpoint of genetics-the Brahmin and the Harijan (previously untouchables) are two of the most purely bred subpopulations for generations. In the first experiment, Raven’s Progressive Matrices, the Stroop test (Das, 1970; Stroop, 1935), an auditory short-term memory test, and an auditory-to-visual cross-modal coding task were administered to children between the ages of 9-12 years. Both the high- and low-caste children were sampled from the same schools from fourth, fifth, sixthgrades. Details ofthe experiment are provided in aprevious article(Das, Jachuck, & Panda, 1970). If culture compensated for lack of economic prosperity, one would expect the poor high caste to be as good as the rich low caste in his cognitive performance. These two groups should, however, be below the rich high caste, but above the poor low caste. Progressive Matrices scores were, indeed, lined up in that hierarchy: 21.22, 19.30, 19.38, and 17.92. Only the difference between the extremegroupswas significant. There was no absolute superiority of the high over the low caste. The Stroop test has word-reading, color-naming, and color-word-interference scores. In word-reading speed, the Brahmins, irrespective of economic class, were superior to the Harijans-reading seems to be a culturerelevant ability for the Brahmins. But in color-naming as well as in the color-word interference, the rich were superior to the poor. It is interesting to speculate whether the rich are more exposed to color in their daily life (clothes, furniture, etc.) than the poor who live in adrab and gray household. The short-term memory test did not distinguish the groups either on caste or rich/poor characteristic. Cross-Modal Coding, which involved recognition memory, too, did not show any clasdcaste differences. Thus the results do

J. P. Das not support clear-cut differences in ability due either to genetic (caste) or the environmental (economic prosperity) factor. The next experiment (Panda & Das, 1970) in this series used the same four clasdcaste categories. But the rich and poor contrast was sharper. They were separated by an income gap of $40.00 per month (difference between office clerks and assistant professor’s salaries). In the previous experiment, there was no gap between the upper limit of the poor and the lower limit of the rich group’s income. Only the Stroop test was common between the two experiments. In addition to the Stroop, two verbal-conditioning tasks, each measuring acquisition and reversal, were given to subjects in a random order. The adjective test consisted of anticipating whether the word “good” or “bad” would follow when one of the two nonsense syllables of equal association value, “Tes” and “Tig” was presented (Das, 1961, 1966). Acquisition phase of the task lasted until attaining a criterion of ten consecutively correct responses, then the reversal phase was introduced where the formerly correct response was wrong, and the formerly wrong response was correct. The reversal trials continued until subjects again attained the same criterion. Thus, for each subject the number of trials to criterion was recorded both during acquisition and reversal. In addition to this, the latency of response during acquisition was recorded. Half of the subjects were assigned to a Tes-good/Tig-bad contingency, while for the other half the contingencies were reversed. The second verbal-conditioning task was the light-press test. This was an adaptation of a verbal conditioning task used by Soviet psychologists, for example, Luria and Krasnogorski (OConnor &Das, 1959).The subject sat facing a display panel with his fingers resting on a key. The panel had a red light mounted on it. In the acquisition period, the red light was switched on by the experimenter and if the subject did not press the key spontaneously within 2 seconds, the experimenter said “press!” and if the subject pressed the key, he was reinforced with “good.” Acquisition continued until the subject pressed the key within 2 seconds on ten consecutive trials, following which the reversal phase was introduced. Here, the experimenter said “don’t press!” following key pressing to the light. The reversal criterion was 10 consecutive absences of key pressing to the light. Latency of acquisition response was recorded by a suitable arrangement of the apparatus. The Stroop test results were similar to those in the first experiment, except that both caste and class main effects were obtained for word-reading speed. The superiority of the rich children in word reading which we had not obtained previously may be due to the sharper rich/poor difference in income among our present sample. The two learning tasks brought out the complexity of the class/caste interactions. In the adjective task, the high-caste children, irrespective of income, were superior to the low-caste children in

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trials to learn and reverse. Economic class was not a significant variable. The light-press task performance, on the other hand, showed the rich, irrespective of caste, to be superior to the poor in trials to learn and to reverse. On latency of response, however, the high-caste children were faster than the low-caste. They were also faster in speed of reading words (Stroop test). It may suggest a general superiority of the high-caste in the speed of information processing. The results, on the whole, demonstrate that being born of highest caste and economic prosperity independently favor a superior verbal ability, and a combination of the two gives one enormous advantage in cognitive abilities. IV. 10, SES. AND COGNITIVE COMPETENCE

In this section we are going to present the results of a survey and experiment involving IQ, SES, and several tests of cognitive ability. The survey was based on 1137 children from Grades One and Two of public schools in Edmonton. All of the children had IQs below 100, with the mean IQ of 92. In addition to these children we had also surveyed all of the 157 children (mean IQ 67), who were in the special classes of the public schools. A. SESand IQ

The primary objectives of the survey were to delineate the biographical and social characteristics of children who have IQs below 100 and to observe whether or not we could obtain the same correlation between SES and IQ in this sample as has been reported in samples of subjects with IQs above 100. A correlation between IQ and SES as high as .50 has been found. Jensen (1970) presents the clearest description of the relation between these two variables. The correlation between genotypic and phenotypic intelligence is about .90, while that between occupational status or SES and phenotypic intelligence as measured by IQ tests is .50. An important question here for the notion that intelligence is genetically determined is whether or not genotypic intelligence has a correlation with SES. In other words, does an individual occupy a high SES on the basis of inherited intelligence rather than on the basis of environmental accidents? Jensen points out that the relationship between genotypic intelligence and SES cannot be assumed t o be zero, as the environmentalist would like it to be, on mathematical grounds. The correlations among a set of variables such as genotype (I), phenotype (2), and SES (3) must meet the following general requirement: rf2 + rf3 + rt, 2r,zr,3r23 cannot have a value greater than 1. When r , 2= .90andr2, = .50,if one substitutes the value of zero as the correlation between genotype and

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SES the net result is greater than 1 . Thus, r , 3 should be greater than zero. In other words, there has to be some relationship between inherited intelligence and SES. This r is larger in Western societies where stratification of intelligence has been achieved through assortative mating. Its value is expected to be much smaller in developing societies. However, it is quite consistent with the geneticist formulation where stratification has not been achieved. B. Results of a Survey of Normal and Retarded Children and Their Parents

SES in our sample was determined on the basis of parental occupation using Blishen’s scale (Blishen, Jones, Naegele, & Porter, 1965). This scale is based both on education and income and is found to correlate very highly with the more elaborate Warner scale (Warner, 1960). The relation between IQ and SES was examined by dividing the SES scores into seven hierarchical class intervals and obtaining the mean IQs of the children in each of those class intervals. A striking linearity was noticed. The IQ showed a consistent increment from the lowest to the highest SES levels, varying from a mean of 90.33 in the highest to 78.66 in the lowest. A one-way analysis of variance yielded a significant F ratio. However, the extent to which variation in IQ as a function of SES can be attributed to heredity is still an open question. The variables most predictive of a child’s IQ in our sample were father’s education, mother’s education, and the parents’ SES. Correlations between each of these and the child’s IQ, respectively, were .26, .29 and .27, based on 1294 children. It appears that mother’s education emerges as the best predictor of child’s IQ. Its role is accentuated when only the retarded group is considered. Here the correlation between mother’s education and IQ increases to .35 (N = 157). The IQ scores were obtained from the school records of the children; most of them had taken the Detroit Beginners, if they were in the regular class, and WISC or Binet. if they were in a special class. C. Short-Term Memory (STM) and SES

We have mentioned earlier that IQ and memory are highly correlated in the middle-SES, but not so in the low-SES groups. When the SES groups are equated on IQ, the low-SES child performs better in associative memory tasks than the high/middle-SES child when IQs are below 100. We have carried out an experiment where several short-term memory (STM) tests were given to retarded and nonretarded (IQ below 100,mean 92) children, from low and middle SES. The purpose was to test the generality of the crossover effect beyond the tasks Jensen uses. Jensen (1971) has also pointed

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out that the high/middle-SES subjects in the upper ZQ ranges do better than the low-SES subjects. But the relationship is reversed in thelower IQ ranges. This cannot be attributed to the fact that memory tasks (Level I) were less culture-bound than reasoning tasks (Level II), hence the low-SES subject does better on it. Why does the same bias produce the opposite result in upper IQ ranges? The crossover effect may be explained in the following manner. The lowSES subject should be inferior to the high in Level I1 because of known IQ differences between the two groups. But, since both are below the average threshold in IQ, Level I1 and Level I will be positively related to some extent. Now, if one randomly selects a group of high-SES and a group of low-SES retardates, the latter will be lower in measured IQ (but equal as to Level I) because of SES. But if one further wishes to match the low-SES individuals on IQ with the high, one would be compelled to select brighter low-SES individuals, who will be equal on Level I1 with the high-SES subjects, and will also be superior to them on Level I due to the process of selection. This superiority on Level I would be reflected in their performance on digit span and serial learning tasks. The four groups of children, middle-SES nonretarded and retarded, and low-SES nonretarded and retarded, were chosen from the sample of 1294 surveyed earlier. The SES groups were matched on IQ whereas the retarded and nonretarded children were matched on mental age. There were 30 children in each group. Subjects were given a visually presented matrix of digits, a visual STM, a serial learning task auditorily presented, and a cross-modal coding from auditory to visual recognition task (Birch & Belmont, 1964).

Average 10

Low 10

FIG.I . Interaction between IQ and SES: Serial recall. Low SES, -; high SES, -. From J . P. Das, IQ, socioeconomic status, and short-term memory. Journal ofEducutioml Psychology, 1912.

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0’

I

Average 10

I

Low 1Q

FIG. 2. Interaction between IQ and SES: Visual STM. Low SES. ; high SES. From J . P. Das, IQ, socioeconomic status, and short-term memory. Journal of’Educationa1 Psychology, 1972. ~

The graphs (Figs. 1 and 2) clearly show a crossover effect, which is statistically supported by a significant IQ x SES interaction for both the visual and the auditory STM tests. Cross-modal coding results showed the same trend, but did not reach statistical significance. One suspects that the coding task is not a pure test of STM, a point which becomes apparent from its loading in a subsequent factor analysis. Unlike Jensen’s interracial samples who were substantially separated in 1Q and SES, all our samples came from the Caucasian subpopulation; and the low-SES children did not come from slum areas. They were in the same neighborhood school as the high-SES children. In IQs, both groups were below 100. Similarly, the high- and low-SES children had, in fact, adjacent occupational scale positions. In spite of the closeness of the samples in IQ and SES, the crossover effect was obtained. The results provide a conservative test for Jensen’s hypothesis and extend its generality beyond the tests he used. Besides the tests of STM and cross-modal coding, the four IQ x SES groups were also given Progressive Matrices (colored) and Graham-Kendall’s Memory for Designs. IQ did not interact with SES on either of these tests. Moreover, the high-SES children did not score higher than the low-SES children. Only one comparison was found to be statistically significant, and this was obtained between the retarded and the nonretarded groups (IQ main effect was statistically significant). The two IQ groups were matched on MA, and according to one point of view(Zigler, 1969) should not be expected to show differences in cognitive abilities. Mean scores for the nonretarded and retarded children one the tests were as follows: Progressive Matrices, 23.9 and 19.1; Memory for Designs errors, 5.5 and 10.5; Cross-Modal Coding, 23.7 and 16.3; Visual STM, 54.2 and 40.4; Auditory Serial Recall, 30.5 and 23.7; Auditory Free Recall, 40.9 and 32.2. Since all retarded children were taken from public schools, they can be classified as secondary rather than primary retardates (Jensen, 1970).

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Accordingly, the secondary type should have an adequate Level I but an inferior Level 11. Whether this should still be valid when the retardedgroup is matched on MA with the nonretarded cannot be clearly derived from Jensen’s model. One prediction from the model would be that, in terms of our present tests, the Progressive Matrices scores should be the furthest apart for retarded and nonretarded children. Memory for Designs and cross-modal coding are closer to Progressive Matrices (see factor loadings in Table I), and therefore are expected to differentiate the two groups more clearly than STM tests. This is not supported by comparing the mean scores given above. The retarded children appear to be equally inferior to the nonretarded in memory as in reasoning tests. This is possible only when the retardates are of the primary type, according to Jensen. The primary retardates will have among them many with neurological damage. One of our tests here, the Memory for Designs, should be sensitive to suchdamage. We reasoned that among our retarded children, those from high SES were more likely to be classed as brain-damaged than those from low SES. Such an expectation, however, was not verified by an examination of the mean and distribution of Memory for Designs test scores.

V. ETHNICITY, PERSONALITY, AND COGNITIVE COMPETENCE: RESULTS OF THREE PARALLEL STUDIES

In this section, attention will be devoted to studies where SES and ethnic background have been varied to interact with each other in three different cultural settings. Subjects were children attending regular school classes. The samples were (1) high- and low-SES white children, and Canadian Indian children of low SES, (2) high- and low-SES black children compared to their white counterparts, and (3) high- and low-caste (Brahmin and Harijan) children, all of whom were given the same battery ofpersonality and cognitive tests. Since we proposed that extra-intellectual autochthonous factors which characterize the disadvantaged child and his parents may depress his cognitive performance, some assessment of parental aspiration and personality was also included in this study.

A. Hypotheses

Some of the subcultural groups were given the personality tests (Rigidity, Locus of Control, etc.), and compared with one another for the first time. No firm hypotheses, therefore, could be advanced. Thus, the studies were partly exploratory in nature. Nonetheless, some tentative hypotheses were formulated.

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The chief variables were SES and ethnic origin. These provided static frames of reference within which the performance of a group of children is examined in personality tests, and tests of cognitive ability. Apart from these, parental expectation and educational aspiration for the child were obtained. A prediction was made that the latter factor would influence the child‘s cognitive attainment. Specifically,parental expectation regarding the child’s education would be a stronger variable in the disadvantaged class than in the advantaged class. It could be the largest factor contributing to individual differences in cognitive task performance within the Negro, Canadian Indian, poor white, and the Harijan samples. The next important factorwas locus of control for behavior as the child perceived it. Therefore, even if intergroup differences might be caused by genetic and/or environmental agents, the difference within the group was predicted to be due to autochthonous factors. Between the groups, significant differences in parental expectations were predicted.

B. Tests and Experiments

1. PARENTAL EXPECTANCY Dyer (1967) has modified an interview schedule originally developed by Wolf (1966) for obtaining an “index of educational environment.” This was used on a sample of school children in Trinidad and found to be more closely related to the child’s achievement in school than SES. We have used only part of this interview schedule, which focusses on (a) parent’s interest in child’s academic progress, (b) knowledge of child’s educational progress, (c) parental aspiration for the education of the child, and (d) parental preparation, financial and otherwise, for higher education of the child. Scores on all these aspects were combined to obtain a total score, which we label parental expectancy.

2. PARENT’S PERSONALITY Belief in an external vs. an internal control of ones behavior is a crucial variable for perception, learning, and social behavior. Rotter (1966) describes it as a generalized expectancy regarding the causal nature “behavioroutcome sequences.” It is also closely related to a person’s awareness of success and failure and his reaction to these (Cromwell, 1963). Thus, the scores on locus of control for parents and children may determine the child’s educational success. The adult locus of control test (Rotter, 1966)was taped for presentation to parents in all of our samples, avoiding the need to read. The children’s test, taken from Crandall, Kratkovsky, and Crandall(1969,

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was read to the child by the experimenter. These tests, along with other personality tests, were translated into the native language (Oriya) of the samples from India. Besides Locus of Control (LC), two other personality tests were given to both parents and children: Eysenck’s (1947, 1960), Personality Inventory measuring Extraversion-Introversion, Neuroticism-Stability and Lie; and Soueif’s ( 1958) Personal Friends Check List measuring rigidity (intolerance of ambiguity). Rigidity is assumed to be orthogonal to both extraversion and neuroticism (Soueif, 1965). Thus the three personality tests taken together cover the major traits of an individual, and if the advantaged and disadvantaged samples of children/parents differ in their personality patterns, it should be apparent from their scores. 3. COGNITIVE ABILITIES

Many of the tests used in this study had been included in the previous studies on caste, and IQ x SES considered earlier. The Stroop test, CrossModal Coding, a modified form of visual STM. Memory for Designs, and Raven Coloured Progressive Matrices were common to the IQ x SES and this study. In addition to these the following two were included. The Figure Copying test, developed by the Gesell Institute (Ilg & Ames, 1964),has been extensively used, and provides an estimate of intellectual ability (Jensen & Rohwer, 1970).This test does not involve memory factor as does the Memory for Designs. Instead, the child is required merely to copy a geometrical figure while it is in view. Speed and persistence of test taking motivation is measured by a task in which the child is asked to make “X” in each of a series of squares, first under no-speed condition, then under an instruction to speed-up as much as possible. The difference is an index of test-taking motivation.

C. White and Canadian Indian Comparisons

The subjects were high- and low-SES white and low-SES Canadian Indian children from Grade Four. Both classes of white children came from the same schools; thus the school environment was the same for all white children. The Canadian Indians were students in a reserve school, and lived with their families on the reserve. There were 30 children in each group. An overall comparison between the three samples was carried out for each test; the results of the one-way analyses of variance are summarized below. 1 . Parental Expectancy. The high-SES white parents had the highest scores on this questionnaire, as expected, and the Canadian Indian parents had the lowest score. However, the low-SES white parents did not have

38

J. P. Das

significantly higher aspiration and expectation than the Canadian Indians with regard to their children’s education. 2. Personality. In extraversion-introversion, the Canadian Indian parents were the most introverted (mean = 7.57) compared to the two white groups (means = 11.90 high-SES, 10.93 low-SES). Neuroticism scores did not differentiate the groups. Rigidity as extreme responses set was found to be highest for the low-SES white parents (M = 31.23). The other two samples were not significantly different from each other. Rigidity is a characteristic of minority groups who experience a greater degree of tension (Soueif, 1958). In that case, the Canadian Indian parents should have the highest score. We had expected that Locus of Control would distinguish the low- from the high-SES parents, and certainly the Canadian Indian from white highSES parents. There was absolutely no difference between these groups. Their children too did not differ in locus of control. The Canadian Indian children were the most introverted compared to the white children, but there was no difference in neuroticism or rigidity. In word-reading speed from Stroop test charts, the Canadian Indian children were the slowest, there being no difference between the white children. One may expect this because they were relatively backward in the English language. Color-naming was also the poorest for the Canadian Indian sample. Raven’s Progressive Matrices scores were significantly higher for the highSES whites (M = 29.37) than for low-SES whites ( M = 26.60), who had higher scores than the Canadian Indian (M = 23.37) samples. Even though the white children came from the same schools, SES differences were obtained. We will see later how they stand on achievement scores. There was no difference between the groups on Memory for Designs, although it has a positive correlation with Progressive Matrices. But in Figure Copying, which does not involve any memory, the Canadian Indians excelled the two white samples: Means were 17.60, 16.83 (high-SES white) and 16.17 (low-SES white). Cross-Modal Coding was the only other cognitive test in which the samples differed. The Canadian Indian children were again the lowest (M = 23.27) compared to the high- (27.30) and low-(26.73) SES whites. The white groups did not differ from each other significantly. All groups had the same testtaking motivation as measured by the making X’s test. 3. Achievement scores: reading and mathematics. The two white groups were compared on reading and mathematics achievement with the hope that these may highlight the disadvantage of the low-SES children. Reading achievement was assessed by the California Achievement Test, and Mathematics by a test developed for Edmonton Public Schools. I n both tests, the

CULTURAL DEPRIVATION AND COGNITIVE COMPETENCE

39

low-SES means (61.53, 62.23) were lower than high-SES means (74.37, 74.43), significant beyond the .01 level. Thus, in the two achievement tests and the Progressive Matrices the high-SES children were superior to the low-SES children. We had expected on the basis of Coleman’s report that by equalizing the school environment the difference between SES should be minimized. This was not supported by the data. On the other hand, the same school and neighborhood for the high- and low-SES children seemed to have reduced personality differences. D. White-Black Comparisons

Four samples of Grade Four white and black children were taken from Montreal. Each ethnic sample was divided into high- and low-SES groups. White groups had 30 children each, but the blacks had 20 in each group. It was very difficult to get the school’s permission to test black children, hence we tested as many as we could get. A 2 x 2 (ethnic x SES) analysis of variance was performed for each test. The results are given under the headings of Parental Expectation, Personality, and Cognitive Performance as in the previous comparison. 1. Parental Expectancy. The main effect for SES was alone significantthe high-SES parents, on the whole, had higher aspiration and interest with regard to their children’s education than the low-SES parents. One might have expected the same results if all our children were white. 2. Personality. Locus of Control again showed that neither the SES contrast nor ethnic contrast resulted in a significant difference. In American studies, the adult Negro had been usually found to be more externally controlled than the white (Rotter, 1966). MontrealNegroes, who are mostly firstto third-generation West Indians, need not share the same belief in external control. In fact, our interviewers (graduate students at McGill) were surprised to see that the adult blacks from low SES had strong self-confidence and belief in their own power. Extraversion and neuroticism did not distinguish the samples, but in rigidity, the blacks showed a stronger extreme response set than white adults. This confirms Soueif‘s (1965) finding regarding higher rigidity scores in minority groups. Children’s personalities in the four groups differed very little. In locus of control, extraversion, neuroticism, and rigidity, they did not differ either because of SES or of ethnic origin. 3. Cognitive Performance. The Stroop test word-reading speed was similar in all samples of children. But in color naming, the whites were somewhat faster than the blacks. This can be compared to the white superi-

J. P. Das ority over the Canadian Indian children we have noted earlier in both word reading and color naming. But, unlike the Canadian Indian, the black child does not seem to have any language handicap (no difference in word-reading speed). Could it be that he is less articulate about color as the poor children in India were found to be when compared to the rich? Progressive Matrices scores were higher for the whites than for the blacks; F was significant below .02 level. The SES main effect and the ethnicity x SES interaction were not significant. The black/white difference has been noted several times in American studies (Jensen, 1969a). In Figure Copying, both main effects were highly significant-black/white F at .01 level and low/high SES below .001 level. The black children were poorer than the white in performance, and in each group, the means showed that the low SES was poorer than the high. Memory for Designs, STM, o r Cross-Modal Coding did not yield any significant differences. Neither were the groups different in test-taking motivation as measured by making X’s test. On the whole, we found that for the Montreal sample, the discriminating tests were Progressive Matrices and Figure Copying and some of the Stroop test charts. In personality, the adult blacks were more rigid than the whites. Rich parents had higher aspiration for their children’s education than the poor. E. Caste4lass Comparisons

If culture has an independent influence apart from economic prosperity, it should be demonstrable in the samples from India. The Brahmin, the highest caste in hierarchy, and the Harijans, the lowest caste, have been separated by birth for generations. Brahminic culture is accepted to be higher, and among the Brahmins, the orthodox types, although usually poor, have preserved their traditional vocations of temple and family priests. The orthodox live in special Brahmin villages, called Sasana in Orissa state where our samples were tested. If culture offsets some of the ill effects of poverty, this will be apparent not only by comparing the poor from Brahmins and Harijans, as we have done before, but also by comparing the orthodox Brahmin who is poor with his city counterpart. Poor city adult Brahmins usually have a low-ranking job (office boy, cook) with the government. We restricted our sample of Harijans in age (about 1 1 years) and grade (fifth class in Orissa schools) to be comparable with samples from Edmonton and Montreal. As a result, it was impossible to obtain 30 children to fill the rich Harijan category. In a previous study reported before, the age range was 9-12 years, and the chil-

CULTURAL DEPRIVATION AND COGNITIVE COMPETENCE

41

dren did not study in the same grade; as a result, we could collect some rich Harijan children for testing. Gross comparisons were made among the four groups-the rich high caste, the orthodox and nonorthodox poor high castes, and the poor low caste-by subjecting their scores in any one test to a one-way analysis of variance. 1. Parental Expectation. The rich high caste had the highest score in this interview schedule. But the hierarchy of the other three groups was somewhat surprising-next to the rich was the nonorthodox poor high-caste parents whose scores were close to the rich, and not significantly different. The orthodox high caste and the poor low caste were grouped together, and were significantly lower than the other two groups. Education in the schools is the same all over, village or town, and is Westernized. It is quite likely that the orthodox parent does not appear to give much value to it. The lowcaste parent’s lack of aspiration, however, may exist for other reasons such as lack of confidence in his child’s ability and acceptance of his caste’s lowest social role. 2 . Personality. We have expected that the low-caste adult would be more fatalistic, and therefore more externally controlled. But there was absolutely no consistent tendency among the four groups. Extraversion, neuroticism, and rigidity did not show up any group differences. 3 . Cognitive Performance. The Stroop test charts brought out some interesting differences. In word-reading speed, the rich and the orthodox Brahmin children were superior to low caste, and almost superior to the nonorthodox poor Brahmin children (p = .07). This is the only cognitive task in which the orthodox group had an advantage over the nonorthodox group. Color-naming speed was better for the rich and the nonorthodox poor Brahmin when compared to the low-caste children. Superiority of the rich over the poor in color naming was previously observed (Panda& Das, 1970). In Progressive Matrices and in Figure Copying, the low-caste children did not do more poorly than the high-caste. This was somewhat surprising, because we had expected at least a rich high-castelpoor low-caste difference as in our previous studies. However, the children in the present study were two classes higher. The low-caste child who has not dropped out, but studies in a higher class, could be brighter than the children from two classes lower, many of whom discontinue their studies in the next 2 years. Cross-modal coding revealed the rich high-caste children’s superiority over the poor low caste, but the intermediate groups were not significantly superior to the low caste. The same results were obtained in STM. Comparison of the group means showed a consistent hierarchy-the rich Brahmin had the highest score followed by the nonorthodox Brahmin, then the ortho-

42

J. P. Das

dox Brahmin, and lastly the poor Harijan. Orthodoxy certainly did not facilitate cross-model coding and STM performances. All groups were equivalent in test-taking motivation, except that in making X’s without speed instruction, the orthodox children appeared to be the slowest. In sum, we did not find that birth in the Brahmin caste had an absolute advantage in cognitive abilities. Economic prosperity, on the other hand, reflected more of an advantage than high-caste birth.

F. Personality and Cognitive Abilities: Multiple Correlations

Personality patterns of adults and children belonging to different subcultures were more alike than different. But there was a range of variation in personality scores within the same subcultural sample. One of our assumptions had been that these autochthonous factors might influence intellectual ability. Besides these, the relation between the basic cognitive tests we have used here, and an accepted cross-cultural measure of intelligence (MacArthur & Elley, 1963), such as the Progressive Matrices, has not been examined before. One also expects that the strength of these relationships would vary because of SES and ethnic c!assifications. We have selected parental expectancy and locus of control of the child as the two variables which might have an effect on the child’s Progressive Matrices scores. Besides these two, SES scores, where available, have been included. Of the cognitive tests, Figure Copying, Cross-Modal Coding, and STM have been chosen, and their multiple regression on Progressive Matrices calculated. These are done for each sample in Edmonton, Montreal, and Orissa. In addition to these, the Edmonton white samples were also given reading achievement, mathematics achievement, and word recall tests, which have been used in computing multiple correlation. 1. EDMONTON SAMPLES

The influence of parental expectation and SES on Progressive Matrices scores was substantial in the high-SES white sample only. Parental expectation accounted for 21.52% of the variance; the addition of SES brought it up to 27.21%. In the other two samples, the R was not significant. This was somewhat unexpected. We mentioned earlier that parental expectation may be the overriding factor in low-SES groups. What the R implies, perhaps, is that parents with higher expectations of their children, and of higher SES within the middle to upper category, have brighter children-a conclusion not inconsistent with a genetic interpretation of IQ. But does parental

CULTURAL DEPRIVATION A N D COGNITIVE COMPETENCE

43

expectation or SES predict achievement better than intelligence? I n the high-SES white group, the only significant variable is parental expectation which accounts for 16.2% of the variance in mathematical achievement. Reading achievement is not predictable from the set of variables including SES, parental expectation, and locus of control. Among the low-SES whites, 20.2% of reading achievement variance was accounted for by parental expectation. This was increased to 35.8%with the addition of SES. Locus of control did not contribute even 1%. Similarly, in mathematical achievement, the first and second variables together accounted for 45.5% of the variance. Thus, as far as achievement rather than intelligence is concerned, the low-SES child profits mostly from the high educational aspirations that his parents have for him. Cognitive Tests and Progressive Matrices. Figure Copying, Cross-Modal Coding, and Visual STM were the variables we have first considered for their multiple R with Progressive Matrices. Of these, the first two are important for all three samples. For high-SES whites, the two together account for 25.6% of the variance; for low-SES whites, 30.4%.In the Canadian Indian sample, STM is also asignificant variable, and the three contribute 34.7% of the variance. On the whole, Figure Copying has the best predictability for performance on Progressive Matrices. Cognitive Tests and Achievement The two white groups were also administered a word memory test which was scored in two ways-serial and free recall. The multiple R withreading achievement was predominantly based on one of the recall scores and the STM. They accounted for 27.5% of the variance in the high-SES group, and 29.8% in the low-SES group. On the other hand, mathematics achievement in the high SES group was influenced most by Figure Copying andcrossModal Coding (22.9% of variance). Low-SES groups differed on this-their two major variables were serial recall and Figure Copying (24.5%). CrossModal Coding added only 2% to this variance. Is it possible to infer that the low-SES children were depending more on memory for mathematical skills than the high-SES children?

2. MONTREAL SAMPLES Parental expectancy and SES contributed significantly to the variance on Progressive Matrices only in the high-SES black group. Locus of control, too, was found to be an important variable-along with parental expectancy they accounted for 42.6% of the variance. Of the remaining groups, none except high-SES whites had a significant variance. Locus of control rather

J. P. Das

44

than parental expectancy or SES was the main variable related to Progressive Matrices in this group. The three variables accounted for 25.8% of the variance. I n high-SES whites, STM, Cross-Modal Coding and Figure Copying together explained 27.7% of the variance in Progressive Matrices. Very similar results were obtained for low-SES whites and low-SES blacks. But, for the high-SES blacks, only Figure Copying had a significant correlation with Progressive Matrices, accounting for 27.8% of the variance. The results were essentially similar to the samples from Edmonton. 3. ORISSASAMPLES

Parental expectancy did not appear as a significant predictor of Progressive Matrices scores in any of the caste/class samples. The only significant predictor was locus of control for the nonorthodox Brahmin sample (1 3.9% of the variance). Does it reflect that the child who scored high tends to have a success-striving attitude-that he did not give up the hard problems in Progressive Matrices easily? The rich and the orthodox Brahmin were the two groups which had significant R’s. For the orthodox Brahmin, Figure Copying, Cross-Modal Coding, and STM accounted for 27.4% of the variance. For the other group, the first two tests accounted for 23.5%, which was of borderline significance (p = .06). In conclusion, it appears that parental expectation was a major predictor of success in Progressive Matrices for all except the samples from Orissa. But it predicts achievement better than intelligence as measured by the Matrices. No consistent pattern of difference emerged when high- and lowSES samples were contrasted. The relationship between the cognitive tests and Progressive Matrices was clearer. Figure Copying and Cross-Modal Coding are found to be good predictors. The nature of the cognitive tests will be apparent from their factor loadings, which are presented in the next section. VI. STRUCTURE

OF COGNITIVE ABILITIES

A. Simultaneous and Successive Processing Factors

Almost all of the cognitive tests which were used in our studies can be classified as reasoning or memory tests. We have mentioned earlier that an alternative classification may be provided in terms of information processing simultaneous and successive synthesis. The classification was suggested by a factor analysis of the tests given to retarded and nonretarded children in the IQ x SES study. Table I shows the factor loadings after Varimax rota-

45

CULTURAL DEPRIVATION A N D COGNITIVE COMPETENCE

TABLE 1 ROTATED (VARIMAX) FACTORSFOR COGNITIVE TESTSI N NORMALAND RETARDEDGROUPS(h’ = 60 IN EACH GROUP) Variable Raven’s Progressive Matrices Graham-Kendall’s Memory for Design’ IQ score from school record Cross-Modal Coding (CMC) STM (Visual) Serial Recall Free Recall Variance

Normal, Grade 2 and 3 children

Retardates, (MA-matched)

I 792

I1

I

161

786

II 007

269 492 742 693 I54 023 1.996

579 I76 -020 294 683 757 1.519

830 592 546 533 048 043 2.173

-06 I 326 482 48 1 855 856 2.039

“The usual score is the total number of errors which has been transformed (X-score) where X is greater than the highest score.

tion. The IQ test score was derived from the school records, and together with the six tests as listed, was included in a principal-component analysis. How can one describe the factors meaningfully? Factors 1 and 2 appear to correspond to the usual division of abilities into reasoning and memory. In that sense, we have again obtained evidence supporting the two broad categories of cognitive ability which Jensen (1970) calls Levels I1 and I. But this interpretation seems to be inadequate when we consider the disparate loadings for the normals and retardates on some of the tests. For example, in Memory for Designs, a high loading on memory obtains for the normals whereas in the retardates, it has a high loading only on the reasoning factor. Similarly, Visual STM seems to load highly on reasoning for the normals; but for the retardates, a substantial loading is also noticed on memory. If one wishes to retain the memory-reasoning interpretation, one could say that the retardates used reasoning to reproduce the designs, whereas the normals used memory. In Visual STM, on the other hand, the normals seem to be using reasoning predominantly, but the retardates use both. It does not appear to be a satisfactory interpretation. In both tests, one would expect associative memory to predominate irrespective of subject samples. Therefore, a more appropriate label was suggested(Das, 1972) for the two factors: simultaneous and successive synthesis, borrowing the terms from Luria (1966a, 1966b). An explanation of the two categories was given in Section I11 of this review. If we look at the factor loadings for the tests used here, the labels seem to be parsimonious. Raven’s Progressive Matrices, marker test for Factor 1,

46

J . P. Das

is presented spatially and requires a simultaneous synthesis. Auditory recall, the marker test for Factor 2, needs successive synthesis. The mixed tests were Memory for Designs, Visual STM, and Cross-Modal Coding. The first of these appears to require successive synthesis for normals, and simultaneous for the retardates. If one is allowed to speculate further, one may add that, in producing the designs, the normal child is defining the task operationally as a sequence of pencil movements which he remembers, and this guides his reproduction. The retardate, on the other hand, has to remember it as a total picture in order that he may be able to reproduce it. Cross-Modal Coding required listening to patterns of taps and then recognizing the test pattern embedded in three visually presented dot patterns. The normal child attacks the problem as one requiring simultaneous integration. The retarded child depends both on simultaneous and successive processing. He does the same for Visual STM, whereas the normal child uses only the simultaneous mode. The two modes of information integration should be generally obtained in cognitive tests. Evidence in favor of this is provided below by factor analyses of the test scores in the cross-cultural study. B. Evidence from Cross-Cultural Studies

1. EDMONTON SAMPLES

The factor loadings (Varimax rotation) for 60 white children (both SES) are presented in Table 11. Factors 1 and 3 can be recognized as representing successive and simultaneous modes respectively. The highest loadings on Factor 1 are for recall and STM. Memory for Designs, Progressive Matrices, and Figure Copying load highly on Factor 3. Cross-Modal Coding has a significant loading on both of these, as might be expected. Factor 2 is clearly a school achievement factor. Factor 4 may be best described as a speed factor. Word reading time has the highest loading on this factor; Visual STM and Cross-Modal coding tasks have significant loadings on this. In both these tests, the child had to look or listen to the stimulus material speedily during presentation. In order to find out if the two SES groups had similar factors and loadings, separate factor analysis for each group should have been carried out. But the present sample size is too small ( N = 30) to be reliable. 2. ORISSA SAMPLES

The samples from Orissa consisted of three high-caste groups and one low-caste group. All the high-caste groups were combined for the purpose of factor analysis. Only six tests had been given to the Orissa samples: Word

47

CULTURAL DEPRIVATION A N D COGNITIVE COMPETENCE

TABLE I1 ROTATED FACTORS (VARIMAX) FOR COGNITIVE AND ACHIEVEMENT TESTS: EDMONTON HIGH-AND Low-SES GROUB COMBINED( N = 60) Variables

IQ Words Raven's Figure copying Memory for Designs Cross-Modal Coding (CMC) Short-Term Memory(STM) Serial Recall Free Recall Reading achievement Math achievement Variance

I

I1

111

IV

204 045 740 674 - 830 433 124 042

045 -879 - 200 -004 - 162 423 46 2 013 0 I9 266 152 1.328

34 7

193

- 130

- 320

181 162 178 451 760 896 898 I84 161 2.684

384 157 -055 059 034 355 340 85 I 844 2.590

004 100

28 1 2.029

Reading, Progressive Matrices, Figure Copying, Memory for Designs, Cross-Modal Coding, and the Visual STM. Table I11 shows the factor loadings, after varimax rotation. The first factor has high loadings on Progressive Matrices, Figure Copying, and Memory for Designs. STM has a very high loading on the third factor. The only other test which has asignificant loading on it is the Progressive Matrices. If we label Factors 1 and 3 as simultaneous and successive, we have to assume that Progressive Matrices for the children in India required some successive integration. This need not be an unacceptable assumption. The remaining factor, Factor 2, is clearly a speed factor, having the highest loading for world-reading speed. Cross-Modal Coding, as before, has a strong loading on this factor. Thus far, the common factors are simultaneous, successive, and speed. Progressive Matrices, Figure Copying, and Memory for Designs have subTABLE 111 ROTATED FACTORS (VARIMAX) FOR COGNITIVE TESTS:HIGH-CASTE ORISSACHILDREN ( N = 90) Variable Words Raven's Figure Copying Memory for Designs Cross-Modal Coding Short-Term Memory (STM) Variance

I

I1

I11

-01 I 624 800 -809 206 -013 1.726

830 253 - 278

032 433 -112 -037 233 918 1.099

111 -640

175 I .282

J. P. Das

48

stantial loadings on the simultaneous factor, STM on the successive factor. The market test for speed or “personal tempo” is the word-reading time from the Stroop chart. 3. MONTREAL SAMPLES Factor analyses of the data from Montreal were separately carried out for high-, and for low-SES groups, disregarding the ethnic origin. We had mentioned earlier that there was some difficulty in collecting data from black children. Wheras all white children were tested at school in a quiet room, the black children were tested at home and community centers, which might make their scores less reliable. Factor analysis of high-SES data (white and black) revealed two factors. All the tests except word reading had a loading of nearly .3 or better on Factor 1. The highest loadings were for Memory for Designs (-.866) and Progressive Matrices (.749). STM had a loading of .467 on this factor. Thus, it appears to be a g factor. Factor 2 can be described as a speed factorthe marker test is word-reading time (-.873). As before, Cross-Modal Coding and STM have substantial loadings on this. Low-SES data(white and black), when analyzed, yielded only one general factor which appeared to combine both g and speed. The highest loadings were for word reading (- .778), Cross-Modal Coding (.814), and STM(.718). What isthedifference then between high and low SES in terms of cognitive factors? None, as far as the data of the present study suggest, except that the abilities in low-SES groups are less differentiated. VII. SUMMARY

The chapter dealt with a topic on which research is in a state of positive acceleration. Therefore it would not have been practical to review most of the work relating to cultural deprivation and cognitive competence. A selecTABLE 1V ROTATEDFACTORS (VARIMAX) FOR COGNITIVE TESTS: HIGH-SES MONTREAL GROWS( N = 50) Variable Words Raven’s Figure Copying Memory for Designs Cross-Modal Coding (CMC) Short-Term Memory (STM) Variance

I

TI

108 749 499 - 866 294 461 1.876

-873 128 345 -022 628 592 1.643

49

CULTURAL DEPRIVATION AND COGNITIVE COMPETENCE

TABLE V FACTORLOADINGSFOR COGNITIVE TESTS: Low-SES MONTREAL GROUPS(N = 50) Variable Words Raven’s Figure Copying Memory for Designs Cross-Modal Coding (CMC) Short-Term Memory (STM) Variance

I - 778 635 694 - 660 814 718 3.102

tive review of certain areas of research was presented in the first three sections. The next three sections discussed the results of the author’s experiments. The major trends in the subject area were described in the Introduction. Besides these, in the course of the review, the following ideas were advanced. I . A modified threshold hypothesis was advanced regarding the effects of early childhood stimulation. It was observed that disadvantaged children between 1 and 2 SDs below IQ 100 may gain substantially from an enriched environment; but those within 1 SD need only be given a chance to operate in the ordinary environment of the nondisadvantaged child which usually should be provided by the school. 2. The role of extraintellectual factors, such as parental aspiration for the child’s education and the school environment, had been pointed out in Coleman’s report. These factors were included in the experiments by the author. It was noticed that parental expectation was indeed positively related to the child’s achievement and intelligence in more than one subcultural group. But, the high-SES child was still superior to the low-SES child in many cognitive test performances even though both groups of children attended the same schools. 3. Cognitive abilities could be classified in terms of information processing-the cognitive tests required simultaneous or successive processing of information in various degrees. Such a categorization was felt to have some advantages over the usual one of reasoning and memory. Factor analytic data generally showed the existence of a simultaneous and a successive processing factor. 4. A definition of intelligence across cultures was suggested. It was the ability to plan and structure behavior effectively for goal attainment. A n effective use of information, or of reasoning and memory abilities, rather than the abilities per se, would thus indicate intelligence. School learning might bias the individual toward using spatial reasoning ability, whereas, in preliterate cultures, memory ability might be more in demand. Thus, it was

J. P. DRS

50

suggested that cultural preferences for a specific mode of information processing could exist, and should be recognized in comparing SES or ethnic groups. ACKNOWLEDGMENT A major part of my research on cognitive abilities reported in this chapter was supported by a grant from Canada Council, Ottawa. I am grateful to Dr. Bruce Ryan who read most of the manuscript critically. REFERENCES Ambrose, A. (Ed.) Stimulation in ear& infancy. New York Academic Press, 1969. Baratz. J . C. A bi-dialectical task for determining language proficiency in economically disadvantaged Negro children. Child Development, 1969,40, 889-901. Baroda University: Annual report of departments of Biochemistry and Foods and Nutrition. Baroda, India, 1966. Bereiter, C. Genetics and educability: Educational implications of the Jensen debate. In J. Hellmuth (Ed.), Disadvantaged child. Vol. 3. New York: Brunner Mazel, 1970. Bereiter, C., & Engelman, J. 0. Teaching Disadvantaged children in the preschool. Englewood Cliffs, N. J.: Prentice-Hall, 1966. Bernstein, B. Social structure, language and learning. Educational Research, 1961.3, 163-176. Birch, H. G., & Belmont, L. Auditory-visual integration in normal and retarded readers. American Journal of Orthopsychiatry, 1964, 36, 852-861. Birch, H. G., & Gussow, J. D. Disadvantaged children. New York: Grune & Stratton, 1970. Blishen, B. R., Jones, F. E., Naegele, K. D., & Porter, J. Canadian society. Toronto: Macrnillan, 1965. Bloom, B. Stability and change in human characteristics. New York Wiley, 1964. Bortner, M., & Birch, H. G. Cognitive capacity and cognitive competence. American Journal of Mental Deficiency, 1970, 14, 735-744. Bruner, J. S . The relevance of education. New York: Norton, 1971. Bruner, J. S., Olver, R. R., & Greenfield, P. M. Studies in cognitive growth. New York: Wiley, 1966. Cattell. R. B. Abilities their structure. growth and action. Boston: Houghton, 1971. Cole, M., & Bruner, J. S. Cultural differences and inferences about psychological processes. American Psychologist. 1971, 26. 867-876. Cole, M., Gay, J., Glick, J. A., & Sharp, D. W. The cultural context of learning and thinking. New York Basic Books, 1971. Coleman, J. S. Equality of educational opportunity. Washington, D.C.: U.S. Department ofHealth, Education, and Welfare, 1966. Crandall, V. C., Kratkovsky. W., & Crandall, V. J. Children’s beliefs in their own control of reinforcements in intellectual academic achievement situations. Child Development, 1965, 36,91-109. Cravioto, J., Gaona, C. E., & Birch, H. G. Early malnutrition and auditory-visual integration in school age children. Journal of Special Education, 1967,2, 75-82. Cromwell, R. L. A social learning approach to mental retardation. In N. R. Ellis (Ed.), Handbook of mental deficiency. New York: McGraw-Hill, 1963. Dart, F. E., & Pradhan, P. L. Cross-cultural teaching of Science. Science, 1967, 155,649-656. Das, J. P. Some correlates of verbal conditioning. Psychological Studies, 1961, 6 , 30-35.

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Das, J. P. Relation between semantic satiation and verbal conditioning. British Journal of Psychology, 1966, 57. 87-9 I. Das, J. P. Changes in Stroop-Test responses as a function of mental age. British Journal of Social Clinical Psychology, 1970, 9, 68-73. Das. J. P. Cultural deprivation: Euphemism & essence. Journal of Educational Thought. 1971, 5, 80-89. Das, J. P. Patterns of cognitive ability in normal and retarded children. American Journalof Mental Deficiency. 1972.71, 6-12. Das, J. P., Jachuck, K., & Panda, T. P. Caste, cultural deprivation and cognitive growth. In H. C. Haywood (Ed.), Social-cultural aspects ofmenral retardation. New York: Appleton, 1970. Denenberg, V. H. (Ed.) Education of the infant and young child, New York: Academic Press, 1970. Deutsch, M., and associates. The disadvantaged child. New York Basic Books, 1967. Dyer, P. B. The effects of environmental variables on the academic achievement of elementary school children in Trinidad. Unpublished doctoral dissertation, University of Alberta, 1967. Eysenck, H. J. Dimensions ofpersonality. London: Routledge & Kegan Paul, 1947. Eysenck, H. J . Experiments in personality. Vols. I & 11. London: Routledge & Kegan Paul, 1960. Farnham-Diggory, S. Cognitive synthesis in negro and white children, Monographs ofthe Societyfor Research in Child Development, 1970, 35 (2, Whole No. 135). Feuerstein, R. A dynamic approach to the causation, prevention, and alleviation of retarded performance. In H. C. Haywood (Ed.), Social-cultural aspects of mental retardation, New York: Appleton, 1970. Pp. 341-377. Feuerstein, R., & Hamburger, M. A proposal to study the process of redevelopment in several groups of deprived early adolescents in both residential and non-residential settings. Unpublished Report, The Youth-Aliyah Department of the Jewish Agency, Jerusalem, November 1965. Fowler, W. The effect of early stimulation in the emergence of cognitive processes. In R. D. Hess & R. M. Bear (Eds.), Early education, Chicago: Aldine, 1968. Pp. 9-36. Collin, E. S. Conditions that facilitate or impede cognitive theory and for education. In R. D. Hess & R. M. Bear (Eds.), Early education, Chicago: Aldine, 1968. Pp. 53-62. Gray, S . W. Intervention with mothers and young children: The focal endeavor of a research and training program. In H. C. Haywood (Ed.), Social cultural aspects of mental retardation. New York: Appleton, 1970. Pp. 508-519. Gray. S. W.. Klaus. R. A.. Miller J. 0.. & Forrester, B. J. Beforefirst grade. New York: Teachers College, Columbia University, Bureau of Publications, 1966. Guinagh, B. J . An experimental study of basic learning ability and intelligence in low-socioeconomic status children. Child development. 1971, 42, 27-36. Harrell, R. F. Woodyard. E., & Gates, A. 1. The effects of mother's diets on the intelligence of offspring. New York Teachers College, Columbia University, Bureau of Publications, 1955. Haywood, H. C., & Tapp, J. T. Experience and the development of adaptive behavior. In N. R. Ellis (Ed.), International review of research in mental retardation. Vol. 1. New York Academic Press, 1966. Hebb, D. 0. The organization ofbehavior. New York: Wiley, 1949. Hess, R. D., & Shipman, V. C. Maternal influences upon early learning: The cognitive environments of urban pre-school children. In R. D. Hess & R. M. Bear (Eds.), Earb education, Chicago: Aldine, 1968. Pp. 91-104. Hunt, J. McV. Intelligence and experience. New York Ronald Press, 1961.

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Ilg, F. L., & Ames, L. School readiness. New York Harper, 1964. Jensen, A. R. How much can we boost I.Q. and scholastic achievement? Harvard Educational Review, 1969, 39, 1-123. (a) Jensen, A. R. Reducing the heredity-environment uncertainty. Harvard Educational Review, 1969, 39,449-483. (b) Jensen, A. R. A theory of primary and secondary familial mental retardation. In N. R. Ellis (Ed.), International review of research in mental retardation. Vol. 4. New York: Academic Press, 1970. Pp. 33-100. Jensen, A. R. A two-factor theory of familial mental retardation. Paper presented at the 4th International Congress of Human Genetics, Paris, September 1971. Jensen, A. R. Genetics. educability. and subpopulation direrences. London: Methuen, 1972, Jensen, A. R., & Rohwer, W. D. An experimental analysis of learning abilities in culturally disadvantaged children. Final Report, 1970, OEO Project No. 2404, US. Office of Economic Opportunity. Kagan, J. On class differences and early development. In V. H. Denenberg (Ed.), Education of the infant and young child. New York Academic Press, 1970. Kohlberg, L. Early education: A cognitive-developmental view. child Development, 1968, 39, 1013-1062.

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Lawton. D. Social class, language and education. London: Routledge & Kegan Paul, 1968. Lenneberg, E. H. On explaining language. Science, 1969. 164, 635-643. Lloyd, D. F., & Pidgeon, D. A. An investigation into the effects of coaching on non-verbal test material with European, Indian, and African Children. British Journal of Educational Psychology, 1961, 32, 145-151. Lorenz, K. Z . King Solomon’s ring. New York Cromwell. 1952. Luria, A. R. The role of speech in the regulation of normal and abnormal behaviour. New York: Liveright, 1961. Luria, A. R. The mentally retarded child. New York Macmillan, 1963. Luria, A. R. Higher cortical functions in man. New York Basic Books, 1966. (a) Luria, A. R. Human brain andpsychologicalprocess. New York Harper, 1966. (b) Luria, A. R. The origin and cerebral organization of man’s conscious action. Proceedings of the Nineteenth International Congress of Psychology, 1971, 19, 37-52. MacArthur, R. S., & Elley, W. B. The reduction of socio-economic bias in intelligence testing. British Journal of Educational Psychology, 1963, 33, 107-1 19. Manson, W. A. Early deprivation in biological perspective. In V. H. Denenberg (Ed.), Education of the infant andyoung child. New York Academic Press, 1970, Pp. 28-50. Miller, J. 0. Cultural deprivation and its modification: Effects of intervention. In H. C. Haywood (Ed.), Social cultural aspects of mental retardation. New York Appleton, 1970. Pp. 451-489. OConnor, N., & Das, J. P. Lability in schizophrenia. British Journal of Psychology, 1959, 50, 334-337.

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Rafalski, H., & Mackiewicz, M. An epidemiological study of physical growth of children in rural districts of Poland. In N. S. Scrimshaw & J. E. Gordon (Eds.) Malnutrition. Learning, and Behavior. Cambridge, Mass.: MIT Press, 1968. Riessman, F. The culturally deprived child. New York Harper, 1962. Rotter, J. B. Generalized expectancies for internal versus external control of reinforcement. Psychological Monographs, 1966, 80. I , Schmidt, W. H. 0. School & intelligence. International Review of Education, 1960,6,416-432. Schmidt, W. H. 0. Socio-economic status, schooling, intelligence, and scholastic progress in a community in which education is not yet compulsory. Paedogogica Europaea, 1966,6, 275-289.

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Stereotyped Acts1 ALFRED A. BAUMEISTER UNIVERSITY OF ALABAMA, UNIVERSITY. ALABAMA

AND

REX FOREHAND UNIVERSITY OF GEORGIA, ATHENS, GEORGIA

I.

.................................................................. ................................................. Research Strategies ................ Correlational Studies .......................................... Intervention Studies .......................................... A . Noncontingent Stimuli: Increase ................. B. Noncontingent Stimuli: Decrease .......................................... C. Contingent Stimuli ......................................... D. Drugs .. ................. Conclusions .................................................................. References ........................................................... Introduction

11. Theoretical Formulations

111. IV. V.

VI.

55 57 62 64 69 69 76 80 89 90 92

I. INTRODUCTION

Stereotyped acts are among the most pervasive characteristics observed in the behavior of moderately to profoundly retarded individuals, particularly those residing in institutions. Indeed, the very frequency and intensity !Preparation of this manuscript and the authors' research reported herein were supported, in part, by grants from the University of Alabama Research Council and Public Health Service Grant No. MH 20992. The authors are indebted to Dr. Gershon Berkson for his very helpful comments in the preparation of this manuscript. This is not to say that Dr. Berkson will agree with all the conclusions we reach, but he certainly made us think about them. 55

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of these behaviors pose critical problems for the clinician, for the first step to meaningful behavior programming obviously involves the control or elimination of these high-frequency and, apparently, maladaptive responses. Aside from their clinical implications, stereotyped mannerisms present some interesting theoretical and empirical questions, as, for example: What is their genesis? What variables control their frequency? Do the various stereotypes develop from the same circumstances? What adaptive function, if any, do these behaviors serve? Although much of the stereotypy literature deals with the mentally retarded, we should emphasize that stereotyped mannerisms are frequently seen in other types of abnormal individuals. In fact, descriptive clinical labels such as “severely retarded” and “autistic” probably are not very useful distinctions when it comes to understanding behavioral stereotypy. Some schizophrenic, or autistic, children engage almost constantly in repetitious responding. Repetitious motor behaviors are also common in blind individuals. In addition, atypical stereotypy can also be produced in animals. Of particular interest to the present discussion is the well-established finding that isolation rearing of chimpanzees and some other subhuman primates almost invariably produces stereotypy, often strikingly similar to repetitious acts observed in humans. In general terms, stereotypy refers to highly consistent and repetitious motor or posturing behaviors, the adaptive consequences of which, if any, are not immediately apparent. Among deviant individuals it usually is not difficult to identify behaviors that reasonably sophisticated observers would agree are “stereotyped.” Indeed, these behaviors are often the most immediately striking characteristic of many retarded, autistic, and blind individuals. However, we should stress that stereotyped behaviors are not discontinuous along dimensions of adaptiveness, deviancy, severity, and frequency. For example, some mating and nest-building behaviors of certain species of animals could be construed as “stereotyped.” Even among normal humans various behaviors often occur that fit the general description given above. Human infants typically display a variety of stereotyped movements, including rocking and digit sucking. There probably are very few males among us who have not studied the rhythmic leg-swinging behavior of the seated, mini-skirted coed. Nail-biting and hair-twirling are other behaviors that can be observed frequently among normal persons. Obviously, if the concept of stereotypy is to have clinical utility, it should encompass behaviors that are excessive, atypical, and maladaptive. On the other hand, from the explanatory and theoretical viewpoints, it probably would not be productive to classify such behaviors rigidly as either desirable or undesirable. Indeed, it may be more meaningful to think in terms of continua from mild to severe, from typical to atypical, from adaptive to maladaptive, and from desirable to undesirable.

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For our purposes here we shall define stereotypy as repetitious, topographically invariant motor behaviors or action sequencies in which reinforcement is not specified or is noncontingent and the performance of which is regarded as pathological. This is similar to the “clinical meaning” suggested by Schroeder (1970). Such a definition is sufficientlybroad to include the variety of stereotypes that commonly occur in abnormal populations. Among retardates, schizophrenics, and isolated-reared chimpanzees, such behaviors as body rocking, head rolling, complex hand movements, and head banging are the most frequently occurring forms of stereotypy. Body rocking consists of the rhythmic sway of the torso from front to back. Head rolling is usually seen as side-to-side movements of the head in a rhythmic fashion. Stereotyped hand movements typically involve either holding the hand at arm’s length and staring at the fingers as they wave back and forth, or flicking a finger close to the eye. Head banging, which is one of the most obviously serious stereotypes, includes repeated and rhythmic blows of the head against a surface. Other common stereotypes include eye poking, body twirling, pill rolling, face slapping, arm banging, object spinning, unusual limb posturing, and digit sucking. The very frequency of occurrence of stereotypy by retardates and other abnormal individuals has attracted considerable research attention. The pathological nature of these behaviors is obviously of great concern to clinicians. Not only are some stereotyped acts explicitly harmful to the individual, but, in general, their occurrence is associated with reduced level of interaction with the environment (Berkson & Mason, 1964b;Lovaas, Litrownik, & Mann, 1971). Thus, most of the research effort in this area has been directed toward means of decelerating stereotypic movements. Furthermore, the presence of such movements across several abnormal populations has encouraged some more theoretically oriented research endeavors. Similarity of stereotyped behaviors in divergent populations offers the opportunity for the discovery of principles which apply to these abnormalities, independent of a particular diagnostic label. These principles, in turn, may tell us something about the origin of such behaviors. Possibly, the functional mechanisms are fundamentally similar. II. THEORETICAL FORMULATIONS

A number of theories have been advanced to account for stereotyped mannerisms. One may say at the outset that none of these views can be supported to the exclusion of the others. Moreover, most theoretical positions in this area have not been very rigorously formulated and it is, therefore, difficult to devise meaningful tests of such theories. By and large, “explanations” of stereotyped behaviors are impressionistic in nature. At one level or another, they all make some “sense.” We shall quickly present

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an overview of these theoretical views at this point. The research literature which bears upon these theories is presented in subsequent sections. One general notion is that stereotyped behavior is an expression of tension, discomfort, or unsatisfied needs (Brody, 1960; Gerard, 1957; Ilg & Ames, 1955; Kaufman & Levitt, 1965). Lourie (1949) concluded that the most widespread function of rhythmic movements is to express and relieve anxiety and tension. Similarly, Mahler ( 1945) suggested that stereotyped behaviors are releases for anxiety. Repetitious acts have also been attributed to the occurrence of ungratified demands (Kubie, 1941). Along these lines, Klaber and Butterfield (1968) have suggested that body rocking in an institutional ward is directly related to feelings of tension, anxiety, and discomfort. Accordingly, they have proposed that body rocking might be a useful measure of institutional effectiveness. A related construct, arousal, has been proposed by Berkson and Mason (1964a) to account for stereotypy observed in isolated-reared chimpanzees. They find that repetitious movements are more prominent if the chimpanzee is disturbed or excited. The arousal interpretation of stereotypy has received the most systematic and careful analysis, primarily by Berkson and his associates. The present authors have, in a series of studies, implicatedfrustrution in relation to stereotyped movements. This notion holds that stereotypy is a learned instrumental behavior. Conditions of nonreinforcement in situations where the subject is expecting reward or where rewards are programmed on an irregular basis are aversive and lead, in turn, to performance of high probability instrumental behaviors. Stereotypy is viewed as a generalized response expression to all frustrating contingencies. Another view is that a certain level of stimulation is optimal for the organism, and that when this “homeostatic” condition is altered the individual will engage in compensatory behaviors. According to Leuba (1959, the concept of optimal stimulation means that “The organism tends to acquire those reactions which, when overall stimulation is low, are accompanied by increasing stimulation; and when overall stimulation is high, those which are accompanied by decreasing stimulation [p. 291.” Because of the high degree of monotony that usually characterizes the environments in which stereotyped movements are observed, many investigators have considered stereotyped behaviors as serving self-stimulatory functions. Guess (1966), for example, has suggested that defective organisms, due to their limited response repertoires, are not adequately responsive to or stimulated by their environments. Thus, primitive self-stimulating activities occur. Berkson and Mason (1964a) have proposed that stereotyped behavior is maintained because it provides self-stimulation through kinesthetic and vestibular channels (Berkson & Mason, 1964a). A similar view, expressed by Cleland and Clark (1966), relates stereotyped movements to impaired neural

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mechanisms which result in diminished quantity and quality of sensory input. Assuming that children require an optimal level of stimulation through motor activity and/or environmental variation, Levy (1944) explained stereotypy as the result of either restraint or monotony. Numerous other investigators (Berkson & Davenport, 1962; Davenport & Menzel, 1963; Kulka, Fry, & Goldstein, 1960; Lourie, 1959; Mason & Green, 1962) have come to essentially the same conclusion. While most of those favoring a stimulation interpretation of stereotypy have construed such behaviors as functionally self-stimulating, an alternative view is that stereotypy serves a filtering or stimulus reduction function. Working with a group of autistic children, all ofwhomdemonstrated stereotyped movements, Hutt and Hutt (1965) attributed these behaviors to chronically high levels of nonspecific activity in the ascending reticular system. They state: “. . . it is probable that stereotyped behaviors originate in high-drive states as displacement activities, and in effect block further sensory input relating to the arousing function [p. 31 ,” Their function, thus, is to prevent arousal from reaching critical limits. I n a somewhat different vein, Stone (1964) proposed that stereotypy may serve as a form of sensory stimulation which produces an alteration in the state of consciousness and leads to sleep. In this view, the functional significance of stereotyped behaviors is that they decrease arousal. Stone found that the occurrence of rocking in three blind retarded children was associated with EEG changes that are similar to those which accompany normal dozing. Another hypothesis that has some theoretical commonality with the stimulus induction notion suggests a need or drive for movement. With several species of animals, for instance, it has been demonstrated that incidence of stereotypy is related to cage size (e.g., Keiper, 1969). Levy (1944) has observed stereotyped behaviors in normal children confined to cribs because of illness. The assumption hereis that movement restraint will eventually produce stereotyped activities. This is a view shaped by Kulka etal. (1 960) who have suggested a kinesthetic drive in infants. Several studies have been reported within this context. Most of these formulations clearly share a common emphasis on organismic factors. They imply that stereotyped movements are reflexive activities regulated within the central nervous and/or sensory system. The controlling conditions for the appearance of this behavior are placed primarily within the organism. Berkson (1967) has best articulated this view: “For the most part the stimuli which initiate, guide and reward stereotyped behaviors have their origin within the organism performing the act. . . . this means that the stimulus-response organization of most stereotyped behaviors is to a great degree enclosed within the individual . . . [p. 851.’’ And, in anotherplace, he says “Most stereotyped acts are organized without important reference to

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the environment [p. 921 .” I n this view, environmental variables assume a secondary role to organismic factors in the production of such behavior in that the individual more or less automatically adjusts his level of stereotypy in relation to gross stimulus change. Actually, this distinction must be construed in terms of relative emphases. Berkson himself, in fact, points out that perhaps a fruitful way to study the mechanisms that underlie stereotypes is to focus on those “few behaviors” whose organization obviously includes the environment. Certainly, it is clear that environmental factors do influence the development and maintenance of stereotyped activity. At the same time, these events must obviously be mediated within the central nervous system. Perhaps another way of stating the issue is as to whether there is something “wrong” with the environment or whether something is intrinsically “wrong” with the individual. Both the tension and self-stimulation hypotheses are open to the criticism of conceptual circularity. Typically, research procedures employed as ostensible tests of these theories fail to include or otherwise allude to any external criteria which would permit independent determination as to whether a variable is, in fact, a tension-inducing agent. A variable is defined as a tension-arouser only if it increases stereotypy; subsequently, stereotyped behavior is explained as an expression of tension. Similarly, no independent operation is available to determine whether an individual is receiving an adequate level of stimulation. If he engages in repetitious movements, an inadequate level of stimulation is inferred; subsequently, stereotypy is postulated to be a form of self-stimulation. Such reasoning is, of course, tautological. Only in the case of the frustration hypothesis has there been a consistent and clear-cut effort to define frustration transituationally. I n this regard, however, it should be noted that some of the variables viewed as “arousers” by Berkson and others have, in other contexts, been tied to both antecedent and consequent defining operations. For example, food deprivation and changes in ambient sound level have a variety of behavioral and physiological concomitants, many of which are reflected in what is often regarded as increased “drive.” In this sense, the arousal interpretation of stereotypy may not be entirely circular. Nevertheless, at the same time, we should like to see direct evidence that the variables referred to as “arousing” have marked drive-inducing effects on the individuals who exhibit high levels of stereotypy. I n regard to the self-stimulation and tension notions, there is little transituational evidence that enables us to escape the circularity in any sense. Recently, several investigators have reversed the relative emphasis of organismic and environmental variables. According to this view, stereotypy is more an instrumental and less a reflexive behavior. Hollis( 1968a)demon-

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strated that stereotyped rocking movements in retardates function as operants and can be brought under control of their consequences. Similarly, Baumeister and Forehand (1972) and Mulhern and Baumeister (1969) have demonstrated that repetitious rocking in retardates obeys some principles of learning. In a number of studies (e.g., Lovaas & Simmons, 1969; Peterson & Peterson, 1968; Tate & Baroff, 1966; Wolf, Risley, & Mees, 1964), stereotyped head banging has been controlled by the application of reinforcement procedures. Spradlin and Girardeau (1966) have speculated that stereotypies, particularly body rocking and head rolling, are superstitious behaviors that are developed and maintained by reinforcement. Among normal persons these are responses, e.g., rocking-chair movements, that occur under tight stimulus control. In an impoverished institutional environment, body rocking and head rolling are highly probable behaviors due to a generally impoverished environment. If noncontingent reinforcement, such as lunch, occurs when the individual is rocking or head rolling, such stereotyped behavior is more probable the next time he is hungry. As the frequency and rate of stereotyped movements increase, there is a concomitant increase in the probability that reinforcement stimuli will occur in the presence of such behavior. Some experimental evidence in general support of this view has recently been reported by Hollis (1971). Others (e.g., Ferster, 1968) have argued that stereotyped acts, particularly the self-destructive variety, are maintained by social stimuli. It is difficult for adults to ignore instances of these behaviors. Such responses thus become functional in that they enable the child to control the behaviors of other people. However, it should be stressed that, while rate of stereotyped movements can be affected by programming contingencies and that these behaviors may be amenable to stimulus control, such facts in themselves are not sufficient to prove that such behaviors were originally learned. Moreoever, the demonstration that people can be taught to rock (Hollis, 1968a) does not necessarily mean that others rock because they learned to do so. We know, for example, that heart rate can be brought under stimulus control, to some extent, by contingent reinforcement. It would be absurd to insist on this basis, however, that the genesis of heart action lies in learning. These, then, represent the major theoretical approaches that have been proposed to account for stereotypy. Obviously, we are dealing here with some overlapping constructs. Possibly, the most obvious distinction relates to the role assigned to instrumental learning in the production and/or maintenance of stereotyped movements. This seems to be a matter of emphasis.

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A . A . Baumeister and R. Forehand Ill. RESEARCH STRATEGIES

Most investigators have assumed that the various forms of repetitious movements are only different manifestations of common underlying processes. As a result, the various stereotyped acts have often been studied as a single class of behaviors, independent of the particular form(head rolling, body rocking, hand movements, head banging) manifested. However, Berkson (1967), among others, has expressed the view that the various forms of stereotypy probably do not fit into one category, at least with respect to their maintaining conditions. Some research evidence (Berkson & Mason, 1964a, 1964b; Kaufman & Levitt, 1965; Lovaas et al., 1971) has supported this contention, suggesting the need to study each form of stereotypy individually. Although a number of studies have been reported in which there is a clear attempt to manipulate stereotyped behaviors, much of the literature in this area is largely descriptive. Included in this latter category is an array of reports dealing with (a) incidence of stereotypy in various populations, (b) relationship of stereotypy to other subject characteristics, (c) comparative frequencies of various stereotypes, and (d) onset and duration of these behaviors. While this type of information is undoubtedly of great value, particularly in an area in which little is known and in which a number of definitional problems remain unresolved, it is the manipulative study that ultimately yields the best understanding of the circumstances under which these behaviors develop and are maintained. Our review, therefore, will stress studies in which there has been a systematic attempt to alter rates of stereotyped movements. Another distinction, although somewhat arbitrary, can be made between laboratory and clinical studies. Laboratory research has been concerned primarily with body rocking. There are a number of reasons for this emphasis. First, the rocking stereotype is the most commonly observed. Second, it is, superficially at least, the most topographically invariant between subjects. Also, the apparent rhythmical nature of the rocking stereotype seems to hold some important theoretical implications. Finally, body rocking is probably the easiest of the various stereotypes to record, both from the point of view of automation and reliability. Clinical studies, on the other hand, have tended to focus more on those behaviors that are selfinjurious. This emphasis is not difficult to understand. A number of techniques have been employed t o measure stereotypy. One of the first involved a simple checklist procedure. If one or more stereotyped acts occur during a specified interval, a check mark is recorded. This obviously must be regarded as a crude level of measurement. More recently, investigators have developed measures based on rate of responding, partic-

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ularly with respect to body rocking and head banging. These rate measures are obtained by counting frequencies of the behavior within very brief intervals of time. Also, several types of automatic recording devices have been used to supplement the direct visual observation method. For example, in our own research, we have employed an ultrasonic motion detector to record rocking. Hollis (1968a) developed a hinged back seat which, when moved, breaks a photo beam. An apparatus that seems to possess many advantages for recording body rocks has recently been described by Stevens (197 1). Briefly, this device consists of a mercury switch attached to the subject’s shoulder. The switch fires at an angle of less than 5 degrees. Although it is true that the growing amount of experimental research in this area has been accompanied by increasingly sophisticated methods of data collection and tighter experimental design, one would still have to say that the level of precision achieved has not been sufficient to resolve some important theoretical issues. Of particular relevance here is the body-rocking stereotype. The unit of behavior usually considered is simply the “rock,” a movement forward, then backward. Rate measures are typically taken by averaging responses over some interval of time. But this is still a fairly gross level of measurement. It tells us nothing about the topography ofthe behavior-its temporal characteristics, amplitude, or form. Clearly, overall measures of rate reflect the operation of a number of parameters including duration of the rock, pauses between rocks, pauses within rocks, bursts of rocks, and pauses between bursts. Moreover, simple direct observation of subjects indicates that there is considerable variability among rockers with respect to various specific parameters of the response. Each subject appears to have his own unique rocking rhythm. Amplitudes, rates, densities, and consistency are all factors inherent in individual differences in body-rocking topography. We consider it important, with respect to certain theoretical issues, to ask which of these specific attributes are affected by either experimental or natural variations in the environment. It is not always enough to show that overall rates can be influenced. For instance, differential reinforcement procedures may affect pauses between rocks or pauses between bursts of rocks. Another possibility is that the character of the body rock itself is affected in terms of amplitude, duration, or pauses. We tend to assume an invariant topography of rocking for a particular individual, but this assumption never really has been empirically verified. Recently, Maris (197 I) developed a mechanical recording device, the “rockometer,” capable of translating each body rock into a waveform. Through a system of levers the gross forward and backward movements of the subject are converted into horizontal movements of a pen across moving

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paper, A string, passing through a series of guides and pulleys, is attached to a lever on the recorder at one end and to the seated subject at the other end. The line is pinned to an elastic tape that passes around the subject’s chest. Although the device can be adjusted to accommodate wide variations in amplitude, Maris calibrated it so that a 6 in. forward movement produces a 2.4 cm excursion of the pen. A paper speed of 1.7 cm/second is sufficient to separate reliably various components ofthe response. A clutch is attached to the paper puller so that samples of rocking behavior may be conveniently taken. Although the rockometer needs some further technical refinements, it is capable of producing individually distinctive and reliable records of rocking movements. Figure 1 presents samples of the records of three subjects. These subjects show marked individual differences in the topography of their rocking responses; however, the high degree of reliability within a subject is worthy of note. Moreover, there is considerable consistency between sessions. IV. CORRELATIONAL STUDIES

Institutionalization is prominently associated with the incidence of stereotyped movements. All of the various stereotypes appear to occur with relatively high frequency among retardates living in institutions. It is, of course,

Subject 5

Day 4

Day 3

Subject 6

Day 1

Doy 3

FIG. 1. Representative Rockometer records from Maris (1971). Data are presented here for three subjects on 2 days. Each cycle in the record represents a single body rock.

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not possible to state unequivocally which is the cause and which is the effect. Nevertheless, the common assumption, and one that has some empirical support (Provence & Lipton, 1962), is that the sterility of many institutional environments, if not the ultimate source of stereotyped behaviors, is at least a proximal cause. It has been proposed, in fact, that frequency and rate of stereotypy can be used as a valid gauge of program effectiveness (Klaber & Butterfield, 1968). At least two systematic efforts have been made to study the distribution of stereotyped behaviors among institutionalized subjects. The first such study was reported by Berkson and Davenport (1962) who randomly selected for observation 71 retarded males from six different cottages within a state institution. Using a checklist technique with observation periods of 100 seconds, Berkson and Davenport attempted to group behaviors into three major categories: (a) self-manipulate, (b) manipulate environment, and (c) stereotypy. N o distinctions were made among the various kinds of stereotypes. Approximately two-thirds of the sample engaged in some form of stereotypy. However, a great deal of variability was observed with respect to frequency, intensity, and consistency of these behaviors. Some small but perhaps theoretically significant correlations were also reported by Berkson and Davenport. Both age and length of institutionalization were positively correlated with frequency of stereotypy; IQ, on the other hand, showed a negative correlation. In addition, the more stereotypy an individual displayed, the less likely he was to manipulate his environment and the more likely he was to manipulate self. Finally, blind subjects, on the average, displayed more stereotyped movements than sighted subjects. All of these correlations have, by and large, been confirmed by other investigators. Although the Berkson and Davenport study revealed, in general terms, the incidence of stereotyped movements among institutionalized retardates, no effort was made to distinguish among the various kinds of stereotyped behaviors. In an effort to specify more precisely the nature and extent ofthe various stereotypies, Kaufman and Levitt (1965) recorded frequencies of body rocking, head rolling, and hand waving among 83 moderately to profoundly retarded residents of an institution. These particular behaviors seem to be the most commonly observed stereotypes. A time sampling procedure was employed in which the occurrence of each of these behaviors was recorded during six intervals over a 7-hour period. Again, a large proportion of these patients exhibited stereotyped motor responses. Of the total sample 69, 63, and 57% were observed, at one time or another, to engage in body rocking, head rolling, and hand waving, respectively. However, correlations between these various behaviors were low, suggesting that an individual tends to specialize in only one form of stereotypy. Among the more interesting observations reported by Kaufman and Levitt

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was that two of these behaviors, body rocking and head rolling, varied systematically with time of the day. Rates were relatively low in the morning (9-10 A.M.) and in the early afternoon (2-3 P.M.). Just before lunch and in midafternoon rates of both behaviors, but body rocking in particular, increased markedly. These variations may be related to institutional routine including such events as feeding and shift changes of personnel. Berkson and Mason ( 1964a) also reported that frequencies of stereotypic behaviors in chimpanzees were positively correlated with level of food deprivation. It should be noted that Hollis (in press) failed to find this relationship with six retarded children. Hollis, however, did not measure stereotypy in a “freefield” situation. There is some direct evidence suggesting that the gross variable of institutionalization is associated with the incidence, intensity, and variety of stereotyped movements. Kaufman (1967) compared institutional and noninstitutional moderately to profoundly retarded subjects with respect to three major categories of behaviors: (a) stereotyped movements, (b) social responses, and (c) manipulations of the environment. The noninstitutional retardates were on the institution waiting list for admission and were matched with the institutional subjects for age and general functional level. The major finding was that institutionalized retardates exhibited more stereotyped movements and fewer social responses than their “home” counterparts. Although this evidence is suggestive concerning the effects of institutionalization, it cannot be taken as conclusive. It does not seem likely that purely chance or irrelevant factors operated to determine who would and who would not be institutionalized. Indeed, the basis for institutionalization, other things such as age and ability held constant, may be a high rate of stereotypy coupled with a particularly low level of social behavior. One of the usual concomitants of stereotyped behavior found in institutional wards is a generally low level of responsiveness of the individual to his environment. H e often seems oblivious to the world about him. Even when the stereotypy focuses upon some external object, such as a piece of cloth, interaction with other features of the normal ward environment is typically diminished. Perhaps we may regard these behaviors as a form of “escape” from a world wanting in variety and richness of stimulation. Whatever its reason, this kind of autistic withdrawal effect has been clearly verified by Berkson (1964) who has shown that stereotypers not only tend to interact less with their environment than nonstereotypers, but also that the former move around the ward area less. For purposes of this review, we are including the self-destructive behaviors among the stereotypies. These, too, seem to occur with high frequency among institutionalized individuals. Although no formal studies of the inci-

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dence of self-destructive acts have been conducted with retarded individuals, casual observation makes it clear that these behaviors occur with sufficient frequency among severely retarded patients to be considered a major therapeutic problem. Within a group of institutionalized schizophrenic children, Green (1967) found that about 40% exhibited self-destructive behaviors. The frequency of these acts is probably somewhat lower among retardates. On the other hand, it is probably also true that a retarded individual who is self-destructive is more likely to be labeled as “disturbed,” i.e., schizophrenic. Although rates and frequencies of stereotyped acts are particularly high among institutionalized individuals, as we have already observed, such acts also occur among nonretarded and noninstitutionalized individuals as well. For example, Lourie ( 1949) reported that 15-20% of apediatric clinic population had, at one time or another, exhibited body rocking, body swaying, or head banging. He estimated that the incidence of these behaviors in private pediatric practice is about 10%. In the majority of these cases, the stereotyped behaviors are transitory, typically persisting for only a short period of time. Only rarely do these behaviors assume chronic dimensions among the typical pediatric population. Stereotyped behaviors are particularly frequent among blind children as well. In fact, so common is the occurrence of these behaviors in this population that they are often referred to as “blindisms.” Berkson and Devenport (1962) and Guess (1966) have found that stereotypy occurs more frequently among blind than among sighted retardates. A number of interpretations involving stimulus deprivation, CNS damage, and emotional disturbance have been made concerning this relationship. However, there is some evidence that blindness, in and of itself, is not the causative factor, at least among subhuman primates (G. Berkson, unpublished results, 1972; Berkson & Karrer, 1968). Of special significance for theoretical issues concerning the origin of stereotyped behaviors are questions related to their timing and their developmental sequence. Many of the behavior patterns that we term as abnormally stereotyped when they occur in older individuals are clearly present in the behavioral repertoire of the normal infants. Several investigators have reported on the incidence of stereotypy among infants. Shentoub and Soulairac (1967) longitudinally followed a group of 300 infants for periods of 9 months to 6 years. They found that between 11 and 17% displayed some form of selfmutilative behavior. The highest frequencies were observed between ages of 9-18 months. By the time the subjects were 5 years old, these behaviors had virtually disappeared. Head banging was observed by Delissavoy (1962) among 15.2% of infants between 19 and 32 months. The average age of onset of head banging was 8 months, terminating at about 36 months. A considerably smaller incidence was reported by Kravitz, Rosenthal, Teplitz, Murphy,

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and Lesser( 1960),who examined a large sample of 1168 normal infants. They found evidence of head banging in only 3.6% of their subjects. However, the developmental course of this behavior was very similar to that reported by Delissavoy. Again, the average age of onset was 8 months, with an average duration of about 17 months. Kravitzet al. also observed head banging in the siblings of about 20% of the head bangers in their sample. One of the most extensive and systematic developmental studies of rhythmic behavior patterns in infancy is one recently reported by Kravitz and Boehm (1971). Their study is of particular interest here because they followed the development of a variety of rhythmic behaviors in normal, low birth weight, and mongoloid babies. In all, their samples included 340 normal infants, 79 infants with low Apgar scores and neonatal disease, 12 babies with cerebral palsy, and 22 cases of mongolism. Data were obtained with respect to age of onset, frequency, and sequence of the following behavior patterns: hand sucking, foot kicking, lip biting, body rocking, toe sucking, head rolling, head banging, and tooth grinding, The various sucking patterns and the kicking and body rocking responses appeared early (before 12 months) in almost all of the normal infants (percentages ranged from 83.4 to 100.0). About 10% of the normal babies displayed the head-rolling response. Head banging was observed in 7%. In both cases, the median age of onset was more than '12 months. The retarded subjects were delayed with respect to all rhythmic behaviors except head rolling and head banging. Those subjects with low Apgar scores were slow to exhibit the hand-sucking response. We may conclude on the basis of these longitudinal investigations that a variety of rhythmic motor patterns accompany normal human development during infancy. Indeed, one may conjecture as to the ultimate effects of constraint on the appearance and production of these behaviors. Although a number of workers have regarded these rhythmic acts as essential to the normal development of motor, social, and learning skills, we actually have little direct evidence to support this view. Be this as it may, the regularity, frequency, and sequential development of such repetitious motor patterns certainly leads us to take the position that each of these behaviors is, in some way or another, essential to normal growth. Only certain of the stereotypes, including head rolling and head banging, appear to be atypical at any point in development. These, in turn, may be indicative of disorganization in accommodation to the environment. It is probably reasonable to conclude that stereotyped mannerisms also occur very early in the life of mentally atypical individuals. For example, Green (1967) reported that 92% of later head bangers had done so in infancy. Head banging is virtually absent among intellectually average children after the period of infancy (Escalona, 1968). The difference seems to be that some

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children do not “grow out” of such behaviors. Something maintains high rates of stereotypy in these individuals. One explanation is that some individuals are reared in circumstances that discourage the development of alternative behaviors, perhaps due to the lack of adequate stimulation or to the absence of appropriate models. Another possibility is that these behaviors are maintained because the consequences they produce continue as reliable functional reinforcers. I t would not be difficult, for example, to imagine a situation in which head banging is consistently followed by social reinforcement. V. INTERVENTION STUDIES

A variety of circumstances have been found to produce changes in stereotyped behavior of retardates, autistic children, and isolated-reared primates. For purposes of convenience we have grouped these factors into four major categories: noncontingent variables that increase stereotypy; noncontingent variables that decrease repetitious movements; contingent stimulation; and drugs. When we speak of “noncontingent” variables, we do nothing more than admit that we have no idea as to what behaviors are being reinforced by which variables. They may very well be under stimulus control, but we cannot specify the contingencies. A. Noncontingent Stimuli: Increase

A wide variety of stimuli have been identified which, when presented noncontingently, are associated with increased rates of stereotypy. Increments in ambient noise level consistently produce increased rates of rocking. Levitt and Kaufman (1969, conceptualizing intense noise as an arouser, presented four levels of ambient sound (51,70, 85, and 100 dB) to 32 institutionalized body-rocking retardates. A positive relationship between rate of rocking and sound intensity level was observed. A number of subjects, who under typical conditions exhibited little stereotypy, did rock during intense sound. White (84dB) and varied noise (music, voices, banging sounds, etc.) were presented by Forehand and Baumeister (1970b) to eight severely retarded patients who displayed high rates of rocking under typical ward conditions. Relative to base line conditions, both noise conditions produced significantly faster rates of rocking. Hollis (1968a) found that a high noise level of 95dB increased the rate of rocking movements in three out of four retardates who had a history of stereotypy. Apparently the effect is to increaseaverage rates of rocking. Maris (l97l), using the rockometer described previously, reported that it is the average and not the momentary rate that is affected. In other words, noise may affect the likelihood of occurrence or the length

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of time the subject engages in this behavior, but does not influence the rate at which the behavior occurs once it is in progress. The subject continues to rock according to his own rhythm. Noise also has a facilitatory effect on the stereotypy of isolated-reared chimpanzees. In an experiment with isolation-reared chimpanzees, Berkson, Mason, and Saxon (1963) displayed an inaccessible moving object that produced a grinding noise. Incidence of rocking was significantly higher under this condition than when a stationary, silent object was presented. A clearcut interpretation of this result is obviously precluded owing to the fact that object movement occurred concomitantly with the noise condition. A followup experiment was conducted by Berkson and Mason (1964a). Nine isolation-reared chimpanzees were exposed to three levels of white noise (68, 74, and 82 dB), a 74 dB buzzer, and a no-noise condition. As with retarded humans, rocking accelerated with increasing noise level. These effects were attributed to heightened arousal associated with increased noise. Food deprivation also appears to be related to the production of stereotyped behavior. Berkson and Mason (1964a) recorded incidence of rocking in nine isolated-reared chimpanzees during 0, 24, and 48 hours of food deprivation. Significant increments in repetitious rocking were observed with increasing levels of deprivation. These investigators interpreted their finding as evidence for the hypothesis that rocking rate and arousal level are functionally related. Tangential support for this hypothesis has been offered by Kaufman and Levitt (1965) who, as we noted earlier, found that time of day is correlated with body rocking in humans. Incidence of body rocking among 83 institutionalized retardates was found to be low immediately after breakfast and increased until just before lunch. However, in the afternoon a similar increase was not found prior to dinner; in fact, the incidence of rocking at this time was the same as immediately following breakfast. Kaufman and Levitt also viewed their findings as support for the arousal or tension hypothesis. Nevertheless, other interpretations, including learning (e.g., scalloping during a fixed interval), appear to be just as plausible. Moreover, as Hollis (1968a) has pointed out, owing to the short deprivation periods and the equivocal results, the effects of food deprivation on rocking of retardates is still uncertain. Additionally, it should be noted that in both of these studies (Berkson & Mason, 1964a; Kaufman & Levitt, 1965) other stereotypes, such as complex hand movements and repetitious head movements, did not vary with length of deprivation. As we noted earlier, the concept offrustration has been implicated theoretically with respect to stereotypy. Mulhern and Baumeister (1969), while attempting to reinforce differentially low rates of rocking, observed an unexpected but substantial increase in rocking rates of two severely retarded

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patients when these subjects were abruptly exposed to a DRL schedule. Mulhern and Baumeister tentatively attributed this increase to frustration deriving from irregular provision of reinforcement. A recent series of experiments by the authors has provided more explicit evidence that interference with goal-directed behavior produces an increment in rate of stereotyped rocking. The definition of frustration employed here is essentially operationally identical to that proposed by Brown (1961). Working with three groups of institutionalized severe retardates, Forehand and Baumeister (197la) obtained prefrustration (base line) measures over a period of days on the subjects. Two groups were then shaped to respond on a lever under a fixed ratio (FR)3 schedule for candy reinforcement. A third group served as a control for habituation of rocking over sessions. After the shaping procedures were completed, one of the two experimental groups received 24 reinforcements on each of4 days followed by four sessions in which the goal-directed response, lever pressing, was blocked by removal of the lever, Subsequent to shaping, the second experimental group was simply exposed, for 4 days, to the situation in which the lever was removed. Relative to the prefrustration measure, the rate of rocking was significantly higher following interference with goal-directed behavior. Furthermore, the increase in stereotypy was directly related to the number of reinforcements prior to the blocking of the goal-oriented response. The major results of this study are graphically summarized in Fig. 2. In a similar vein, one might predict that extinction of a goal-directed response should lead to a temporary increment in rocking (Baumeister &

‘O

t I

Prefrustration

Frustration

FIG. 2 Rates of body rocking during prefrustration frustration periods. GI represents subjects given extended lever-pulling training prior to frustration. Subjects in G2 were given only limited lever-pulling training, while G3 subjects served as controls with no leverpulling training. Solid line = direct observation; dashed line = motion detector. (From Forehand & Baumeister, 1971a.)

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Forehand, 1971). Such an operation conforms to Amsel’s definition (1958) of frustration: nonreward of a previously rewarded behavior. After taking a prefrustration measure, Baumeister and Forehand shaped their subjects to respond on a lever for candy on an FR 2 schedule. Subsequently, each subject received 20 reinforcements on each of 3 days. During the next four sessions subjects were given I5 reinforcements, followed by an extinction phase during which no additional reinforcements for lever responding were provided. The average rate of rocking during extinction was significantly greater than during the prefrustration period, indicating that nonreward of instrumental behavior is associated with an increase in stereotyped rocking. However, it should be added that while this effect was statistically significant, in relative terms the increased rocking subsequent to lever extinction was not particularly marked. I n an attempt to duplicate a more “realistic” frustrating situation, a third study focused on the effects of frustration on rocking in the institutional ward (Forehand & Baumeister, 1970~).Frustration was defined as the sudden withdrawal of an edible substance before consumption was completed. After prefrustration measures of rocking were taken, a partially consumed edible was abruptly withdrawn (frustration), and subsequent rocking was recorded. Under these conditions, stereotyped rocking increased significantly relative to the base line. In sum, these experiments seem to indicate that the operations typically employed to induce experimental frustration do significantly affect stereotyped body rocking of retardates. Stereotypy may be ageneralized response tendency to frustrating situations. Another general conclusion which may be drawn from these results is that frustration of an instrumental response may accelerate some other unrelated, but high probability, behavior. It is possible, of course, to construe frustration as a special case of arousal, particularly if one thinks in terms of enhanced drive. The frustration conceptualization may possibly apply to the atypical repetitious behavior of animals as well. Irregular provision of food has been shown to produce head banging in a monkey(Levison. 1970).The repetitious behavior initially developed when a cage door accidentally dropped on the animal’s head and shoulders on two separate occasions. Subsequent disruption of the regular feeding schedule resulted in head banging. Stereotyped head banging was also observed in three additional contexts: (a) disruption of the usual environment; (b) the presence of strangers; and (c) termination of interactions with the experimenter at the time cages were cleaned. Restraint and confinement also appear to produce stereotypy. After taking base line measures over a period of 3 days, Forehand and Baumeister (1970a) restrained six retarded high-rate rockers so that no rocking stereotypy could occur. Torso, arm, and hand movements were restrained. Fol-

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lowing 18 minutes of restraint, each subject was unstrapped, and subsequent rocking was immediately recorded. The procedure was then repeated with each subject so that the design consisted of base line, restraint, base line, and restraint conditions. The experiment was replicated with the same subjects for three sessions on separate days. A consistent and significant increase following each restraint period relative to the base line conditions was observed. Invigoration of the rocking response appeared to be temporary. The effect was greatest during the first few minutes following release after which the subject showed a tendency to return to his base line level of performance. These results are shown in Fig. 3. Of course, the terms “confinement” and “restraint” are relative. The procedures employed by Forehand and Baumeister represent an extreme form of restraint. However, other studies have produced evidence showing that even less extreme conditions of restraint do affect stereotyped movements. Frequencies of stereotypy by retardates during confinement in cribs and during an out-of-crib condition were compared by Warren and Burns( 1970). Toys were available under both conditions, and observations were made during the typical ward routine. Their results indicated a significantly higher incidence of the following stereotypes during in-crib time relative to out-ofcrib time: rocking, sucking, body manipulations, and head movements. Head banging occurred more often outside the crib. Subsequent observations of 18 head bangers led Warren and Burns to conclude that this behavior may be controlled by different contingencies.

W I-

40

-

30

-

z

3

a a W

v)

0‘0 c 2

U W

r 20

+-

1

1

I

I

4

2

3

4

INTERVALS

FIG 3. Rates of body rocking prior to restraint (B, and B,) and subsequent to restraint(R, and R,). Data are plotted for 4-minute intervals over within-subject replications of the experiment.

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Stimulus restricted environments, as distinguished from confinements, have also been associated with increased stereotypy. Berkson and Mason ( 1963) recorded rates of stereotyped responses of institutionalized retardates in a dayroom of an institution, a ward dining room, and in an empty and unfamiliar room. Level of stereotypy was significantly higher in the stimulusrestricted environment than in the dayroom. Berkson and Mason also observed high-rate body rockers in a dayroom, an unfamiliar cubicle, and on an outdoor playground. Less stereotypy was manifested on the playground than in the first two situations. Such findings led Berkson and Mason to postulate that the level of repetitious acts is inversely related to the extent which the environment evokes alternate activities. Furthermore, their data indicated that self-manipulation changed in the same direction as stereotypy-higher instances of each under restricting situations. These are findings that could be taken as support for the self-stimulation hypothesis. As we shall see in a later section, this evidence leads to some complex interpretations of the relationship between arousal and stereotypy. In an extension of the Berkson and Mason study (1963), Forehand and Baumeister (1971b) found that the environment effect with retarded rockers is at least partially dependent on the individual’s IQ. Rates of stereotyped rocking of “high” (20-30) and ‘‘low’’ (untestable) IQ institutionalized individuals were recorded for 3 hour periods, both in the ward setting and in a restricted environment (6 feet x 6 feet x 6 feet sound-attenuated cubicle). Body-rocking rate of high IQ retardates was higher in the restricting environment than in the ward, while the average rate of the low IQ group was not dependent upon location. There is a possible confounding present in these data in that the low IQ group showed a much higher rate of rocking on the ward than the high IQ subjects. It is conceivable that the low IQ subjects did not display increased rocking when placed in the cubicle due to the possibility that they were already rocking “to the best of their ability.” Apparently the effects of restriction are similar for subhuman primates. A number of studies that bear on this issue have been reported. In one such study, Davenport and Menzel (1963) compared the behaviors of isolationreared (21 months) chimpanzees with the behaviors of wild-born animals raised in enriched environments. Stereotypy developed in the isolationreared animals by as early as 8 months, whereas such behavior was not observed at any age among the latter subjects. In a similar study, Mason and Green (1962) compared rhesus monkeys reared in isolation for 12-23 months with animals reared with companions. The test situation was an unfamiliar room in which each animal was observed individually. The isolation-reared group displayed significantly more stereotyped movements than the companion-reared group. Similarly, Menzel, Davenport, and Rogers (l963b) found that chimpanzees raised in restricted environments engaged in stereo-

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typed behaviors with significantlygreater frequency than wild-born animals when the subjects were placed in a small test cubicle. In a related experiment, Berkson, Mason, and Saxon ( 1963) studied stereotypy of isolated-reared chimpanzees in three situations: an outdoor home cage measuring 39 feet x 57 feet; an outdoor bar cage measuring 69 inches x 72 inches x 85 inches; and an enclosed cubicle measuring 81 inches x 59 inches x 78 inches with no possibility for seeing out. In the cubicle, bar-cage, and home-cage repetitious behavior occurred in 85%, SO%, and 15% of the observation intervals, respectively. The authors proposed that the high level of stereotypy in the cage was the result of increased arousal or excitation. Furthermore, they suggested that the performance of stereotyped movements is also dependent upon the extent to which the subject is able to perform alternative activities. If other activities are restricted, then stereotypy seems to be adirect function of arousal. Isolation rearing also appears to cause a diminution of exploratory behaviors among chimpanzees. Menzel, Davenport, and Rogers( 1963a) tested wild-born and isolation-reared subjects in an unfamiliar room in which nine objects were present. While the isolation-reared subjects continued to engage in their stereotyped mannerisms, the wild-born animals actively explored the objects. Apparently, the emergence of stereotyped behaviors in subhuman primates is related to the age at which separation from the mother occurs. Berkson (1968) removed 25 crabeating macaques from their mothers at ages 0, 1, 2, 4, or 6 months. These animals were observed both in their home cages and in novel environments. One of the main findings was that all groups exhibited abnormal stereotypies, and that these effects were particularly pronounced in subjects separated early. Furthermore, the behaviors of isolation-reared animals were normal in a familiar setting. Differences become apparent when the subjects were placed in strange surroundings. Finally, the abnormal stereotyped behaviors seem to be prolonged and excessive manifestations of normal patterns that occur when the animal is reared with his mother. We may tentatively conclude from the isolation-rearing studies that stereotyped patterns are produced by a thwarting or frustration of normal parent-child interactions. Most of these behaviors have normal homologs but due to the absence of social stimulation and the lack of proper cues, they become conditioned to inappropriate stimulus variations in the environment. Studies with humans in this regard are obviously difficult to conduct, and what data we have are conflicting. Provence and Lipton (1962) observed a high incidence of rocking among institutionalized babies. On the other hand, in their well-known study of institutional babies, Spitz and Wolf (1949) found little evidence of response stereotypy.

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Although studies of the effects of isolation and restriction have been carried out under a diverse set of circumstances, some general conclusions do seem possible. Direct physical restraint, isolation rearing, confinement, and various kinds of limiting situations support the notion that a restricted environment is associated with increased body rocking. This conclusion appears to contain some theoretical as well as practical implications. Berkson (1967) has, on the basis of this evidence, concluded that, in chimpanzees at least, rocking is related to the animals’ general arousal level. At the same time, he points out that this is a complex relationship involving not only arousal, but the availability of alternative activities. While, indeed, there does seem to be considerable evidence favoring an arousal interpretation of stereotypy, we are inclined to wonder about the specific nature of this interaction. Do all the various stimuli described as arousers produce the same mediating processes? What are the mechanisms by which increased arousal is translated into increased stereotypy? What is the role of learning? How do other high probability behaviors influence the stereotypy arousal relationship? These and other questions must receive some more definitive answers before arousal offers much more than a general description of the factors related to behavioral stereotypy. The social environment, too, apparently makes a difference with respect to the frequency of rocking behaviors. Although we might expect, on the basis of some other studies, that social privation would lead to an increase in stereotyped movements, such does not seem to be the case, at least among severely retarded humans. The presence of other patients has been associated with increased stereotyped rocking of institutional retardates (Baumeister & Forehand, 1970). Subjects were observed to rock less in a room by themselves than they were in the company of other patients. Although we initially made the assumption that rocking might have an imitative component to it, this does not seem to be the case. Increased rocking was observed whether or not the “company” included rockers or nonrockers. 8 . Noncontingent Stimuli: Decrease

There are several classes of stimuli which have been related to reduction in stereotyped behavior. Most of these seem, in one way or another, to provide the subject with something else to do. Enriched visual stimulation seems to produce such an effect. Using a small (6 feet x 6 feet x 6 feet) empty cubicle as a test environment, Forehand and Baumeister (1970b) considered the relationship between visual stimulation and repetitious rocking of severe retardates. Presentation of either colored pictures of objects or a white light significantly reduced rocking relative to base line conditions. Furthermore, the colored pictures were associated with a greater reduction

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in stereotypy than the white light, indicating that the content of visual stimulation is important. A reasonable assumption is that visual stimulation gives the subject something to do other than rock. However, Maris (1971) was unable to show a reduction in rocking under conditions of enhanced visual stimulation, although his was a direct replication of the Forehand and Baumeister study. A more reliable finding is that stereotyped behaviors seem to decrease when the subject is given the opportunity to engage motorically in alternate activities. A number of studies have been reported which deal directly with this issue. I n some instances an alternative response is deliberately shaped by the experimenter; in other cases, activities are simply made available to the subject. A n example of the former is given by Hollis( 1968a)who studied the effect of ball pulling for candy reinforcement on rocking behavior of retardates. When ball pulling was reinforced, it became a high probability behavior, and rocking rarely occurred. Hollis concluded that repetitious rocking can be prevented by providing an alternate activity that produces programmed consequences. A similar finding was reported by Forehand and Baumeister (1971a). Although the data are not entirely consistent, it does appear that, under some conditions, programmed alternate activity affects other kinds of stereotyped movements as well. Stereotyped head banging was reduced in an autistic child by reinforcing (praise) an alternate activity, clapping and singing to music (Lovaas, Freitag, Gold, & Kassorla, 1965a). Relative to sessions in which no social approval was given for clapping and singing, the reinforcement sessions were associated with more appropriate music behavior and less head banging. A replication with another alternate activity, bar pressing, was also reported by these authors. Praise contingent on bar pressing was associated with a lower level of stereotyped head banging than during a no-praise condition. In one of the first studies directed toward this issue, Davenport and Berkson (1963) recorded incidence of stereotypy of severe retardates under four object conditions (rubber ball, rubber doll, plastic ball containing marbles, and wooden block) and a no-object condition. The subjects were not objectively reinforced for manipulating these objects. Presentation of objects by an experimenter to the retardates resulted in significantly reduced rates of stereotypy. Furthermore, incidence of repetitious movements was significantly less with the most manipulated (preferred) object than with the least preferred object. These findings were generally confirmed by Guess and Rutherford ( 1 967) who reported that blind retardates exhibited less stereotypy when given objects to manipulate. Levy (1944) has also noted that hospitalized children displayed stereotyped behaviors when deprived of toys, but these behaviors ceased when toys were returned. The presence of

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toys also seems t o reduce some of the stereotyped activities of crib-confined retardates as well (Warren & Burns, 1970). There may be a social reinforcement factor implicated in these findings. Berkson and Mason (1964b) found that, relative to a control condition (noobjects and no-experimenter condition), handing objects to retardates and talking to them resulted in a significant reduction of stereotypy. However, the mere availability of objects to manipulate when no experimenter was present did not decrease stereotypy relative to the control condition. Indeed, under some conditions increased complexity ofthe environment may lead to an increase in stereotyped movements (Hutt & Hutt, 1965). Furthermore, Berkson and Mason observed that body rockers engage in more object manipulation and demonstrate greater reduction of stereotypy than retardates who display complex hand movements. This finding supports the notion that different forms of stereotypy, i.e., rocking, hand movements, and head banging, are not a homogeneous class of behaviors; that they may arise from different circumstances: that they may be maintained by different classes of events, and that they may differ with respect to functional significance. It should be noted that many of these studies were undertaken in situations largely unfamiliar to the subjects. We have already seen that stereotypy is sometimes affected by simply placing the subject in unfamiliar surroundings. There may be some complex behavioral interactions involving the extent to which the subject is familiar with his environment and the social cues provided in the novel situation. Moseley, Faust, and Reardon (1970) examined the effects of objects on stereotypy of retardates in an environment familiar to the subjects. Stereotypy was recorded in the usual ward situation under no-object, objects-only (ball, rubber elephant, plastic duck, and plastic blocks), and social conditions. During the “objects-only” condition the toys were simply placed near the subject, while under the “social” condition the experimenter handed the toys to the child and talked to him. Relative to the absence of objects, the social condition significantly decreased incidence of stereotypy. The objects-only situation failed to reduce repetitious movements significantly. This would seem to confirm the finding of Berkson and Mason (1964b) mentioned previously while at the same time pointing up the importance of social stimuli. Another way to look at the relationship between stereotypy and object manipulation is to consider the level of interaction with the environment during periods of stereotypy as opposed to periods when the subject is not engaging in these movements. In their study, Berkson and Mason (1964b) reported that stereotypers displayed less object manipulation than nonstereotypers only during those intervals in which the former were actually performing stereotyped movements. In intervals in which stereotypy did not occur, the amount of object manipulation of stereotyperswas not signifi-

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cantly different from that of nonstereotypers. A similar finding has been reported with four mute autistic children who frequently engaged in stereotypy (Lovaas et al., 1971). The children were initially trained to approach a dispenser for candy reinforcement at the sound of a tone. The interval between tone onset and approach behavior, labeled as response latency, was recorded both during periods in which stereotypy was present and when it was not. Instrumental response latencies were significantly greater during intervals in which stereotyped behaviors occurred, indicating that such behavior interferes with the occurrence of the approach response-a response that was more adaptive within the experimental context. With increased training in responding to the tone, response latencies during stereotype intervals decreased. Lovass and his associates speculated that the lowered response latencies with continued training reflected the diminishing control of the reinforcers generated by stereotypy and the increasing control of the candy reinforcement. An additional finding of interest was that each subject’s level of stereotyped behavior was greater during satiated than nonsatiated sessions. This is not what one might expect based on an arousal interpretation of stereotyped movements. Again, this is an area in which there appears to be some generality from human to animal behavior. The presence of manipulable objects has also been found to decrease stereotypy of isolation-reared chimpanzees. Menzel (1963) presented 75 objects to two such chimpanzees. Stereotyped acts were found to be reciprocally related to object grasping-the latter increased and the former decreased over a 25-day period. Menzel et al. (1963b) compared isolation-reared and wild-born chimpanzees under conditions where fixed, movable, and free objects were present. The animals reared in isolation rarely engaged in object manipulation and displayed frequent stereotyped movements. In contrast, the feral chimpanzees actively contacted and grasped the objects and rarely displayed repetitious movements. Apparently direct social stimuli may affect stereotyped movements of chimps in the same manner as object manipulation. Berkson and Mason (l964a) exposed nine isolated-reared chimpanzees to each of three conditions: a passive experimenter; an experimenter who groomed (light touch with forefingers on body) the animal; and an experimenter who tickled the animal on his belly and side. Tickling was associated with significantly less rocking than the passive-experimenter condition. Again, it is possible to conclude that the opportunity to engage in an alternate activity reduces repetitious rocking. However, it is of considerable interest to note that other stereotyped behaviors (repetitious head movements, limb postures, eye poking, and digit sucking) were not affected the same way as rocking. In fact, tickling and grooming were associated with significantly more of these stereotyped movements than the passive-experimenter condition.

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In summary, alternate activity is associated with reduced stereotypy under two conditions: (a) programmed consequences for engaging in the alternate activity (even though the subject could engage in the stereotyped pattern); and (b) active handling of objects to the individual. While engaged in their stereotyped movements, retardates tend not to react spontaneously to the presence of novel objects. This is especially true of complex hand movements. C. Contingent Stimuli

Apparently, the rate of stereotyped movements, particularly body rocking and head banging, can be controlled by the contingent presentation of certain classes of stimuli. These include both positive and aversive events. Consider, first, the effects of shock. Contingent electric shock seems to have pronounced inhibitory consequences. Lovaas, Schaeffer, and Simmons (1965b) reported a study in which shock was given to two schizophrenic children contingent upon stereotyped and tantrum behaviors. The two children were initially observed to spend 7040% of the day engaging in body rocking and hand movements. A shock of 1-second duration was delivered whenever self-stimulatory or aggressive behavior occurred. During two preshock sessions, repetitious movements and tantrums occurred between 65 and 85% of the time for both children. During shock sessions, the behaviors decreased immediately to zero and remained there for 11 months. A slight increase occurred after 11 months, but one noncontingent shock immediately eliminated the behaviors again. The effect of contingent shock on body rocking of three severely retarded high-rate stereotypers was studied by Baumeister and Forehand (1972) in a more formal experimental sense. Each full body rock was immediately followed by .5 seconds of a constant current shock of 1.75 MA RMS. During base line, the subjects displayed fairly high rates of rocking, averaging 22.7, 35.3, and 35.9 rocks per minute. During contingent shock, their means dropped to 1.6, 5 . I , and . I rocks per minute; this decrement in rocking occurring during the first session and remaining low throughout subsequent sessions. This is evidence for conditioned avoidance learning. The results of this experiment are displayed in Fig. 4. Having demonstrated that shock produces a rapid and profound decrement in rocking does not mean that these effects will generalize to another context or that they will persist over long periods of time. Baumeister and Forehand recorded body rocks for each subject before and after the shock sessions in an adjacent waiting room, similar to the experimental room. Rates in the adjacent room did not change over the course of the experiment, even when the shock apparatus was attached to the subject. One may con-

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clude, therefore, that the inhibitory effects of shock are highly situationspecific, and that suppression does not readily generalize. On the other hand, as in the study reported by Lovaas et al. (1965b), the duration of the effect was substantial. Only one of the original three subjects was available for testing after a 10-month period. His rate of rocking in the waiting room was equivalent to that observed 10 months earlier. However, when seated in the experimental room, this subject did not rock. As one might expect, shock has been applied more frequently to those stereotyped behaviors that are obviously self-injurious. A number of studies, more clinical than experimental in nature, have been reported in which shock has been used as a punishment for stereotyped acts. Stereotypic head banging and face slapping were eliminated in a psychotic, retarded child by the contingent administration of shock (Tate & Baroff, 1966). Preshock rates of the stereotyped behaviors were recorded. Then each incident of head banging and face slapping was immediately followed by a brief shock. The stereotyped behaviors decreased from 5.0 per minute during preshock to .06 per minute during the first shock session. During subsequent days, shock was sometimes administered immediately after the occurrence of the stereotyped act and sometimes delayed 30 seconds. These procedures were followed for 167 days, during the last 20 of which no head banging or face slapping was emitted.

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Shock has also been used by Lovaas and Simmons( 1969) to suppress head banging and face slapping of three retarded children. Basal rates of these behaviors exceeded 100/10 minutes on the average. In each case, shock presented contingently resulted in an immediate termination of the target behaviors. The suppression was found to be situation specific: shock in one situation or by one person did not generalize to other situations or persons. This finding is in accord with that noted previously by Baumeister and Forehand. However, Lovaas and Simmons also demonstrated with one subject that a formerly neutral stimulus (the word “no”), after being paired with shock, was subsequently capable of suppressing self-destructive behavior when presented contingently. Under certain well-defined and controlled conditions, the aversive properties of shock obviously do generalize to other stimuli. Finally, Lovaas and Simmons observed some unanticipated but desirable side effects of shock treatment. Attending to an adult increased and whining decreased concomitantly with the reduction of head banging and face slapping. Taken collectively, then, these data indicate shock produces immediate suppression of both body rocking and head banging, at least in the context in which the shock was applied. Moreover, these effects seem to be very durable. Contingent shouting at and shaking of the subject has also been demonstrated to inhibit rocking. Accordingly, we classify these events as punishing. Risley (1968) worked with a 6 year-old girl who exhibited several autistic behaviors, including body rocking. This behavior occurred on the average of 25% of each session for 107 20-30-minute sessions (base line). Treatment consisted of the experimenter shouting “Stop that !” seizing the child by the upper arm, and shaking her whenever she began rocking. This contingency reduced time spent rocking from 25% to less than 1% per session. The frequency of rocking episodes also decreased steadily from .94/ minute in the first treatment session to .03/minute in the tenth treatment session. A similar effect was also observed by Baumeister and Forehand (1972). A contingent verbal command (“Stop rocking!”) was used with six body rocking retardates who had IQs between 20 and 30 and who could respond to simple verbal stimuli. The contingent shouts significantly reduced the rate of rocking relative to base line conditions. Data were obtained for each subject under two base line periods and two treatment periods. During base line I , treatment I, base line 11, and treatment 11, the mean rates of rocking were 17.0,0.4, 9.7, and 0.2, respectively. In order to evaluate the possibility of a “startle” effect, four additional subjects were run under conditions where each body rock produced a .5 second 75dB white noise. No systematic change in rates of rocking was observed over base line and treatment sessions. The human voice apparently had some distinctive punishing properties for these subjects.

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Other types of punishers have been used in efforts to modify self-injurious behavior. Banks and Locke (1966) worked with three profoundly retarded blind children, all of whom exhibited high rates of eyegouging. Punishment was administered by pulling the subject’s hair contingent upon the eyegouging response. This treatment was applied during a 10-minute session for each of three successive days. As in the case of shock, the hair-pulling treatment produced a rapid suppression of eye gouging. However, this effect was transient in that by the day following each punishment sessi on response rates had returned to near their preexperimental levels. Unlike electric shock, the hair-pulling treatment appears to produce only temporary suppression effects. A more unusual approach, involving a music distortion technique, has recently been reported by Greene, Hoats, and Hornick (1970). Their subject was a blind severely retarded male, 15 years of age, who displayed disruptive body rocking in a classroom setting. During each conditioning session the subject was allowed to listen to his favorite music. However, when he rocked, the music was markedly distorted by the experimenter. A large number of sessions were run, including continuous reinforcement (CRF) conditioning, extinction, reconditioning on CRF, and partial reinforcement. The music distortion contingency resulted in an immediate and substantial suppression of rocking. During the extinction phase, rate of rocking returned to its free operant level. Reconditioning brought the rate down again. Partial reinforcement, eventually reaching a 1:3 ratio, was sufficient to maintain the low rate of stereotypy. While, admittedly an Nof 1 is not sufficient to enable us to make many generalizations, the control achieved by Greene et al. is quite remarkable. Certainly, theirs is a procedure warranting further attention. In addition, this study suggests that a wide range of stimuli may have direct suppressive effects on stereotyped acts. Some of these stimuli may be less offensive to normal sensibilities than electric shock. The time-out procedure may also be a promising technique for controlling head-banging behaviors. Hamilton, Stephens, and Allen (1967) terminated repetitious head and back banging in a severely retarded institutionalized female by placing her in a time-out area for 30 minutes contingent on each occurrence of the behavior. From a basal rate of approximately 20 episodes per minute, the time-out procedures quickly eliminated the target behaviors. Over the following 9-month interval, no stereotyped head or back banging occurred. Concomitantly with the elimination of the stereotypic behavior the child interacted more productively with her environment and began to participate in ward activities. A similar effect has been reported by Wolf, Risley, and Mees (1964) for an autistic child who engaged in face slapping and head banging. In this case, the repetitious self-destructive behaviors were immediately followed by confining the child in his room until the behav-

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ior terminated. After a 2 1/2-month period, the behaviors had not reappeared except on infrequent occasions. Evidently, even brief periods of time-out can be effective under some circumstances. Tate and Baroff (1966) were able to reduce rates of head banging and face slapping in an autistic child by the contingent withdrawal of physical contact for 3 seconds. During base line, physical contact was not withdrawn. The rate per minute of stereotyped self-destructive behavior was 6.6 during base line I, .1 during treatment I, 3.3 during base line 11, and 1 .O during treatment 11, indicating that withdrawal of physical contact was quickly effective in reducing frequencies of the target behaviors. Time-out from other kinds of stimuli may have similar effects. Mattos (1969) was able to reduce facial tics and digit sucking in a severely retarded child by making time-out from music contingent on these behaviors. Why should time-out procedures be effective? Actually, the time-out contingency probably involves a number of consequences. One possibility is that time-out or isolation functions as a punishment. Another possibility is that some reinforcing stimuli are withdrawn by the procedure. The study by Tate and Baroff (1966) implies that the latter may more likely be the important component. If one regards self-destructive acts as learned social behaviors then one should predict: (a) a decrease in rate if the social consequences are withheld; and (b) an increase in rate if social reinforcement occurs consequent to this behavior. A study reported by Lovaas and Simmons (1969) seems to support these inferences. Two children who engaged in high rates of self-destructive acts were isolated daily for 11/2-hour periods. In each case the extinction procedures produced a gradual drop in self-destructive behavior. Moreover, as is often the case with extinction of an instrumental response, the rate was particularly high during the initial extinction sessions. On the other side of the coin, when social attention was contingently directed to the self-destructive acts, their rates increased markedly. The results presented by Lovaas and Simmons provide strong evidence that stereotyped self-destructive acts are maintained by social consequences. This does not, of course, prove that these behaviors were originally learned. In any case, Lovaas and Simmons do not recommend extinction procedures for the treatment of self-mutilative behaviors. Not only does it take a long time for such behaviors to drop off, but there is also that initial increment to worry about. In view of these considerations, they seem to favor contingent electric shock as a more effective means for controlling self-destructive behavior. An alternative to both extinction and shock is to reinforce some other behavior that is incompatible with the undesirable one. Mulhern and Baumeister (1969) attempted to reduce rate of body rocking in two severe

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retardates by reinforcing the response of sitting still for a prescribed period. Discriminative stimuli were provided to inform the subjects that no reinforcement would be forthcoming while they engaged in rocking. Relative to base line, a gradual reduction in rocking was observed over sessions. The major results of this study are presented in Fig. 5. Similarly, Hollis (1968a) found that differential reinforcement of low rates (DRL) reduced the rocking of a retardate from approximately 80 responsesper minute to about 4 responses per minute. Stereotypes other than rocking apparently can also be controlled by D R L procedures. Rate of head banging and face slapping was reduced by Peterson and Peterson (1968) in a retardate by making positive reinforcement contingent upon reduction in rate of the behavior. After a base line period, food was initially made contingent upon a 3-5-second interval in which no self-destructive responses were emitted. If the behaviors did occur, food was removed until a 10-second interval free of head banging and face slap-

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FIG. 5. These curves show body-rocking responses for two subjects plotted for total number of responses over sessions and for rates per minute. “Base” represents free responding in the experimental sessions. Other points represent responding under conditions designed to reinforce low rates of rocking. Subject A = 0 - 0 ; subject B = 0 - 0 . (From Mulhern & Baumeister, 1969, Experiment 11.)

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ping lapsed. The stereotyped behavior was reduced from 26.6 responses per minute during base line to 14.2 responses per minute during treatment. A second treatment was undertaken to decrease the behavior further. Again, nonoccurrence of the head banging and face slapping for 3-5 seconds was reinforced with food. However, following the occurrence of the stereotyped behavior, the subject was required to walk 12 feet to a chair. If the stereotyped behaviors did not occur during the walk, reinforcement was presented immediately. If self-destructive acts did occur, the subject, in order to receive food, had to walk from one chair to another until such acts did not occur. After over 20 sessions, there was a gradual reduction in the stereotypy until it disappeared entirely. A second base line was associated with an increase in the behavior, while another treatment period again reduced head banging and face slapping. As the investigators noted, it is impossible to separate the walking procedure from the effects of reinforcement. Similar studies with similar results have been reported (Allen & Harris, 1966; Brawley, Harris, Allen, Fleming, & Peterson, 1969). In general, one may conclude that withholding of reinforcement for the stereotyped act while at the same time reinforcing some competitive behavior is aworkable therapeutic practice. Most of these reports, however, tell us little about the nature of the stereotyped behaviors themselves. A particularly provocative study has recently been completed by Weisberg, Passman, and Russell (in press) who found that they could affect the rate of hand gesturing in two nonverbal severely retarded subjects by a combination of imitative and nonimitative procedures. These subjects were initially taught to imitate movements by an adult model, who paired the particular response to be imitated with the words “Do this.” Then, while a contrasting response continued to be imitatively reinforced, the adult demonstrated the stereotyped hand movement and said “Do not do this.” The motor prompts were gradually faded, and the verbal cues eventually became reliable discriminative stimuli for the performance or nonperformance of the stereotyped behavior. This study goes beyond the simple discovery of reinforcers for these behaviors, demonstrating that verbal stimuli can be transformed into relatively durable and reliable discriminative cues for the regulation of stereotypic movements. Some stimuli presented contingently on rocking have been found to increase that behavior. In his functional analysis of rocking behavior of retardates, Hollis ( 1968a, 1971) found that positive reinforcement (candy, cereal, and Kool-Aid) contingent on rocking significantly increased rocking rates. Relative to base line, fixed ratio (FR) and variable interval (VI) schedules of reinforcement accelerated the rate of body rocking of three retarded individuals. The FR schedule of reinforcement was found to generate a high rate of responding, typical for this particular schedule.

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Cumulative curves of rocking under the VI schedule of reinforcement were typical for that schedule-a low constant rate of responding. One subject who was not a rocker was conditioned to rock by shaping procedures. This retardate’s rocking increased from zero prior to shaping to typical VI and FR curves of responding when he was reinforced on these schedules. These are compelling data showing that rocking is susceptible to instrumental conditioning. In a related study, Hollis (in press) demonstrated that adventitious reinforcement in a “free-field” situation accelerated stereotyped responding. But, on the other hand, after base lines had been established for FR and VI responding, subsequent independent delivery of reinforcement failed to maintain base rates of responding. These are effects that might be expected if stereotypy is a learned “superstitious” behavior. Positive food reinforcement may also be effective in both shaping and increasing the rate of head banging. I n a study with two monkeys, head banging was shaped, maintained on an FR 10 schedule, brought under stimulus control, extinguished, and reestablished (Shaefer, 1970). Social attention, presented contingently upon head banging, increases the frequency of the behavior. We have already mentioned the study by Lovaas and Simmons (1969) in this regard. In another study by Lovaas and his associates (1965a), the comment “I don’t think you are bad” was delivered following each head-banging and arm-banging response in a schizophrenic child. Compared to control sessions, frequency of self-destructive behavior was systematically higher during the sessions when the experimenter commented on the head banging. In a second study by Lovaas (Lovaas & Simmons, 1969), verbal comment (“Don’t do that, Greg, everything is O.K.”) and physical contact, contingent on self-destructive head banging, increased the incidence of the behavior in a retarded child in two of the three times such consequences were introduced. With the same child playing blocks and going on a walk, contingent on head banging, increased the incidence of the repetitious self-destructive acts. Clearly, a number of alternatives are available to the clinician who wishes to reduce or eliminate stereotyped and self-injurious behavior(s). First, one may differentially reinforce some other behaviors incompatible or competitive with the unwanted response. As an alternative, one may withdraw consequences, usually social, with a view toward extinguishing the stereotyped act. Finally, the clinician may apply shock directly consequent to the stereotyped response. As we have seen, each of these therapeutic procedures may, under some circumstances, prove to be beneficial. Nevertheless, the question may be raised as to which remediative approach is the most efficacious. In a recent study reported by Corte, Wolf, and Locke( 1971), an effort was

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made to compare these various approaches. Four children were treated who exhibited a variety of self-injurious behaviors, including face slapping, head banging, hair pulling, face scratching, and finger biting. Electric shock punishment virtually eliminated these behaviors in all subjects. The extinction procedure proved to be least effective, while differential reinforcement of noninjurious behaviors produced marginally positive results. However, it should be stressed that the effects of shock punishment, as in the case of studies already cited, were very specific and discriminated. Obviously, a program designed to eliminate stereotyped movements by the application of contingent shock should incorporate systematic treatments in avariety of relevant contexts to enhance generalization. All of the various contingent-response techniques that have been attempted for the purpose of decelerating stereotyped movements seem to have their disadvantages. They either take too long, are only partially effective, do not generalize readily, produce only temporary effects, or involve procedures which may be distasteful. Another method, called Overcorrection, has recently been proposed by Foxx and Azrin (in press) as allegedly more efficient and effective for the reduction of stereotyped movements than those methods described previously. I n brief, the rationale of this method, in the case of “self-stimulatory” behaviors such as hand waving, is to require the subject to practice intensively a related but “correct” form of behavior. For example, Foxx and Azrin describe the case of a severely retarded girl who exhibited a high rate of nonfunctional head rolling. Each time the child began to head roll, the trainer would clasp the child’s head to prevent the stereotyped movement. She was then taught to move her head up, down, or straight upon verbal instruction. During the initial stages of this “Functional Movement Training,” the teacher manually guided the appropriate head movements. Manual guidance was faded out and the behavior brought under verbal control. Thus, when the child exhibited the head-rolling response she was instructed to practice intensively the other head-holding behaviors. Foxx and Azrin report four cases in which astereotyped movement was reduced to a near zero rate by these procedures. In addition to their description of a rather novel approach to the control of stereotyped movements, Foxx and Azrin also provided direct comparisons of the Overcorrection procedure with several others we have already discussed including reinforcement for competing behavior and punishment. I n general, their results show that Overcorrection was the most efficient and effective method. We regard this conclusion, however, as tentative and perhaps somewhat overdrawn. For one thing, Foxx and Azrin did not achieve the positive results with alternative methods some other investigators have observed. Secondly and more importantly, the Overcorrection procedure, it seems to us, embodies a variety of contingencies

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including ( I ) withdrawal of reinforcement for the stereotypy. (2) punishment of stereotypy, (3) restraint, (4)reinforcement of competing responses, and (5) alterations i n the social environment. It is difficult to say which of these factors, singly or in combination, produced the effects attributed to Overcorrection. In any case, this is a procedure that certainly warrants the attention of both clinicians and researchers. These various studies, taken together, suggest that some instances of stereotyped behaviors may be instrumental responses, controlled by discriminative and reinforcing stimuli, particularly social cues. Certainly in the case of self-injurious acts, it is easy to see how they might be maintained by social consequences, Of course, the demonstration that such behaviors can be accelerated or decelerated by the administration of reinforcing stimuli or that they can be discriminated does not necessarily mean that all stereotypes are operants. However, until shown otherwise, we are persuaded that learning has a great deal to do with the development and maintenance of stereotyped behaviors. The most important issue concerns identification of the “naturally” reinforcing stimuli. D. Drugs

The effects of both stimulants and tranquilizers on frequencies and rates of stereotyped acts have been studied for obvious reasons. Clearly, a large quantity of almost any drug is apt to affect behavior. The question is whether clinically meaningful amounts produce significant alterations in stereotyped behaviors. There are some theoretical implications in these drug studies as well. According to arousal interpretations of stereotypy, energizers ought to increase while tranquilizers ought to decrease stereotypy. The results of drug studies with retardates, however, are inconclusive. More consistent effects have been observed with animals. Hollis (1967) administered 2, 4, and 8 mg of dextroamphetamine to two severe retardates on different test days. The drug did not produce a significant change in rocking rate. In another study (Berkson, 1965), two levels of amphetamine (10 mg/ 100 lb and 15 mg/ 100 lb) were administered on two different treatment days. Compared to a placebo condition, the stimulant had no apparent effect on rocking and hand movements of three severe retardates who frequently demonstrated such behavior. Berkson pointed out that the lack of drug effect may have resulted from the relatively low dosage levels used. Davis. Sprague, and Werry (1969) compared rocking incidence of nine severely retarded individuals under stimulant drug (methylphenidate .44mdkg), a placebo, and no-drug conditions. Rockingdid not vary significantly under the three treatments. On the other hand, in two studies with chimpanzees, stimulants have been

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found to increase repetitious acts. The effects of amphetamine on stereotyped rocking of isolation-reared chimpanzees were tested by Berkson and Mason (1964a). The animals were initially habituated to the experimental situation. It was hypothesized that a decrease in rocking would occur with habituation, and that the administration of amphetamine would reverse the habituation effect. Two hours prior to testing, 1 mg/kg dose of Dexedrine was administered to each animal. Relative to the no-drug days, the stimulant significantly increased the incidence of stereotyped rocking. Similar results were reported by Fitz-Gerald (1964) in an investigation of the effects of amphetamine on stereotypy of isolation-reared chimpanzees. A 1 mg/ kg dosage of dextroamphetamine was administered to each animal 2 hours before testing. Repetitious movements increased significantly with the drug administration. The effects of tranquilizing drugs on rocking have also been tested. In one study a 10 mg/kg dosage of chlorpromazine (Thorazine syrum) was administered to chimpanzees 1 hour before testing (Fitz-Gerald, 1964). The drug resulted in a significant decrease in incidence of stereotypy. Chlorpromazine (Thorazine) was found by Hollis (1968b) to reduce the rocking behavior of one severe retardate. The child, a high-rate rocker, was taught to pull a ball for reinforcement. During control sessions, a high rate of rocking occurred when the ball-pulling response was placed on extinction. Under the drug condition, chlorpromazineeffectively eliminated rocking movements during the extinction phase. In a study reported by Berkson (1965), the effects of two levels of barbiturates (Seconal: 1.5 gr/100 lb; 2.0 gr/100 lb) on stereotypy of three severe retardates were evaluated. The higher level of Seconal tended to put the individuals to sleep. Relative to a placebo condition, no other barbiturate effects were observed with either dosage. Daviset a / .(1969) examined the effects of Thoridazine (1.3 mg/kg) on nine severe retardates. A record was made over three sessions of overall activity, including five stereotyped and six nonstereotyped behaviors. The tranquilizer significantly reduced stereotyped behaviors without affecting the nonstereotyped ones. In general, it seems that tranquilizers have the effect of reducing stereotypy. VI. CONCLUSIONS

Our review of the research literature leads to the conclusion that incidence of stereotyped behavior is affected by a number of variables. Noncontingent presentation of some types of stimuli, such as noise, food deprivation, and restricted environments is associated with increased stereotypy levels. Situations in which goal-directed behavior is thwarted also produce increments in stereotyped activity. Other stimuli, presented noncontingently, such as

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visual stimulation and the opportunity for alternate activity, are found to lead to a decrease in repetitious movements. Various types of contingent stimuli, including both positive and aversive events, appear to be effective in establishing, increasing, and decreasing stereotyped acts. With retardates, drugs have had variable effects, although tranquilizers seem to reduce stereotyped rocking. Drug treatment with chimpanzees has generally produced results consistent with an arousal interpretation of stereotypy. Each of the various theories that have been advanced to account for stereotypy receives support from the research findings. The arousal theory holds that stereotyped behavior will increase as drive and/or tension increases. Several types of stimuli which are typically viewed as tensionproducing agents have been associated with increased stereotypy. For example, hunger, intense sound, and frustration are regarded by some investigators (Amsel, 1958; Kaufman & Levitt, 1965, Levitt & Kaufman, 1965) as arousers or tension producers that contribute to drive level. Although there are certain inconsistencies in the literature, we must conclude that the arousal interpretation of stereotypy receives agreat deal of support. The self-stimulation theory holds that a certain level of stimulation is necessary for the organism, and stereotypy is one way to provide(or reduce) such stimulation. If, on the other hand, the environment provides ample stimulation, stereotypy, since it is no longer functional, ought to be diminished. There is some evidence favoring this interpretation as well. For example, toys, social interaction, and visual stimulation generally have been found to lead to reduced stereotypy. The decrease in rocking with the presentation of an alternate form of activity also lends some support to the selfstimulation theory of stereotypy. However, as pointed out earlier, the self-stimulation hypothesis is particularly open to the criticism of circularity. If a particular treatment fails to produce a change in the predicted direction, then one has the alternative of saying that it was the treatment and not the

Animal Crackers

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6. Reproduced with permission of National Newspaper Syndicate, Chicago, Illinois.

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theory that was at fault. In the case of the frustration studies, however, this circularity seems to have been operationally averted. The notion that stereotyped movements are operant behaviors is supported to a considerable extent. We believe that these are essentially normal behaviors that have, through an extensive conditioning process, become abnormally functional to a variety of cues. Perhaps the very act itself, cued by some powerful and reliable conditioned stimulus, ultimately becomes self-reinforcing. This point is made exceptionally well in the following cartoon. The evidence indicates such behaviors obey basic principles of learning. a. b. c. d.

stereotypy can be shaped; contingent positive reinforcement increases stereotypy rate; contingent aversive stimuli decrease rate of repetitious behavior; different schedules of reinforcement produce different rates of stereotyped acts; e. extinction decreases the rate of such behavior; and f. stereotypy can be brought under stimulus control.

On the other hand, all this does not necessarily mean that the behaviors were originally brought about by shaping, or that in the ward setting it is controlled by the same reinforcers as in the laboratory. The research evidence does not clearly support one theory while rejecting the others. However, the primary concern in most research undertakings with stereotypy has been to identify conditions and variables that are instrumental in the maintenance of the acts. Within this context, the learning theory would appear to be the most parsimonious and productive. With operant techniques, it has been demonstrated that stereotyped movements can be established, maintained at different rates, and almost totally eliminated in an experimental context in individuals with chronic histories of the behavior. Whether or not learning can account for all manifestations of stereotypy is uncertain; however, the application of such principles has demonstrated that repetitious acts can be at least partially controlled without reference to unobservable organismic variables. REFERENCES Allen, K. E., & Harris, F. R. Elimination of a child's excessive scratching by training the mother in reinforcement procedure. Behaviour Research and Therapy, 1966, 4, 79-84. Amsel, A. The roles of frustrative nonreward in noncontinuous reward situations. Psychological Bulletin, 1958. 55, 102-1 19. Banks, M., & Locke, B. J. Self-injurious stereotypes and mild punishment with retarded subjects. Parsons Research Center, Working Paper No. 123, Parsons, Kansas, 1966. Baumeister, A. A. & Forehand, R. Social facilitation of body rocking in severely retarded patients. Journal of Clinical Psychology , 1910, 26, 303-305.

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Baumeister, A. A., & Forehand, R. Effects of extinction of an instrumental response on stereotyped body rocking in severe retardates. Psychological Record, 1971, 21, 235-240. Baumeister, A. A,, & Forehand, R. Effects of contingent shock and verbal command on body rocking of retardates. Journal of Clinical Psychology, 1972, 28, 586-590. Berkson, G. Stereotyped movements of mental defectives: V. Ward behavior and its relation to an experimental task. American Journal of Mental Deficiency, 1964, 69,253-264. Berkson, G . Stereotyped movements of mental defectives VI. N o effect of amphetamine or a barbiturate. Perceptual and Motor Skills, 1965, 21, 698. Berkson, G. Abnormal stereotyped motor acts. In J. Zubin & H. F. Hunt (Eds.), Comparative psychopathology-Animal and human. New York Grune & Stratton, 1967, Pp. 76-94. Berkson, G. Development of abnormal stereotyped behaviors. Development Psychology, 1968, 1, 118-132. Berkson, G. Visual defect does not produce stereotyped movements. Unpublished manuscript, 1972. Berkson. G., & Davenport. R. K.Stereotyped movements in mental defectives: I. Initial survey. American Journal of Mental Deficiency, 1962.66, 849-852. Berkson, G., & Karrer, R. Travel vision in infant monkeys: Maturation rate and abnormal stereotyped behaviors. Developmental Psychobiology, 1968, 1, 170-174. Berkson, G., & Mason, W. Stereotyped movements of mental defectives: 111. Situation effects. American Journal of Mental Deficiency, 1963, 68, 40W12. Berkson, G., & Mason, W. Stereotyped behaviors of chimpanzees: relation to general arousal and alternative activities. Perceptual ond Motor Skills, 1964, 19, 635-652. (a) Berkson, G., & Mason, W. Stereotyped movements of mental defectives: IV. Theeffect oftoys and the character of the acts. American Journal of Mental Deficiency, 1964,68,511-524. (b), Berkson, G., Mason, W. A., & Saxon, S. V. Situation and stimulus effects on stereotyped behaviors of chimpanzees. Journal of Comparative and Physiological Psychology, 1963, 56, 786-192. Brawley, E. R., Harris, F. R., Allen, K.E., Fleming, R. S.,& Peterson, R. F. Behavior modification of an autistic child. Behavioral Science, 1969, 14, 87-97. Brody, S. Self-rocking in infancy. Journal of the American Psychoanalytic Society, 1960,8,464491. Brown. J . S. The motivation of behavior. New York: McGraw-Hill, 1961. Cleland, C. C., & Clark, C. M. Sensory deprivation and aberrant behavior among idiots. American Journal of Mental Defciency, 1966, 71, 213-225. Corte, H. E., Wolf, M.M., & Locke, B. J. A comparison of procedures for eliminating selfinjurious behavior of retarded adolescents. Journal of Applied Behavior Analysis, 1971, 4,201-210. Davenport, R. K.,& Berkson, G . Stereotyped movements of mental defectives: 11. Effects of novel objects. American Journal of Mental Deficiency, 1963,67, 879-882. Davenport, R. K.,& Menzel, E. W., Jr. Stereotyped behavior ofthe infant chimpanzee. Archives of General Psychiatry, 1963, 8, 99-104. Davis, K. V., Sprague, R. L., & Werry, J. S. Stereotyped behavior and activity level in severe retardates: The effect of drugs. American Journal of Mental Defiiency, 1969,73,721-727. Delissavoy, V. Headbanging in childhood. Child Development, 1962, 33, 43-56. Escalona, S. K. The roots of individuality. Chicago: Aldine, 1968. Ferster, C. B. Operant reinforcement of infantile autism. In S. Lesse (Ed.), An evaluationofthe results of the psychotherapies. Springfield, Ill.: Thomas, 1968. Pp. 23 1-236. FitzCerald, F. L. The effect of drugs upon stereotyped behavior in young chimpanzees. Unpublished doctoral dissertation, McGill University, 1964. Cited by Hollis (1968a). Forehand, R., & Baumeister, A. A. Body rocking and activity level as a function of prior movement restraint. American Journal of Mental Deficienq, 1970, 74, 608-610. (a)

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Forehand, R.,& Baumeister. A. A. The effect of auditory and visual stimulation of stereotyped rocking behavior and general activity of severe retardates. Journal of Clinical Psychology, 1970, 26, 426-429. (b) Forehand, R.,& Baumeister, A. A. Effect of frustration on stereotyped body rocking: Followup. Perceptual and Motor Skills, 1970, 31, 894. (c) Forehand, R., & Baumeister, A. A. Rate of stereotyped body rocking of severe retardatesas a function of frustration of goal-directed behavior. Journal of Abnormal Psychology, 197 1, 78, 35-42. (a) Forehand, R.,& Baumeister, A. A. Stereotyped body rocking asafunction ofsituation, IQ, and time. Journal of Clinical Psychology, 1971, 27, 324-326. (b) Foxx, R. M., & Azrin, N. H. The elimination of self-stimulatory behavior of autistic and retarded children by overcorrection. Journal of Applied Behavior Ana[vsis. in press. Gerard, M. The emorionally disturbed child. New York Child Welfare League ofAmerica, 1957. Green, A. H. Self-mutilation in schizophrenic children. Archives of General Psychiatry, 1967, 17, 234-244.

Greene, R. J., Hoats, D. L., & Hornick, A. J. Music distortion: A new technique for behavior modification. Psychological Record, 1970, 20, 107-109. Guess, D. The influence ofvisual and ambulation restrictions on stereotyped behavior. American Journal of Mental Defciency, 1966.70. 542-547. Guess, D., & Rutherford, G. Experimental attempts to reduce stereotyping among blind retardates. American Journal of Mental Deficiency, 1967, 71, 984-986. Hamilton, J., Stephens, L. & Allen, P. Controlling aggressive and destructive behavior in severely retarded institutionalized residents. American Journal of Mental Deficiency, 1967, 71, 852-856.

Hollis, J. H. Direct measurement of the effects of drugs and alternate activity on stereotyped behavior. Parsons Research Center, Working Paper No. 168, Parsons, Kansas, 1967. Hollis, J. H. Analysis of rocking behavior, Parsons Research Center. Working Paper No. 193, Parsons, Kansas. 1968. (a) Hollis, J. H. Chlorpromazine: Direct measurement ofdifferential behavior effect. Science, 1968. 159, 1487-1489. (b) Hollis, J. H. Body-rocking: Effects of sound and reinforcement. American Journal ofMenta1 Deficiency, 1971,75,642-644. Hollis, J. H. “Superstition”: A systematic study of independent and contingent events on human free operant responses. American Journal of Mental Deficiency, (in press). Hutt, C., & Hutt, S. Effects of environmental complexity on stereotyped behavior ofchildren. Animal Behaviour, 1965, 13, 1-4. Ilg, F. L.. & Ames, L. B. Child behavior. New York Harper, 1955. Kaufman, M. E. The effects of institutionalization on development of stereotyped and social behaviors in mental defectives. American Journal of Mental Deficiency, 1967.71, 58 1-585. Kaufman, M. E., & Levitt, H. A study of three stereotyped behaviors in institutionalized mental defectives. American Journal of Mental Deficiency, 1965, 69, 467-473. Keiper, R. R. Causal factors of stereotypes in caged birds. Animal Behavior, 1969,17,114-119. Klaber, M. M., & Butterfield, E. C. Stereotyped rocking-a measure of institution and ward effectiveness. American Journal of Mental Deficiency, 1968, 73, 13-20. Kravitz, H., & Boehm, J. J. Rhythmic habit patterns in infancy: their sequence, age of onset, and frequency. Child Development, 1971, 42, 399-413. Kravitz, H., Rosenthal, V., Teplitz, Z., Murphy, J., & Lesser, R. A study of headbanging in infants and children. Diseases of the Nervous Sysrem, 1960, 21, 203208. Kubie, L. S.The repetitive core of neurosis. Psychoanalytic Quarterly, 1941, 10, 2 S 4 3 .

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Kulka, A., Fry. C., & Goldstein. F. J. Kinesthetic needs in infancy. American Journalof Orthopsychiatry, 1960, 30, 562-571. Leuba, C. Toward some integration of learning theories: The concept of optimal stimulation. Psychological Reports. 1955. I . 27-32. Levison, C. A. The development of headbanging in a young Rhesusmonkey.American Journal of Mental Deficiency. 1970. 15, 323-328. Levitt, H., & Kaufman, M.’E. Sound induced drive and stereotyped behavior in mentaldefectives. American Journal of Mental Deficiency, 1965,69, 729-735. Levy. D. M. On the problem of movement restraint. American Journalof Orthopsychiatry. 1944. 14.64467I . Lourie. R. S. The role of rhythmic patterns in childhood. American Journal ofPsychiatty, 1959, 105,653-660. Lovaas, 0. I., Freitag, G., Gold, V. J., & Kassorla, I. C. Experimental studies in childhood schizophrenia: Analysis of self-destructive behavior. Journal of Experimental child Psychology, 1965, 2. 67-84. (a) Lovaas, 0. I., Litrownik. A,, & Mann R. Response latencies to auditory stimuli in autistic children engaged in self-stimulatory behavior. Behavior Research and Therapy, 1971, 9, 39-49. Lovaas, 0. 1.. Schaeffer, B., & Simmons J. Q . Building social behavior in autistic children by the use ofelectricshock. JournalofExperimentalResearchin Personality, 1965.1.99-109. (b) Lovaas, 0. I., & Simmons, J. Q. Manipulation of self-destruction in three retardedchildren. Journal of Applied Behavior Analysis. 1969, 2, 143-157. Mahler, M. S. Ego-psychology applied to behavior problems. In N. C. D. Lewis & B. L. Pacella (Eds.), Modern trends in child psychiatry. New York: International Universities Press, 1945. Maris, R. S. Stereotyped body-rocking in severely retarded patients: A study of rhythm and topography. Unpublished doctoral dissertation, University of Alabama, 1971. Mason, W. A,, & Green, P. C. The effects of social restriction on the behavior of rhesus monkeys: IV. Responses to a novel environment and to an alien species. Journal 01 Comparative and Physiological Psychology, 1962, 55, 363-368. Mattos, R. L. Operant control of facial ticing and finger sucking in a severely retarded child. Paper presented at the annual convention of the American Association on Mental Deficiency. San Francisco, 1969. Menzel, E. W., Jr. The effects of cumulative experience on responses to novel objects in young isolated-reared chimpanzees. Behaviour, 1963, 21, 1-12. Menzel, E. W., Jr., Davenport, R. K., & Rogers, C. M. Effectsofenvironmental restriction upon the chimpanzee’s responsiveness in novel situations. Journal of Cornpararive and Physiological Psychology, 1963, 56, 329-334. (a) Menzel, E. W., Jr., Davenport, R. K., & Rogers, C. M. Theeffectsofenvironmental restriction upon the chimpanzee’s responsiveness to objects. Journal o/ Comparative Physiological Pswhology, 1963. 56. 78-85. (b) Moseley. A.. Faust. M.. & Reardon. D. M. Effectsofsocialand nonsocialstimuli on thestereotyped behaviors of retarded children. American Journal of Mental Deficiency, 1970, 14, 809-8 1 1. Mulhern, T., & Baumeister, A . A. An experimental attempt to reduce stereotypy by reinforcement procedures. American Journal of Mental Defciency, 1969, 74, 69-74. Peterson, R. F., & Peterson, L. R. The use of positive reinforcement in the control of selfdestructive behavior in a retarded boy. Journal of Experimental Psychology, 1968, 6. 35 1-360.

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Provence, S., & Lipton, R. C. Infants in institutions. New York International Universities Press, 1962. Risley, T. The effects and side effects of punishing the autistic behaviors of a deviant child. Journal of Applied Behavior Analysis, 1968, 1, 21-34. Schroeder, S. R. Usage of stereotypy as a descriptive term. Psychological Record, 1970, 20, 337-342. Shaefer, H. H. Self-injurious behavior: Shaping headbanging in monkeys. Journal of Applied Behavior Analysis, 1970.3, 1 1 1-1 16. Shentoub, S., & Soulairac, A. L'enfant automatilateur. Cited by A. H. Green, Archives of General Psychiatry. 1967, 17, 234-244. Spitz, R. A., & Wolf, K. M. Autoeroticism. Psychoanalytic Studies of the Child. 1949,3,85-120. Spradlin, J . E., & Girardeau, F.L. The behavior of moderately and severely retarded persons. In N. R. Ellis (Ed.), International review of research in mental retardation. Vol I . New York Academic Press, 1966. Stevens, E. A. Some effects of tempo changes on stereotyped rocking movements of low-level mentally retarded subjects. American Journal of Mental Deficiency, 197 I , 76, 76-8 I . Stone, A. A. Consciousness: Altered levels in blind retarded children. Psychomatic Medicine, 1964, 26, 14-19. Tate, B. G., & Baroff, G. S. Aversive control of self-injurious behavior in a psychotic boy. Behaviour Research and Therapy, 1966,4,281-287. Warren, S. A,, & Burns, N. R. Crib confinement as a factor in repetitive and stereotyped behavior in retardates. Mental Retardation, 1970, 8, 25-29. Weisberg, P., Passman, R. H., & Russell, J. E. Modification of bizarre gestures of retardates through imitative and nonimitative reinforcement procedures. Journal of the Experimental Analysis of Behavior, (in press). Wolf, M., Risley, T., & Mees, H. Application of operant conditioning procedures to the behavior problems of an autistic child. Behaviour Research and Therapy, 1964, 1, 305-312.

Research on the Vocational Habilitation of the Retarded: The Present, The Future1 MARC W. GOLDZ CHILDREN'S RESEARCH CENTER UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN, CHAMPAIGN, ILLINOIS

A. A Social Perspective

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111. The Future

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IV. Concluding Comments ........................................................ References . . . . . . . . . . . . . . . .

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1. INTRODUCTION

The intention of this review is to describe the present status of research on the vocational habilitation of the retarded and to propose directions for future efforts. This is not intended as a review of the literature. References are used only to support statements made and to provide the reader with resources for more in-depth study. The vocational training of mentally retarded individuals presently utilizes the resources of three primary disciplines: rehabilitation, psychology, and education. Research from these I Preparation of this paper was supported by the National Institutes of Health, U.S. Public Health Service, through Grants MH 07346 and HD 05951. 'Some of the writing and secretarial work was also supported by the Department ofspecial Education, California State College at Los Angeles, for which the author is grateful.

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disciplines is discussed. Reszarch from two other sources not normally associated with rehabilitation is also discussed in terms of its potential contribution to the field. These are industrial management and industrial engineering. Throughout this paper the term field will be used where reference is to disciplines, activities, individuals, and organizations whose primary function is the habilitation of the mentally retarded. An attempt is made in this article to emphasize the importance of the relationship between principles developed in laboratory settings and the application of these principles to vocational training. For the reader who is content with existing levels of expectancy presently held by society and by professionals in the field, or who believes that we have succeeded so long as the retarded are kept busy in workshops or placed on any job, this review has little value. For those who believe that there is a substantial gap between how the retarded function vocationally, at present, and how they could function, this paper contains descriptions of what is being done and what could be done to achieve the goal of maximum opportunity for growth. Before exploring the possibilities for change, it is necessary to provide a perspective. While this volume is international in scope, the context to which this article refers is the United States, where the economic system is capitalistic, and where a surplus labor force (the unemployed) is almost always present. A. A Social Perspective

Historically, people have organized themselves to accommodate, change, or eliminate other people who are sufficiently different to call unfavorable attention to themselves (Heiny, 1971). Farber (1968) perceives such people as constituting a surplus population. In terms of work, they are either not specifically trained for existing jobs in the labor market, or they are incapable of, unwilling to, or prevented from filling such positions. He further points out that society could easily function without them. Because of the considerable energy spent on their maintenance however, they play an important organizational role by (1) requiring the generation of special institutions such as special education and vocational rehabilitation, (2) by providing an excess labor pool, and (3) by aiding in the perpetuation of social classes. The implications of Farber’s perceptions to the vocational training of the retarded are clear: some of the energies presently used for maintenance of this unproductive portion of the population should be directed toward training the retarded to somehow effectively compete in the labor market with other members of the surplus population who are not additionally stigmatized by the label “retarded.” This, of course, is the goal of research on the vocational habilitation of the retarded. Farber suggests four kinds of programming which could be used to

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facilitate the assimilation of the retarded into the mainstream of society: (1) better use of techniques for training the mentally retarded to adapt; (2) changes in family structure and environment; (3) restructuring of societal institutions and their interactions; and (4) changes in the values by which society functions. Farber (1968, and personal communication) is pessimistic about the vocational and social prognosis of the retarded in the absence of a revised modern society. The position is taken here that certain changes would greatly enhance the chances for vocational viability of the retarded, and that the nation is fast developing a technology that will allow achieving this goal within the existing value structure of contemporary society. The larger goal of complete assimilation, including independent or semi-independent living and full participation in society, is another matter. There is a great deal of activity in this country attempting to revise institutional arrangements in the direction of community residential units (e.g., Kirk, Karnes, & Kirk, 1955; Kugel & Wolfensberger, 1969). The interaction between this activity and the developmedt of a technology of instruction will certainly have an impact on society. The ultimate success of fully assimilating the retarded into society, as Farber points out, will still be dependent on the degree to which contemporary values are modified toward personal growth of all people rather than institutional efficiency. Related to the influence of the values of society there is the basic issue of societal expectancies for the retarded. The interaction of economic and industrial growth with the development of increased societal awareness has resulted in the set of perceptions which society and the social sciences presently hold regarding the retarded. The amount of national resources committed to the retarded, the kinds of programs developed and funded, and even the specific kinds of skills taught are reflections of these perceptions and interact to perpetuate existing practices and expectancies and to resist change. The large discrepancy between the kinds of lives led by the retarded in the United States and in European countries such as Sweden(Kylen, Sommarstrom, & Akesson, 1971), Holland (Dybwad, 1961), Denmark (Dolnick, 1971), and England (Williams, 1967), must be, in the main, attributed to our societal expectancies. How this country developed to its present level regarding expectancies for the retarded is not appropriate for discussion here. However, a few comments about the vocational training literature will serve to complete the perspective into which Sections I1 and 111 are intended to be placed. B. A Pedagogical Perspective

The vocational habilitation of the retarded has a long history, in terms of both service and research programs. One major criticism of virtually all of the literature, experimental and programmatic, is that it has described

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behavior of the retarded in the context of simple, menial tasks which require little training, skill, or attention, even for the retarded. No distinction has been made between performance on the simple tasks used and more complex tasks. The literature is consistent in its finding that the retarded, who are unsuccessful in competitive employment, fail because of their inability to handle the social interactions necessary to function in a work setting. Although a positive relationship has been shown between production rate and employers’ judgment of job success(Chaffin, 1969). no identified studies report failure to perform on the actual task as the reason for dismissal. The author contends that this consistent finding is an artifact of the jobs on which the retarded are placed. That is, they are placed only on thosejobs where little or no training is required to learn the necessary skills. This relates back to the inappropriate expectancies held by both professionals and the public, handed down since early work with the retarded (e.g., Delp, 1957; Tredgold, 1908), which preclude placing them on jobs that require more than minimal skill training. If expectancies are to be revised, all research findings and activities to date must be considered only within the context of performance on simple tasks. Data on production, deviant behavior, perceptualmotor behavior, attention span, and social interaction might well be influenced by the level of difficulty of the task. With very little data available where complex tasks were used, an incomplete picture of the retarded is all that is available. A second major criticism of the literature is the lack of definable training techniques. The lack of training purported here may seem surprising because of the frequency with which the term appears. When training appears throughout our literature, it almost without exception refers to exposure rather than treatment, or, it refers to placing clients on a job station where it is hoped training occurs. Training, as used in this review, refers to controlled, systematic manipulations of the environment, administered in such a way that its effect can be measured and recorded. The rigidity of this definition is, in part, a reaction to the osmotic nature of what is usually called training. Perusal of the literature reveals hundreds of descriptions of training programs which yield no evidence of specific techniques for developing vocational behavior (e.g., Affleck, 1967; Etienne & Morlock, 1971; Greenstein & Fangman, 1969; Kolstoe, 1960). Organizational structures in which development is supposed to occur, descriptions of content to be covered, and resources involved are usually reported and not the actual mechanisms which directly effect development. There is an emerging trend away from exposure and toward training. Changes are occurring across the entire range of activities embodied in the field (e.g., Burke, 1971; Prehm, 1970). The rest of this chapter explores such changes in terms of existing knowledge and new directions.

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II. THE PRESENT

This section attempts to describe the existing state of the field. The age of many of the references attests to the paucity of activity, making the past and present synonymous in some areas. Hopefully, an accurate perspective of conditions present through 1971 is given. A. Service Programs

Service programs are defined here as programs designed primarily to prepare the students or clients in their charge for successful adult living. Schools and workshops are the two major sources of vocational training service programs for the retarded. Included in these categories are institutional and noninstitutional settings, and public and private agencies. While patterns of service are changing, in the direction of community-based residential facilities and independent living, existing service programs can still be classified as school or workshop programs. 1. SCHOOLS

School programs for the retarded have existed in one form or another for many years (e.g., Cegelka, 1970; Kokaska, 1968; Mathews, 1919; Patterson & Rundquist, 1933; Thomas, 1928). The literature on school programs has the following characteristics: (1) Most of the literature is descriptive (e.g., Muller & Lewis, 1966; Sengstock, 1964; Etienne & Morlock, 1971). (2) Research on school programs is primarily concerned with the effects of in situ variables such as socioeconomic level, employment status, and IQ, and uses follow-up data as the primary measure of success(e.g., Doleshalk Jackson, 1970; Kennedy, 1966; McIntosch, 1949; Miller, 1954). (3) Almost none of the research is experimental in terms of manipulating training procedures (see Section 11, B, 2). (4) The emphasis is on organizational structure (e.g., Budde, 1969). The current trend, which originated with the work of Eskridge (1964), is toward programs operated jointly by school systems and state departments of vocational rehabilitation (e.g., Ayers, 1969; Brolin & Thomas, 1971; Clark, 1967; Henze & Meissner, 1970;Younie, 1966).With the emphasis still on organization, little evidence of the training process appears. Direct observation of programs across the country leads the author to the following conclusions: ( 1 ) Little connection exists between classroom activities and work activities. (2) Where work experience is part of the program, training is left to the students’ job supervisors. (3) Criteria for success are poorly defined. (4) Subjective evaluation of student performance by the job supervisor is often the only measure by which the student is judged. (5) There is

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a reliance on the creativity and enthusiasm of staff in the absence of a technology of systematic training. As university programs specifically designed to train personnel for secondary programs develop (e.g., Brolin & Thomas, 1971; Hamerlynck & EspeSeth, 1969; Redkey, 1971; Younie& Clark, 1969), attention should shift away from organizational matters and toward the technology of instruction. 2. SHELTERED WORKSHOPS The history of the sheltered workshop movement for the retarded is well documented elsewhere (e.g., DiMichael, 1960;Nelson, 1971;Wolfensberger, 1967). This movement has resulted in the establishement of three main types of workshops for the retarded: the transitional shop, where clients coming from school programs, homes, or institutions prepare for placement into competitive employment; the extended care or terminal shop, where clients believed to be incapable of achieving competitive employment work for indefinite periods; and the comprehensive shop which attempts to service both types of clients. The comprehensive shop, which often provides services for persons with a variety of handicaps, is the most common, probably because of the diverse needs and limited resources of most communities. Some workshops are beginning to accept only clients sponsored by divisions of vocational rehabilitation (transitional shops). Other shops, influenced by parent groups and departments of mental health, are moving more toward extended care services. With the tremendous proliferation of many types of sheltered workshops, meaningful quantitative documentation of trends is difficult. In addition to the population being served, workshops differ from one another in their philosophy regarding the function of work in the shop. For those agencies with a heavy emphasis on counseling and placement the shop is often perceived (but not described) as a holding place between counseling sessions or before placement. Shop staff are viewed as having to do more with goods and production than with clients and often are not included as an integral part of the habilitation program. The position taken here is that this perception usually results in major staff problems, a caste system, and a significant amount of client time spent in nonhabilitative activities. Where counseling and placement are heavily emphasized, work is not usually seen as the medium for change and growth. In agencies where the emphasis is more on extended care than on placement, work is again perceived as a holding device, but in this case, apermanent one. Work is what is required to keep clients busy, to help support the shop, and to maintain an image of productivity. In the extended care shop,

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one seldom finds a systematic attempt to increase productivity on existing contracts or to obtain increasingly complex and remunerative contracts. As far back as 1958, Dubrow (1958) expressed the feeling that extended care workshops should be largely self-supporting. However, few, if any, such shops exist today, 13 years later. In comprehensive shops, where there are varying degrees of emphasis on counseling and placement and varying ratios of transitional clients to extended-care clients, all of the criticisms given for extended care and transitional shops are applicable. Little real training is carried out in the shop. Contracts and production remain at menial, low-remuneration levels, and little attempt is made to change. Excuses for the status quo typically include staff having little time to seek more habilitative and remunerative contracts, or to work on new programs; the lack of good contracts even when sought; and general labor conditions. Although the value of a full-time procurement person is well documented (e.g., Dolnick, 1963,1964;Wolfensberger, 1967), few such positions exist. It is not easy to demonstrate the availability of good contracts. There are several possible reasons for the difficulty: (1) Workshop personnel have no confidence in their clients’ ability to perform accurately and consistently on anything more than very simple, repetitive tasks. (2) Clients are perceived by the working community, and the professional community, as being capable of only the most menial, nuisance-type work. (3) Procurement officers do not have contacts established for more complex contracts, except where a limiting bias has already been firmly established. (4) Most shops are not presently equipped, in terms of staff, attitude, machinery, or industrial know-how to handle effectively the increased training, quality-control, and production demands of such contracts. Highly sophisticated techniques of production efficiency and client training (see Section 11, B, 2) are just beginning to evidence themselves in workshops. Regardless of the type of shop, one issue stands out above all others as the key to successful workshop operation-contracts. The kind and amount of work found in the shop is of paramount importance. The main difference between sheltered workshops and other service facilities (e.g., schools, institutions, hospitals) is that workshops utilize work as the primary medium for client development. At least, philosophically this is true. In most cases the work found in sheltered workshops does not provide this medium. Instead, nonwork activities are instituted to effect change, or the shop merely provides a milieu and hopes change occurs. If the full potential of sheltered workshops is to be realized, major emphasis must be on contracts or subcontracts. They must be selected on the basis of habilitative value. The ideal work contract has the following charac-

Marc W. Gold teristics: (1) It requires skills that must be taught rather than skills which the clients already have. This includes some skills learned and transferred from other contracts. (2) There must be sufficient lead time to set up production and training to allow for client considerations and not just production considerations. (3) The contract should be heavy on labor. That is, the amount of shop space taken up by the contract should be in proportion to the number of clients employed on the job. If a contract takes up 40% of the shop floor, it should provide full-time work for at least 40%of the clients. This emphasis is the opposite for industry where labor is kept at a minimum. (4)The contract should have enough different operations to allow for a variety of job stations. A simple contract has only simple operations. A complex contract has the potential for a range of different operations. (5)The contract should be profitable for both the shop and the clients. Bidding should take into consideration the same factors that are considered by any subcontractor. This would exclude nonwork programs, counseling, and some, but not all, of the time needed to train clients. If clients are producing with at least the same quality as nonhandicapped workers, and are paid a wage commensurate with nonhandicapped workers, labor rate should not be the factor reduced to allow for competitive bidding. Production efficiency, client training, material handling, and service to the customer should be the main parameters manipulated to effect competitive bidding. The points mentioned above represent only an initial attempt to clarify the importance of contracts. But, it seems clear that a truly habilitative milieu, for both transitional and extended-care clients, depends heavily on the effective use of contracts. For a highly relevant industrial perspective the reader is referred to Brewser (1969) and Levine (1967). The issue of automation is directly related to both school and workshop programs in terms of its effects on contracts and placement. An excellent discussion on automation and the mentally retarded is found in the work of Kokaska (1968). His review provides a perspective from outside and within the field. He concludes that the retarded have evidenced the ability to maintain themselves in competitive employment despite the advent of automation. DiMichael ( 1969), who has periodically and accurately described the rehabilitation field, evidences optimism regarding the effects of automation on the handicapped. He points out the qualitative rather than quantitative changes in the labor force, and also gives examples of how the handicapped have been able to adapt. In a review of current literature, Nixon (1970) identifies further support for an optimistic outlook for unskilled and semiskilled labor in the next decade. H e also discusses the need for more research on job analysis for adequate matching of retardates’ full potential with specific job opportunities. Research related to this and other issues in the field is discussed below.

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6 . Research

Research is defined here as activities which have, as their primary focus, obtaining information leading to the development of a technology for the field. Because it is current practice to separate evaluation and training, they are discussed separately. However, an attempt will be made later in the article to justify merging evaluation and training into a single and far more efficacious endeavor than is the case at present. 1. PREDICTION A N D EVALUATION

The extensive literature on vocational evaluation and prediction is full of statistical significance but devoid of practical significance. Dependent measures of performance on the tests developed and utilized are correlated with measures on instruments for which validity and reliability have not been established with the populations, and under the conditions in which they are used. Where prediction is the goal, concurrent validity is often used as an indices of predictive validity. In addition, criteria for vocational success are often established retrospectively, and are not easily generalized across work situations. Despite the boredom likely to be generated, the author felt an extensive review was necessary in order to substantiate the criticisms given above and at the end of this section. Consequently, the literature on prediction and evaluation is euphemistically reviewed here in some detail. a. Intelligence Tests Most studies indicate that intelligence tests correlate with work potential, but have limited utility as predictive measures. In astudy comparing agroup of retardates employed outside the workshop with a group of “terminal” workshop subjects, a statistically significant difference was found between groups on the Performance sections of the WAIS and the Wechsler-Bellvue, but not on the Full Scale(Appe1, Williams, & Fischel, 1962).In another study Kolstoe (1961) found no statistically significant differences between the IQ scores of employed and unemployed retardates. Verbal and Performance scores were not discussed. Meadow and Greenspan (1961), using the WISC as part of a battery of tests, found that information obtained from this battery was not sufficient for predictive use. Fry (1956) found a performance efficiency quotient derived from the WAIS Performance IQ to be the best predictive measure of work success. This study was done using 38 institutionalized girls to determine the qualifications necessary for successful performance both inside and outside an institution. The quotient was correlated with a job rating from a laundry foreman, with assistance from a psychologist.

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Bae (1968) found that once the subjects in her study were screened and accepted into training programs, good and fair trainees were not differentiated by WISC and WAIS Verbal, Performance, or Full Scale IQ scores. The Binet has been shown to correlate with other tests used for vocational assessment. Wagner and Hawver (1969, working with a population of trainable adults, found a correlation of .64 between the Binet and the O’Conner Finger Dexterity Test (p < .001). Significantcorrelations were also found between the Binet and several other manual dexterity tests. The Porteus Maze Test was studied to determine its value in differentiating employed from umemployed retardates. Tobias and Gorelick (1962) describe a study done at the Association for the Help of RetardedChildren (AHRC) in New York City. The subjects consisted of 32 ex-trainees of a workshop. Sixteen had held jobs in competitive industry for at least 6 months. The other 16 had not found employment. All subjects had at least 1 year of training. The groups were matched on IQ. Results from the Maze Test yielded a difference between groups significant at the .01 level. With a dividing point of 8.5 (raw score), thePorteus MazeTest would have correctly assessed 24 of the 33 subjects in the study. According to Porteus (1959), the test measures “planfullness.” Tobias and Gorelick suggest that the reason the Maze Test predicted success in competitive employment but not in the sheltered workshop is that, because of the extensive control of the environment in the workshop setting, the value of “planfullness” is eliminated. In competitive employment such control is not usually found. It has been the author’s experience to observe just the opposite. That is, industrial production is characterized by organization, efficiency, and constancy of movement, and other controls, while sheltered workshops are usually inefficient, in comparison, and lack control of all but the most deviant, nonproductive behavior. A correlation of .35 (p < .01) was found between the MazeTest and a work efficiency rating based on the average hourly earnings for a 4-week period, using 65 trainees. I n an earlier study, Tobias and Gorelick (1960~)found that the Goodenough Scale could predict work efficiency as well as the WAIS Full Scale IQ does, but not as well as the WAIS Performance IQ. The Evaluation Tests (Tobias, 1960) a battery used at AHRC, was used for the correlation. The Goodenough Scale and the WAIS Full Scale correlated .40 and .43, respectively. with the Evaluation Tests. The WAIS Performance IQ correlated .50 with the Evaluation Tests. All three correlations are significant at the .01 level. b. Manual Dexterity Tests Many manual dexterity tests have been used with the retarded (e.g., Ferguson, 1965; C. H. Patterson, 1964; Mocek, Lerner, Rothstein, & Umben-

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haw, 1965), although the retarded have not been included in the normative sample. The Wagner and Hawver study (1965) previously described ran multiple correlations between the following manual dexterity tests: O’Conner Finger Dexterity Test; O’Conner Tweezer Dexterity Test; Minnesota Rate of Manipulation Placing Test; and Minnesota Rate of Manipulation Turning Test. Correlations of each of the four tests with each of the other three ran from .66 to .82, and were all significant at the .001 level. This would indicate that they are all, to some degree, measuring the same thing. Each of these tests was correlated with the criterion ranking of the chief instructor which was based on the following criteria: (1) respects authority and is willing to take directions; (2) generally completes assignments; (3) work is usually of good quality; (4) seems to get along reasonably well with co-workers; and ( 5 ) learns new workshop skills without too much difficulty. Correlations with the ranking were: O’Conner Tweezer Dexterity Test-SO(p < .Ol); Minnesota Rate of Manipulation Turning Test-S3 (p < .Ol); O’Conner Finger Dexterity Test-.66 (p < .001); and Minnesota Rate of Manipulation Placing Test--.64 (p < .001). A Kendall Coefficient, which is a measure of interrelationship between rankings of all variables, was significant at the .OOl level, indicating that some general factor is involved. In the correlational study done by Wagner and Hawver(1965), the Goodenough-Harris Test correlated .48 with the OConner Finger Dexterity (p < .05); .38 with the O’Conner Tweezer Dexterity Test (not significant); .54 with the Minnesota Rate of Manipulation Placing Test ( p < .01); .48 with the Minnesota Rate of Manipulation Turning Test ( p < .05); .82 with the Bender-Gestalt Test (p < .001); .55 with the Stanford Binet (L, M, L-M) (p < .01); and .71 with a criterion ranking based on workshop performance as evaluated by the chief instructor of the workshop (pc .001). Twenty-seven subjects, 11 females and 16 males, were used. The ages ranged from 21 to 34 years (mean = 23.7, SD = 3.1). IQs ranged from 13 to 49 (mean = 34.4, SD = 8.8). Distefano, Ellis, and Sloan (1958) measured the proficiency of mental defectives on a variety of motor tests and examined the interrelationships among the tests, MA and CA. The subjects consisted of 40 males ranging in MA from 5.33 to 11.50 years (mean = 9.90, SD = 2.19). The range forCA was from 9.66 to 29.00 years (mean = 19.73, SD = 5.10). There were 36 females. The CA range for the femaleswas from 11.48to 32.41 years(mean = 22.25, SD = 7.07). MA range was from 5.50 to 10.83 years (mean = 9.14, SD = 2.01). The tests used were the Lincoln-Oseretsky Motor Development Scale, the Rail Walking Test, the Minnesota Rate of Manipulation Turning Test, the Hand-Steadiness Test, and the Strength of Grip Test. Except for performance on the Minnesota Rate of Manipulation Turning Test, the males were more proficient than the females, although this difference was

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significant only on the Rail Walking Test (p < .05).The Lincoln-Oseretsky turning and placing performances were found to be the most highly related to MA in both the male and femalegroups.Correlations between the LincolnOseretsky and MA were .40 for males and .58 for females. It was inferred that intelligence and motor proficiency, as measured by the tests used, are positively related in mental deficients whose CA is beyond that time during which rapid development in motor and intellectual ability usually occurs. Elkin (1967), in a correlational study of work sample tasks, intelligence tests and dexterity tests, found significant correlations between his four work sample tasks, between age and total work performance, between length of institutionalization and task performance by males, and between male total work scores and 17 of the 19 predictive variables used in the study. Tobias and Gorelick (l960a) studied the effectiveness of the Purdue Pegboard in evaluating work potential of retarded adults. They found that, as the Purdue tests increase in complexity, so does its linear relationship with intelligence. Using 73 retardates with IQs ranging from 35 to 78 (mean = 63, SD = 10.6), they found that the WAIS Full Scale IQ correlated .56 (p < .01) with the Right- Left- Both scores of the Purdue, and .67 (p < .Ol) with the Assembly score. The WAIS Verbal IQ correlated only .34 (p < .01) and .43 ( p < .01) respectively, with the Purdue tests. But the WAIS Performance 1Q correlated .57 ( p < .01) with the Right- Left- Both score and .73 ( p < .01) with the Assembly score. A correlation of .44 was found between the WAIS Full Scale IQ and wire clamp assembling. The correlation between the Purdue and the wire clamp assembling was .75. No correlation was reported between the WAIS Performance IQ and the assembly task. A correlation of .54 (p < .01) was found between the Purdue and hourly average of disassembled screws. This was found using a group of 25 retardates ranging in IQ from 30 to 50. In another analysis, a correlation of .64(p < .01) was found between the Purdue and hourly earnings. This was with agroup of 68 retardates. No other information was given for this group. Tobias and Gorelick concluded that the Purdue Pegboard appeared to be a superior instrument in predicting productivity on the type of work available at the workshop where their research took place. For a nonfield perspective on dexterity tests, the reader is referred to Fleishman and Hemphill (1954). c. Work Sample Tasks The work sample technique, also known by several other names(Bailey, 1958; Cohen & Williams, 1961; Overs, 1964; Sinick, 1962; TOWER, 1967; Usdane, 1953), has become quite popular. It involves standardizing and obtaining normative data on typical work tasks. It is used extensively throughout the country (Speiser & Cohen, 1966), although the rationale on which it is based currently has only face validity. DiMichael (1960) noted

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that the mentally retarded perform below norms on standardized tests of manual ability, and that actual job samples have a face validity lacking in standardized tests. He also points out that the client can be compared with other employees who are producing in the same workshop. Sinick (1962) pointed out that factors such as recency of schooling, educational deprivation, insufficient motivation, excessive anxiety, cultural deficiencies, cultural atypicality, and bilingualism are less likely to influence work task performance than conventional tests. The resemblance of work tasks to actual jobs, causing the client to believe that he is truly being trained for such a job, is given as apossible advantage. Bailey( 1958) describes a number of benefits derived from the use of the work sample approach. Among these are the following: (1) They provide prevocational experience. (2) The client learns to see, feel, smell, and become fatigued by work. (3) The client is motivated. (4) The client gains a realistic concept of work. ( 5 ) The client readjusts goals or gains confidence and seeks higher attainment. (6) The work trial method helps those who cannot succeed find out before there is too much frustration. These questionable benefits seem more relevant to other than the retarded, if at all. Several approaches to the development of work sample instruments are found in the literature. DiMichael (1960) advocates a standardized battery of work samples to assess different abilities. However, there obviously needs to be evidence that differential performance on work tasks is related to differential performance on jobs (Sinick, 1962). Overs, Koechert, and Bergman (1964) discuss the compromise between reliability and validity, Those instruments that are highly reliable, such as many of the manual dexterity tests, lack predictive validity because of the narrow range of behavior they sample. Instruments such as behavior rating scales or ratings of performance on subcontract work in a workshop may be highly meaningful, but lack reliability because of the absence of standardized methods of reporting, measuring, and describing behavior. The potential value of the Gork sample approach, then, is to develop standardized methods of reporting behavior in a situation that is commensurate with the kind of work the client is likely to be doing. Overs and his colleagues describe an attempt to do this. Although the project was not designed specifically to meet the needs of the mentally retarded, all of the principles discussed apply. Typical psychometric test development procedures were used. This would seem a superfluous note but for the absence of such procedures in the development of many work sample batteries. The Evaluation Tests (Tobias, 1960) is a work sample battery designed for use with the mentally retarded. The tasks consist of folding table cloths, sorting buttons, lacing display cards, assembling pistol key chains, assembling puzzles, packaging poker chips, and racking for electroplating.

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Skills tested include manual dexterity, visual-motor coordination, ability to follow directions, the ability to follow a sequence of multiple, ordered operations, degrees of depth perception and spatial relationships, and the ability to count incidental to completing tasks. The test is administered under natural workshop conditions. A trial consists of the completion of a given number of units. The time taken for completion comprises the raw score which is converted to a percentile score. Before the first trial the client learns the task to be done. Upon demonstration of the ability to execute the task the test begins. Three trials are given for each test, and are administered 2 days apart. Trials are also separated by other kinds of work, or by trials on other tests in the battery. Administration of the battery takes up to 3 weeks. The third trial is considered most important. It still only represents nonreinforced performance, but after practice. Normative data was obtained using a population of 60 retardates, some with accompanying handicaps, ranging in age from 17 to 25 years. The IQ range was from 42 to 83 (mean = 66.5, SD = 8.18). Intercorrelations between the tests show that most of the tests seem related. That is, clients who do well on one test tend to do relatively well on the other tests. The pistol-assembly task, which correlated the highest with the other tests, was used for comparisons with other criteria. The percent decrease in time taken to complete 50 assemblies over trials correlated - .07 (not significant) with IQ. This suggests that intelligence is not related to the rate of improvement. The correlation between IQ and hourly wage was. 14(not significant). The correlation between the Evaluation Tests and hourly wage over a Imonth period was .52 ( p < .01). This suggeststhat the tests might have some predictive value in similar situations, especially with the development of local norms. It should be noted that the group from which normative data were collected had a mean IQ in the higher range of retardation. Further analysis, or more data, is needed before this instrument could be used confidently with lower level retardates. Ladas (1961), using a standardized battery almost identical with the one developed at AHRC (Tobias, 1960), studied the relationship between work sample learning rates and workshop productivity. He found that learning rate was not independent of other factors and was not effective, in this study, as a predictor. Katz (1959) found that the mean of a battery of work samples(Ladas, 1961) correlated .72 with the Purdue Pegboard, .68 with the Bennet Hand Tool Dexterity Test, and .69 with the O’Conner Tweezer Dexterity Test. Although information was not reported for particular subjects used for the study the workshop report shows a mean IQ for the workshop clients of approximately 52. The TOWER System (1967) is a work sample battery developed for use

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with the handicapped. It utilizes over 100 work samples covering the following 14 broad occupational families: clerical, drafting, drawing, electronics assembly, jewelry manufacturing, leather goods, lettering, machine shop, mail clerk, optical mechanics, pantograph engraving, sewing machine operation, welding, and workshop assembly. The nature of many of the work samples, the amount of receptive and expressive language required, in addition to the general criticism of work samples included in this section, suggests that the TOWER System has limited value for all but the most capable retardates found in vocational training programs. Criticisms of work sample batteries include the following: (1) Work samples are more a training exercise than an instrument of evaluation as traditionally conceived. (2) They are time-consuming, in need of continual revision, and devoid of pressures that characterize the competitive work situation (Blackman & Siperstein, 1968). (3) Scores obtained during the initial practice periods in an activity do not predict terminal efficiency (Parker & Fleishman, 1961). (4) Existing batteries are very expensive. These criticisms are appropriate because of the way in which such tests are presently administered. Problems inferred from these criticisms can be eliminated. If measures of acquisition rate and performance rate are made separately and under standardized conditions, and if norms are developed, then the instrument may legitimately be considered evaluative, even in the traditional sense. The difference is the kind of information obtained. With most skill tests rate of performance is the measure taken, with little effort made to either consider the effects of acquisition on this measure, or to look at acquisition rate as equally important information. It is not surprising that Parker and Fleishman (1961), and others, find scores obtained during the initial practice periods to be less than representative of terminal efficiency. For the retarded it is even less surprising to find acquisition and performance confounded during early trials, which is usually the only condition under which test data are obtained. The criticism by Blackman and Siperstein (1968) that work samples are time consuming, may be correct, but must be considered in light of the quantity and quality of information obtained per unit of time spent. In addition, if the client is learning the kinds of skills he can use later, while he is being evaluated, this would make much more efficient use of such time. Work samples need not be devoid of pressures that characterize the competitive work situation. Pressure could be one of the parameters added to present test batteries. For example, having learned and then produced a particular work sample task, a client could work on that task next to other workers, or be instructed to produce a given number of units in a specified period of time. In addition to subjective evaluation, the comparison of his performance under one of these conditions with his performance under the

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no-pressure conditions following acquisition, would yield quantifiable, objective information relevant to his functioning under pressure. The general procedure inferred from this example could be used to evaluate many aspects of work-oriented behaviors.

d. Other Relevant Research In a study that has some implication for the evaluation procedure, Tobias and Gorelick (l960b) studied the tendency of retardates to arrange and organize their completed work far beyond requirements of the job. The term used to describe this phenomenon was “orderliness.” They used the entire population in a workshop (AHRC) which consisted of 60 retardates with a mean age of just below 22 years and ranging in IQ from 26 to 75. The procedure was to test one retardate at a time. Each subject worked on a simple assembly task. Two trials of 1 hour each were given. On one of the trials the subject was told to put the finished products on the table. On the second trial he was told to drop the finished products into a box on the floor. Half of the group started one way, half the other. Three groups were identified: (1) Rigid Ordering-arranged finished products in some geometric arrangement such as straight lines, or all placed in the same direction; (2) Vague Ordering-started a pattern at the beginning of the hour but did not maintain it for the full hour. (It was postulated that this was due to short attention span and distractibility.); and (3) Haphazard Arrangements-no patterns. When Groups I and 3 were compared, a difference of 6 was found between mean IQs ( p < .05). This suggests that, although there is overlap between the groups, there is a tendency for the more intelligent retardates to use a haphazard arrangement. When “orderliness” was compared with productivity for Group 1, the trial that allowed the Rigid Ordering Group to “order” showed a lessening in production that was significant at the .01 level. The same comparison done with the Haphazard Group showed no significant difference in production rate. As might be expected, the Vague Ordering Group showed asmaller difference in production under the “order” condition than the Rigid Ordering Group, but was more affected by the condition than the Haphazard Arrangements Group. From these data it might be inferred that, with those retardates that fall into the Rigid Ordering Group, productivity rises as external conditions prevent “orderliness” from occurring. Acceptance of the results of this study would have implications for work organization, especially where the workers are lower-level retardates. Franks and Franks (1962) compared conditionability to work adjustment. A classical conditioning paradigm was used. The subjects were conditioned to elicit an eyeblink response to a tone. Three groups of retarded girls were

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used. Group I consisted of 18 girls working effectively in the community. The IQ range for this group was 32 to 74 (mean = 58). Group 2 consisted of 36 girls who were working fairly effectively, but only within the hospital setting. This group ranged in IQ from 38 to 86 (mean = 70). Group 3 was composed of 12 girls who were considered occupationally inadequate and did not carry a regular work assignment. The IQ range for this group was from 40 to 82 (mean = 64). Data indicated that Group 1 conditioned most readily and was most resistant to extinction. Thisgroup was followed closely by Group 2. There was some overlap during acquisition by Group 2. Group 3 was considerably worse than the other two groups at acquiring the conditioned response and was the most susceptible to extinction. Group 3 differed significantly ( p < .01) from Groups 1 and 2 combined, on both acquisition and extinction. According to the authors, these data are consistent with the theory that poor conditioners may profit less from life’s experiences and be less likely to build up good work habits. They also infer from the data that factors other than brain damage are related to the presence of poor conditionability and hence to poor work adjustment. Those subjects whose vocational adjustment was poor were also those who were relatively poor at forming conditioned eyeblink responses in the laboratory. In an effort to study self-concept development, O’Neil(l968) measured the ability of mentally retarded adolescents to rate relative work potential. He used a pictorial comparison method with staff members providing a standard for evaluation. He found that the trainees were able to use work standards to evaluate their own potential for community placement for themselves and their peers. Trainees who were later employed were more consistent raters. Their results did not establish that self-concept development and level of work adjustment were clearly related.

e. Summary on Prediction and Evaluation In summary, no attempt has been made to distinguish between acquisition and performance, i.e., between learning ability and production ability. Equally important, no attempt has been made to make the evaluation period fruitful to the client in terms of the development of the skills which are being evaluated. If anything isgained from the evaluation period, it is usually adjustive in nature with the clients often spending many hours or days being nonproductive and not learning new skills. It is also possible that many retarded clients, who are in a work setting for the first time, develop inappropriate concepts regarding work, which are based on nonproductivity and low-level tasks and which are reflected in future performance. Current prediction and evaluation procedures and tests as they are presently conducted are not very successful.

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2. TRAINING In the introduction to this article, training is defined as controlled, systematic manipulations of the environment, administered in such a way that their effects can be measured and recorded. This definition is equally applicable to both research and service. If training is not administered as defined, clients spend most of their time in nonhabilitative activities, what growth takes place is inferred or goes by unnoticed, and programs remain static in the absence of feedback regarding their effectiveness. In order for programs to facilitate growth “by the hour” rather than “by the week” or “month,” training, as defined, must take place. Research on training may be dichotomized as the development of procedures to either modify existing rates of behavior or facilitate the acquisition of new behaviors. Not much training research has been done, much less implemented. While the rest of the review draws selectively from the literature, the section on training is, hopefully, comprehensive. Modijjing Rates of Existing Behaviors Most sheltered workshop clients do not understand the relationship between the money they receive on Friday and their performance during the week. Many do not understand “money” at all. While it is true that reinforcement should occur immediately following the desired behavior, it is impractical to d o so in most work situations, even sheltered ones. Common practice is to pay workers, or clients, on a weekly basis. Parenthetically, the money many sheltered workshop clients make often goes either to their home or into a savings account, neither ofwhich are particularly reinforcing (Campbell, 1971). Most of the studies reported here address this problem. Evans and Spradlin (1966) investigated the effects of incentives and instructions as controlling variables of productivity of institutionalized, mildly retarded males (mean IQ = 66.67, SD = 7.22). The incentive schedules used involved a piece-rate plan in which a unit of pay was provided per unit of work produced, and a salary plan in which a unit of pay was provided at the end of a specified unit of time, with no production contingency. The task was to pull a knob. Number of responses per session was the dependent variable. All subjects received all conditions. Although there was a statistically significant ( p < .05) difference in production, in favor of the piecerate condition, the authors point out the real difference was only about 10% in terms of absolute productivity. This difference is surprisingly small when viewed from the position of reinforcement theory. Two no-salary conditions were subsequently tried. In one, subjects were told to pull the knob. In the other they were told not to pull the knob. The authors concluded that ( I ) money, even when it is noncontingent on responding, does lead to higher a.

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response rates than when no money is involved; (2) verbal instructions area potent antecedent variable with high-level retarded subjects; and (3) a high response rate can be reestablished by instructions, as well as decreased or maintained. The tendency to underestimate the control of antecedent variables in situations where they are very powerful was also discussed. Huddle (1967), working with institutionalized retardates, utilized a 16piece television rectifier assembly to study the effects of competition, cooperation, and monetary reward on work performance. Paid subjects received 1 cent per unit, paid daily. He found that payment of monetary rewards had a significant effect on performance. Reward, however, was confounded with experimenter and institution, making this data difficult to interpret. No other significant main effects or interactions were obtained. In a study of the effects of immediate monetary reward on performance Steinman (197 1) gave pennies for task completion time which was faster than mean base rate performance to eight mentally retarded adults on a simulated production line packaging task, which consisted of packaging checkers. All subjects improved their performance on the task under reinforcement. Steinman suggests that a training program might begin with the use of continuous reinforcement or low variable-ratio reinforcement and move gradually toward the once-a-week pay period which is commonly found in workshop programs, and competitive work situations. In a similar study by Hunt and Zimmerman (1969), productivity in exit ward patients participating in a simulated workshop setting was examined as a function of introducing a bonus pay procedure. The primary difference between this study and the one by Steinman was that subjects in this study were paid at the end of the working period. They were told in advance that during the bonus period they would be given coupons redeemable for canteen items. Work units completed per hour served as the dependent variable. The task consisted of counting pages to make scratch pads. The bonus procedure significantly increased group productivity above that previously attained under nonbonus conditions and differentially maintained productivity at values consitently higher than those attained during temporally adjacent nonbonus periods. The authors suggest that verbal instructions given in conjunction with the procedures could have accounted for some of the results. Zimmerman, Stuckey, Garlick, and Miller (1969b) applied a token reinforcement system to study effects on the productivity of multiply handicapped clients in a sheltered workshop. The task performed by 15 of the 16 subjects was a Western Electric terminal board assembly. The sixteenth client folded Goodwill bags. Assembly involved inserting 49 small U-shaped metal terminals into slots of a perforated plastic connector block which is part of a telephone set. The bag-folding task required folding a bag five

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times, placing a rubber band over the folds, and throwing the bags into a box. The experiment included the following sequence: (1) 7 weeks of base line performance under standard workshop conditions; (2) 2 weeks of apractice condition in which verbal information about production, and nonredeemable points were given daily; (3) 2 weeks of a points condition in which verbal information about production was given daily, and clients received and could spend point cards; (4) 2 weeks of alternating conditions (2) and (3) daily, in which the type of consequence available at the end of each day, identified via instruction, was given at the beginning of each day; ( 5 ) 2 weeks of return to base line condition. The results were that (a) productivity increased significantly when the base line condition was replaced by the practice condition; (b) productivity increased significantly again when the condition was replaced by the points condition; (c) the productivity on point days was significantly higher than the practice days during the alternate period; (d) productivity under the final base rate condition was significantly lower than under conditions in which points could be earned; and (e) productivity was somewhat higher under the second base line condition than under the initial base line condition. Although the authors state that 14 of the 16 subjects in the study were mentally retarded, no information was given as to the degree. The instructions utilized suggest that the clients might have been borderline or mildly retarded. The tasks used were of a fairly simple and repetitive nature. Nevertheless, the impressive information provided, that systematic control of reinforcement contingencies produced predictable changes has implications for sheltered workshop production with all levels of retardates and with more complex tasks. The authors stress the importance of controlling and measuring the effects of work conditions. In another study, Zimmerman, Overpeck, Eisenberg, and Garlick (1 969a) used seven clients from the Zimmerman et al. (1969b) study and six other clients, and the same tasks described in that study. The use of isolationavoidance procedures and production-contingent work reinforcement to stimulate productivity were studied. The isolation-avoidance procedure consisted of using production rate to determine whether or not the client could participate with other trainees on the following day. That is, if the client failed to meet a production goal on one day, he was isolated from the group on the following day. The procedure demonstrated was highly effective with the clients and tasks used. Production-contingent work reinforcement consisted of utilizing choice of work as a reinforcement for meeting production goals. The two subjects who were exposed to this condition showed significant increases in performance as a result of this procedure. A description of the application of the procedures developed by Zimmerman and his colleagues may be found in the article by Campbell (197 1). Screven, Straka, and Lafond (197 1) report a program of research designed

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to provide clients with an understanding of the relationship between money received and work output. Simple tasks such as filling a tray with 12 red and 12 black checkers and putting them into a cardboard box, and filling a counter board with 50 golf tees and bagging them are used. They have examined the effects of various mechanical reinforcement devices, goal setting, and various sequences leading from immediate, contingent reinforcement to weekly pay and report good results. For example, in one of the studies for which data were reported, rate increases of from 50 to 100%were obtained using bonus pay procedures and manipulating the schedule of reinforcement. Because of the considerable amounts of equipment, space, and staff time required for their procedures, the feasibility of applying their techniques to other settings needs to be demonstrated. Another program of research on the development of training procedures for trainable retarded students in public school settings is being directed by Lou Brown. In the first study reported(Brown & Pearce, 1970),the use of feedback, modeling, and reinforcement procedures similar to those used by Zimmerman and his colleagues were assessed. Using three students and an envelope-stuffing task, they found considerable individual differences but, in general, found all variables to be sufficiently effective to warrant further study. The next experiment (Brown, Johnson, Gadberry, & Fenrick, 1971) utilized six trainable students performing the same task to study the effects of individual versus assembly line production and social versus social plus tangible reinforcement. The four possible procedures were administered in a series of 36 15-minute periods. Tangible reinforcement consisted of tokens which, collectively, were redeemable for components of a “banana split.” Typical verbal social reinforcers were used randomly. Feedback, which involved writing and explaining production figures on the chalkboard, was given to all students throughout. Individual performance consitently exceeded assembly line performance. Performance under the tangible reinforcement condition increased an average of 60% for individual performance and 49% for assembly line performance. Pacing and balancing problems of assembly line production were discussed. The authors emphasized that the study was done in a classroom by classroom teachers, and that such positive results suggest more use of these procedures in classroom settings. A third study (Brown, Van Deventer, Perlmutter, & Jones, 1972b) examined the effects of charting and pay on production rate. Eighteen trainable students collated a four-page catalog, representative of most simple, repetitive tasks which require little or no training to perform and which are the mainstay of subcontract work found in sheltered workshops in this country. After reaching a criterion of three consecutive correct trials, students produced under the following five conditions: ( I ) base line, consisting of three

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10-minute periods; (2) charting, consisting of showing students the relationship between productivity and a line on a graph and having them produce and chart in 10-minute periods until production stabilized; (3) repeat of condition (1); (4) repeat of condition (2); and (5) charting and money, consisting of paying each client 5 cents for each 10-minute period in which production exceeded previous performance. Teacher performance was used to establish a norm against which to compare. Using typical workshop practices productivity was labeled work activity level (low), competitive sheltered work level (medium), or competitive employment level (high) on the basis of the highly questionable normative performance of teachers in the school. During the first base line period, all students performed within the work activity range (0-39.6 units per 10-minute period). The first charting condition produced increases for all students, but the amounts of increase varied widely (3.2-59 units per 10-minute period). The second base line condition and chart condition produced mixed results. The introduction of money produced substantial increases. Three students reached competitive levels of productivity, as defined (over 46 units per 10-minute period). Most of the other students had some periods in which they produced within the competitive range but averaged somewhat lower. Only one student failed to produce above the minimum work activity level. Errors decreased over sessions and were virtually eliminated by the end of the study. A similar study was done by Logan, Kinsinger, Shelton, and J. M. Brown (1971). The fourth study involved quality, quantity, and durability of work performance (Brown, Bellamy, Perlmutter, Sackowitz, & Sontag, 1972a). Four students were taught t o assemble packs of cards using what appeared to be highly verbal training procedures. Following acquisition of the task the following sequence of manipulations was performed: ( I ) base line, during which time no feedback or reinforcement was given; (2) weekly payment, during which time students were told in advance that they would receive, at the end of the week, a penny for each accurately assembled pack; (3) session payment, which involved payment every 15 minutes and feedback on accuracy; (4) high rate contingency, during which payment was contingent on productivity exceeding that of any previous period; (5) daily payment, which included removing the high rate contingency and giving feedback on quality; and (6) weekly payment, as in the second condition. Student performance was again compared to the performance of four teachers, who were considered to have produced at a normal rate. Quality of performance increased over sessions for all students. All students showed substantial quantitative growth, and two of the four students reached competitive production range, as defined by teacher performance. Durability, defined as maintenance of high and accurate performance levels during the weekly payment schedule, was attained by two of the students.

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While these studies do not provide a clear cut description of an effective workshop or prevocational pay system, they do lay the groundwork for the development of such a system, which is discussed further in Section 111, B, 2. The kind of programmatic research done by Brown and his colleagues, in addition to its content value, exemplifies the potential for cooperation between researchers and practitioners. An interesting attempt to utilize clients to administer reinforcements to other clients is reported by Kazdin (1971). Successful applications included increasing appropriate conversation by clients giving each other tokens for talking; a client learning to walk with his head erect, instead of on his shoulder, by giving tokens to other clients who praised him when he held his head correctly; and a client decreasing talking and laughing to himself, and increasing talking with others, by him giving and receiving tokens for social interaction. Kazdin points out the preliminary nature of his data, which were not reported, and mentions several advantages of using clients to administer reinforcements. In summary, research on modifying rates of behavior has produced a small but impressive groundwork on which to base future efforts. In addition to the varied procedures and degrees of effectiveness shown, there are two other findings which are evidenced across studies: (1) Procedures designed to elevate performance levels seem to have some effect on the quality as well as the quantity of performance. (2) Verbal directions appear to be powerful controlling variables of performance but have not been systematically investigated, at least not in workshop settings. b. Facilitating the Acquisition of New Behaviors The literature on facilitating the acquisition of new behaviors is, indeed, sparse. There are hundreds of articles describing training programs, which do not delineate the specific manipulations made which facilitate development. Instead they describe clients, facilities, activities, and other aspects of the milieu in which training is supposed to occur, but not the training itself. The studies reported here were selected because they specify the manipulations made and because they fit the definition of training used in this review. One of the most fruitful areas of training research is the use of autoinstructional techniques. Such techniques in the field is a recent occurrence (Bitter & Bolanovich, 1966; Eldred, 1965).The studies reported here include the development of both hardware and software specifically for such use. Screven et al. (197 1) describe their adaptation of a commercially produced machine. Features of the adapted versions include match-to-sample press panels; controlled audio feedback and response-contingent pacing; and slide projector and movie projector hook-ups. Software includes the use of both audio and visual materials; taped vocal reinforcement and feedback; pro-

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grams using printed material, symbols, and pictures; and programs to name and to discriminate colors, to make small change, to listen, to train clients to use the machine; and some basic reading programs. Their experience with this equipment has generated the following opinions regarding the use of autoinstructional equipment: (1) The use of such devices increases the likelihood of carefully organizing and sequencing materials. (2) Materials can be reworked efficiently. (3) Such devices are replicable. (4) Operating the equipment is sufficiently reinforcing, in itself, to sustain attention for long periods. ( 5 ) The use of automatically dispensed reinforcers draws clients’ attention away from the stimulus materials. (6) Where added reinforcement is needed, it can be programmed into the visual and audio presentations in the form of verbal praise or visual cartoons. (7) Machine presentation appears to be superior to nonmachine presentation of the same materials in terms of client error rate, frequency of nontask behavior, and number of reruns needed to reach criterion performance. While the data to support these statements were not presented, their observations seem consistent with the rest of the programmed instruction literature. Blackman and Siperstein (1967) describe the use of an autoinstructional device to train educable retarded individuals to plug solder. The device used coordinated slides and tape. Considerable reworking of both the slide sequences and the instructional tapes was suggested, although the procedure was considered more efficient than alternative conventional procedures in terms of holding client attention, reducing distractibility, standardizing instruction, and individualizing instruction. The program developed incorporated the following: (1) a detailed task analysis; (2) systematic review of previous steps; (3) brief, easily understood directions; and (4) the integration of supervisor feedback and machine presentation. Blackman and Siperstein feel that their procedures should be further studied, and that marketable skills appropriately taught to the retarded, using such procedures, should be identified. The most extensive program involving the use of autoinstructional devices for the field was conducted at the Devereux Foundation (H. Platt, J. Cifelli, & W. Knaus. undated). At least three new devices were designed in the program in addition to the adaptation of already existing, equipment. The software described is very verbal and intended for use with mildly retarded individuals. Numerous studies designed to test the efficacy of the autoinstructional devices and programs developed were reported in detail. The authors concluded the following: (1) In most cases higher achievement test scores were obtained using autoinstructional devices. (2) Autoinstructional devices were most effective when used in conjunction with material introduced by the teacher. (3) Performance on proficiency tests was lowest with students who were exposed only to the machine method. (4) The use of auto-

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instructional met hods reduces learning time. ( 5 ) Programmed instructional material facilitated retention. The program at Devereux also includes a large dissemination component which consists of frequent presentations at conferences and at universities, the distribution of written materials, and the manufacture and sale of their devices. In summary, the literature on the use of autoinstructional devices is impressive. Even within the limited scope of the research described, the practical possibilities are encouraging. Programming, in the operant sense, is certainly not limited to use with autoinstructional devices. Programming of the total sheltered workshop environment is the focus of the research carried on under the direction of James Crosson (Crosson, Youngberg, & White, 1970). This research differs from the other operant work reported in this article in that the emphasis is on the acquisition of new behaviors rather than on the modification of existing rates of behaviors. The initial report (Crosson & deJung, 1967) describes a study in which a group of severely retarded males were successfully trained to perform three simple workshop tasks, using principles of shaping, operant discrimination, and chaining. The value of the study is not that severely retarded individuals can acquire such behavior, but that the task was analyzed and presented effectively. This involved defining the correlated response topographies and redefining each task in terms of operants. Each component of the task was then taught using modeling, verbal, and nonverbal assistance and physical assistance (priming). The experimenters gradually removed (faded) assistance as the task was learned. Reinforcements, which consisted of candy and verbal praise, were also faded over trials until reinforcement was given only at the end of each session. The effects of the procedures used were reported in detail and provide avaluable resource for further use of operant techniques to facilitate acquisition of new behaviors. In addition to the acquisition study, a 2- and 12-month retention study was performed (Crosson, 1969) which yielded retention of over 90% of the discriminations by all subjects. In a more recent publication, Crosson et al., (1970) expanded the techniques and theories encompassed in the studies reviewed to an entire workshop environment. They use the term “transenvironmental programming” to describe a workshop program based on an awareness of the functional relationship between behavioral and environmental events. Training objectives for the program include specification of criterion performance for successful completion of the program, specific skills to be learned, the sequence in which the behaviors are to be learned, and the specific training procedures to be used. They emphasize the importance of response measures and give an excellent description of the kinds of data and methods of collection used. In addition, an idealized sequence for moving clients from

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immediate primary reinforcement to the normal reinforcement systems found in work settings is described. The basic model was based on the following hypotheses: (a) The deficient repertoires of retarded clients are largely a function of inappropriate or deficient responses to “natural” programs which occur, for the normal child, throughout the developmental period. (b) Remediation of the deficient repertoires can be rapidly accomplished through “compression” of critical elements of the “natural” developmental program through careful selection of target behaviors and refined programming procedures. Data were obtained on nine of 26 clients enrolled in the program. Of the nine, four were involved in a prevocational phase, and five were in community placement programs. Of the four clients in the prevocational group, all of whom were being trained on various components of in-house custodial tasks, three demonstrated significant acceleration in correct performance rates. The five clients in the community placement program were trained for specific preanalyzed job placements in the local county through a two-stage process of simulated in-house preplacement programming, and subsequent on-the-job training. All clients demonstrated rapid acceleration of correct performance in both the simulated and on-the-job conditions (D. Jacobson, unpublished manuscript, University of Oregon, 1972; C. D. Youngberg, unpublished manuscript, University Oregon, 1972). Generally speaking, program effects were more rapidly established in the community placement group. The prevocational groups demonstrated considerably greater degrees of performance variability under progress conditions, a finding which was thought to be partially due to imprecise programming. The results of the pilot effort, while not considered conclusive, were thought to lend support to the “compression” hypothesis (J. E. Crosson, personal communication). The development of vocational skill training procedures is also the goal of a program of research being conducted by the author (Gold, 1972) at Children’s Research Center, University of Illinois. More broadly stated, the research incorporates the many biases evidenced in this review in an attempt to elevate the skill functioning of the retarded and the expectancies of the society in which they live. Gold (1969) utilized task analysis, nonverbal training, and concepts and procedures from The Zeaman and House (1963) Attention Theory to facilitate the acquisition of a complex assembly task by retarded adolescents. Sixty-four moderately and severely retarded adolescents enrolled in four sheltered workshops were trained to assemble a 15piece (training task) and a 24-piece (transfer task) bicycle brake. One-half of the subjects worked with the parts of the training task brake as they came from the factory, having to make discriminations using the shape of each part (form dimension). The others worked with parts that were color-coded (color and form dimensions). Coding consisted of painting that surface of each part that is facing the subject when it is placed in the proper position

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for assembling. All groups worked with the parts of the transfer task brake as they came from the factory (form dimension only). Sixty-three out of sixty-four subjects reached a criterion of six correct out ofeight consecutive trials on both brakes. One subject reached criterion on the training task brake only. The addition of the color cue resulted in the color-form group learning the task in half the trials required by the form-only group. In addition, a significant transfer effect was obtained. One year later, 53 of the original 64 subjects were rerun, with half of the subjects doing the 24-piece brake first. With no interim experience on the brakes or on tasks differing from the subjects' experience before the experiment, highly significant retention effects were obtained (Gold, 1972). The principles and procedures demonstrated have been described subsequently in terms of classroom application (Gold & Scott, 1971) and have led to aprogramofresearch now in progress. Another study completed involved a replication in which no difference between institutional and noninstitutional subjects was found (M. W. Gold, unpublished). In another study, 20 subjects, some from the first study, produced the 15-piece brake individually, 1 hour per day for 10days, with no social or other reinforcements given, except a brief salutation at the beginning and end of each session. Mean production for the 200 hours was 24.9 brakes per hour per subject, with a 6% error rate. Individual subject performance ranged from a mean of 17 per hour to a mean of 60 per hour. The correlation between trials to criterion during acquisition and mean units completed per hour was .26. This raises some questions regarding the validity of conventional work samples and suggests further study of the relationship between acquisition and production. Studies planned or in progress are discussed in Section 111, B, 2. One of the goals of this research is that the techniques can be used by first-line service personnel without much training. Experimenters are chosen with this in mind. They are recruited from among volunteers in the workshops and acquaintances of workshop personnel. None have had any formal training or paid experience working with the retarded. Training consists of from two to six 2-hour group training sessions followed by I week of independent practice, then actual data collection with gradually decreasing supervision. Excellent results have been obtained. No experimenter effects are evidenced in the data. Several of the data collectors have been subsequently hired as shop floor supervisors.

C. Summary of the Present

The field is undergoing many changes. Many service agencies have rea'ched the point where energies formerly devoted to establishing organizations and communications have been fruitful and can now be directed

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toward programs. This change in focus is, in part, facilitated by the beginnings of a technology of instruction, which is developing from research conducted in service agencies by, in most cases, university-based researchers. Much of the work that has been done was directed at prediction and evaluation. The work on evaluation, particularly work sample theory, has provided us with some meaningful information to use as a basis for further development. The work on prediction, in the view of the author, has resulted in little usable information. The development of training procedures is a recent addition to the field. Even the relatively small proportion of energy expended to date has resulted in a substantial body of information awaiting large-scale dissemination and further development. 111. THE FUTURE

The discussion now turns to the future, with the intention of providing impetus for debate. The first two parts of this section follow up on the descriptions given of the present. The third part, prospective involvements, focuses on literature from outside the field which has exciting potential for application. In the third section authors are explicitly identified to maximize the impact of their observations. A. Recommendations for Service Programs

The field has recently concluded an era marked by a tremendous proliferation of school and workshop programs, initiated in most cases through federal and state support. The emphasis has necessarily been directed toward organizational development, funding, and other exigencies of creating new facilities and agencies. Most agencies served as their own prototype in the absence of proven models. At present communities either have programs of their own or have access to information which will eliminate most of the trial and error which has previously been so common. Now it is time to focus on program. The author contends that agencies have necessarily directed the majority of their energies toward the development of organizational structures within which programs operate, but have spent little energy on the programs themselves. Staff, schedules, equipment, and activities do not constitute a program. A program exists only when these resources interact in a setting which results in measurable day-to-day development in habilitants. If the field is to proceed, a technology of habilitation, developed through the cooperation of researchers and practitioners, must emerge.

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There is a large gap between laboratory research on learning and application. There are several reasons for this gap: (1) Few researchers or practitioners study the relationship between principles of learning and the teaching of skills. (2) Laboratory research examines variables for their theoretical interest rather than immediate practical use. (3) There is an absence of research designed to replicate and validate laboratory findings in applied settings. (4) Few attempts have been made to translate the jargon of the laboratory researcher into a form understood by the practitioner (Deno, 1970; Gold, 1968). (5) There is a lack of awareness of, and communication with, resources outside the field (Younie, 1967). (6) There is resistance on the part of both researchers and practitioners to change. Part of the solution is the development of “middle-road researchers” whose function would be to combine the control, methodology, design, and hypothesis testing from basic research with an interest in the solution of applied problems leading to the development of training procedures (Crosson, 1969; Gold, 1970). Such researchers would be responsible for the development and implementation of an applied technology through direct involvement with service agencies, and professional and governmental organizations. Their responsibility would also include the identification of applied problems in need of study. Few programs exist, at present, to train such researchers, or to do this research. Concurrent with the development of middle-road research programs, there must be research on the dissemination of information emerging from this research. The limitations of existing technology are magnified by the virtual wall between available information and current practice. In most fields the available literature lags behind the state of the technical art, making it difficult for other practitioners to acquire the latest techniques available (Marangell, 1971). The lag is indeed large in this field. Valuable information, which has been available for years, has yet to find its way into practice in all but a very few programs. Another factor in need of attention is the relationship between researchers and practitioners. For an excellent description of some of the causes for difficulties between researchers and practitioners in rehabilitation the reader is referred to Rusalem (1969). Most of Rusalem’s comments, however cogent, are not applicable to the kinds of research emphasized throughout this article. His comments refer primarily to research on adjustment, placement, diagnosis, and counseling, whereas this review focuses on skill training. He encompasses the entire field of rehabilitation, and not specifically the retarded, and seems to be referring, primarily, to within-rehabilitation researchers rather than researchers from other disciplines who are applying their skills to the field of rehabilitation.

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Rusalem (1969) feels that for rehabilitation research to be truly productive, researchers should be allowed to proceed on their own, without haiing to attend to the needs and demands expressed by service personnel in the field. For the research emphasized in the article, the author disagrees. Applied researchers do have a responsibility to address the problems of thepractitioner. This is not to suggest that researchers bounce from problem to problem at the dictates of practitioners. However, addressing problems of skill training and the establishment of appropriate work behaviors do not necessarily require longitudinal or other lengthy experiments. The preponderance of lengthy experiments found in rehabilitation can probably be attributed to the emphasis on correlational rather than experimental psychology, which has permeated the field (Cronbach, 1957). Using paradigms from experimental psychology and, in fact, information already acquired using these paradigms, many of the immediate problems of the practitioner could be solved quickly, expediently, and inexpensively. The need is to facilitate meaningful, perpetual, and direct communication between researchers and practitioners. Such a relationship has been inferred before: ". . . it is possible not to perceive that the arts and manufactures of the country are intimately connected with the progress of the severer sciences; and that, as we advance in the cause of improvement, every step requires, for its success, that this connexion should be rendered more intimate [Babbage, 1832, p. 2701 .'' One possible way to expedite communication is for service agencies to support research in their facilities. This means administrative interest, space, access to clients, and some personnel. Much of this kind of support could be absorbed within exisiting agency expenditures while greatly reducing need for grant support to the researcher. The benefits to the agency would include: ( I ) continuous input to the researcher regarding critical areas in need of study; (2) continuous exposure of staff to techniques and procedures used in the research, but equally applicable for service through formal in-service training and informal coffee chats; (3) participation by clients in activities designed to facilitate change in their functioning; (4)agency prestige through research involvement; (5) access to sources of information not normally available to service agencies because of service load. Benefits to researchers would include: (1) an opportunity to identify relevance at a time when it is becoming increasingly relevant to do so; (2) financial support; (3) a way to maintain a realistic perspective; (4)an opportunity to implement and test findings beyond the experimental level; and (5) increased opportunity for validity testing. The establishment of such a movement might be encouraged through the dissemination of the description of such relationships. Since fall, 1970,such a relationship has existed between the Children's Research Center at the

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University of Illinois at Urbana-Champaign, and several service agencies in the Midwest. In each instance, agencies provide research space, access to clients, and some labor as part of a consultation contract. Children’s Research Center provides consultant reports, seminars, scheduled staff observations, and access to a comprehensive library. These relationships have resulted in significant changes in both the agencies and the research. For the agencies, changes have included methods of evaluating clients, production design, material flow, client training, record keeping, and reinforcement systems. Changes in the research program include addressing problems not previously considered and a major change in focus which is discussed in Section 111, B, 4. Parenthetically, the ongoing dialogue between the practitioners and the researchers has been very enjoyable and seems to be a strong reinforcer for continued interaction. For the future, then, the field should actively pursue the establishment of ongoing, in-depth relationships between researchers and practitioners. B. Recommendations for Research

If the field is to proceed maximally, its research must provide aleading edge. Statements regarding accountability, dissemination, client evaluation, training, and new input need to be made, challenged, and addressed if research is to assume a meaningful role. Below is one attempt at such a statement. 1. ACCOUNTABILITY

The resources devoted to research must yield more return than if expended some other way. Unless those in the field are reinforced for research its resources will continue to be utilized for more and more of the same thing. Most practitioners have little reason to consider research a part of the field. Their only contact with it has been vicarious, through coursework or lecture, with little or no information coming to them which is both usable and identifiable as coming from research. If practitioners do not get substantial return for their involvement with researchers, in terms of new information and the implementation of existing information, there will continue to be little or no meaningful interaction, and, eventually, funds for research will dry up. Some researchers feel this process has already begun. To the present, a researcher has been held accountable only in terms of grant reports and publications. This may be sufficient for basic research, or for very esoteric applied research. But for the research emphasized in this review, accountability should go much further. Such research must be

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evaluated by those for whom the research is designed to provide information. This would contribute to the solution of problems regarding translation and implementation. 2.

DISSEMINATION

Information obtained from research must be widely disseminated. The criterion for successful dissemination should be the direct observation of the information disseminated being correctly utilized in agencies not directly connected with the research. The efficacy of current dissemination practices such as courses, publications, convention presentations, and one-shot consultations should be evaluated and revised and new practices developed which involve more bidirectional than unidirectional exchange. The process of dissemination should receive considerable attention in its own right. Research projects designed to disseminate information from other projects are already in operation, but seem to be using conventional and thus far ineffective processes rather than seeking alternatives. Without major changes in the existing dissemination process there is little value in collecting more information, merely to have it sit, unused, on library shelves or administrators’ desks. The research program conducted by Gold (1972) includes considerable emphasis on dissemination. In addition to consulting activities, and the usual publishing and convention presentations, the program has developed a less extensive library on vocational training of the retarded. The library grows constantly, through continuous perusal of reference lists and journals and contains, presently, close to 1500 entries, which are cross-referenced and categorized for efficient accessibility. On an increasing basis, personnel from throughout the Midwest are coming to the center to utilize this resource. This is seen as an integral part of the “middle-road” research program which is discussed in Section 111, A, 1. 3. PREDICTION AND EVALUATION

Research on evaluation should move away from prediction. The voluminous literature reported attests to the monumental failure we have experienced trying to develop valid predictors. Interestingly, the attempts of industry and the military to develop predictors have yielded statistically significant correlations comparable to the work in retardation, but are far more valid and utilitarian because they are used almost exclusively to predict success on a particular job or task (Fleishman, 1965). When this is the case, all of the types of validities and reliabilities can be tested. Even under such ideal conditions, which we could never hope to approach, ultimate decisions still often rest on performance on the task itself rather than on the predictor (Jones, 1966). I t should also be pointed out that prediction, outside of the

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field, is used primarily as a means of screening individuals out of something, rather than as a means of determining how to keep them in. So long as the emphasis remains on generalized training and placement is on menial tasks, prediction should be discarded as a useless drain on our resources. However, if there is a move in the direction of placements which require skill and training, and toward occupational groupings which provide a reasonably stable pool of jobs, then prediction may be possible, necessary, and expedient. Until then, evaluation should concentrate on description rather than prediction. Research on descriptive evaluation must result in procedures which yield demonstrably useful information. Present evaluation procedures result in information which is either very dependable and of little use, or very descriptive but undependable because of semantic ambiguities. What is needed is very dependable and very descriptive information. In Section 11, B, 1, numerous criticisms of existing evaluation procedures were discussed with suggestions for change. The basic concept of work samples appears to provide the most fruitful approach to evaluation. However, major changes in present usage are necessary. Acquisition and production must be separated. The length of time and conditions necessary to learn various tasks should be separated from how fast the production is after the tasks have been learned. If both acquisition and production dataare obtained, on a variety of tasks and levels of difficulty, then highly reliable and descriptive data will be obtained and training will necessarily occur, simultaneously with evaluation. Other variables, such as following directions, working with others, pressure, etc., can all be systematically included. The result would be a matrix of work sample tasks which might constitute the majority of a transitional client’s experience and would yield quantifiable and yet descriptive information and demonstrable changes in behavior. Such an approach would also insure a more realistic relationship between evaluation and training. 4. TRAINING

Research on training must have as its goal the development of procedures which can be implemented in the absence of sophisticated equipment, large sums of money, and highly trained first-line service personnel. For the existing information described in Section 11, B, 2, this means further research to adapt, translate, and disseminate what is already known. This has been discussed above. But most of the technology is yet to be developed. a. Increasing Rates of Existing Behaviors A variety of techniques have been presented, all of which have some merit. The effects of the various procedures, over time, on a variety of tasks, and with all levels of clients should be determined. If possible a comprehensive

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reinforcement program for client productivity should be developed which would have sufficient clarity and alternatives to be universally applicable. Definitions, language, data collection, criteria for the various levels of reinforcement in the sequence, and where to go for help would have to be dealt with very carefully. Although this sounds like an unapproachable panacea, the operant literature does seem to have the necessary basic set of rules for such an accomplishment. Utilizing the same basic rules, a completely separate system should be developed for nonproductive behaviors. Different reinforcers in a different system should be used for eliminating inappropriate behaviors, and establishing appropriate nonproductive behaviors such as self-help, and social and language skills. Although these behaviors obviously interact with productive behaviors (actual job tasks), it is contended here that separate systems and reinforcers would be much better for both clients and staff. In addition, a clearer picture of the relationship between productive and nonproductive behaviors might be obtained. b. Facilitating the Acquistion of New Behaviors In light of the perspective given in this review, the small beginnings of a technology for facilitating the acquisition of new behaviors is surprising. The few studies done evidence the potential impact of this research on the field. The work on autoinstructional devices has a good start. Further work on the development of reasonably priced, flexible hardware is needed. But the development of software will require the greater effort. Verbal and nonverbal programs for basic skills and more common occupational skills should be developed along with explicit procedures for using such materials. The effective use of autoinstructional devices could become a major force in the field. In addition, it might prove even more valuable if data collection were programmed in such a way that information from all agencies using the same programs could be collectively analyzed and reported. The use of transenvironmental programming was discussed. With some translation and more detailed explanation, such a system might be effectively implemented by workshop personnel not familiar with the terminology and the operant perspective. Research utilizing stimulus control procedures, nonverbal techniques, and an emphasis on attentional variables was described. This program of research has just begun. Preliminary data and feedback from service personnel suggest several areas in need of examination: (1) the relationship between task complexity and inappropriate behavior; (2) the effects of extraneous irrelevant stimuli on production and the control of such effects; (3) the effects of various training procedures on transfer and retention; (4) the height of skill achievement obtainable by the retarded at all

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levels; and ( 5 ) ways in which this information can be used to achieve thegoals of the field. An integral part of this research is the utilization of information and techniques not previously applied to the field. The next section deals with some of this information. C. Prospective Involvements

The section on prospective involvements requires some explanation. The areas discussed are not often turned to as resources for the field. While there are occasional isolated reports in the literature, little has been done to utilize these resources. It is intended here to describe these areas briefly for the following reasons: (1) to make the reader aware of information which is available and immediately applicable to both service and research; (2) to indicate potentially fruitful areas for research; and (3) to show the commonalities between these areas and the field. The literature described is but a sampling. Perusal of these areas reveals many relevant topics which are not dealt with here because of space limitations and author bias. For example, the personnel literature abounds with articles on motivation, incentives, organizational efficiency, and other topics of interest. Another fascinating discovery is the literature specifically on the handicapped, written by management for management, which has not found its way into the habilitation literature. Some of this is discussed below. I. INDUSTRIAL MANAGEMENT

The area of management dealing with personnel is replete with professional journals, e.g.. Personnel, Personnel Journal, Personnel Practice Bulletin. A wide variety of topics is discussed in these journals. The sampling described here includes (a) the handicapped, (b) training, (c) the disadvantaged, and (d) productivity. a. The Handicapped Industry has long been interested in the handicapped (e.g., Gilbreth & Gilbreth, 1953).Professionals in the behavioral sciences, however, have been remiss in their attention to this interest. Placement of the retarded into industry is justified by quoting figures, citing articles, and using vocabulary and techniques all from the field. In addition, industry is usually regarded as a customer rather than a partner. The literature of industry evidences an awareness and willingness to participate. Joseph P. Monge, Vice President and Treasurer of International Paper Company, calls for industry to face its responsibility, to revise its job specifications, and to hire the handicapped (Monge, 1969).

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Lawrence N. Loban (1968), Training Supervisor at Crown Zellerbach Corporation, San Francisco, California, describes the problem of imposed handicap. With considerable insight, Loban describes the practice of industry to keep handicapped individuals from certain jobs, not because of their inability to perform the job adequately, but just because the handicap exists. He discussed the problem of arbitrarily imposed educational requirements. Especially of interest is his perception of the result obtained when industry ignores its obligations to the handicapped. Using an industrial rather than social mode of expression, he says that industry must eliminate unnecessary barriers itself if it is to remain free from legislation which will mandate hiring practices and reduce freedom of selection. This is a logical position, understandable to industry, and probably far more cogent than the same position as it might be expressed from within the field. If business does not assume responsibility for its power, someone else will (Davis 8c Blomstrom, 1966). Davis (1967) also feels that once a power is lost to government, it is lost for a long time. This provides us with apowerful tool for getting industry to participate in the habilitation of the retarded. This is, do it on your own and retain control before you are forced to do it and lose control. For further discussion of the social responsibility of industry the reader is referred to Carrington (1970), Carrol and Pati (1970), and Petit ( 1967). Describing the employment of handicapped individuals in Australia, Howe (1965) points out that physical or mental impairments should be considered as handicaps only as they serve to reduce prospects of employment, Through selective matching of individuals and positions, most impaired individuals can find employment. One of the most valuable aspects of the industrial management literature is the description of the performance of handicapped workers, written by management. W . G . Firth (1965) is the Managing Director of P. J. Firth Ltd., Enfield, New South Wales, which employs over 200 individuals. Among his observations are: (1) The production of retarded workers is comparable to that of other workers. (2) Retarded workers are more consistent in their work. (3) They move around and talk less than nonretarded workers. (4) They fit in well with other employees. (5) They are practical. (6) They tend to be more stable than nonretarded employees in areas involving simpie repetitive tasks where high labor turnover is normally experienced. Firth also describes briefly how his company got involved with the retarded through his attendance at a service club meeting. At the time the article was written, 13 retarded individuals were employed at the plant. The information provided by Firth is not new to the field. But the validation by industrial management provides invaluable support for promoting the placement of retarded individuals in industry.

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Kelly and Simon (1 969), business and management professors, surveyed company experience with retarded workers. They found plant managers concerned about issues regarding productivity, training, speed, supervision, endurance, and safety. To obtain information on these issues, they held interviews with supervisors of all retarded employees who had been rehabilitated and placed in competitive employment situations in the Greater Denver Metropolitan Area. Their findings concurred with those of Firth, despite differences in cultural and geographical setting, and in the backgrounds of the authors. Reports such as these from industry, must be found, publicized, and used effectively if the field is to achieve its goal. b. Training Use of the word training in the vocational habilitation of the retarded was discussed in Section I, B. Current research on training of the retarded, as defined in this review, is discussed in Section 11, B, 2. Training, as the term is used in industry, usually refers to specific skills taught for specific jobs (Ackerman, 1968; Broadwell, 1966; Whitesell & Pietrus, 1965). Considerable energy has been expanded to develop techniques for training, many ofwhich are relevant for use with the retarded. The literature exemplified here evidences several trends which might well be duplicated by the field. First is the attempt to define the role and objectives of training. For industry, training means closing the gap between existing and desirable conditions (Prieve & Wentorf, 1970). This requires describing the desired state of the organization. According to McGehee and Thayer (196 1) this involves: (I) organizational analysis, i.e., an examination of the whole organization; (2) operational analysis, i.e., examination of the task requirement for specific jobs; and (3) manpower analysis, which concerns the skill, knowledge, or attitudes needed by each employee. Prieve and Wentorf (1970) point out the need to include individual differences and attitudes in the analyses in order to effect meaningful training, even though objectives are ultimately tied to organizational efficiency rather to than personal fulfillment. The issue of personal fulfillment versus organizational efficiency is a topic of debate in industry. Some feel that the objectives of training are related solely to organizational efficiency (e.g., Denova, 1968; Hennessey, 1967), while others believe that individual and societal goals are equally important (e.g., Ackerman, 1968; Turrentine, 1968; Weir, 1971). These issues have their parallel in the habilitation field. Sheltered workshop staffs often debate the relative importance of production and habilitation. It is contended here that good habilitation procedures will facilitate good production. It is interesting that there is a movement in industry toward social responsibility and personal fulfillment (e.g., Ackerman, 1968; Loban, 1968; Monge, 1969),

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and a movement in the field toward organizational efficiency (e.g., Chione & Snyder, 1968; Crosson et al., 1970; Screven et al., 1971). These movements could result in the elimination of two major barriers to the habilitation of the retarded: ( I ) resistance on the part of industry to participate; and (2) the present inability of the field to provide clients with marketable work skills. Until training objectives are specified in terms of specific, general, and salable skills for either competitive or sheltered employment, meaningful training programs will not emerge. Industry can provide a model. For an in-depth study of how industry develops objectives for training the reader is referred to the works of Ackerman (l968), McGehee and Thayer (l96l), Whitesell and Pietrus (1965), and Prieve and Wentorf [ 1970). A second trend in the industrial training literature relates to the identification and evaluation of training devices. The use of devices and techniques requiring considerable verbal facility is common in industry, but adaptations to the retarded seem feasible. For example, programmed instruction (Hennessey, 1967) and audio-visual machines (White, 1968), both of which have been used in the field (see Section 11,B,2), are used in avarietyofways not familiar to the field. For a survey of the use of training aids in industry the reader is referred to Chin-Quan and Eastaugh (1969). A third, and perhaps the most relevant trend in the industrial training literature, is the descriptions of specific company training programs. Companies share training successes with one another, despite their competitive nature, whereas programs in the field seldom benefit from each other’s efforts. F. A. M. Mackay (1966), Training Officer at Fibremakers, Ltd., Bayswater, Victoria, describes learning principles underlying their training program. Included are the following: ( I ) Preliminary exercises will facilitate learning for some tasks. (2) Learning of complex tasks by breaking them down into a series of simple tasks; (3) The simple tasks are best combined progressively with particular attention paid to the transitions; (4)Awareness of criteria will facilitate learning; ( 5 ) Spaced practice is better than massed practice; (6) Provisions must be made for gradual development of stamina. Mackay also discusses task analysis of each operation to determine sensory and manual skill requirements, bottlenecks in production, and faults in production procedures. This information is used to develop a training manual for the training program. Mackay justifies the program in terms of reductions in training time, wastage, and wages paid to trainees, and, most significantly, in terms of the company being enabled to meet the demand for skilled labor. All of his points are directly applicable to the field and need little, if any, modification to be implemented. A similar program is described by P. Smith (1968). As Manager of Staff Training and Development for Arnott-Brockhoff-Guest Pty. Ltd., Burwood,

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Victoria, Smith trains operators involved in highly repetitive manual jobs related to the manufacture of biscuits. He describes training for wrapping and packaging operators and gives details of how training is scheduled so as to minimize fatigue and maximize efficiency. Training includes basic exercises to prevent muscle strain, the development of judgment of length, the use of equipment, hygiene, introduction to the plant, weighing, bagging, quality control, safety, and wage structure. The training schedule and most of the topics are highly relevant to the field. He also notes that people of lower intelligence often take longer to train but are more reliable in performance, and find job satisfaction where others tend to lose concentration. Further discussion of industrial training practices may be found in the discussion on the disadvantaged which follows. c. The Disadvantaged

The literature on training programs for the disadvantaged and hardcore unemployed has literally exploded in the last few years. This literature is germane to the field for several reasons: (1) Those populations labeled either retarded or disadvantaged are by no means mutually exclusive, if for no other reason than the fallible assumptions of the labeling process; (2) The socioeconomic status of the retarded and the disadvantaged are, in most cases, the same; (3) Societal and industrial barriers exist for both categories; (4) Educational experiences in both categories are similar; ( 5 ) The area of training the disadvantaged has received considerable attention and support; ( 6 ) Many individuals with expertise outside the field have applied their skills to the area; (7) There is increasing pressure from government for those presently serving the retarded to address the problems of the disadvantaged. The literature here is only a small sampling of what is available, but should suffice to indicate the potential for further inquiry. For an historical review of federal programs for the disadvantaged the reader is referred to Levine (1970). He contends that training must be for the highest possible occupational achievement if favorable cost-benefit figures are to be obtained, and if individuals are to receive maximum benefits of training, both economic and personal. Levine calls for more effort in evaluating the human gains resulting from these programs. A similar effort is needed in the field, one which also utilizes a cost-benefit approach. Doing so might facilitate better recognition of successes and failures and direct attention to critical issues of training and organization. Largely as a result of federal pressure and funds, industry is turning its attention to the problems of the hardcore unemployed. It is impossible to discern, in most cases, whether this results from genuine interest in the problem as a human one or only as it serves corporate interests. In any case,

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maximum advantage must be taken of this interest. This means the inclusion of that segment of the hardcore population additionally labeled retarded. Some companies are involved in large-scale efforts to provide much more than just vocational training. For example, Pitney Bowes participates in a program which includes identification and recruitment, counseling, training of basic academics, and even the building of integrated, moderate-income housing (Turrentine, 1968). Eastman Kodak contracted with the Board for Fundamental Education, one of numerous nonprofit organizations established to raise the living standards and aspirations of the undereducated (Gassler, 1967). Their program consists of basic courses in reading, consumer skills, and arithmetic. Classes are characterized by noncompetitive situations, seminar-type interactions, much reinforcement, high-interest material, and no presuppositions regarding entering skills of students, all characteristics relevant for use in the field. In another program, called New Careers (Riessman, 1968), companies such as General Foods, Oxford Chemical Corporation, and Supermarket General Corporation are hiring workers with minimum education, without training or experience, and are providing basic training from the start. For a critical analysis of these kinds of programs the reader is referred to Weir (1971) and to Sloan (1970), whose perspectives are equally applicable to programs in the field. Programs such as these can serve the field in at least two ways: (1) by servicing clients, and (2) by providing models for training and for working cooperatively with industry and government. d. Productivity The industrial literature on worker productivity has heavy emphasis on motivational factors (Ackerman, 1970; Herzberg, 1968), and does not contain, in the author’s opinion, particularly useful information for application to habilitation programs. However, perusal of this literature would provide the reader with an understanding of what clients will be exposed to if they enter competitive employment. For descriptions on industrial approaches to motivation, the reader is referred to Ackerman (1970), Brethower and Rummler (1966), and Herzberg (1968). For excellent descriptions on industrial worker productivity, see Groff (197 1) and Lupton (197 1).

2. INDUSTRIAL ENGINEERING Problems relating to production line efficiency and worker performance on assembly lines have long been the concern of industrial engineers. As the habilitation field develops, these concerns will become increasingly a part of the picture. The two areas of the literature sampled here should demonstrate the value of further study.

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a. Job Design and Job Enlargement The industrial revolution and subsequent developments have resulted in a pattern of job design characterized by task specialization, low-level skill requirements, very specificjob content, procedures and use of tools, repetitousness, and minimum control by the worker of the production process (Bucklow, 1967). The job design literature is heavily influenced by the work of L. E. Davis (e.g., 1957, 1966; Davis & Canter, 1956).The references cited provide a wealth of information on industrial practices regarding production design. The one specfic aspect to be covered here is the contention of Davis that job enlargement is an important concept for industry which, from the author’s view, has considerable application to the field. The reader is referred also to Conant and Kilbridge (1969, Guest (1957), Pauling (1968), Stewart (1967), and Tuggle (1969). Job enlargement refers to increasing the responsibility of workers, quantitatively and/or qualitatively. It differs from conventional job design in that workers become responsible for their own pace, quality control, rectification of mistakes, machine set-up and repair, and choice of method. The result of job enlargement is to produce jobs at a higher level of skill (Hulin & Blood, 1968). Hulin and Blood feel that job enlargement is overrated and base their findings on a comprehensive review of the literature. Hulin (personal communication) feels that the use of job enlargement, as presented below, does appear valid and is not subject to the criticisms he and Blood raise. The concept of job enlargement seems almost to epitomize the direction inferred from this review, especially for lower-level retarded individuals. The retarded should be doing much more complex work. Ifthe effects ofjob enlargement transfer, it could be hypothesized that retarded individuals would evidence less of the behaviors that have precipitated such labels as short attention span, distractible, hyperactive, etc. In addition, increased habilitative value and increased potential for placement would result from increased skill training and greater responsibility. The job enlargement literature should be carefully studied by the field. If the concepts and criticisms are understood, it could become a valuable resource. b. Methods- Time Measurement Methods-Time Measurement (MTM) is another controversial area of industrial engineering. The procedure, developed for use in industry, is based on the early work of the Gilbreths on motion study (e.g., Gilbreth, 1911; Gilbreth & Gilbreth, 1917, 1953) and Frederick W. Taylor on time study (e.g., Taylor, 1895, 1903, 1911). The MTM system, first published in 1948, analyzes manual operations into their required basic motions and assigns a fixed, predetermined time standard to each motion. The time standards are determined on the basis of voluminous data, and take into consideration the nature of each motion and its context (Maynard, Stege.

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merten, & Schwab, 1948). MTM is one of several predetermined motiontime systems. These systems, which are designed to determine work time standards, are restricted to operations whose performance times are affected only by the workers. They are characterized by their ability to arrive at a time standard in advance of the operation actually being performed (Rohmert, 1971). Criticisms include a lack of regard for individual operator characteristics, e.g., sex, age, height, degree of fatigue, degree of practice of skill, and motivation; no regard for working conditions, e.g., light, noise, temperature; and no regard to work place layout, e.g., height, degree of fatigue, and presentation of articles being worked on (Rohmert, 1971). Of these systems, MTM is seen as the most relevant for use in workshops and with the retarded for the following reasons: ( I ) Performance ratings are not necessary; (2) Only one sample of the product is necessary to determine a standard; (3) MTM is familiarto industry; (4) Good production procedures can be established before production begins (Stroud, 1970). The basic unit of movement in MTM is the Gilbreth Basic Element, or therblig. These units have also been referred to as basic divisions of accomplishment (Lowry, Maynard, & Stegemerten, 1940). Gilbreth is credited with identifying 17 basic elements, or therbligs (Holmes, 1945; Maynard et al., 1948). Since his original work, the list has expanded and contracted several times (Honeycutt, 1963; Morrow, 1946). At present, MTM uses the following nine basic movements: reach, move, turn and apply pressure, grasp, position, release, disengage, eye travel time and eye focus, and body, leg, and foot motions. The unit of time used in MTM is the Time Measurement Unit (TMU), which equals .00001 hours, or .0006 minutes, or .036 seconds. The decision to have the basic unit as such was based on the established industrial practice of expressing production standards in terms of decimal hours, and the need for small units of time to measure the minute therbligs. TMU values are assigned to each therblig according to the conditions under which it occurs. Several variables contribute to each value. Distance moved has the most significant effect on performance time. It affects TMU values for reach, move, and body, leg, and foot motions. Distances up to 30 inches, about as far as is practical to move without body movement, are accommodated in the tables. Types of motion before and/or following the therblig, are taken into account for reach and move. The three types of motion are: (1) at rest when therblig begins and ends; (2) in motion at beginning or end; and (3) in motion at beginning and end. Weight allowance isa variable for move. Tables contain weight allowances for up to 47.5 pounds, and take into consideration actual weight of object moved, effects of resistance, e.g.. brushing thick paint onto a surface, and the effect of premovement muscular tension. Symmetry is a variable for position, and considers the amount of rotation a part might require for positioning. Ease ofhandling is a

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variable for position and for disengage and is divided into easy or difficult to handle. Class offit is a variable for position and fordisengage. It refers to the amount of pressure needed to insert or separate parts. Categories include loose, close, and exact or tight. Level of conrrol is a variable for reach, move, grasp, release, and body, leg, and foot motions. This variable receives considerable attention. Dimensions of control which contribute to the TMU values include muscular, visual, and mental control and level of motion, e.g., automatic, moderate accuracy, and much accuracy. To put the system in some perspective, Rohmert (197 1) describes the average length of one motion element as .005 minute. A working cycle which takes 1 minute might be split up into some 200 motion elements, each of which is defined by perhaps five variables. Thus about 1000 data items might be needed in order to set up the time standard for one operation of 1 minute duration. The time needed to carry out the analysis for such an operation would be between 150 and 300 minutes. There are significant implications for using MTM in sheltered workshops, in research on skill training, and perhaps in research on all types of motor learning. At the most practical level, the use of MTM in sheltered workshops is good business. In one of the few reported instances (Chione & Snyder, 1968) the gross income of the workshop doubled, as did the income of the trainees. Within 6 months the figures had tripled. Chione and Snyder applied MTM methods to several aspects of workshop operation. First, to physical layout, rearranging work stations and eliminating unnecessary steps. Second, MTM was used for bidding. The effect was to provide accurate data on which to base estimates of output rate, and consequently, more competitive bidding. Third, it was used to compare individual client performance with that of average workers, using percentage ratings. Fourth, it provided an accurate means of paying commensurate wages, that is, normal pay for that portion of the normal labor rate produced. Lastly. it was used to identify and eliminate those basic motions that a client could not perform. There are other possible uses of MTM in the vocational training of the retarded. In evaluation, application of MTM to the work sample movement (see Section 111. B, 3) might facilitate a large increment in its value. For instance, work samples could be compared or equated on the basis of their therbligs, and the classes and conditions of each. In training, therbligs could be systematically added to facilitate acquisition and faded out prior to production. It should be noted that the use of predetermined motion-time systems is not universally accepted in industry and receives considerable criticism. However, these criticisms do not appear to be directed toward the kinds of applications suggested, but rather to labor-management issues.

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IV. CONCLUDING COMMENTS

The field of the habilitation of the mentally retarded, as it exists today in the United States, has been described. I t exists within a context where the population with whom it deals is perceived by almost everyone as being far less capable than is really the case. Long-standing expectancies, which have recently been shown to be inappropriate, are slow to change. The majority of efforts expended have been on the development of organizational structures, leaving little for actual program. But this is beginning to change as a result of established structures and an emerging technology. The goal of the field was expressed as maximum opportunity for growth. The following is a summary of the debatable recommendations made throughout this review, intended to help facilitate that goal.

I . The focus must change from organizational considerations to the development of program (Section 111, A). 2. The field must develop middle-road researchers (Section 111, A). 3. Service agencies and research agencies must establish ongoing relationships (Section 111, A). 4. Resources devoted to research must yield more return than ifexpended some other way (Section 111, B. 1). 5. Research must be evaluated by those for whom the research is designed to provide information (Section 111, B, I). 6. Information obtained from research must be widely disseminated (Sections 111. A and 111, B, 2). 7. Research on evaluation should move away from prediction (Section 111, B, 3). 8. Research on evaluation must result in procedures which yield demonstrably useful information (Section 111, B, 3). 9. Research on training must have as its goal the development of procedures which can be implemented in the absence of sophisticated equipment, large sums of money, and highly trained first-line service personnel (Section 111, B, 4). 10. A comprehensive, universally applicable reinforcement system for productivity should be developed (Section 111, B, 4). 11.The field should identify and adapt relevant information from other disciplines (Section 111, C). 12. Training objectives must be clearly defined (Section 111, C, 1). 13. The application of MTM and job enlargement should be investigated (Section 111, C, 2). The basis for a technology is established. The resources are available, and the field is ready for change. A number of recommendations have been made with the intention of helping to stimulate the dialogue which must ensue if the personnel are to meet their responsibility to those in their charge.

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and Motor Skills, 1958, 8, 231-234. Doleshal, L. L.. Jr., & Jackson, J. S. Evaluation and follow-up study of theTexasCooperative School Program. Rehabilitation Literature, 1970. 31, 268-269. Dolnick. M. M. Contract procurement procticer of rheltered workshops. Chicago: National Society for Crippled Children and Adults, 1963. Dolnick. M. M. Contractor opinions of sheltered workshops. Journal of Rehabilitation, 1961. 30(2). 23-25. Dolnick, M. M. Sheltered workshop programs in The Netherlands. Rehabilitation Record, 1971, 12(2), 35-38. Dubrow, M. Work procurement and job production. American Journal of Mental Deficiency, 1958, 63, 355-359. Dybad, G. Rehabilitation for the adult retardates. American Journal of Public Healthj 1961, 51, 998-1004. Eldred, D. M. Use of P.I. at Vermont State Hospital. Programmed Instruction. 1965,5(2), 9-1 I . Elkin, L. Prediction productivity of trainable retardates on experimental workshop tasks. American Journal of Mental Deficiency, 1967, 11, 576-580. Eskridge, C. S. An approach through special education and vocational rehabilitation in preparing educable retarded youth for work. In F. E. Lord, J. Stubbins, & H. V. Wall (Chm.), Institutes on work education for educable retarded youth. Los Angeles: California State College at Los Angeles, 1964. Pp. 11-14. Etienne. J.. & Morlock, D. A . A pre-vocational program for institutionalized mental retardates. Training School Bulletin. I91 I , 61, 228-234. Evans, G. W., & Spradlin, J. E. Incentives and instructions ascontrollingvariablesofproductivity. American Journal of Mental Deficiency, 1966.71, 129-132. Farber, B. Mental retardation: Its social concept and social consequences. New York Houghton, 1968. Ferguson, R. G. Evaluating vocational aptitudes and characteristics of mentally retarded young adults in an industrial-agricultural workshop. American Journal of Mental Defciency, 1958, 62, 787-79 I. Firth, W. G. Employment of mentally handicapped workers. Personnel Practice Bulletin, 1965, 21(5), 24-25. Fleishman, E. A. The prediction of total task performance from prior practice on task components. Human Factors, 1965, I, 18-27. Fleishman, E. A , , & Hempel, W. E., Jr. A factor analysis of dexterity tests. Personnel Psychology. 1954, I, 15-32. Franks, V., & Franks, C . M. Classical conditioning procedures as an index of vocational adjustment among mental defectives. Perceptual and Motor Skills, 1962, 14. 241-242. Fry, M. A predictive measure ofwork success for high grade mental defectives. American Journal of Mental Deficiency, 1956, 61, 402-408. Gassler, L. S. How companies are helping the undereducated worker. Personnel, 1967,44(4), 47-55. Gilbreth. F. B. Motion study. New York: Van Nostrand, 191 I. Gilbreth. F. B., & Gilbreth. L. M. Applied motion studv. New York: Sturgis & Walton, 1917. Gilbreth, F; B., & Gilbreth, L. M. Motion study for the handicapped. In W. R. Spreigel& C. E. Myers (Eds.), The wrifings of the Gilbrerhs. Homewood, 111.: Richard 0. Irwin, 1953. Gold, M. W. Preworkshop skills for the trainable: a sequential technique. Education and Trainingofthe Mentally Retarded. 1968, 3, 31-37. Gold, M. W. The acquisition of a complex assembly task by retarded adolescents. Final Report, May 1969, University of Illinois at Urbana-Champaign.

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Gold, M. W. Middle road research: a statement and an example. Paper presented at theGatlinburg Conference on Research and Theory in Mental Retardation, Gatlinburg, Tennessee, March 1970. Gold, M. W. Stimulus factors in skill training of the retarded on a complex assembly task acquisition. transfer and retention. American Journal of Mental Deficienq. 1972. 76, 517526. Gold, M. W., & Scott, K. G. Discrimination learning. In W. B. Stephens (Ed.), Training the developmentally young. New York: John Day, 197 I. Greenstein, M., & Fangman, T. J. Vocational training for the mentally retarded in a metropolitan setting. Focus on Exceptional Children, 1969, l(5). I d . Groff, G. K. Worker productivity: an integrated view. Business Horizons, 1971, l5(2), 78-86. Guest, R. H. Job enlargement-a revolution in job design. Personnel Administration, 1957, 20(2),9-16. Hamerlynck, L. A., & Espeseth, V. K. Dual specialist: vocational rehabilitation counselor and teacher of the mentally retarded. Mental Retardation. 1969,7(3), 49-50. Heiny, R. W. History of special education. In L. C. Deighton (Ed.), Encyclopedia oj'education. Vol. 8. New York MacMillan, 1971. Hennessey, D. E. Getting results from programmed instruction. Personnel, 1967,44(5),69-73. Henze, R., & Meissner, A. Cooperative school-rehabilitation centers. Final Report, July 1970, Project RD-1810-G interdistrict school. Rehabilitation program for less able retarded adolescents. Educational Research and Development Council of theTwin Cities Metropolitan Area, Minneapolis. Herzberg, F. One more time: How do you motivateemployees? HarvardBusiness Review, 1968, 46(I), 53-62. Holmes, W. G. Applied time and motion study. New York: Ronald Press, 1945. Honeycutt, J. M., Jr. The basic motions of MTM. Pittsburgh Maynard Foundation, 1963. Howe, M. A. Employment of the handicapped. Personnel Practice Bulletin, 1965, 21(5), 7-13. Huddle, D. D. Work performance of trainable adults as influenced bycompetition, cooperation, andmonetary reward. American Journal of Mental Deficiency, 1967, 72, 198-21 1. H u h , C. L., & Blood, M. R. Job enlargement, individual differences, and worker response. Psychological Bullelin. 1968, 69(1), 41-55. Hunt, J. G., & Zimmerman, J. Stimulating productivity in a simulated sheltered workshop setting. American Journal of Mental Deficiency, 1969,14, 43-49. Jones, M. B. Individual differences. In E. A. Bilodeau (Ed.), Acquisition of skill. NewYork: Academic Press, 1966. Pp. 109-146. Katz, E. (Ed.) Second Progress report, Unpublished report on URA Project No. RD-205, Aid Retarded Children, San Francisco, 1959. Kazdin, A. Toward a client administered token reinforcement program. Educationand Training #fthe Mentally Retarded, 1971, 6, 52-55. Kelly, J. M.. & Simon, A. J. The mentally handicapped as workers-a survey of company experience. Personnel, 1969, 46(5), 58-64. Kennedy, R. J. R. A Connecticut community revisited. Report on Project No. 655 January 1966, Office of Vocational Rehabilitation, U.S. Department of HEW, Washington, D. C. Kirk, S. A.. Karnes, M. B., & Kirk, W. B. You andyour retarded child. New York: Macmillan, 1955. Kokaska. C, J. The vocational preparation of the educable mentally retarded. Ypsilanti. Mich.: University Printing, Eastern Michigan University, 1968. Kolstoe, 0. P. The employment evaluation and training program. American Journal of Mental Deficiency, 1960, 65, 17-31.

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Kolstoe, 0. P. An examination of some characteristics which discriminate between employed and not not employed mentally retarded males. American Journal of Mental Deficiency, 1961, 66,472482. Kugel, R., & Wolfensberger, W. Changing patterns in residential servicesfor the mentally retarded. Washington, D. C.: President’s Committee on Mental Retardation, 1969. Kylen, N. G., Sommarstrom, I . , & Akesson, A. Work adjustment and developmental levels in mental retardation. Unpublished report, Institution of Applied Psychology, University of Stockholm, 1971. Ladas, P. G. Worksample learning rates of the mentally retarded trainee as indicators of production in a worktraining center. Personnel and Guidance Journal, 1961,39, 396-402. Levine, A. S.Job training programs for the disadvantaged: how can they become more effective? Welfare in Review, 1970, 8(1), 1-7. Levine, M. J. Subcontracting-rights and restrictions. Personnel, 1967, 44(3), 42-53. Loban, L. N. The problem of imposed handicap. Personnel Journal, 1968,47,323-327. Logan, 0 . L., Kinsinger, J., Shelton, G., & Brown, J. M. The use of multiple reinforcers in a rehabilitation setting. Mental Retardation. 197 I , 9(3), 3-6. Lowry, S. M., Maynard, H. B., & Stegemerten, G. J. Time and motion study. New York: McG raw-H ill, 1940. Lupton, T. Wage and salary payment for higher productivity. Work Study & Management Services. I97 I , 15, 272-28 I . Mackay, F. A. M. Training of semi-skilled workers at Fibremakers Ltd. PersonnelPractice Bulletin, 1966, 22(3), 17-26. Marangell, F. The new language of skills. Personnel Journal, 1971, 50, 280-287. Mathews, M. G. One hundred institutionally trained male defectives in the community under supervision. Mental Hygiene, 1919,6, 332-342. Maynard, H. B.. Stegemerten, G. J., & Schwab, J. L. Mefhods-Time Measurement. New York McGraw-Hill, 1948. McGehee, W.. & Thayer, P. W. Training in business and industry. New York Wiley, 1961. Mclntosch. W. J. Follow-up study of one thousand non-academic boys. Excepfional Children, 1949, 15, 166-170, 191. Meadow, L., & Greenspin, E. Employability of lower level mental retardates. American Journal of Mental Deficiency, 1961, 65,623628. Miller, L. E. A follow-through high school program for the mentally handicapped. American journal of Mental Deficiency. 1954, 58, 553-556. Mocek, E., Lerner, J. S., Rothstein, J. H., & Umbenhaur, G. W. Report of special on-the-job training demonstration project for mentally retarded youth and adults. Children’s Home for Mentally Retarded Children and Adults, San Mateo, California, 1965. Monge. J. P. Untapped labor force. Personnel, 1969, 46(5). Morrow, R. L. Time study and motion economy. New York Ronald Press. 1946. Muller, V., & Lewis, M. A work program for the mentally retarded students. Journalof Secondary Education, 1966,41(2). 75-80. Nelson, N. Workshops for the handicapped in the United Stares. Springfield, Ill.: Thomas, 1971. Nixon, R. A. Impact of automation and technological change on employability ofthe mentally retarded. American Journal of Mental Deficiency, 1970, 75, 152-155. O’Neil, L. P. Evaluation of relative work potential: a measure of self-concept development. American Journal of Mental Deficiency. 1968, 72, 6 14-6 19. Overs, R. P. Evaluation for work by job sample tasks. (Prelim. ed.) Cleveland, Ohio: Vocational Guidance and Rehabilitation Services, 1964. Overs, R. P., Koechert, G. A., & Bergman, R. H. Obtaining and using actual job samples in a work evaluation program. Final Report Project No. RD-412, VRA, Vocational Guidance

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1903, June, Paper No. 1003. Taylor, F. W. The principles of scientific management. New York: Harper, 191 I . Thomas, H. P. The employment history of auxiliary pupils between 16 and 21 years of age in Springfield, Massachusetts, Proceedings and Addresses oJ the American Association for the Study of the Feebleminded. 1928, 33, 132-148. Tobias, J. Evaluation of vocational potential of mentally retarded young adults. Training SchoolBulletin, 1960, 56, 122-135. Tobias, J., & Gorelick, J. The effectiveness of the Purdue Pegboard in evaluating work potential of retarded adults. Training School Bulletin, 1960, 57, 94-104 (a). Tobias, J., & Gorelick, J. A n investigation of “orderliness” as a characteristic of mentally retarded adults. American Journal oJMental Deficiency, 1960,64, 761-764 (b). Tobias, J., & Gorelick, J. The utility of the Goodenough Scale in the appraisal of retarded adults. American Journal of Mental Deficiency, 1960, 65, 64-68. (c). Tobias, J., & Gorelick, J. The Porteus maze test and the appraisal ofretarded adults.American Journal of Mental Deficiency, 1962, 66, 600-606. TOWER: Testing orientation and work evaluation. New York Rehabilitation Institute for the Crippled and Disabled, 1967. Tredgold, A. F. A text-book of mental deficiency (amentia). London: Bailliere, 1908. Tuggle, G. Job enlargement: an assault on assembly line inefficiencies. Industrial Engineering, 1969, 1(2), 26-3 I . Turrentine, J. L. A corporate program for urban action. Personnel, 1968, 45(4), 15-20. Usdane, W. M. Vocational counseling with the severely handicapped. Archives of Physiological Medicine and Rehabilitation, 1953, 34, 607-616. Wagner, E. E., & Hawver, D. A. Correlations between psychological tests and sheltered workshop performance for severely retarded adults. American JournalofMentalDeficiency, 1965.69.685-691, Weir, K. C. Hard core training and employment. Personnel Journal, 1971, 50, 364-366. White, G. R. New audio-visual approach cuts employee training time. PersonnelJournal, 1968, 47, 509-510. Whitesell. W. E.. & Pietrus. J. T. Training and the learning process. Personnel. 1965,42.4550. Williams, P. Industrial training and remunerative employment of the profoundly retarded. Journal of Mental Subnormality, 1967, 13. 14-23. Wolfensberger, W. Vocational preparation and occupation. In A. A. Baumeister (Ed.), Mental retardation. Chicago: Aldine, 1967. Pp. 232-273. Younie, W. J. Increasing cooperation between school programs for the retarded and rehabilitation services: an expkrimental teaching approach. Mental Retardation, 1966,4(3), 9-14. Younie, W. J. Developing instructional materials for vocational education of the retarded. In G. E. Ayers (Ed.), New directions in habilitating thementallyretarded. Vocational Rehabilitational Subsection, American Association on Mental Deficiency Conference, Denver, May 1967. Younie, W. J., & Clark, G. M. Personnel training needs for cooperative secondary school programs for mentally retarded youth. Education and Training of the Mentally Retarded, 1969.4, 186-194. Zeaman, D., & House, B. J. The role of attention in retardatediscrimination learning. In N. R. Ellis (Ed.), Handbook of mental dejiciency. New York: McGraw-Hill, 1963. Pp. 159-223. Zimmerman, J., Overpeck, C., Eisenberg, G. & Garlick. B. Operant conditioning in sheltered workshops. Rehabilitation Literature, 1969, 30, 326-334. (a). Zimmerman, J., Stuckey, T., Garlick, B., & Miller, M. Effects of token reinforcement on Productivity in multiple handicapped clients in a sheltered workshop. Rehabilitation Literature, 1969, 30, 3441. (b).

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Consolidating Facts into the Schematized Learning and Memory System of Educable Retardates1 HERMAN H. SPIT2 E. R. JOHNSTONE TRAMING AND RESEARCH CENTER, BORDENTOWN. NEW JERSEY

I. Psychology’s Frame of Reference .............................................. 11. Psychology’s Forgotten Past ........................... .... 111. The Idealized Memory System ............................. A. Attending ........ .... ............................. B. The Icon ............................................................. C. Immediate Memory . D. Storage ............................................................... E. Retrieval ............. IV. Discovering Redundancy A. Redundancy in Digit S B. Redundancy in Paired V. Summary ................. References ...............

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150 151 151

I. PSYCHOLOGY’S FRAME OF REFERENCE

If a curious observer asks, “How much can you say with a large degree of certainty about educable mental retardates?” what should we reply? For that matter, how many enduring facts are there in the entire field of psychology? We are quite busy with our complicated analysis of variance, and ‘This paper is a slightly modified version of a paper by the same title presented at the Gatlinburg Conference on Research andTheory in Mental Retardation, Gatlinburg, Tennessee, March, 1972. I appreciate assistance and critical readings by members of the Johnstone Research Department, and thank John J. Winters, Jr., for suggesting the use of free recall in the paired-associate experiment. 149

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often enough emerge with 3- or Cway interactions which defy interpretation. Herbert Simon ( 1970), comparing psychology’s experimental paradigms with the parametric experiments associated with physics, made a telling point when he noted that the null hypothesis was unnecessary in determining that, in a vacuum, objects fall at the rate of 32 feet per second per second. But there are many who believe that the human organism is much too complicated for this type of lawful assessment. Perhaps-but by using probability levels and a standard performance criterion, it is possible to reply to our curious observer that, in fact, there are some things we can say with a great deal of confidence about normal human organisms, and yes, even about educable mental retardates.

II. PSYCHOLOGY’S FORGOTTEN PAST

Research is most productive when undertaken within a theoretical structure. Happily, experimental psychology has finally emerged from dust bowl empiricism, shaken itself free of the cobwebs, and recognized the rather elementary fact that a great deal takes place between the input of the stimulus and the organism’s response. When I say “emerged” I do not mean that psychologists had never recognized the reality of this fact. Prior to behaviorism it was an essential part of psychology’s domain. The following quotation is from an issue of a journal called The Psychological Clinic. The author is Charlotte Easby-Grave (1924): What seems to be increased capacity (beyond six years of age) is nothing more than proficiency. dcpending on the ability to organiLe and retain. It is possible that the modal spanof four to five obtained from children of the six year level is the true span, and the higher spans received from older children and adults are the result merely of grouping and organization, and not a (rue span [p. 2791.

G. M. Whipple (1910) stated, in an issue of the Journal of Educational Psychology: “The development of these grouping schemes is perhaps the most important single factor in practice improvement, at least after habituation of the preliminary tasks [p. 2611 .” And here is what R. S. Woodworth wrote in 1913: If we look hack over this account of the associations formed in memorizing, we cannot fail to be impressed with their great variety-serial position, connections of items within a group and of group with group, and extra ideas centering in various ways. We may well be struck also with the importance of perception or apprehension in the learning process-perception of relations, patterns and meanings. To look at a list of numbers or nonsense syllables, you would think that the thing to be done was to forge links between the adjacent terms, but the actual learning proceeds largely in quite another way. It does not start with elements and unite these, but it starts with groups, or even with the whole series, and proceeds largely by analysis and the finding of parts and relations [from Woodworth, 1938. p. 351.

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151

Here are Woodworth’s (1938) comments on his own 1913 statement. The quotation is from the first mimeographed edition of this chapter written in 1913 before the influences of Gestalt psychology began to be felt. The conclusions expressed were based mostly upon the work of G. E. Miiller. They have not been overthrown but rather confirmed by more recent studies. The importance of an initial orientation in the material to be learned, of locating and grouping the items, and offinding or inventing meaningful relations has become ever more certain with the progress of investigation [p. 351.

George Katona (1940) titled his book “Organizing and Memorizing.” At the same time, Wolfgang Kohler (1940) was saying: “We have practically identified specific interaction in perceptual grouping with specific interaction as a basic event in recognition and recall [p. 1351.” During Watson’s reign, and during the rule of his heir, B. F. Skinner, there was an underground movement. And now, in 1972, such terms as instinct, thought, ideation, organization, and imagery have emerged from the past. As with Lovecraft’s hidden creatures, they have been there all along, waiting.

111. THE IDEALIZED M E M O R Y SYSTEM

The theoretical structure which will be used here is the idealized memory system, trichotomized for simplicity into input, storage, and retrieval. The organism attends to the stimulus, which enters the central nervous system, perseverates for a short time in the sensory register (SR),and is stored temporarily (short-term memory, STM) and, perhaps, more permanently (long-term memory, LTM). Once stored in long-term memory, the stimulus can be retrieved at some later time or, perhaps, may be lost forever (see, e.g., Atkinson & Shiffrin, 1968).Can we characterize these symbols-attending, sensory register, working STM, storage, and retrieval-by numbers? A. Attending

The first element, attending, has problems enough, particularly when various aspects of a stimulus compete for attention. This is an area where Zeaman (in press) and his co-workers have been seeking to change symbols to numbers. But the problems change with the task. For example, if educable retardates are shown a card with numbers on it, and are told to remember the numbers, most of them will attend to the numbers. Nevertheless, there must be wide variations in how fast they read the numbers and, more important, in how subjects distribute their attention. Another way of looking at the initial input is to use Neisser’s (1967) twolevel approach. O n the first level, the material is scanned; on the second level, the observer focuses attention on a particular aspect of the material.

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Evidence from visual search experiments (Spitz, 1969) and from tachistoscopic recognition experiments (Winters & Gerjuoy, 1969) suggest that retardates do not scan material as efficiently as equal CA normals. Their approach is less patterned, less methodically sequential. This is part of the subjective input problem to which we will return. B. Thelcon

The perseveration of a stimulus-in vision, at least-has been given many labels: the memory after-image, the poststimulus trace, the icon and, most recently, the sensory register. All refer to the fact that, when avisual stimulus is flashed on a screen, the observer’s image of the stimulus lasts beyond the stimulus offset. I n other words, a faithful representation of the stimulus persists in the central nervous system. Of course, the duration of the icon is dependent on the experimental conditions, particularly on the brightness and duration of the display. In natural circumstances the icon cannot persist too long, or continuous input would be distorted. Nevertheless, the special conditions arranged to study the icon tell us something about the central nervous system. Here we have some numbers to replace our symbols, and the results may appear surprising. Studies on backward masking and sensory integration with normal subjects suggest that the duration of the icon in normals ranges from 20 t o 75 mseconds. Our own experiments (Spitz & Thor, 1968; Spitz & Webreck, 1971) indicate that the duration of the icon for educable retardates is at least within this range, and perhaps a little longer. In other words, there appears to be no retardate deficit in the duration of the icon; in fact, it is possible that retardates have a more lasting icon which could interfere with rapid input of stimuli. Results from a number of studies (Holden, 1970; Thor, 1971) do indicate that educable retardates do not process repetitive stimuli as rapidly as do normals. C. Immediate Memory

Once into the system, the material resides temporarily in immediate memory, labeled variously as STM, consciousness, working memory, and channel capacity. Here, too, we can plug in some numbers. One of the oldest measures of immediate memory is the digit span, but the criterion has been vague. Is channel capacity the number of digits correct 100% of the time, or 50% of the time? It seems to me that, in fact, 90% is the best criterion for channel capacity, since it approaches perfection and yet allows for minor errors. The literature was searched for all digit span studies with nonretarded

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153

subjects in which the results were presented as percentage correct, or in which the percentage correct could be calculated. Only studies in which the time per digit was about 1 second were included. The results are shown in Table I. The period covered was 1916 to the present. The presentation modes were Auditory Sequential, Visual Simultaneous, o r Visual Sequential, and the response modes were written or oral. The results are very clear. The digit span channel capacity is 6 k 1. This is a fact we can convey to our curious observer. Of course, these were unpracticed subjects. The digit span can be increased to 13 or 14 digits because, with practice, subjects became more proficient in grouping the digits. Still, even with large numbers of digits the upper limit for subjective grouping appears to be about 5 (e.g., 13 digits would be grouped as 5-5-3) (Martin & Fernberger, 1929). What about educable retardates? There is much less evidence available, but what there is suggests a digit-span channel capacity of 3 4 digits (see Table 11). Note that the time per digit is much longer than 1 second, except for the last study (where the span is 4 digits), and that all presentations are Visual Simultaneous. However, these findings can be supplemented by a huge data pool of Auditory Sequential presentations available from the Wechsler tests, if it is conceded that a large number of subjects compensates for the lack of experimental control. We took from the Johnstone files the raw Digits Forward scores of 183 students 13-19 years old, who had performance IQs of 50-79. We used Wechsler’s double-error criterion, in which the testee must fail two consecutive digit spans at a single length; but we also scored the test using a single error criterion. The results, shown in Fig. 1, indicate that the 90% criterion is reached at 3 digits. Using the double-error criterion, the group comes very close to reaching a channel capacity of 4. It appears that, with a little practice, 4 would be reached, but 5 is clearly beyond capacity. We have, then, a digit-span channel capacity of 3-4 for educable retardates, and 5-7 for normals, including college students. There is no overlap. This is a remarkably small difference, and unlikely to account for the huge difference in general performance between educable retardates and college students. Of course, a small difference can be compounded over time. Nevertheless, it appears that the rote memory of educable retardates, though not as good as normals of equal CA, is not so bad that it can account for the difference in general performance. Before leaving this area, a word should be said about the magical number 3. It is, with educable retardates, about as haunting as Miller found the magical number 7 with normals. Consider, for example, Ellis’s (1970) findings using the probe technique. When digits were used, retardates per-

e

vl

P

TABLE I NORMALS'IMMEDIATE MEMORY SPAN (290'6 CORRECT) FOR DIGITSW H E N EXPOSURE TIMEIS 1 2 3 SECONDS Author

Exposure time

PER

DIGIT'

Presentation methodb

Response mode

162-164 College subjects 475 College subjects

Aud. Seq. Vis. Sim. Aud. Seq.

Written Written Written

6 7 6

Aud. Seq. Aud. Seq.

Written Oral

6 7

I seddigit 1 sec/digit 1 sec/digit

1263 Collecge subjects 261 College subjects 100, probably College subjects 7 Colleagues 24 College subjects 10 College subjects

Aud. Seq. Aud. Seq. Aud. S e q . Vis. Seq.

Written Written Oral Oral

5 5 5

1.3 sec/digit 1.3 sec/digit

44 High school subjects

Vis. Sim. Vis. Sim.

Oral Oral

7 6

Subjects

Capacity ~

Gates (1916)

0.75 sec/digit

Humpstone (1919) Brotemarkle (1924) Exp. I Exp. VI Guilford & Dallenbach (1 925) Oberly ( 1928) Crannell & Parrish (1957) Dalrymple-Alford (1967) Spitz er a!. (1 972) Exp. 111 Exp. IV

1 sec/digit

1 sec/digit 1 sec/digit

0.7 secidigit

22 Adults

aFrom Spitz (1972b). Copyright 1972 by the American Psychological Association and reproduced by permission bAud. = auditory; Vis. = visual; Seq. = sequential; Sim. = simultaneous.

5

;n

r: J m

5r!

N

m

D

r m P

7J

TABLE I1 EDUCABLE RETARDATES'IMMEDIATE MEMORYSPAN ( 2 90% CORRECT) Exposure time

Author Spitz (1966, Data reanalyzed) MacMillan (1970a)

2.5-3 sec/digit 2.5-3 seddigit

MacMillan (1970b)

2.5-3 sec/digit

Spitz et al. (1972)

1.2-1.5 sec/digit

Subjects

40 Ret's" 60,14.63 10 Ret's 65,12.79 30 Ret's

n:

zz

3 FOR

DIGITS

Presentation methodb

Response mode

Vis. Sim.

3

z

0

Capacity

%

Oral

3

P

Vis. Sim. (Subjects read aloud) Vis. Sim.

Oral

3

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Herman H. Spitz

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FIG. I . Performance of educable retardates on the Wechsler Digits Forwardsubtest. From Spitz (in press).

formed at about 95% accuracy on the 3-digit series, but dropped to 80% on the 4-digit series. The average number of digits correctly recalled over increasing list length remained at about 3-3+ digits. D. Storage

We turn now to storage. Studies with normals suggest that an almost infinite amount of material can be stored. In one paired-associate study (Wallace, Turner, & Perkins, 1957), normals were instructed to form a mental picture connecting pairs of words. For example, if the pair was hat and lion, the mental image formed to connect them might be alion wearing a hat. The subjects were allowed to set their own pace, and the entire sequence was presented just once. In testing for recall, subjects were given one word of each pair, and had to supply the other. For 500 pairs, 496 (out of 500) words were correctly recalled; for 700 pairs, 664 (out of 700) words were correctly recalled. The upper limit of human storage could not be reached and, because of time limitations, testing was discontinued. Studies using prompted recall (Bahrick, 1969), cued recall (Tulving & Pearlstone, 1966), and recognition (Postman, Jenkins, & Postman, 1948) also suggest the awesome size of the human memory bank.

SCHEMATIZED LEARNING A N D MEMORY SYSTEM OF EDUCABLE RETARDATES

157

A large number of similar verbal mediation studies with educable retardates suggest that, when proper mediators are supplied, storage of paired associates-even when measured by recall of backward associations-is quite good. Thurlow and Turnure (1971), for example, report that, when given eight paired associates, each pair embedded in two-sentence paragraphs, educable retardates recall over 90% correct on the first trial. Given 16 paired associates, they recall 70% on the first trial. And studies from Scott’s laboratory (Urbano, Scott, & McCarthy, 1971) suggest that retardates’ recognition memory is also rather good. If a person recognizes an object as one he has seen before, then a representation of all or part of that object must have been stored. The storage capacity of educable retardates, once the material has gotten into the system, does not seem to be badly impaired. E. Retrieval

There is only one element remaining: retrieval. Free recall is a measure of retrieval, and the evidence suggests that the unaided free recall of retardates is relatively poor. In verbal clustering studies, when words which are amenable to clustering are presented randomly, retardates recall-by the fifth trial-only about 11 of 20, compared to 17 recalled by college students. But when the words are presented already clustered, they recall about 14 words. When the words are presented in clusters, and also requested by category names, the retardates recall 17 words-equal to the unaided recall of college students (Gerjuoy & Spitz, 1966). In Tulving’s terminology (Tulving & Pearlstone, 1966), the words were always available, but they were just not accessible. Input structuring, particularly temporal and spatial grouping, can be of some help in immediate rote memory. But more important, diverse types of input structuring can be of great assistance when dealing with large amounts of material, and when longer peroids of retention are required (Spitz, 1966). A related problem is whether retardates effectively integrate new material with appropriate material previously learned. When material enters the memory system it enters a background of the organism’s past learning. Consequently in much of learning it is important not only that the material itself be organized, but that the learner integrate new material with old. This is a form of subjective organization about which we know too little. I n any case, we have little control over this type of organization, and a great deal of control over the organization of the presented material. The essential point when dealing with retardates is that material must be presented in a form which makes it more easily accessible during free recall. The importance of input organization for educable retardates is not in

Herman H . Spitz

158

getting the material into storage; almost all of the material, apparently, will be stored. But it must be stored in a form which makes it more easily accessible. It appears that retardates are routinely plagued by a phenomenon which also affects normals. Recent evidence indicates that when normals forget, it is primarily because they fail to gain access to stored material. That is, forgetting is cue-dependent rather than trace-dependent (Tulving & Psotka, 1971). In my view, a primary difference between educable retardates and normals is the speed and manner in which retardates scan and selectively organize the material for storage. Chaotic input makes for chaotic retrieval.

IV. DISCOVERING R E D U N D A N C Y In this regard, I would like to present some recent studies which tell us something a bout how retardates handle material which contains information-reducing potential. I refer to redundant material.

A.

Redundancy in Digit Spans

We have used the digit span test to find out how readily retardates discover redundancy (Spitz, Goettler, & Webreck, 1972; Spitz & Webreck, 1972). Table I11 is an example of various digit arrangements for a 6-digit string. Note that there are two types of 50% redundancy: Couplet Redundancy, in which each number immediately follows itself once; and Repetition Redundancy, in which the first half of the numbers are repeated. Under Grouped Conditions, the redundancy is emphasized by underlining and spatial separation. Four-, six-, and eight-digit lengths were used, and the presentation was Visual Simultaneous. Results can be summarized i s follows: (1) For educable adolescent retardates and equal MA normals the presence of couplet redundancy is easier to discover than the presence of repetition redundancy. This can be seen in Fig. 2. Note that performance of retardates and third graders on couplet redundancy, represented by the hatched line, is generally better than TABLE 111

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on repetition redundancy, represented by the dotted line. (2) When repetition redundancy is externally emphasized-by underlining and spatialseparation -performance on those digits improves dramatically (see Fig. 3). These are new groups of subjects. Note particularly the dotted line at numerosity 8 for retardates. The improvement by retardates, and also third graders, is shown in Fig. 4. The hatched line represents retardates. On the 6- and 8-digit strings, there is 60-1 14% better performance for subjects receiving the repetition redundancy externally grouped than for subjects receiving it ungrouped. Retardates who had the 6- and 8-digit redundant strings underlined and grouped performed about twice as well as retardates who did not. When there is no external grouping, performance on the couplet redundancy is superior because couplet redundancy is more readily discovered. About 90% of the retardates responded in groups of two when presented with couplst redundancy. On the other hand, when presented with digits containing repetition redundancy, only 63% responded in groups of threes to 6-digit strings, and only 40% responded in groups of fours to 8-digit strings. But when repetition redundancy was externally emphasized, three-three responding went from 63 to 88%, and four-four responding went from 40 to 78%. Couplet redundancy is recognized more easily because the first two digits cue the subject to its presence. However, repetition redundancy, once

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recognized, results in better recall because the first half is immediately available for repetition. We know when a redundancy is discovered by the manner in which the subject groups the digits. When couplet redundancy is recognized, the response is in couplets. When repetition redundancy is recognized, the subject groups the first half and the second half. And performance is tied to recognition. For example, in Fig. 5 the solid line shows the percent correct for 8digit strings presented to educable retardates in the manner shown at the bottom of the figure. In this study (Spitz & Webreck, 1972), subjectswent from an ungrouped, to agrouped, then back to an ungrouped condition. The striped line shows the agreement between the redundancy and response grouping; that is, the percentage of time subjects responded in groups of fours. The parallel relationship shows quite clearly that performance is tied to grouping strategy. It also shows that retardates do far better when the initially presented material is grouped for them, but that they do learn to recognize and utilize the redundancy, once having been given external help. As a matter of fact, retardates can learn to use 50% repetition redundancy even without outside help. Figure 6 shows the performance of retardates given 6-, 8-, and 10-length digits containing repetition redundancy (Spitz

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& Webreck. 1972). The “U” symbolizes ungrouped digits, and the “G” symbolizes externally grouped digits. The control group (bottom curve) received 6-, 8-, and 10-digit strings which were not redundant. These results show that, although external grouping clearly assists the retardates on initial testing, by the third session (even when it occurred seven days later) the subjects who were never given external grouping were performing as well as subjects who were. Educable retardates can, with a little practice and experience, discover and utilize 50% redundancy. 6 . Redundancy in Paired Associates

The problem with using digits is the difficulty in varying redundancy level. However, there are other ways of systematically varying redundancy. Table IV shows material used in a paired-associate study (Spitz, 1972a). The redundancy is in the response terms. For example, in the 83% redun-

SCHEMATIZED LEARNING AND MEMORY SYSTEM OF EDUCABLE RETARDATES

163

dancy condition, the subject who recognizes the redundancy merely has to remember what number A goes with, and then just say B to the rest of the numbers. In other words, the material is 5/6, or 83% redundant. At 67% redundancy, the subject who recognizes that there are two A’s and four B’s need learn only 4-A and 7-A, and that the rest are B’s. This material was presented by the standard anticipation method, and the results are shown in Fig. 7. T A B L E IV PAIRED-ASSOCIATE STIMULI AT

FOUR

LEVELS OF REDUNDANCY

6 B 7 8 4 A

8 B 3 B

5 B

6 I 4 3 5 8

B A A B B B

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Different subjects served in each condition. All subject did very well in the 83% redundancy condition, in which there was only one A, and -except for one point-errors increased as redundancy level decreased. The retardates are most affected at the first decrease in redundancy, but the eighth graders are not really affected until the 33% redundancy level. On an intuitive level, it seemed likely that if the material were presented all at once, subjects would perform much better. That is, with all the pairs presented simultaneously, the fact that in the 67% condition, for example, there were two A’s and four B’s should be immediately apparent. This procedure was built into the next experiment. In addition, subjects were given free recall. That is, after studying the pairs for 18 seconds, all six stimulus terms were presented at once for 18 seconds. Subjects were told that they could respond in any order they wished. Thus, if a subject recognized that there were two A’s and four B’s, the opportunity was available to respond with the two A’s first, then with the four B’s. Results are shown in Fig. 8, along with the results from the anticipation method shown previously in Fig. 7. Results from the anticipation method are shown by the striped line; results from the simultaneous/free recall method by the solid line. The retardates are shown in the first panel. Note particularly the 33% redundancy condition. Surprisingly, at the lowest redundancy level retardates did much worse when the material was presented simultaneously. Only 2 of 12 reached the criterion of two correct trials by

Herman H. Spitz

164

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our cutoff point of 30 trials. They performed very poorly when presented with all the material at once. The third graders did slightly, but not significantly, poorer than they had in the anticipation condition; but the eighth graders (in the third panel) did significantly better in the simultaneous than in the anticipation condition. Apparently, the retardates were overwhelmed when presented with the high information material all at once, and were unable to find a successful strategy to deal with it. The equal C A normals, on the other hand, when presented the material all at once, distributed their time more efficiently. They quickly discovered the presence of redundancy and made use of it. This is demonstrated in Fig. 9, where amount of “clustering” behavior is shown. Clustering, as in categorical clustering experiments, is quite simply the number of times a response letter follows itself. For example, if-

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Third bd Ret'd

*---*

Herman H. Spitz

166

in the 67% redundancy condition-a subject correctly responded with the two A’s first, then with all the B’s, clustering score would be 4. Percentage of clustering (i.e., obtained divided by total possible) was tabulated for each subject who had reached the criterion of two consecutive correct trials prior to the 30-trial limit. The curves are drawn backward, starting from the criterion trials, so they represent different trial points for different subjects. Note that in the 50% and 67% redundancy conditions there is a sharp rise in clustering at criterion. Most subjects suddenly recognized the redundancy, and responded accordingly. On the 33% redundancy condition, this occurred only for the eighth graders. Most of the third graders, on the other hand, reached criterion the hard way, by learning all six paired associates without making effective use of the redundancy in the material. Retardates are not represented in the third panel, since only two reached criterion. These results strongly suggest that the major difference between subject groups in the 33% redundancy condition is the greater capacity of the eighth graders to discover and utilize the redundancy. Of course, the materials and procedures are quite different, but the results do suggest that when redundancy is reduced from 50% to 33”/;j,it is not readily recognized or used by retardates. Results also suggest that, for high-information material, simultaneous presentation is somewhat catastrophic. Even with total time constant, feeding in the material a little at a time is much the better way. For normals of equal CA, on the other hand, with simultaneous presentation they find and use the redundancy more readily and, consequently, perform more efficiently. V. SUMMARY

A number of studies have contributed to our understanding of how retardates perform at each of the stages in the schematized learning and memory system. It appears that a major difference between educable retardates and equal-CA normals occurs at the retrieval stage, and results largely from retardates’ inefficient organization at input. If material is stored in organized form, external and/or subjective cueing is more likely to result in successful retrieval. Examples of retardates’ difficulties in recognizing and utilizing information-reducing aspects of a stimulus were presented as evidence of their general problem in selectively scanning and organizing material at input. REFERENCES Atkinson, R. C., & Shiffrin, R. M. Human memory: A proposed system and its control processes. I n K. W. Spence & J.T. Spence(Eds.), Thepsychologyoflearningandmotivarion: Advances in research and theory. Vol. 2 . New Y o r k Academic Press, 1968, Pp. 89-195.

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Bahrick, H. P. Measurement of memory by prompted recall. JournalofExperimentaI Psychology, 1969, 79. 213-219. Brotemarkle, R. A. Some memory span test problems. Psychological Clinic, 1924, 15,229-258. Crannell, C. U., & Parrish, J. M. A comparison of immediate memory span for digits, letters and words. Journal of Psychology, 1957.44, 319-327. Dalrymple-Alford, E. C. Repetition and immediate memory. British Journal of Psychology. 1967, 68, 63-67. Easby-Grave, C. Tests and norms at the six year old performance level. Psychological Clinic, 1924, 15, 261-300. Ellis, N. R. Memory processes in retardates and normals. In N. R. Ellis (Ed.), International review of research in mental retardation. Vol. 4. New Y o r k Academic Press, 1970. Pp. 1-32. Gates, A. 1. Mnemonic span for visual and auditory digits. JournalofExperimentalPsychology, 1916, 1, 393403. Gerjuoy, I. R., & Spitz, H. H. Associative clustering in free recall: Intellectual and developmental variables. American Journal of Mental Deficiency, 1966,10, 918-927. Guilford, J. P.. & Dallenbach, K. M. The determination of memory span by the method of constant stimuli. American Journal of Psychology, 1925, 36, 621-628. Holden, E. A., Jr. Unimodal and multimodal sequential information processing in normals and retardates. Journal of Experimental Psychology, 1970, 86, 181-185. Humpstone, H. J. Memory span tests. Psychological Clinic, 1919, 12, 196-200. Katona, G . Organizing and memorizing. New York: Columbia University Press, 1940. Kohler, W. Dynamics in psychology. New York: Liveright, 1940. MacMillan, D. L. Effects of input organization on recall of digits by EMR children.American Journal of Mental Deficiency, 1970,14, 692496. (a) MacMillan, D. L. Comparison of nonretarded and EMR children’s use of input organization. American Journal of Mental Deficiency, 1970.14, 762-764. (b) Martin, P. R.,& Fernberger, S. W. Improvement in memory span. American Journal ofpsychology, 1929, 41. 91-94. Neisser, U. Cognitive psychology. New York: Appleton, 1967. Oberly, H. S. A comparison of spans of “attention” and memory. American Journal ofPsychology, 1928, 40, 295-302. Postman L., Jenkins, W. O., & Postman, D. L. An experimental comparison of activerecall and recognition. American Journal of Psychologv. 1948, 61, 51 1-519. Simon. H. A. How big is a chunk? Measuring information processing parameters that are directly observable. Paper presented at the meeting of the Eastern Psychological Association, Atlantic City, New Jersey, April 1970. Spitz, H. H. The role of input organization in the learning and memory of mental retardates. In N. R. Ellis (Ed.), International review of research inmentalretardation.Vol. 2.NewYork: Academic Press, 1966. Pp. 29-56. Spitz, H. H. Effects of stimulus information reduction on search time of retarded adolescents and normal children. JournalofExperimentaI Psychology, 1969,82,482-487. Spitz. H. H. Effects of redundancy level and presentation method on the paired-associate learning of educable retardates, third graders, and eighth graders. Journal of Experimental Psychology, 1972, 95, 164-170. (a) Spitz. H. H . Note on immediate memory for digits: lnvariance over the years. Psychological Bulletin. 1972, 78, 183-185. (b) Spitz. H. H. The channel capacity of educable mental retardates. In D. K. Routh (Ed.), The experimental psychology ofmental retardation. Chicago: Aldine, in press. Spitz. H. H . . Goettler. D. R., & Webreck. C. A. Effects of two types of redundancy on visual digit span performance of retardates and varying aged normals. Developmental P.rychologico1. 1972. 6 . 92-103.

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Spitz, H. H., & Thor, D. H. Visual backward masking in retardates and normals. Perception & Psychophysics, 1968,4, 245-246. Spitz, H. H., & Webreck, C. A. Effects of age and mental retardation on temporalintegration of visual stimuli. Perceptual and Motor Skills, 1971. 33, 3-10. Spitz, H. H., & Webreck, C. A. Effects of spontaneous vs. externally-cued learning on the permanent storage of a schema by retardates. American Journal of Mental Deficiency, 1972, 77, 163-168. Thor, D. H. Numerosity discrimination of repetitive visual stimuli by mildly retarded adolescents and normal children. Journal of Abnormal Psychology, 1971, 78, 30-34. Thurlow, M. L., & Turnure. J. E. Mental elaboration and the extension of mediational research: List length effects on verbal elaboration phenomena in the mentally retarded. Research and Development Center in Education of Handicapped Children Research Report No. 19, University of Minnesota, Minneapolis, 1971. Tulving, E., & Pearlstone, 2. Availability versus accessibility of information in memory for words. Journal of Verbal Learning and Verbal Behavior, 1966, 5, 38 1-39 I . Tulving, E., & Psotka, J. Retroactive inhibition in free recall: Inaccessibility of information available in the memory store. Journal of Experimental Psychology, 1971, 87, 1-8. Urbano, R. C., Scott, K. G., & McCarthy, K. Recognition memory: The relationship of accuracy and latency of response under different memory loads in retardates. Journal of Experimental Child Psychology, 197 I , 12, 270-277. Wallace, W. H., Turner, S. H., & Perkins, C. C. Preliminary studies of human information Storage. DA Project No. 3-99-12-023, U.S. Army Signal Engineering Laboratories, Fort Monmouth, New Jersey, 1957. Whipple, G. M. The effect of practice upon the range of visual attention and of visual apprehension. Journal of Educational Psychology, 1910, 1, 249-269. Winters, J. J., Jr., & Gerjuoy, 1. R. Recognition of tachistoscopically exposed letters by normals and retardates. Perception & Psychophysics, 1969, 5, 2 1-24, Woodworth, R. S. Experimental psychology. New York Holt, 1938. Zeaman, D. One programmatic approach to retardation. In D. K. Routh (Ed.), Theexperimental psychology of mental retardation. Chicago: Aldine, in press.

An Attention-Retention Theory

of Retardate Discrimination Learning' MARY ANN FISHER AND DAVID ZEAMAN UNIVERSITY OF CONNECTICUT, STORRS. CONNECTICUT

I. Introduction ................................................................. A. Background .................................................

.............................................. ..................................

C. Outline of Attention-Retention Theory A. Statics

171 171 171 171

..........

A. Response or Stimulus Selection ............ B. Components, Compounds, and Configurations ............................ C. S-S vs S-R ..............................................................

......................... V. One or Two Le .............................................. .......................................... A. The Issue ....... ................................ ......................... VI. Strengths or Relative Strengths ...............................................

A. The Issue ................................................................ B. Other Theoretical Positions . ............................ C. Statement of Our Position ............................ D. Justification .......................................... VII. Gradual vs All-or-Nothing Learning ..................... A. The Issue ................................................................

179 183 184

185 185 185 186 186 187 187 188

189

IThe research reported in this paper has been supported by Grant M-1099 of theNational Institute of Mental Health, and Research Career Program Award K6-HD-20,325 of theNationa1 Institute of Child Health and Human Development, U.S. Public Health Service. This research has been made possible by the active cooperation of Francis P. Kelley, Superintendent of the Mansfield State Training School, Mansfield Depot, Connecticut. I69

Mary Ann Fisher and David Zeaman

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B. Discriminative Learning .............................. 189 C. Our Position .......... .......................... D. Justification ............ .............................. 1% ....... 191 VIII. Mechanism of Learning ...................................... A. The Issue ................................................ B. Alternative Theoretical Positions .................... .............

IX. Generalization ............ ..............

....................................... ........................................

X. B. A-RTheory

...

197

. . . . . . . . . . . . 199

XI. Modifiability of the Links .... A. The Issue: Modifiable vs No

able Aspects of Attention

....................................... D. Justification ................... XII. Breadth of Attention .............. A. The Issue ......................

206

.................

C. A-R Theory ......................... D. Justification XIII. Feedback .....................................................

..............................

B. Theoretical Alternatives

217

...........

XIV.

A. Overview ............................

xv.

......................

C. Justification

................... 242 B. Alternative Theoretical Positions ....................... C. Statement of Our Theoretical Position

XVI. Control Processes and Structural Features A. The Issue ...............

...... ...............................

244

171

ATTENTION-RETENTIONTHEORY

I. INTRODUCTION A. Background

An attention-retention theory of retardate discrimination learning will be presented together with empirical support in the form of 40 experimental effects deducible from the theory. The two processes of attention and retention are not the only ones postulated to occur; the name Attention-Retention (or A-R) Theory was chosen because the inclusion of these two processes distinguishes A-R theory from other models of discrimination. The new formulation is a modification, extension, and amalgam of two other theories, the Attention Theory of Zeaman and House (1963) and the Retention Theory of Atkinson and Shiffrin (1969). The former was explicitly designed for the two-choice discrimination learning of retardates in 1963, but in the intervening years, new data, particularly in the area of retention, have made revision necessary. The retention postulates of Atkinson and Shiffrin were written to apply to the data of a variety of verbal learning and memory experiments with normal adult subjects, but we have found their major ideas both adaptable to the domain of retardate discriminative learning and compatible with Attention Theory. 6 . Organizational Scheme

First a qualitative outline of A-R Theory will be presented followed by a concise quantitative statement of the theory and an outline of the data domain of the theory. Thirteen sections then follow, each identifying a basic issue on which theorists of discriminative processes have taken opposing (or at least different) stances. The issues are described, our position stated, and then justified on empirical and rational grounds. C. Outline of Attention-Retention Theory

A simplified picture of the overall structure of the theory can be seen in an information-flow, block diagram of the principal events and transformations to which the theory is addressed. Stimulus information in the discriminative display is conceived in part to be dimensional in nature. The dimensions, such as color, form, position, size, etc., are not defined independently. Any categorical aspects of the surround, including categories of meaning, are candidates for dimensional status. If the theory works (handles data adequately) with a particular dimensional specification, then we have discovered a good dimension. Later sections will deal with the strengths and weaknesses of this formulation.

172

Mary Ann Fisher and David Zeaman DIMENSION SELECTION

CUE-SICNIQICANCE

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FIG.1. Block diagram of Attention-Retention Theory.

The Attention Selector chooses one or more dimensions and transforms these to the respective cues of the dimensions. For example, attention to the color dimension reveals that the presented cues are red and green, or attention to position indicates that one stimulus is on the left, the other on the right. The Attention Selector or Response is the first member of the theoretical chain of two major stages. The next subjective link in the chain is an instrumental choice of one of the cues in the two-choice display. This choice is mediated by two substages, the first a cue-significance stage in which the various cues are associated with different reward-outcomes, and the second substage a rule for combing the cue-significances to form an overt response of approach (or avoidance) of one of the two discriminative stimuli. The reward (or nonreward) outcome of the particular cue selection made on a trial is stored in a tripartite memory system. The association of a cue and its reward-outcome (an S-S connection) is first entered into a time-decaying Short-Term Store. This S-S information may then be entered into a Rehearsal Buffer (which acts as a subjective repetition of previous training) or the information may by-pass the Buffer and go directly into the Long-Term Store. The Buffer output also goes into the Long-Term Store. There may be conflicting information in the memory stores. Either of the two stimulus objects may have multiple cues some of which are remembered as having been associated with reward and some as associated with nonreward. This dilemma is resolved by a choice-mechanism or decision-rule called the Response Generator, which takes all the available cue-reward

ATTENTION-RETENTION THEORY

173

information and converts this to an overt response of selection of one of the two stimulus objects. The Feedback Loop is the remaining structural aspect of thediagram. The cue-reward information contained within the memory system leads not only into the Response Generator but is also fed back to the Attention Selector. This means that what the subject remembers about the reward values ofthe cues affects his decision on which stimulus dimension to attend to. This completes a sketch of the structure of the theory. Missing are not only the details of operation of the parts, but also the dynamic aspects or changes in the quantity and qualities of information stored in the various blocks of the diagram. Two principal types of changes, or processes, are postulated by the theory: learning and retention. With respect to learning, the two inferred links in the chain (attention and cue-significance) undergo changes. The terminal reward or nonreward on each trial causes acquisition or extinction, respectively, of both dimensional selection and cue-significances. Equations are written describing the increments and decrements in strengths of attention to the various dimensions. Learning equations are also written for the transition of cue-significancesinto the Long-Term Store. The acquisition and extinction parameters (0’s) of these equations are viewed as structural features of the organism reflecting fixed capacities possibly relatable to fixed components of intelligence. The dynamic properties of the retentional system include a spontaneous rate of decay from the Short-Term Store (a), a limit on the number of items that can be rehearsed in the Buffer (p), and a parameter (a) representing the probability that new cue information will replace old items in an already filled Buffer. The S parameter is considered a structuralfeature of the organism (as are the learning, or 0, parameters) while the other parameters(@and p ) are classified as control processes in that they can be altered by experiential factors. These are not regarded as likely candidates for relation to fixed components of intelligence, hence to retardation. More will be said later of the “control process”-“structural feature” distinction when the details of the dynamic aspects of the system have been explicated. II. A CONCISE QUANTITATIVE STATEMENT OF THE THEORY

The theory may be stated in three sets of postulates: one static set which determines within-trial responding, and two sets describing the dynamic processes of learning and retention occurring between trials. The learning postulates portray the effects of trial outcomes on the associative strengths. The retention postulates deal with the changes which take place in associa-

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tive strengths between the outcome of the previous trial and the start of the current trial. A. Statics

1 . DEFINITIONS Let Ci, ( i = 1, 2. 3, . . . , n) be the set of cues on the ith dimension in the positive stimulus on trial 1 . Ci,is the corresponding set in the negative stimulus. Subscripts i and t are omitted in the following discussion when dimension i and trial r are understood not to vary. Further define r = covert selection of C r = covert selection o f C ? = null response R -t = overt selection of positive stimulus R, = overt selection of negative stimulus. -

The short-term strength of the positive cues, S(r), is the sum of the Short-Term Store (STS) strengths, S, of each of the cues in C.

The Buffer positive cue strength, B(r), is the sum of Buffer strengths, B, of each of the cues in C. B(r)

=

B(c) CEC

The long-term positive strength, L(r), is the sum of the Long-Term Store (LTS) strengths, L, of each of the cues in C.

Corresponding equations can be written for the strengths of the negative cues i n T : for STS,Buffer, and LTS. Later developments require the computation of differences in cuesignificance for C a n d r . Let s = number of cues in both STS and C err, and b = number of cues in both Buffer and C err, then define cue significance differences AS

= (S(r)

-

S(t)(/s

A B =(B(r) - B(f)l/b

AL = 2 L(r)/[L(r) LTS respectively

+ L(f)]

-

1, attributable to STS. Buffer, and

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ATTENTION-RETENTION THEORY

2. POSTULATES a. Strongest Store Prevails The memory store which has the strongest difference in cue-significance determines the preference, P(r), for C o v e r c . If the maximum of AS, AB, and AL is

I

+

AS (from STS), then P(r) = .5 .5 [S(r) - S(i)]/s A B (from Buffer), then P(r) = [B(r) - B(i)]/b AL (from LTS), then P(r) = L(r)/ [L(r) P(i) = 1 - P(r)

+ L(f)]

6. Cue-Signijcance Feedback The effective probability of attending to a dimension, EPo, is jointly determined by the initial probability, Po, of observing a dimension and the feedback, APr, from the preferences for the cues on that dimension.

APr EPo

= =

(P(r) - P(i)( P o . APr

c. Chaining

Within each dimension the probability of covertly selectingthe cues on the positive stimulus (i.e., making response r) is the product of effectively observing that dimension and the preference P(r) for the positive cues. Prob(r)

=

EPo P(r)

Prob(i)

=

EPo . P(i)

Prob(?)

=

Po

Similarly,

and -

EPo (null response)

The last equation represents the possibility that the subject may not respond (makes a null response) to the cues of either the positive or negative stimulus on a particular dimension. When this occurs the dimension has been observed (prob = Po), but not effectively observed (prob = EPo).

d. Overt Response Generation The probability of overt selection of the positive stimulus is the ratio of positive covert responses (summed over all dimensions) to the total number of covert responses, N(r) and N(f), according to a matching rule. Prob (R) = N(r)/[N(r) + N(r)] If N(r) + N(i) = 0, Prob(R) = 1/2

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Mary Ann Fisher and David Zeaman

B. Dynamics: Learning and Retention

I . OBSERVING RESPONSE LEARNING The acquisition and extinction of associations are represented separately for the Attention Selector, STS, Buffer, and LTS. Define

k

=

total number of cues in Buffer

Ooa = acquisition rate parameter for attention Ooe = extinction rate parameter for attention

Attention to any dimension is enhanced if the trial outcome confirms the subject’s expectancies about reward values of cues on that dimension.

Po,,

+ e,,

Po,

I =

(1 - Po,) if r (acquisition)

Violations of cue-reward expectancies decreases attention to a dimension.

Po, +

,

=

Po,

-

eoePo, if

i. (extinction)

If the subject makes the null response,?, for this dimension, no change occurs in the observing response strength. 2. SHORT-TERM STOREENTRY If a dimension has been observed on trial t , one of two kinds of reward values, + or -, may be associated with each cue element (c or E ) within C a n d r . The signed strength of this cue-reward information is represented by S such that S(c)

=

+

I and

S(C)

=

-

1 unless

the null response is made, in which case S(C)

=

S(E)

=

0

When new associations enter STS at the end of a trial, all previous associations for this dimension are erased. 3. BUFFERENTRY a. Definitions

p = the current limit on the number of associations in Buffer on a particular trial for a given dimension; LY = the probability that an associative item on a given dimension will enter a filled Buffer;

177

ATTENTION-RETENTION THEORY

k = the number of items currently in the Buffer; L = the degree of learning, or LTS strength of association, of an item considered for the Buffer entry. An item is “well-learned” if its L-value is very high (indicating strong preference) or very low (indicating strong aversion). b. Postulates i. Well-learned items ( L > .98, or L c .02) are not eligible for entry into the Buffer. ii. No changes occur in the Buffer following a null response. iii. In general, for p > O , item strengths, (B), will occupy the Buffer with

B(c) B(E)

=

+ 1 if r

= -

1 iff

for the following conditions: (1) The Buffer is unfilled (k
a. Dejnitions Ova = acquisition rate parameter for items in LTS 8, = extinction rate parameter for items in LTS

j

=

total number of items in STS or the Buffer

b. Postulates i. LTS strength, L, varies from zero to one at the end of a trial and is changed at that time by the current contents of STS and Buffer. ii. For each stored representation, x, of a cue associated with “+” (reward) in STS or Buffer, L is increased.

L,+l(x) = Ldx)

+ (@,$j)[l

-

L,(x)l

iii. For each stored representation of a cue associated with “-”(nonreward) in STS or Buffer, L is decreased.

L,+dX) = L,(X) - (8,$j)Lt(4

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Mary Ann Fisher and David Zeaman

5. SHORT-TERM DECAY STS associative strengths decay exponentially to zero as a function of time the intertrial interval, with decay parameter 8 . At any time, T , after the end of the trial, the magnitudes (but not signs) of the associative strengths [S(x) and S(x)] in STS decline from starting strength S , .

(T) during

s,=

S , . S - T

6. BUFFER-LTSINTERACTION

Items already in Buffer may become well-learned in LTS through additional training or rehearsal. Such items are deleted from the Buffer before the beginning of the next trial. The criteria for well-learnedness are the same as those used for restricting well-learned items from the Buffer entry (L > .98. L < .02). Ill. OUTLINE OF THE DATA DOMAIN OF THE THEORY

To give an overall view of the kinds of discriminative learning phenomena A-R theory is addressed to, Table I lists a number of effects roughly grouped by area, together with the theoretical parameter values necessary to reproduce the effects by Stat-child simulations.* For the most part a standard set of parameters was used to simulate all the effects at least semi-quantitatively. This set is listed below.

e,,

= .5 floe = .I Ora = .5

ere = .5 T =

6

=

APr

=

(Y

=

1 (corresponds to 15 seconds) 1.4

.6 (initially) .5

Other parameter restrictions are as follows. The Buffer capacity ,PJ is usually set at 0 for experiments using a traditional Trials-to-Criterion Design (which put little demand on memory), and at I for Miniature Designs(many problems per session with only a few trialsper problem). Since the Miniature Design is usually aimed at uncovering retentional effects, control is sought *The program which generated these results is available from the authors. It is written in CPS, a subset of the PL/I language adapted for useon an IBM2741 remote terminalconnected to an IBM 360. Documentation includes flow diagrams and instructions on program use.

ATTENTION-RETENTIONTHEORY

179

for attention by use of extensive pretraining on relevant dimensions. For these designs we therefore set the initial observing response probabilities (Po) at 1 .O. The last parameter isn, the number of variable dimensions having nonnegligible cue-preference differences (APr’s). This parameter is to some extent under the methodological control of the experimenter, who can eliminate a dimension either by making the cues of a particular dimension constant (APr = 0) or by pretraining the cue-preferences to neutrality (APr = 0). Most of our subjects are well-pretrained to eliminate position tendencies. The effective dimensions remaining are usually color and form, so n is typically set at 1 or 2 depending upon the physical variability of the cues of these dimensions. Where simulations have not been presented in the text, the table entry indicates the parameter manipulations necessary to produce the effect. These are enclosed within parentheses. The IQ entry, R or N, indicates the subject population, retarded or normal, respectively, for which the empirical effect has been demonstrated. Normal subjects are children within the MA range of our retarded population, except for the Trabasso and Bower study. IV. WHAT IS LEARNED A. Response or Stimulus Selection

That something is learned in a discriminative task seems obvious enough, since the typical subject exits with a solution (reward on every trial) not present at the start of training. Agreement among theorists ends at about this level of analysis. Even among the large class of theorists who assume that a part of the learning (at least) is an association of some stimulus components with some response tendencies, opinions differ on the nature of the response (or strategy or hypothesis), and on the nature of the stimulus. Two large camps can be identified with respect to the nature of the response, those who favor a response selection view, and those who regard discriminative learning as a process of stimulus selection (see Lovejoy, 1968). As an example of the distinction, a subject in a standard two-choice visual discrimination may learn to select from among the various stimulus components the positive cue, and approach it regardless of its left-right position. The response selection view, on the other hand, has the subject solve a discrimination problem by going left when the stimulus configuration has the positive stimulus on the left, otherwise to the right. The relative merits of these alternative formulations are well reviewed by Lovejoy (1968) and by Sutherland and Mackintosh (1971) with conclusions supporting the stimulus selection position, for animal discrimination learning. The arguments they assemble for stimulus rather than response

Mary Ann Fisher and David Zeaman

180

TABLE I A LIST OF MAJOREMPIRICAL PHENOMENA WITH ASSOCIATED PARAMETER CHANGES NEEDEDFOR A-R THEORYSIMULATIONS; SAMPLE REFERENCES; A N D b C U S OF TEXT DISCUSSION Empirical effects Learnine I . Ogival learning curves

Parameter changes

Sample references

Text sections

v

2. Gradual learning in Long-Term Store 3. Facilitation by dimensional redundancy 4. Ultimate solution with variable irrelevant dimensions 5. Apparent one-trial learning 6. Decremental effects of cue redundancy 7. Stimulus compound and component learning 8. Cue-significance learning by contiguity 9 Independent control by positive and negative cues 10 Decremental influence of irrelevant dimensions

Attention I I . Multiple-looking 12. Facilitation by introduction of a novel cue 13. Decremental effects of reduced physical cue-differences

Initial Po

.2

=

(None) n = I and 2:

initial PO, = PO, (None)

=

Zeaman and House (1963); Shepp and Zeaman (1966) Sperber, Greenfield, and House (1972) Zeaman and Denegre (1967)

1X.D x,c

Campione, Hyman. and Zeaman (1965)

XIII,D,l,c

XV1,B.I XIV.C.4.d XII,D,5

.8

(p = I,a= 9)

(None) (Initial Po for compounds > 0) (None)

(None)

(Initial Pos for irrelevant dimensions

XIV,C,Z,d House and Zeaman (1959) XIV,C,4,6 Hyman (1967); House (1971) House and Zeaman (1963) 1V.B

Shepp (1962. 1963, 1964); Shepp, House, and Zeaman (1967) House and Zeaman (1958); Zeaman and House (1962) Zeaman, Thaller, and House (1964)

1v.c

v,c,I V,C,I

> 0) See Fig. 9 (Increment APr with introduction of novel cue) (APr a direct function of physical cue differences)

Fisher, Martin, McBane, and Zeaman (1969) Zeaman, House, and Orlando (1958)

XI1.D. I

Shepp and Zeaman (1966)

1X.D XIII,D,l,c

XIII.D, I ,c

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ATTENTION-RETENTION THEORY

TABLE I (Conlinued) ~~~

Empirical effects 14. Cue-blocking

15. Reduction of cue-

blocking with novel cues 16. Incidental learning

Transfer 17. Overlearning reversal effect (ORE) 18. Reversal midplateau 19. lntradimensional and extradimensional shift effects 20. Effects of dimensional preferences on ID-ED shifts 21. ID-ED washout with repeated shifts 22. ID-ED washout with constant irrelevant dimensions 23. Incremental effects of initial cuepreference differences 24. Conflict and combination of cues

25. Transitivity Retention 26. Decremental effects of intertrial interval 27. Retroactive interference by interpolated items

Parameter changes

Sample references

(A Pr-10 before redundancy training) (Novel cue reinstates initial APr>O) (APr > 0 at start of redundant training) ( I , ,=

.3

Anderson (1971) (Na)

XIII,D,I,g

Trabasso and Bower (1968) (N")

XIII,B,Ig

Ross (1966): Siege1 and Stevenson (1966) (NO )

XIII, D , l g

Shepp and Turrisi (1969)

X1,D.I X,C.lP X,C, I ,d

n=2

o,,

Shepp and Turrisi (1969)

= .3

n=2 None

(Higher initial Pos for preferred dimensions) /l = I , n = .9

~~~

-

Text sections

Campione et al. (1965)

XI,D,I X,C,l,h

Brown (1970); Suchman and Trabasso (1966a. 1966b) (N)

X1,D.I X,C.l,c

Scott( 1966); House ( 1968) Dickerson (1967)

XII,D.3

XI I I ,D. 1,d (APr = 0 for constant dimensions) (A Pr directly Campione and Wentworth XIII,D,l,b controlled by ( 1969) cue-preferences)

House and Zeaman (1963) XII,D,4

/$ = 1. a = .9, initial APr for form higher than for color (None)

Campione (1969b)

XV.D.1 VI,D,I

/$ = 1

Klinman (1964)

XIV,C, I ,a

1

Klinman(1964)

XIV,C,l.a

=

~~

~

~

" N indicates use of Normal rather than retarded subjects.

(Continued)

Mary Ann Fisher and David Zeaman

182 TABLE I (Continued) Empirical effects

Parameter changes

28. Increased interp=1 ference with proacting items 29. Increasing proacp=l tion with longer intertrial intervals s = 2.2 30. Delayed response 31. Retroactive effects p=1 in concurrent problems

Sample references

Text sections

Knight (1968)

XIV,C,3,b

Knight (1968)

XIV,C,l,b

House and Zeaman(l961) B. J. House, A. Martin, B. McBane. and R. Brainerd (unpublished results, 1969) Klinman (1964)

XIV,C,l,c XIV,C,l,d

McBane and Zeaman (1970) Campione and Zeaman (1969); Scott (1966)

XIV,C,Z,b

p=l

Knight (1968)

XIV,C,3,b

p=l

XIV.C,2,b XIV,C,3,b XIV,C,3.C

32. Retroaction and similarity of items 33. Proaction and similarity of items 34. Decreasing retroaction with welllearned interpolations 35. Decreasing interference with welllearned proacting items 36. Release from P.I.

p=1

37. Decreased R.I. with items of strength 38. Reduction of intertrial forgetting with overlearning 39. Less R.1. with redundant stimuli 40. Buffer (Rehearsal) Learning

p=1

McBane and Zeaman (1970); Knight (1968) Stukuls (1968)

p=1

Stukuls (1968)

XIV,C,3,c

p=l

Campione and Zeaman (1969) McBane (1972)

XIV,C,4,a

p=l

p=I

(p increases with special training)

XIV,C,2,a

XIV,C,3,a

XIV.C.2.c XVII,B,3,a

selection hold as well for retardate discrimination learning, but one source of evidence, not cited by these authors, which appears compelling to us is as follows. Retarded subjects have been able to solve discriminative problems with multivariable irrelevant stimuli. That is, on every trial new cues are introduced on an irrelevant dimension (Zeaman & Denegre, 1967; Zeaman

ATTENTION-RETENTIONTHEORY

183

et al., 1964). This means that the subject never sees the same stimulus configuration twice. Consequently, the response selection view requiring right or left responses to different configurations predicts no learning. For this reason we adhere to the stimulus selection view. One complexity emerges, however. Since we will later infer, for these subjects, a chain of two discriminative stages, the question of Responsevs.-Stimulus Selection holds for both. A fuller description of the nature of both stages in our inferred chain is postponed for later sections. For the present, both fall within the spirit of a Stimulus Selection specification. The first response (or “attention” response) is a selection of a stimulus dimension (or dimensions); the second is the selection of one of the two cues on the noticed dimension to be associated with reward. 6 . Components, Compounds, and Configurations

Another issue subsumable under the “What Is Learned” rubric is the nature of the stimulus specification. Three kinds of stimulus aggregates have been posited to control responding in discriminative learning: components, compounds, and configurations. A component is a single aspect of a complex stimulus (either positive or negative) such as “red” or “square” or “left,” while a compound is a joint aspect of a stimulus defined in terms of two or more properties such as “redtriangle” (an instance of a color-form compound) or “black-left’’ (a colorposition compound). It must be emphasized here that these compounds are distinctive from each of their components. Indeed, a compound is theoretically regarded as another component of a special kind. These stimulus specifications are the same as those adopted by House and Zeaman (1963). Empirical support for the analysis comes from the same source. These authors provided ample experimental evidence of the use of both component and compound aspects of stimuli by retarded subjects. The extent of compound-versus-component learning is left an empirical question. Remaining is the matter of a configurational specification, commonly used by Response Selection Theorists(Bush & Mosteller, 1955; Gulliksen & Wolfle, 1938), who view configurations as transverse compounds, i.e., aggregates of both positive and negative stimuli taken as an unanalyzed whole. In this case a black stimulus coupled with a white one is not the same black stimulus as one coupled with a red stimulus, or, as a more frequently used example, black-left vs. white-right is a different configuration from black-right vs white-left. If transverse compounds are defined broadly enough to include any

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Mary Ann Fisher and David Zeaman

aspect of the discriminative array including both the positive and negative stimuli, then our concept of stimulus “dimension” may be regarded as a kind of transverse compound since it involves both positive and negative stimuli. If the positive and negative stimuli do not differ in cue values of a dimension, we assume (it will be developed later) that this dimension is not attended to. The color dimension, for instance, would not control attention ifboth positive and negative cues were red. With respect to transverse compounds, then, our theory is somewhat complex, since a transverse aspect of the display controls the attention response, but not the instrumental responses of approach or avoidance. The major, but not sole, reason for assuming dimensional control of the attending response is that it provides a theoretical mechanism to account for the otherwise puzzling empirical phenomena of intradimensional (ID) and extradimensional (ED) transfer effects commonly reported with our subjects (see Campione et al.. 1965; Wolff, 1967). A secondary reason for adoption of the dimensional formulation stems from the fact that it helps us take a consistent theoretical stance on another substantial issue under the heading of “What Is Learned.” This is the question of the use of relative vs. absolute stimulus properties in discriminative learning. Transposition studies (see Reese, 1968) have shown that subjects of even low developmental levels are capable of making discriminative responses to relative as well as absolute aspects of stimuli. A relational aspect of a discriminative display such as relative size requires a response to a transverse property of the two or more stimuli presented. Relative size is one particular transverse aspect that a subject can attend to as adimension. If a subject attends to relative size, then the instrumental response of approaching the larger or smaller cue may follow. Relational dimensions such as size, brightness, hue, etc., compete for attention. An Attention Theory analysis of oddity-similarity learning has been provided by House (1964b), together with retardate data consistent with the analysis. C.

S-SVS. S-R

The final subissue of the “What Is Learned” question to be considered will be that of S-S vs. S-R associations. Thus far, only S-R connections have been postulated (dimensions to observing responses and cues to instrumental responses). However in our adaptation and fusion of the Atkinson and Shiffrin (1969) memory postulates within Attention Theory, we have relaxed this restriction and represented some of the information in memory to be in the form of cue-reward connections, which are more S-S in nature than S-R. For purposes of gross classification, this extension throws us more into the cognitive camp, a fate we regard as not worse than death. The empirical justification for the inclusion of some S-S retention postu-

A’ITENTION-RETENTION THEORY

185

lates is largely programmatic and lies in the deductive account they yield of the variety of retentional phenomena to be described in latersections. Additional evidence (also of an indirect nature) for cue-reward conditioning comes from a study by Eimas and Shepp (1964) in which the noncontingent pairing of a to-be-positive discriminative cue and reward prior to discriminative learning resulted in facilitation of later training of a standard two-choice discriminative problem. Further relevant data on retardates, showing that other arrangements of noncontingent cue-reward contiguity strongly affect discriminative learning, have been presented by Shepp (1962, 1963, 1964), House (1964), and Shepp et al. (1967). D. Summary

The general answer to the question “What Is Learned” given by Attention-Retention Theory is this: the retardate in solving a two-choice visual discrimination may learn to attend to one or more of the variable dimensions of the discriminative display. The cues of these dimensions may through learning become associated with reward values (plus or minus) which then control approach or avoidance responses. Whether the subject learns to attend to compound or component dimensions, relative or absolute, depends upon the previous training and capacities of the organism, not upon restrictions of the theory. V. ONE OR TWO LEARNING PROCESSES

A. The Issue

The experimental operations defining discrimination learning are differential reinforcement of response in the presence of different stimuli. The simplest and most usual case is consistent reward of one stimulus and consistent nonreward of another (a lOO%-O% schedule). Corresponding to these operations of reinforcement and nonreinforcement are theoretical processes of acquisition and extinction, respectively, or excitation and inhibition. Some theorists, however, make use of, or emphasize, just one of these processes while others use both. Harlow (1959) takes a monoprocess position on this issue, that discrimination learning is largely the elimination of error tendencies. An opposing view is taken by those investigators who show that errorless (hence extinctionless) discrimination learning is not only possible but efficient (Terrace, 1963). Only acquisition enters these studies, presumably, with the positive stimulus receiving more reinforcement than the negative. Duoprocess theorists abound. Examples include Hull (1943), Spence (1936), Bush and Mosteller

186

Mary Ann Fisher and David Zeaman

(1955), and Estes and Burke (1953). Admittedly, a number of theoriststhose who use cognitive terms such as “hypotheses” and “strategies”-are somewhat difficult to classify on this issue (e.g., Levine, 1966; Restle, 1962). Special problems are encountered by chaining theorists on this problem in that acquisition and extinction may be assumed to operate on the modification of one or both responses in the chain. In the chaining theory of Trabasso and Bower (1968), the initial member of the chain, the attention link is not modifiable, but the second (a cue-selection response), does undergo change. Although the theorists do not use these theoretical terms, the changes correspond to acquisition and extinction in the following sense: the positive and negative cues of the dimensions attended to become associated with their respective reward value outcomes (in an all-or-none manner). Other chaining theorists, such as Zeaman and House (1963), Lovejoy (1968), and Sutherland and Mackintosh (I97 1) have acquisition and extinction postulates applied to both members of the discriminative response chain. B. Our Theoretical Position

We have modified but not abandoned the previous stance taken by Attention Theory (1963) on this issue. The operations of reinforcement and nonreinforcement are still postulated to produce consequent changes in acquisition and extinction for both the initial attention response and the cue-selection components of the chain. The fact that the first is a change in S-R strength and the second a change in S-S association does not alter the argument that strengths of association (of either kind) undergo increment (gradual or allor-none) with reward and decrement with nonreward. Calling these changes acquisition and extinction does not do violence to the spirit of the model. Formal statements of our learning and extinction postulates are given in Section 11, B, 1 and Section 11, B, 4. C. Justification of Our Position

1. EMPIRICAL

The evidence for dual process in retardate discrimination learning is indirect, but comes largely from demonstrations that discriminative responding is to some extent under the independent control of both the positive and negative cues. Reinforcement of the positive cue presented alone or nonreinforcement of the negative cue presented alone show positive transfer effects on later discriminative training with both cues present (Losty, 1971). Although such demonstrations are partially contaminated by novelty preferences in low-MA retardates, the conclusion arrived at, from a number of studies using a variety of methods to assess relative strengths of approach

ATTENTION-RETENTION THEORY

187

and avoidance, is that both positive and negative stimuli are used by these subjects (House & Zeaman, 1958; Zeaman & House, 1962). The evidence for dual processes controlling the attentional link is more indirect and programmatic. The strongest inferences for extinction of the attentional response comes from the demonstration that retardates can achieve perfect learning in the solution of problems with several variable irrelevant dimensions. The presence of variable irrelevant dimensions initially impedes solution (Zeaman & Denegre, 1967; Zeaman el al., 1964) assumedly because these irrelevant dimensions have some starting probability of being attended to. At later stages of training, irrelevant dimensions must be disregarded to permit perfect performance. The theoretical reason for this lies in the extinction of attention to irrelevant dimensions. Another source of data leading to the inference of the extinction of attention may be extracted from analyses of the Overlearning Reversal Effect (ORE) and Reversal Midplateaus, described in later sections. Independent evidence of the operation of acquisition effect on the attentional link is not yet available. All the dimensional transfer effects (ID and ED), the ORE, and Reversal Midplateaus might conceivably be accounted for (without a quantitative model) by appeal to extinction of irrelevant dimensions. Indirect evidence against this derives from the fact that all our theoretical simulations of retardate discrimination learning have assumed both acquisition and extinction to be operating, and the best-fitting simulations have never turned out to be those with acquisition parameters ofzero value. In fact the acquisition parameters are never lower in magnitude than those of extinction. 2. THEORETICAL A good case can be made for a dual process interpretation using the criterion of theoretical generality. We posit both acquisition and extinction processes, but then allow the rate of these processes to be empirically determined by the fitting of theory to data. If either process is weak or absent, the acquisition or extinction parameters may approximate zero by demands of data. In an obvious sense, then, our dual process theory includes monoprocess, as a special case, permissible if data-simulation dictates.

VI. STRENGTHS OR RELATIVE STRENGTHS

A. The Issue

If associative strengths are posited for both links in the discriminative chain, a question arises: should these be represented as relative or absolute strengths? A relative specification defines the strength of association A in

188

Mary Ann Fisher and David Zeaman

relation to other strengths, say B and C, operating at the same time. A simple measure would be a conditional probability of a choice of A given the set of A, B and C (Prob AIA, B, C). Such a measure says nothing about strength of A, B, and C in other contexts. A n absolute specification assigns some numerical values to A, B, and C regardless of context. This approach makes the strong but testable assumption that the individual strengths are transsituational, applying in any context. Adoption of an absolute specification carries with it the requirement of an additional rule indicating how the individual strengths interact in different contexts. Luce (1959) has published such a rule, which converts strengths to probabilities in varying contexts. 9. Other Theoretical Positions

Merely to show the diversity of opinion on this issue we cite examples of theories which (1) have both links of the discriminative chain represented as relative strengths: Zeaman and House (1963) and House and Zeaman (1963); (2) both links absolute: Trabasso and Bower (1968); and (3) the first link absolute, the second link relative: Lovejoy (1968) and Sutherland and Mackintosh(l971). C. Statement of Our Position

In A-R Theory, all associative strengths are represented as absolute, and Luce’s Rule is used to convert these to probabilities in varying contexts. For our purposes, the rule may be stated as follows: given associations (either dimensional or cue) ai of strengths w(ai), the probability of choice of any aj when it is in the context c is w(aj) divided by the sum of all the w(ai)’s in c. An example of the use of this rule in A-R Theory is given by the computation of cue-preference P(r) for LTS in Section 11, A, 2, a . D. Justification

1. EMPIRICAL

The only test of Luce’s Rule in the domain of retardate discriminative learning has been published by Campione (l969b), who successfully tested the trans-situationality (transitivity) of cue strengths in an experiment which controlled dimensional strengths. No corresponding test for dimensional strengths has has yet been devised.

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2. THEORETICAL Having the same rules and representations of dimensional as well as cue strengths makes for theoretical simplicity. Generality is another good reason for assuming that dimensions as well as cues have trans-situational strengths. Until new data indicate otherwise, we maintain these assumptions since more predictions can be made with them than without. VII. GRADUAL VS. ALL-OR-NOTHING LEARNING A. The Issue

A major problem in all quantitative models, discriminative or otherwise, concerns the rate at which learning theoretically takes place-gradually, or in a stepwise, all-or-nothing fashion. The issue is an old one dating back at least 40 years to the continuity-noncontinuity controversy of Krechevsky (1932) and Spence (1936), and it is still controversial. Other theorists taking a stand on this issue include Lashley ( 1 929) and Guthrie( 1959), and a number of Gestalt psychologists who have nonquantitative models of all-or-nothing learning. Published more recently are quantitative models of all-or-nothing learning such as those of Estes ( 1 960), Bower (1967), and Restle ( 1962). Many instances of Markovian models having this feature could also be cited. Among the quantitative theories of gradual learning, there may be listed those of Hull (1943) and Spence (1936) as the granddaddy examples. B. Discriminative Learning Theorists

Modelers who prefer the notion of an underlying strength of habit (or response) usually opt for a gradual learning assumption with some learning parameter ( 0 ) controlling the amount of strength accruing on each learning trial. Typical of this class are the recent models of Lovejoy( 1968), Sutherland and Mackintosh ( 1 97 I), and Zeaman and House (1963) for chaining theories; representative of nonchaining theorists with gradual learning are those of Hull (1943) and Spence (1936). I n competition are theorists such asTrabasso and Bower (1968), Levine (1966), and Estes (1960), who support an essentially noncontinuity position with no intermediate states of learning. C. Our Position

For a theory which posits a chain of two stages of learning, the rate-oflearning question applies to both stages. We have allowed the possibility of

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either gradual or stepwise learning of the initial stage of observing response acquisition by adoption of the linear acquisition and extinction equations (see Section 11) which describe the rate of growth or decline of strengths of dimensional observing responses. The learning rate parameters (Ooa and Ooe) may have any values demanded by the data. Stepwise learning is approximated as these 8 values approach unity; gradual learning is inferred as the 0’s deviate from 1.O. The learning of cue-significance information is more complex because there are assumed to be both short-term and long-term components. If we respect the tradition of defining learning as a long-term phenomenon, then we can restrict the argument here to a consideration of just the transition of cue-reward information from the short-term memory storages of STS and Buffer to the LTS. Here again we make use of linear equations of the same form as for first-stage learning with attendant implications of the possibility of either gradual or stepwise learning. The learning rate parameters for these equations are not necessarily identical in value to those of first-stage learning. D. Justification

The empirical tests of the all-or-nothing versus gradual learning assumption have come from a variety of sources. The most frequently cited evidence for stepwise learning derives from the ogival shapes of empirical discrimination learning curves. The subjects’ performance remains at a chance level of responding for varying numbers of trials then improves rapidly in an approximately stepwise fashion to criterion level regardless of how long the initial plateau. The statistical property of starionariry (chance-level precriterial responding) argues to the same point. Another source of evidence stems from transfer experiments in which subjects who have been trained for some time on a discrimination, but have shown no improvement, learn a reversal at rates not different from untrained subjects. Another source of transfer evidence has been presented by Rock (1 957) in which trained but as yet unlearned paired-associate items can be replaced by new items with no decrement in speed of list learning. Estes (1960) has used a three-trial, reinforcement-test-test paradigm for paired-associates learning (in which the test trials are assumed to be neutral in reinforcing effect) to show that items are in one of just two states, learned or unlearned. Experiments of the general types described above, adapted for retardate disciminative learning, are not readily found in the literature. Perhaps the only relevant evidence on retardates comes from a verbal learning experiment by House( 1963) who showed that unrecalled verbal items do not change strength despite many repetitions (shown also by Rock for normal adult subjects).

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Finally, there are a number of fine-grain, statistical analyses of learning data, such as conditional probabilities of a correct response following one or more errors in presolution responding, or geometric distributions of total errors which have logical bearings on all-or-nothing versus gradual learning. Retardate data, here too, are thin. It has been shown frequently enough in the theoretical literature that none of these data sources provides a crucial test of the competing theories. Keppel and Underwood (1962) for example, have demonstrated that gradual learning models with a threshold feature can handle much of the noncontinuity data, and Polson and Greeno (1969) have shown that nonstationarity of presolution performance does not necessarily preclude all classes of allor-none models. The answer must come from large programs of theoretically integrated research in which competing models are shown to be better or worse in fitting many aspects of large assemblages of data. On the theoretical level, our adoption of linear acquisition and extinction equations is, in a real sense, a neutral position, since equations of this kind are consistent with both a gradual or stepwise postulate. All-or-nothing models of the kind that Estes (1960) and others have published imply equations of this type, as do the Hull-Spence kind of model. In the former case, however, the equations describe the mean performance of a group of like subjects, or the mean performance of a single subject learning a population of like problems. The “gradual learning” assumption, on the other hand, presumes to apply to the individual subject learning a single problem. Differences in consequences of the two approaches may appear as has been pointed out when certain fine-grain sequential statistics are considered. For a chaining model which allows varying probabilities (or strengths) of both stages, no theorist to date has worked out explicit, differential predictions of sequential statistics for gradual versus stepwise learning assumptions. Such predictions could in principle be made using Stat-children, but this has not yet been done, nor are there any published retardate data to bear on the problem. For these reasons we are content with a neutral theoretical stance on this issue, although our adoption of the notion of underlying strengths indicates that we lean toward the gradualist camp. Some indirectly supportive data on this point are presented in Section XIV, C, 4, d . VIII. MECHANISM OF LEARNING

A. The Issue

The broad issue raised here is the mechanism of learning, a question closely associated with that asked earlier, “What is learned?” The two traditional mechanisms of Contiguity and Effect are related in our theory to S-S

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and S-R learning respectively. Both mechanisms are postulated to operate, but on different responses: Contiguity on cue-reward significance,Effect on attention. The S-S association of discriminative cues and reward (or nonreward) stimuli are formed by the contiguous pairing of these stimuli in the typical discriminative trial. In contrast, the associations of stimulus dimensions and attention responses are formed, theoretically, by contingent outcomes (effects) of these responses. The question naturally follows: what outcomes have reinforcing effects on attention? Three sources of reinforcement have been postulated by different theorists: (1) primary reinforcement by the reward or goal object; or (2) secondary reinforcement by the discriminative cues contingent upon attention; or (3) reinforcement by the informational outcome of attention to different dimensions. Such theoretical diversity helps identify this as an important issue in discrimination learning. B. Alternative Theoretical Positions

The large majority of discrimination learning theorists has favored the Effect Mechanism over the Contiguity Principle, (e.g., Hull, 1943; Kendler & Kendler, 1962; Lovejoy, 1968; Spence, 1936; Sutherland & Mackintosh, 197 1; Zeaman & House, 1963) but Contiguity has had its adherents. Guthrie, of course, was prominent here, as an S-RContiguity theorist. Tolman (1932) also held that S-S connections (“what-follows-what”) were the substance of what is learned, with Contiguity as the sufficient condition. The more recent theorizations of Estes (1969) reflect a composite of the views of Guthrie and Tolman. He posits the association by contiguity of both S-Rand S-Sconnections. In the discriminative paradigm the three major components of stimulus, response, and outcome (reward-nonreward) are all associated as a function of contiguous experiences of them. The role of reward in such theories is such as to act as amotivational factor on performance rather than on learning. Among the Effect theorists, the source of reinforcement is a divisive issue, as has been mentioned. For Hull (1943), Spence (1936), Lovejoy (l968), and Zeaman and House (1963), as examples, the goal object (whatever is used as an external reward) serves as the source of “primary” reinforcement for all response members of the discriminative chain. As one of the earliest Chaining Theorists, however, Wyckoff (1952) assumed that the difference in secondary reinforcing values of the positive and negative cues served as the source of differential reinforcement of the observing response which precedes the effective appearance of the cues. The third source of possible reinforcement that has received theoretical attention is more cognitive than the others, and consists of the confirmation of expectations. Sutherland and

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Mackintosh (1971) have espoused this view in their account of animal discrimination learning. If an animal attends to a dimension (or chooses an “analyzer” in their terms) and then chooses one of the cues of a dimension, the result will be a strengthening of the analyzer if the reward value(positive or negative) of the cue chosen is as expected, otherwise the result will be a weakening of the analyzer, Since this is the mechanism that we have chosen for retardate discrimination learning, further description of this complex view will be given in a later section. C. Statement of Our Position

With respect to the mechanism of learning, we assume that retardates learn to associate by contiguity the reward values of the cues of the dimensions they notice. Learned preferences for stimulus dimensions will be generated by the differential reinforcement of attention to those dimensions yielding accurate cue-reward predictions by the subject. Some examples may make these mechanisms clearer. A subject attends to a particular dimension, color, for example, and as a consequence sees that there are two cues, red and green. If on the basis of prior training he prefers red and chooses it, a confirmation of this preference (by the reward) would strengthen attention to color. Ifgreen were the correct cue, attention to color would be weakened. Since these outcomes would be the same as those predicted by a simple primary (or secondary) reinforcement effect, a second example is considered which distinguishes the competing views. Suppose again that attention is to color and the preference is for red, but now assume that for other reasons the subject chooses the stimulus object bearing the green cue. If the green is incorrect and no reward is given, what should happen to the strength of attention to color? A simple reinforcement assumption predicts extinction, but our counterassumption is for acquisition because the outcome of the trial confirmed the expectations of the subject (that green was incorrect and red correct). But why should a subject who prefers red choose the stimulus object carrying a green hue? The answer “for other reasons” given above needs explication. The explanation lies in the possibility of increased breadth of attention (multiple-looking). The subject may attend to more than one dimension on a single trial, and the cues on another dimension may control the final choice of the subject. If the cues on another observed dimension override in importance those of a particular dimension then a subject may end a trial choosing a stimulus object having some properties that he does not prefer. The theorist must decide whether his subjects will be rewarded or extinguished solely by the outcome of a trial, or whether they will consider the outcome in relation to their

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expectations. The two views make different predictions of the results of trials exemplified above. Our current theory adopts the latter view. D. Justification

The kinds of experimental results supporting the notion that attention is reinforced by informational feedback or confirmation of expectations have been well-described for animal discrimination learning by Sutherland and Mackintosh (1971). When rats are given a choice of alternative responses equated for rewarding or punishing outcomes, they learn to prefer the response yielding stimulus information about the various outcomes (see Lockard, 1963; Prokasy, 1956.) Details of this literature are not reviewed here because corresponding experiments with retarded subjects have, to our knowledge, not yet been run, although they could easily be carried out. Our guess is that if rats are this cognitive, humans(even retardates) are even more likely to be. Feldstein and Witryol( 1971) have recently published evidence of the reward value of information in normal children in the retardate MA range. In any case, our theoretical commitment is such as to predict successful outcomes of such experiments with retardates. Furthermore, indirect support comes from the fact that use of this assumption in our postulate set enables us to handle the bulk of our retardate data not directly aimed at testing this assumption. The use of S-S learning postulates to represent the acquisition and extinction of cue-reward information is to some extent justified, at this time, on rational grounds, although evidence for S-S conditioning in retardates has been cited in earlier sections. To adopt with some convenience the theoretical machinery of Atkinson and Shiffrin (1969), the content of the various memory systems is represented as cue-reward (or sign-significate) information, the particulars of which are spelled out in other sections. Our approach here is viewed as also consonant with that of Estes, who has shown with a novel set of experiments that normal adult subjects can learn “stimulusreward associations in the absence of any opportunity for the direct strengthening of stimulus-response associations by the rewards [Estes, 1969, p. 931.” Relevant data on this point with normal children may be found in a study by Witryol, Lowden, and Fagan (1967). For more direct empirical support of our assumption, these experiments ought to be run with retardate subjects. IX. GENERALIZATION A. The Issue

At the level of data, stimulus generalization has been conventionally regarded as merely the complement of discrimination. The extent to which

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two stimuli give rise to differential responding is a measure of their discrimination; the extent to which the two stimuli elicit the same strength of response is a measure of the generalization between them. At the level of theory, however, conventions diverge. Theorists such as Hull (1943) and Spence ( 1960) postulate a spontaneous generalization process resembling the earlier notions of Pavlovian irradiation. Habit strength trained to a specific stimulus spreads spontaneously to neighboring stimuli as adecreasing function of the physical (or psychological) distance between trained and tested stimuli. According to this view, the incompleteness of generalization represents a spontaneous discrimination without differential reinforcement. Further discrimination is brought about through experimental extinction of generalized response strength to the negative cue. This sort of theory predicts that the speed of discrimination learning will be an inverse function of the physical differences between the stimuli to be discriminated. An alternative view, stemming historically from Lashley and Wade (1946), holds that generalization effects are not attributable to some spontaneous generalization process but are related instead to failures of attention. A more recent variant of this argument has been advanced by Shepp and Zeaman (1966) who point out that “. . . stimulusgeneralization is not the only theoretical mechanism capable of predicting more rapid solution of discrimination problems with larger stimulus differences.” Chaining models of discrimination such as those of Wyckoff (1952) and Zeaman and House (1963) can deduce this effect without a generalization postulate. In the attention theory of Zeaman and House, the probability of making a correct discriminative response in a two-choice situation is a positive function of the product of two other probabilities-that of attending to the relevant stimulus dimension, and that of choosing the correct cue of the dimension attended to. If it is next assumed that the probability of attending to the relevant dimension at the start of training is directly related to the difference between the positive and negative cues, then improvement in discriminative performance can be deduced to be a direct function of physical cue-differences. In short, this theory postulates that attention controls learning, and that cue differences control attention. Although both chaining and nonchaining models share the common deduction of better performance with large cue differences, they part company in predicting different quantitative details of the process. In Attention Theory, the effects of variation in initial attention probability are largely reflected in the length of the initial chance portion of discrimination learning curves rather than in the rates of approach to asymptote (which are controlled by learning rate parameters). Nonchaining theories, to our knowledge, do not share this property.

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6 . Alternative Theoretical Positions

Representative of the explicit models positing a stimulus generalization process are those of Hull (1943), Bush and Mosteller (195 l), and Spence (1960). Among the formal chaining models of discrimination learning such as those of Wyckoff (1952), Zeaman and House (1963), Lovejoy (1968), Trabasso and Bower (1968), or Sutherland and Mackintosh (1971), none contains a generalization postulate. Furthermore, as published, none to our knowledge explicitly relates either the first or second member of the discriminative chain to differences in cue values. The point to be made, however, is that any of these chaining models, as Shepp and Zeaman (1966) have suggested, could easily add the needed assumption that cue-differences affect the attention link in the chain. For our current theory this is what we have done. C. Position Statement

A fairly simple statement is adequate for our purpose. The effective probability of attending to a dimension is directly related to the physical difference between the cues of that dimension.

D.

Justification

Many published experiments have shown prompter solution of discriminative problems with larger (rather than smaller) cue differences. These need not be reviewed here because the competing theoretical camps can handle this simple fact adequately, and because only one of these experiments (by Shepp & Zeaman, 1966) has provided the theoretically crucial analysis of the effects of cue-distance on the shapes of the learning functions. The Shepp and Zeaman results are reproduced in Fig. 2. The empirical learning functions shown at left describe the performances of retardates learning to discriminate brightness and size with two degrees of cue-separation. Backward learning curves more adequately reflect shapes of underlying functions, and the plots of these show rather clearly that the effects of cue-distance are not upon the rates of approach to asymptote but upon the length of the early, presolution near-chance portions of the curve. Commonality of rates of rise of the four functions are shown in the middle section of the figure. The functions in the far-right section are theoretical, indicating the expected effects of difference in initial probability of attending to the relevant dimension (Po (1.0)). Differences in learning rate parameters (6, and Or) do not producecurves of these shapes, so that theories which relate cue-differences to learning rate

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(through generalization) are contraindicated by these data. Cue-differences act instead on attention probabilities. E. Final Statement

An explicit formal statement of the relation between cue-difference and attention in the present theory would be of the general form EPo,;, = f (du,). Since it is likely that the function, f, would vary from dimension to dimension, we d o not specify the function with greater precision than to indicate that it should be monotonic and direct beginning at the origin (0,O). The last feature (origin at O,O), has the strong implication that constant dimensions (those with zero cue differences) have no possibility of being noticed. I f cue-differences affect attention probabilities, and cue-differences are themselves the consequence of attention, a logical problem of backwardaction-in-time emerges. The problem is resolved by postulation of a Feedback Loop (see Fig. 1). On every trial, the subject scans the ith dimension

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with probability Poi, reads the resultant cue-information output, and then computes an effective probability of attention (EPoi) as a function of both Poi and cue difference. The EPois then determine which dimensions are responded to. The mechanisms of this Feedback Loop are further described in Section XII. A formal statement of cue-significance feedback is given in Section 11, A, 2, b. X. CHAINING A. Issues and Theorists

A gross division of discriminative theories might be made on the explicit inclusion (or exclusion) of a chaining postulate. The nonchaining or Singlelink theories exemplified by Hull (1943), Spence (1936), and Bush and Mosteller (195 1) represent the learning of adiscrimination as the acquisition and extinction of associations acting in parallel. Chaining theories such as those of Wyckoff (1952), Zeaman and House (1963), Lovejoy (1968), Trabasso and Bower (1968), and Sutherland and Mackintosh (1971) postulate a chain of links acting serially. Some theories difficult to classify in this respect are Hypothesis Sampling Models of the type constructed by Restle (1962), Levine (1966), and others who have, we believe, tacit assumptions of a chain, but do not formally represent these. The Stimulus Sampling Theory of Estes and Burke( 1953) is similar in this respect in that the sampling of stimulus elements could be viewed as a covert response serially preceding the conditioning of the sampled elements. A composite of the chaining-nonchaining view has been adopted by Kendler and Kendler (1962). For subjects of low development level, a Single-link model is employed; for subjects of higher level, discriminations are presumably mediated by a verbal labeling response as one of the two links in the discriminative chain. Among the various chaining theories, opinions vary on the nature of the first link. For the attentional theories (Zeaman and House, Lovejoy, and Sutherland and Mackintosh), the first covert response is dimensional in nature. The subject attends to entire dimensions of stimuli rather than to specific cues. Not all chaining theories are thus; Wyckoff’s initial observing response is not explicitly dimensional, and hypothesis or stimulus sampling models may or may not have the dimensional feature. 6 . A-R Theory

Our current position preserves the basic chaining notion of attention theory (Zeaman & House, 1963) with an initial dimensional response followed by a cue-specific stage of learning. The subject first may attend to one

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or more of the stimulus dimensions present, and then associates the cues of the noticed dimensions with reward values. Formal chaining postulates have been given in Section 11, A, 2, c. C. Justification

1. EMPIRICAL

a. Ogival Learning Curves As a minimum requirement, a theory of retardate discrimination learning must be able to account for the commonly observed learning curves. Examples are shown in Fig. 2 of Section IX. Typically, the curves may display an initial chance-level plateau followed by a positively accelerated rise. Final levels of performance are usually preceded by a period of negative acceleration. That Attention Theory can predict functions of this shape has been adequately demonstrated. The current version of A-R Theory has the same property. Figure 3 shows a theoretically derived function using parameter values appropriate for the bulk of our other simulations. Although not all relevant theories can predict ogival functions, the probative value of such demonstrations is weak, since so many competing theories (chaining or nonchaining) can handle the fact. h. Dimensional Transfer Effects The most crucial evidence for the chaining assumption with a dimensional first stage comes from empirical demonstrations of intradimensional (ID) and extradimensional (ED) transfer effects. After training with cues of one dimension relevant, retardates will show stronger performance when shifted

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to a problem with new cues on the same dimension (ID shift), in comparison to the weaker performance arising from a shift to a problem with adifferent relevant dimension (ED shift). A great number of studies have been published with both retarded and nonretarded subjects demonstrating ID and ED effects (Shepp & Turrisi, 1966; see Wolff, 1966, for about 200 relevant studies). To provide a strong test of dimensional mediation, ED-ID transfer studies should use new cues on both the relevant and irrelevant dimension during the shift phase of the experiment to rule out cue-specific interpretations of the kind offered by D’Amato and Jagoda( 1961).Very few studiesof this kind have been reported. One which meets this “all different” cue requirement has been published by Campione et al. (1965) with retarded subjects. In this study, each of three groups of subjects (ID, ED, and Reversal) was divided in half. Half learned a form problem with color a two-valued irrelevant; the other half learned a corresponding color problem. After original learning the ID Group was trained on a new problem on the same dimension with new cues on both form and color, the ED Group was trained on the other dimension, again with new cues of both dimensions, and the Reversal Group was given the same problem with reward values of cues reversed. Figure 4 graphically displays the results. The expected superiority of the ID over the ED condition was obtained during shift despite the use of new cues on both dimensions. The reversal data are considered in a following section. Not only does the “new-cue” control rule out cue-specific interpretations, it also controls for “stimulus novelty” explanations of the results. Without

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new cues on both relevant and irrelevant dimension, the usual ED-ID experiment introduces novel relevant cues in the ID but not the ED Shift. If novel cues have increased saliency because of their novelty (as they likely do) the superiority of ID Shift could be accounted for by this factor (rather than dimensional transfer) unless adequately controlled. Simulations of ED-ID effects by A-R Theory are shown in Fig. 5. Two groups of Stat-children were “trained” to a high criterion on aproblem with one dimension relevant and with one two-valued irrelevant. Following this, the groups were transferred to a problem with all new cues, with either the same dimension relevant (ID) or the previously irrelevant dimension relevant (ED). In the simulation, both dimensions are of moderate strength at the beginning of training (Po = .5); at the end of training, the ID Group achieved a Po = 1.O for the relevant dimension on shift, while the irrelevant dimension remained at .5. The opposite values obtained for the ED Group. The parameter values for the simulation are given in Table I. The agreement of data and theory here is principally in the ordering of the conditions and the gross magnitude of the differences. The effect, both theoretically and empirically, is not due to any easily discovered specific cue transfer, but to the growth of some cue-independent aspect of the strength of the dimensional observing response. c. Dimensional Preference and Learning Rate in ED-ID Shifts

In the ED-ID Shift literature, dimensional preferences are experimentally produced by discriminative training with a particular dimension relevant. A different class of experiments makes use of dimensional preferences not experimentally produced, but having some earlier origin. For example, a subject may first be required to indicate a dimensional preference by an optional matching task, then required to learn a discrimination in which the preferred dimension is either relevant or irrelevant. The observation of faster

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learning of the preferred dimension then becomes another demonstration of dimensional transfer. A single illustration clarifies the argument. A subject is asked to match a standard stimulus (a red circle) to one of two sample stimuli (a blue circle versus a red square). Choice of the blue circle indicates a preference for form; the red square indicates color. Next, an ordinary discriminative learning task is devised with one dimension (either color or form) relevant and the other variable and irrelevant. The preferred dimension should be learned faster, and has been found to be so. Ideally, different cues should be used in the preference test than in the learning task to rule out cue-specific interpretations, as is true for the EDID shift demonstrations. Two studies which meet the “new-cue” requirement are those of Brown (1970) and of Suchman and Trabasso (l966a, 1966b). In these studies the expected results were obtained. The degree of initial preference for the relevant dimension was a good predictor of the speed of discriminative learning. The interpretation is theoretically the same as that offered for ED-ID shift phenomena. d. Reversals: The ORE and Midplateaus Overtraining on original learning has been shown to facilitate reversal. The literature on this Overtraining Reversal Effect (ORE) is vast and is not reviewed here. The major theoretical reason for such experimental outpouring derives from the embarrassment the ORE presumably causes for Singlelink Theories, and the support it provides for chaining interpretations. According to the latter view, overtraining further strengthens the dimensional first link in the chain and thus delivers facilitation during reversal, where the same dimension is relevant. Another reversal phenomenon is the midplateau. At the outset of reversal, the subject’s performance must necessarily start at a low level of correctness. 1t has been observed that under some conditions, the reversal learning curve rises quickly to a near-chance level, flattens off in a midplateau before rising again with positive acceleration t o criterion level. The Chaining explanation of the effect is simple enough. During the early reversal trials, the subject makes mistakes. These cause extinction of the observing response to the relevant dimension. If, as a consequence, an irrelevant dimension becomes dominant, performance will be at the chance level for a while until the relevant dimension again gains ascendancy. From this it can be seen that the weaker the attention to the relevant dimension at the outset of reversal, the more likely will another dimension become dominant, and the longer it will take for the relevant dimension to regain dominance. This reasoning implies that overtraining on original learning will shorten or eliminate the midplateau.

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That these three empirical effects, the ORE, the midplateau, and the reduction of the midplateau with overtraining, are indeed consequences of A-R Theory is shown in Fig. 6. A group of Stat-children was “trained” on a reversal with parameters equivalent to overlearning on the original problem (high Po). Forward and backward curves are presented in Fig. 6 to show the midplateaus more clearly. The backward curve gives a better description of the form of the function near criterion, while the forward curve represents better the underlying function at the outset of training. The midplateaus can be seen in both functions. Another group of Stat-children was run under a nonovertraining condition. The reversal function of thisgroup is also plotted in Fig. 6, and shows an overall slower rate of solution (the ORE) and a longer midplateau. The final rise to criterion of the nonovertrained group was not simulated because the theory must generate ultimate (perfect) solution with the parameters used (see Table 11). The ORE and midplateau phenomena have been demonstrated with retardate subjects. Data on these have been presented by Zeaman and House (1 963), but the clearest demonstrations have been published more recently by Shepp and Turrisi (1969). Figure 7 reproduces portions of their findings. Moderately retarded children were trained on a two-choice color-form object discrimination and then reversed. One group was highly overtrained, the other not. Forward and backward reversal functions for each group are drawn. An attempt has not yet been made to find precise parameter fits for the Shepp and Turrisi data, but the data and theory agree in demonstrating

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FIG.7. Data from Shepp and Turrisi (1969). Reversal learning curves after Overtraining or Nonovertraining on Original Learning (with Correction or Noncorrection Technique). The early stages of the Midplateau can be seen in the left panel. The duration of the Midplateau can be seen more easily in the right panel, which uses larger trial blocks.

the presence or absence of the effects under appropriate conditions with order-of-magnitude quantitative approximation. 2. THEORETICAL

None of the empirical effects described in this section (about a half-dozen) can be claimed to be derivable uniquely from A-R Theory, or from chaining models in general. Spence, for example, has shown that his 1936 model can predict ogival learning functions and systematic presolution responding. Wolford and Bower (1969) proved that with some parameter combinations, Spence’s model can yield predictions of faster reversal than ED Shift, although Kendler (1971) has indicated that the predictions do not hold in general for properly designed experiments. D’Amato and Jagoda (1961) have offered a nonmediational account of the outcome of some ED-ID shift experiments, although limitations of their explanation have been pointed out above. A modification of Spence’s model that might not be so limited has been offered by Spiker (1971). He claims that his model can be extended to handle ED-ID effects, but the details have not yet been published. Medin (1969) is another theorist who has attempted to derive dimensional shift effects from a nonchaining model. His explanations postulate changes in generalization gradients or learning rates which hold within but not between dimensions. It is our conviction that all Single-link interpretations of dimensional

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transfer effects tacitly assume that the subject responds differently to cues within and across dimensions, that is, the subject is in some sense responding dimensionally. This holds for Spence’s model also, even when not applied to dimensional transfer problems, since the approach strengths of the various cues are assumed to be developed in a pairwise fashion by dimension (e.g., white and black cues are paired for the brightness dimension, left and right for the position dimension-the subject does not approach white and avoid left). Perhaps the biggest (but not the only) difference between chaining and nonchaining theories lies in the degree of explicitness of the assumption of some dimensional response antedating or accompanying the cue-specific discriminative responses. The virtues claimed for A-R Theory include not only the explicitness of the assumptions on chaining and dimensionality, but the relative ease and directness of deduction of the effects here considered. Special or extreme parameter values are unnecessary. Another theoretical advantage of the chaining formulation is its generality. Single-link learning san be construed as a special case of chaining, but not the other way around. For conditions under which the first link can be assumed to have a fixed probability of 1, we have, in effect, a single-link system. Viewed this way, the question of Single-link vs. Chaining boils down to the empirical question: what are the parameters of the system under different conditions?

XI. MODIFIABILITY OF THE LINKS

A. The Issue: Modifiable vs. Nonmodifiable Aspects of Attention

A n aspect of attention is called modifiable, or directable, insofar as the response strength or sampling probability for a particular dimension (for a given set of cues) may change with reinforcement. It is nondirectable if it remains constant for a given set of cues throughout training. Observations which appear to require modifiable components of attention are the ID-ED Shift Effects and the ORE, as described in the previous section. It is hard to account for these effectswithout assuming some learned changes in direction of attention. On the other hand there are other observations which suggest that such changes are not permanent or complete. The first of these is the persistence of position habits (House& Zeaman, 1958),while the second is the interaction of dimensional preferences and dimensional transfer (Brown, 1970; Campione, 1969a). In the latter, shifting to the dominant dimension results in a smaller ID-ED difference than does shifting to the weaker dimension. These instances of regression to earlier learned or innate dimensional preferences suggest some nonmodifiable aspects of attention.

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206 B. Theoretical Alternatives

Some theories of discrimination learning have only modifiable aspects of attention, some have partly modifiable, partly not, and others have completely unmodifiable aspects of attention. 1.

COMPLETELY

D IRECTABLE COMPONENTS OF ATTENTION

The theories in which all of the strength of the dimensional response is directable are the Attention Theory of Zeaman and House (l963), and the Observing Response Theory of Wyckoff (1952). Each of these theories has a dimensional response strength not bound to cues, which may vary from0 to 1, and which is subject to acquisition and extinction through reinforcing consequences on each trial the response is made. The One-Look Model of Zeaman and House also provides indirect acquisition and extinction of responses not made.

2. COMPLETELY NONDIRECTABLE COMPONENTS OF ATTENTION One theory exists in which all the dimensional saliences remain fixed on every trial. It is the House and Zeaman (1963) Multiple-Look, Markov Model. The models of Restle (1962), and Trabasso and Bower (1968) have dimensional saliences which are subject to change with success trials(due to neutralization and focusing), but return to a fixed value after each error. On the basis of this error trial return, attention in this theory is classified as unmodifiable. Spence’s (1960) model has a similar feature, the response strength difference to the cues (APr) allows apparent control by a dimension to change while the salience of the dimension remains fixed. In Restle and Spence, all dimensions are of equal salience. 3. DUAL MODELS

The first dual model (Lovejoy, 1968) explicitly distinguishes for each dimension of attention a nondirectable, innate component (D) which remains fixed, and a directable component ( A ) which changes with reinforcement. The value of D may be any number, while the sum of the A’s must equal one. This last requirement assures that when one dimension is incremented, the others are decremented and vice-versa. A dimensional salience may grow, then, only as far as D + 1. Depending on the innate salience of the other dimensions, this may or may not be sufficient for focusing. The response strength (A Pr) feature, however, insures focusing no matter how small D + 1 is. The equation describing this process is C = (D + A)/V( 1 - V), where C is a dimensional control weight and V is the relative cue strength of one of the available cues on that dimension. This weight, normalized by

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division by the sum of all dimensional weights, becomes the probability of control by this dimension. Sutherland and Mackintosh (1971) adapt this same mechanism for their Multiple-Look model. C. Our Position

A-R Theory has completely directable aspects of attention with no fixed components of saliency. Reinforcement and nonreinforcement strengthen or weaken a dimensional response on each trial that these occur. No indirect acquisition or extinction effects are posited to occur since all dimensions act independently in parallel. The equation describing the dynamics of attentional learning is given in Section 11, B, 1. D. Justification

1. EMPIRICAL The experimental effects of primary interest in testing the consequences of these three theoretical approaches are the dimensional strength transfer effects of ID and ED Shifts and the ORE. The completely adjustable, noncue-bound models easily predict these effects. Except for A-R Theory, however, this class of theories is unable to predict the observed interaction of dimensional preferences and dimensional transfer. The completely nondirectable models are at a loss to predict any dimensional transfer effects. These models have a particular goal of ease of prediction and analytic convenience rather than empirical generality. Spence’s model can predict ORE (Wolford & Bower, 1969) but requires extreme parameter values which are not consistent with other applications of the theory (see also the comments of Kendler, 1971). Lovejoy’s dual model, directed particularly to the behavior of rats, can account for the ORE. Lovejoy has not however reported investigations of any parameter values which would support an ID-ED shift difference in the direction observed in children. The prime empirical r‘eason motivating Lovejoy to include a nondirectable component of attention was the persistence of position habits in rats. When a discriminative problem becomes difficult for a rat, it returns to a position habit. Retardates are commonly observed to do this also. The fact can be handled theoretically by assuming (with Lovejoy) a fixed native salience for the position dimension. Other theoretical solutions are possible, however. If, as in A-R Theory, the subject has independent probabilities of attending to more than one dimension, the probability of attending to position could remain appreciable while another dimension is becoming dominant. If then, the dominance of the other dimension is disturbed by introduction of dif-

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ficult new cues, a temporary return to dominance of the position dimension is theoretically possible in our parallel, independent processing system. 2. THEORETICAL The endurance of dimensional dominance does not, of necessity, imply that there must be some fixed strength associated with each dimension. A-R Theory is not yet seriously challenged by the data, primarily because the neutralization of a dominant dimension may be accomplished through the APr feedback rule. If APr is near zero, then the effective attention to that dimension, EPo, is also near zero, while the Po itself remains high and ready to be reinstated by introduction of new cues. This feature provides a theoretical mechanism for regression to dominant or preferred dimensions. XII. BREADTH OF AlTENTlON A. The Issue

How many things can one attend to at once? This question was considered by philosophers of antiquity, and remains apuzzle for psychologists of today. The experimental answer appears to depend upon what is being attended to and how short a time “at once” means. Translating to the domain of discriminative learning, the question may be rephrased how many dimensions are attended to on a single trial? B. Theoretical Alternatives

Classification of theories may first be made on the basis of the number of “looks” per trial single or multiple. If the breadth of attention is not restricted to a single dimension, the next question is how large and constant is the number of dimensions sampled. The third issue is when the sampling is done: at the beginning or end of a trial, or both, and whether resampling occurs on all trials or just error trials. For theorists who assume resampling, the final question is one of “local consistency.” If a subject resamples dimensions at the end of a trial, he may alter his cue-preferences in accordance with the trial outcome (local consistency) or not. Table I1 classifies some major theories on these issues. The unsettled nature of the breadth of attention issue is reflected by the rich variety of alternatives described in the table. C. A-RTheory

As indicated, our theoretical position assumes that the subject may attend to and learn about more than one dimension on a single trial. The further

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TABLE I1 CLASSIFICATION OF THEORIES ACCORDING TO BREADTH-OF-ATTENTIONASSUMPTIONS Theory

Number of looks

Sampling

Zeaman and House Lovejoy

Single

Beginning of every trial Beginning of every trial

Restle

Multiple, fixed sample size

Trabasso and Bower

Multiple, fixed sample size

Spence (1936)

Multiple

All dimensions sampled

House and Zeaman

Multiple, sample size is a random variable Multiple, sample size is a random variable Multiple, except when one analyzer is very strong, then single Sample size is a random variable

Beginning of every trial

None

Beginning of every trial

None

Beginning of every trial

None

Singlea

AttentionRetention Sutherland and Mackintosh

Maintain sample consistent with previous correct trial Same as Reslte

~~

Resampling None After trial outcome, with probability I, and local consistency After error outcome, without local consistency After error outcome, with local consistency None

~

aLovejoy has what might be called a look-and-a-half. The subject’s response is controlled by a single dimension, but learning may occur on some other dimension.

assumption is made that attention to one dimension is unaffected by attention to any other dimension (i.e., independent or parallel processing). D. Justification

1. EVIDENCE FOR M ULTIPLE-LOOKING A reasonably direct test for attention to more than one dimension (multiple-looking) is provided by training on a problem with redundant relevant dimensions, followed by tests on the individual component dimensions. For example, a discrimination is trained with both color and form relevant, then separate test trials are run for the color information (with form held constant)

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and for the form information (color constant). Special controls are needed. First, only a single training trial can be used, otherwise the single-looker may learn about form on one trial, color on another. Second, only a single test on each component should be run to prevent learning on earlier tests affecting later tests. Data on retardates are available from an experiment using this Component-Test-of-Redundant-Information Design. Fisher et al. (1969) trained two groups of higher and lower MA on a two-choice visual discrimination with color and form relevant. In order to get sufficient learning in asingle trial, a Demonstration-Trial procedure was adopted which has been found to be highly efficient. On the training trial, only the positive stimulus is presented (demonstrated) with instructions to learn and remember this stimulus. Let us say that the demonstrated stimulus is a red square. Two component tests are then run. If color were to be tested, the subject may be shown red and green circles, and is told to choose “the old one, the one shown before.” Choice of red indicates retention of color information. A form test might be a blue square and a blue triangle. Choice of the square indicates retention of form. The color form component tests are run in counterbalanced order. Proof of multiple-looking comes from performance levels greater than 75%, since the single-looking subject could average this well (100% on the one dimension attended and 50% guessing on the other averages to 75%).

’POMI 10 ou O l f

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FIG.8. Tests for component information of color and form after a single redundant Demonstration Trial (left panel). Corresponding tests for a Standard redundant training trial (right panel). Retarded subjects at two MA levels were run under both conditions. Performance levels above 75% (dotted line) imply multiple-looking.

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21 I

Performances reliably higher than 75% were obtained, and are graphed in Fig. 8, in the left panel. The higher MA level subjects show considerably more evidence of multiple-looking than the lower levels. The use of a standard discriminative learning design, with both positive and negative stimuli appearing on the training trial, yielded results shown in the right panel of Fig. 8 for two other comparison groups. Evidence of multiple-looking is marginal for the brighter subjects and is missing entirely for the duller. A first-order theoretical approximation of these results has been computed by Bonnie McBane who simulated the conditions of the experiment with two groups of Stat-children. Two dimensions were made relevant but the initial probabilities of observing each were madevery high for onegroup (starting at about .95) and much lower for the other(starting at about .25 and increasing over the experiment). The starting probabilities of looking at both dimensions for one group was thus approximately .9 for one group and .07 for the other, since the multiple-looking probabilities are merely the products of the Pos for each dimension. The results of the simulation are presented in Fig. 9, together with the other parameter values used. Simulation of the data from the Standard Condition are not yet available, but the effects can easily be approximated by adjustment of the parameter values for initial attention to the two component dimensions. A simple conclusion from these results is that under some conditions, and for some retarded subjects, the breadth of attention is greater than a single dimension on each trial, and that any theory of retardate discriminative learning must therefore allow for this possibility. The data suggest, at least, that breadth of attention may have adevelopmental parameter, with brighter subjects having a greater breadth of attention for tasks that demand it. The last point emerging from these results is the suggestion that breadth of attention is to an extent adjustable depending upon situational variables. The weaker extent of multiple-looking with the Standard Procedure than with the Demonstration-Trial Method suggests this. More will be said in a later section about this control process aspect of attentional breadth. 2. THEORETICAL COMPLEXITY OF MULTIPLE-LOOKING One-look models are very attractive mathematically in their relative simplicity and tractability. If the data tell us, however, that multiple-looking occurs, simplicity must give way to generality, but not without considerable cost in theoretical complexity. The first bother to emerge is that offomsing. To solve a discriminative problem with only one relevant dimension and other irrelevant dimensions, the mulitple-looker must learn somehow or other to stop looking at the irrelevant dimensions, and focus only on the relevant. The second problem is that ofcombination andconflict of cues. Con-

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STATCHILDREN

HIGH, - @

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70

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TESTS

FIG. 9. Two groups of Stat-children simulating the performance of the High- and LowMA Groups of Fig. 8, under the Demonstration Trial Procedure. The High Stat-children had higher parameters for initial attention (Po = .95); for the Low Group P = .25. Parameter conditions differing from those of Table I were Or = .99, Ooe = . I . p was zero except for the High Group under the Form Condition, in which case p = I , a = .9. Decay rates were 1.4 for the Highs, 2.2 for the Lows.

sider the subject who notices on a single trial that one of the stimuli is both red and square. If red were previously correct and square incorrect, what would he do in this conflict situation? How does he combine his conflicting tendencies to decide upon an overt response? This is the problem ofresponse generation. A third complexity, that of learning, also arises from conflict in information about two dimensions. For instance, on a conflict trial, the subject may prefer one stimulus because of its form cues but the other stimulus for its color cues. Whatever rule of overt response generation is used to translate these conflicting preferences into action, only one covert preference agrees with the overt response. The question is: should only that preference be reinforced or extinguished by trial outcome, or should preferences on both dimensions be modified, and how? A related issue concerns the learning and extinction of the dimensional observing responses in cueconflict trials, a matter previously discussed in Section VIII. A variety o f theoretical positions has been advanced for solution of these problems. In the Hypothesis Sampling theories of Trabasso and Bower (1968) and o f Restle (1962), focusing of attention in achieved bydropping from the focus sample dimensions which are inconsistent with trial outcome. This occurs only on “success” trials. After an error, the system “unfocuses” again and reverts to the original fixed state of multiple-looking. In the model of Sutherland and Mackintosh (1971), several focusing

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mechanisms are considered. First, analyzer strengths are subject to direct acquisition or extinction effects by trial outcomes. These effects favor relevant dimensions since reinforcement is more consistent for them. Secondly, indirect acquisition and extinction also occur since analyzer strengths sum to a constant amount. In A-R Theory, direct acquisition and extinction of attentional strengths by outcomes are assumed but no indirect changes are posited. An additional mechanism, common to both theories, also fosters the focusing of attention through a feedback principle. When the cues of an observed dimension develop large preference differences, the effective probability of looking at that dimension is enhanced. The principle is discussed in the next section. The Response Generation problem admits of two general types of solutions: maximizing and matching. In a cue-conflict situation, if the subject considers only his strongest preference in determining overt response, a maximizing principle is used. If a kind of average of conflictingpreferences is computed for each stimulus, the term matching is descriptive. Details of this issue are in the Response Generation section. The question of cue-preference learning in conflict situations appears to receive uniform treatment in one major respect among the Multiple-Look theories we have examined. Cue preferences for all observed dimensions are changed by outcomes regardless of whether the dimensions (or cues) agree with overt performance or not. Where opinions diverge is in how trial outcomes change conflicting preferences. Some examples follow. In the Trabasso and Bower (1968) model, a successtrial neutralizes erroneous cue preferences and preserves correct preferences for observed dimensions. On error trials, cue preferences are changed(loca1consistency). For Sutherland and Mackintosh (1971) and in A-R Theory, a different rule obtains: on all observed dimensions, the correct cue preferences are reinforced, and incorrect preferences are extinguished on every trial. Resolution of each of these breadth-of-attention subissues by experimental tests of any directness is, as might be expected, problematic. Still, we can look for indirectly related empirical consequences of the position we have adopted and indicate which assumptions are most closely tested by the data. The focusing and feedback problems are dealt with in another section, as is response generation. Some evidence exists for the independent or parallel processing assumption that might be reviewed next. 3. ID-ED WASHOUT

The usual ID-ED experiment makes use of just asingle shift from original learning to one of the two transfer conditions. A variant of this design has a series of shifts, alternating between ED and ID shifts. Scott (1966) and House

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Mary Ann Fisher and David Zeaman

(1968), using a Miniature-Experiment Design, with a small number of trialsper-problem found that with irregularly alternating ID-ED shifts, the difference between performances under its two conditions were minimal. With normal children, Campione and Wentworth (1969) report the ID-ED washout on the second of two successive shifts. That A-R Theory can handle this washout of ID-ED effect can be shown with a theoretical simulation using two groups of identical Stat-children. Both groups were given a series of three-trial problems alternating as I D or ED shifts. The first group received an I D shift for the first shift. The second group received an ED shift first. The two groups thus remained out of phase. Figure 10 plots the results with all the I D points connected and all the ED points connected (although these belong to separate but parametrically equivalent groups). The first point on Fig. 10 is for the first problem, which cannot be regarded as a shift. Over the next four problems, the expected ID-ED differences appear for two problems and are lost on the next two. With extended series of problems the overall ID-ED differences would be diminishingly small. The initial parameters for this simulation were Po = .7 for each of the two dimensions and Buffer size = 1 and a = .9. Other parameters were consistent with those usually employed for Miniature Experiments. The simulation is successful in showing that the theory can predict a washout of the ID-ED effect in a multiple-problem, repeated-shifts design. T o predict this effect, the theory relies on the independent buildup of higher and higher attention probabilities t o each of the alternately relevant dimensions. Without a parallel processing postulate, the deduction of this interesting phenomenon is difficult. Whether other theories can handle it we are not sure. 4. CONFLICT AND COMBINATION OF CUES

When a two-valued irrelevant dimension is included in a three-trial problem, a conflict arises the first time the cues of the irrelevant dimension change

PROBLEMS

FIG.10. Washout of ID-ED shift effects in two groups of Stat-children given alternating ID-ED shift problems. The points have been connected for the same condition rather than the same group.

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ATTENTION-RETENTION THEORY

association with the relevant positive and negative cues. To illustrate, if the positive cue, p, appears with irrelevant cue, x, on trial I , but then appears with the other irrelevant cue, y, on trial 2, a conflict is defined. If p and x remain associated on trial 2, the cues combine (i.e., are redundant). Thus there are two types of trials to be considered. Call the combination of relevant and irrelevant cues on trial 1 “A.” Call the conflict trial (with respect to trial 1) “A’.” In a series of three-trial problems, then, trials 2 and 3 can be of the form AA, AA’, A’A, or A‘A‘. Retardate data for these kinds of trial sequences are available from an experiment by Hoffman and House, discussed in detail in House and Zeaman (1963). Only the form-relevant data are reproduced in Fig. 11, but the “color-relevant” half of the data can be simulated equally as well with the same parameters. The conflict trials remain above chance because form is, as usual, more salient than color. The theoretical simulations provided approximations of the data which we consider reasonable since most of the parameters used here have also been used in our other simulations. The value of these data lies less in their crucialness for tests of competing theories than in their parameter-fixing aspects.

5. REDUNDANCY Another phenomenon that can be predicted by a multiple-looking model is the facilitating effects of adding redundant dimensions to a discrimination problem. Some relevant data have been published by Zeaman and Denegre (1967) and are reproduced in Fig. 12. Moderately retarded children were presented a series of three-trial problems with one, two, or three relevant dimensions. Performances on trials 2 and 3 reflect strongly the facilitation attributable to redundancy. We have simulations available for one and two relevant dimensions using parameter values consistent with other data from Miniature Experiments with our subject population. Figure 13 shows the

TRIALS

FIG. 1 I . Data and theory: conflict and combination of cues in a three-trial problem with a two-valued irrelevant dimension. The irrelevant cues on an A‘ trial have opposite reward values from those on an A trial. Theory functions are A-R Theory Stat-children with theusual parameters.

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TRIALS FIG. 12. Performance on trials 2 and 3 on Original Learning for Problems with one, two, or three relevant dimensions, illustrating facilitative redundancy (from Zeaman & Denegre, 1967). Copyright 1967 by the American Psychological Association and reproduced by permission.

results. The agreement of theory and data lies in the ordering of conditions and roughly in overall levels, using borrowed parameters. Theoretically the greater the number of relevant dimensions, the more likely is the subject to make at least one correct observing response, thereby providing the occasion to learn the correct cue-preferences. Also, there are correspondingly fewer dimensions to be extinguished. Again, the crucialness of the data for multiple-looking or parallel processing is not very great. One-look models can predict facilitative redundancy with ease, as has been shown, for example, by Zeaman and House (1963). Facilitative redundancy is merely consistent with our multiplelooking theory in a semiquantitative way.

6. OVERSHADOWING One empirical effect that may challenge rather than support our assumption of independent attentional strengths is the phenomenon of overshadowing: the presence of a strong dimension inhibits learning about a weak dimen2 REL.

*Y 1I00

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. 9

L

0 Y

Y

L

e

0

1 REL.

60

-05 0 1 1

3 3

TR5 IALS 7 5 7 TRIALS

9 9

FIG. 13. Stat-child learning curves for one and two relevant dimensions showing facilitative redundancy as in Fig. 12.

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ATTENTION-RETENTION THEORY

sion, although both are redundant and relevant. The effect can be shown on transfer trials in which the strong dimension is removed and subjects show little knowledge about the cues of the weak dimension (compared with subjects trained with only the weak dimension relevant). Another way in which overshadowing has shown up is in the consistent negative correlation of amount learned about two redundant dimensions of near-equal salience. Both these effects have been shown in rats (see Sutherland & Mackintosh, 1971) and in college students (Trabasso & Bower, 1968), so it is not unlikely that retarded children might also show the same effects, although we have no data. The deduction of overshadowing is difficult in our system because changes in attention to one dimension do not affect attention to others. Sutherland and Mackintosh have proposed two possible theoretical mechanisms which can be used in conjunction with multiple-look postulates to derive overshadowing to be a strong effect. In the meantime, we hold to our multiplelooking and independent-processing assumption because of their accord with other data. XIII. FEEDBACK A. The Issue

To account for dimensional transfer effects, several theories already discussed have inferred that attention is controlled by dimensional aspects of stimuli. The basic question here is whethernreproperties, as well as dimensions, exert some control of attention. Since the role of a dimensional observing response is to make cues available to the subject, any assumption that the cues in turn act back upon the observing response that produced them can be described as a feedback principle. 6. Theoretical Alternatives

In the pioneer, observing-response theory of Wyckoff (1952), cue-preference differences were assumed to affect the likelihood of their being noticed. Lovejoy (1968) also has formalized a feedback principle in his concept of a “controller” dimension. Basic attentional strength is the sum of nondirectable (D) and directable (A) components, but these are not the only factors that determine which dimension will control behavior. “Controller” strength of adimension is computed from basic attentional strength modified by the preference (V and 1 - V) for the two cues on that dimension. The equation is C = (D + A)/V( 1 - V). This means there are two kinds of attention, basic and controlling, in which the latter is computed from the former through cue feedback.

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Mary Ann Fisher and David Zeaman

Sutherland and Mackintosh ( 1971) have adopted the identical mechanism with minor changes in terminology. A case can be made for inferring a feedback mechanism in the discriminative theories of Spence (1960) and Medin (1969), but since neither of these has an explicit dimensional response, elaboration of the point will be omitted. C. A-RTheory

Reference to the theoretical block diagram in Fig. 1 shows afeedback loop running from the cue-significance system to dimension selection. Within the “Attention Selector” box are (adjustable) strengths of attending to dimensions (Po’s). After the cue-significance operates on these, new attentional strengths are computed, called effective attentional strengths (EPo’s). The difference in preferences for the cues on each dimension are measured theoretically by a quantity called APr which in turn can be computed by the absolute difference in preferences for the two cues. Effective attention (EPo) for each dimension is the product of Po and APr. The equations are presented in Section 11, A, 2, b. D. Justification

1. EMPIRICAL There are seven empirical effects that the feedback rule helps to bring within the compass of multiple-looking theory. The major work done by the feedback rule lies in the focusing it produces on dimensions having relatively strong cue-significance, without extinction of attention to other dimensions. The seven phenomena are next described, along with the mechanisms of feedback control. a. Facilitation by Introduction of a Novel Cue Retardates, failing for many trials on a discriminative problem, have been observed to improve dramatically when a new positive or new negative stimulus is introduced. This facilitation by a novel cue has been reported by Zeaman et al. (1958). The effect is easily interpreted by appeal to feedback. If the reasonable assumption were made that the cues of the original problem had inappreciable significance for the failing subject, then A Pr would be very low for the relevant dimension. Substitution of a novel cue for one of two equally preferred can help increase A Pr, if, as is likely, the novel cue is not exactly equal in preference to the old cue. In any case, it could not hurt. The theory can therefore predict the novel cue findings by the simple assumption that the introduction of a novel cue changes to some extent the cue-prefer-

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ence differences (A Pr) which had previously been low. The parameter to be adjusted here is initial L(x), the LTS-cue-preference measure, which controls initial APr.

b. Effects of Learned Differences in Cue-Preferences Campione and Wentworth (1969) performed a clever experiment to demonstrate that differential cue-preferences served as a determinant of attention. They compared speed of discriminative learning during ED-ID shift performances with introduction of new or old cues on the relevant dimension. The old cues were those for which preferences had been formed during a prior learning task. The new cues were untrained. Control for specific cue-preferences in the “old” condition was mounted by having half the group with the preferred cues positive, and the other half negative. Speed of solution of the discrimination was reliably faster in the “old” condition, supporting the conclusion that cue-preference differences had appreciable effect on attention. Retardate data are unavailable for this effect, but the subjects in this experiment (normal children) had mental ages in the range of many of our retardates (approximately 7fyears). c. Effects of Physical Differences in Cues Strong evidence that cue properties affect attention is derived from the data of Shepp and Zeaman (1966) described in Section IX,Fig. 2. There it was shown that larger physical differences between the positive and negative cues led to faster solution. That the effect was on attention rather than learning was inferred from the shapes of learning functions. Theoretically the attention variable controls length of initial plateaus rather than slopes. From this it was reasoned that cue-differences control attention. Feedback provides a mechanism for this. The only assumption that is required is that larger physical differences between cues provide greater opportunity for initial cue preferences to operate. The parameter involved is again initial L(x), or A Pr. d. Loss of ID-ED Effect with Constant helevants Several studies have shown that dimensional transfer effects disappear when the cues of the irrelevant dimension are held constant within a trial. Dickerson (1967), Dickerson, Wagner, and Campione (1970), and B. E. Shepp and V. A. Gray (unpublished results, 1971) have presented evidence with young, normal children demonstrating strong differences between ED and ID performances when the cues of the competing dimensions were variable on all trials. When, however, the cues of the irrelevant dimension during shift were held constant at a single value, inappreciable differences were found between ED and ID conditions. The feedback principle predicts

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such an effect since the constancy of the cues o n the irrelevant dimension eliminates effective attention to that dimension (APr = 0, hence EPo = 0). With no competition from irrelevant dimensions the remaining relevant dimension (with variable cues, of course) controls performance to about the same extent in both ED and ID conditions. House and Zeaman (1962) report an ID-ED study on retardates in which the cues on the irrelevant dimension were either constant or variable during training, but always variable within trials during shift. Under those conditions the ID-ED differences did not, on the average, tend to disappear, an effect also consistent with the feedback principle. In this case cue preference differences (APr’s) would be present during shift in equal degree for both relevant dimensions, but since these APr’s multiply stronger Po’s in the ID than ED condition, the expected outcome is an ID-ED difference. The very same effect has been reported by B. E. Shepp and V. A. Gray(unpub1ished results, 197 1) with normal kindergarteners.

e. Perfect Learning with Variable Irrelevant Cues Irrelevant dimensions are not indirectly extinguished in our system. If during the learning of a relevant dimension the irrelevant dimension does not receive appreciable direct extinction, the irrelevant dimension will maintain appreciable attentional strength (Po). Now if the cues on the irrelevant dimension are variable, and some preference difference for these cues remains, then the effective probability of attending to the irrelevant dimension (EPo) will also remain, and the system will not show perfect learning(asymptote of zero errors). Retarded subjects do, of course, approximate perfect learning of discriminative problems as shown for example in Fig. 2 and 18, so it is necessary to have some mechanism within the theory to eliminate effective attention to irrelevant dimensions. This is largely achieved by neutralizing of cue-preference differences with consequent elimination of effective attention to irrelevant dimensions via the feedback principle. For neutralization of the cue-preference differences on a variable irrelevant dimension, all that is needed is appropriate assignments for the parameters controlling changes in cue-preferences (the usual 0 values). Whatever parameter assignments are made to achieve theoretical perfect learning must also be consistent with constraints set by simulation of other effects. Special or unusual parameters are not needed to deduce perfect learning with variable irrelevant cues. This is shown in Fig. 18.

f: Perfect Learning with Initial Multiple-Looking The problem described in the previous section is not restricted to conditions of variable irrelevant cues, but is inherent in any multiple-looking system. Not all multiple-look models can predict perfect learning. The model of House and Zeaman (1963) is a case in point; it accounts well for the data

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of Miniature Experiments in which only asmall number of trials are given per problem. In this domain, perfect learning is seldom achieved in data, so the inability of the model to predict perfect learning is no immediate embarrassment. If, however, in the middle of a series of miniature experiments one inserts a trials-to-criterion problem, other data indicate that perfect learning can be accomplished by retardates. The point we wish to make here is simply that the present model permits multiple-looking during the course of problem solution (with one relevant dimension) and still permits ultimate focusing on the one relevant dimension. New simulations are not necessary here. A-R Theory has been shown capable of predicting perfect learning, and during the course of learning multiple-looking has occured to some extent, since the probability of multiple-looking is related to the products of the independent probabilities of looking at the various dimensions. At the end of training, only one dimension is focused upon (effectively attended to) because of the feedback influence, but other dimensions may still have some probabilities of being noticed (Po > 0). g. Cue-Blocking In cue-blocking experiments the subject is trained on a problem with two dimensions, the first relevant, the second variable and irrelevant. The subject is then presented a number (N) of trials in which both dimensions, using the same cues, are relevant and redundant. Component tests at the end of training show that less was learned about the irrelevant-made-relevant dimensions under these conditions, than when only N trials of both relevant are given (Sutherland & Holgate, 1966). The theoretical effect of the first training trials in the blocked group is to reduce the cue-preference difference on the second dimension to a low value, thereby lowering the effective Observing Response strength during the second stage, and inhibiting new learning about the cues. If the inhibition is not complete (partial blocking), the term “incidental learning” is used to describe the extent of learning of the cues on the presumably blocked dimension. Sutherland and Mackintosh (1971) review the large literature for animal subjects on blocking and incidental-learning effects. On the human level, experiments using variants of the cue-blocking and incidental-learning paradigm have been conducted with subjects varying widely in developmental level. To cite some of these, Trabasso and Bower (1968) report complete cue-blocking in college students while Stevenson (1954) and Siege1and Stevenson (1966) have shown partial blocking for subjects varying widely in developmental level. The most recent demonstration of blocking in young children has been done by Anderson (1971). A variant of a cue-blocking experiment by Shepp and Ross (reported briefly in Ross, 1966) showed some degree of incidental learning with retarded subjects, but with no assessment of the degree of blocking.

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The phenomenon of cue-blocking falls out easily as a consequence of A-R Theory. During the initial stage of such experiments the cues of the irrelevant dimension tend to have their preference values neutralized. The feedback mechanism then dictates that effective attention to the originally irrelevant dimension will be very low when this dimension is now made relevant. It has been found with animal subjects and adult humans that cue blocking effects are reduced or eliminated if novel cues are introduced on the to-beblocked dimension during the redundancy phase of such experiments (Mackintosh, 1965; Trabasso & Bower, 1968). This effect, not yet studied with children or retardates, is readily deducible from A-R Theory. The only assumption needed is that novel cues have some preference difference at the time of their introduction, an assumption made for all our simulations. The feedback of cue-preferences boosts attention to the redundant dimension and predisposes the subject to incidental learning rather than to blocking. Partial blocking or incidental learning can also be predicted if the training operations are such as to only partially neutralize the cues during first stage learning. From this it can be seen that A-R Theory is prepared to account for any outcome of cue-blocking or incidental learning depending upon parameter assignments. If the parameters for particular subjects and conditions are fixed by prior experiments, then our system is no longer post hoc. There is at present insufficient data on cue-blocking and incidental learning with retardates to provide a critical test of A-R Theory. We will merely state at this juncture that within the parameter ranges we typically use for retardates, both blocking and incidental learning are simulable. Precise tests of theory are possible, but the experiments have not yet been run. A critical test of two competing theories of cue-blocking could be arranged. Attentional theories such as those of Sutherland and Mackintosh (1971) or Zeaman and House (1963) do not have parallel processing of dimensions. These versions can account for cue-blocking in quite a different way than A-R Theory. During the initial phase of acue-blocking experiment attention is focused on one dimension, providing competition for all other dimensions. The blocking that occurs during the redundant phase may theoretically be attributable to response competition among dimensions. In A-R Theory there is no attentional response competition; focusing is accomplished by feedback from cue-neutralization (or direct acquisition and extinction effects). The differential consequences of these two theories in a cue-blocking experiment can be arranged simply by having either a constant or variable irrelevant dimension during the first phase of the experiment. Unless the cues of the to-be-blocked dimension are variable and irrelevant, A-R Theory (depending as it does on cue-neutralization for focusing) does not predict cue-blocking, under the constant condition, whereas the nonparallel-processing theories do. Retardate data are badly needed here.

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XIV. RETENTION A. Overview

Quantitative theories of memory (iconic and Short-Term Store, retrieval, and Long-Term Store) have burgeoned in recent years. For apartial review, the book edited by Norman (1970), Models of Human Memory, provides an up-to-date summary. Most of this work has been designed for application to normal adult subjects, but extensions to the area of retardate memory have been made in the programmatic work of Ellis( 1970),Belmont (1966), Belmont and Butterfield (1969), and Scott and Scott (1968). Given these advances, it is surprising that no attempts have been made at formal integration of memory theory with the previous developments in retardate discrimination learning theory (see Estes, 1970, for a recent summary). A-R Theory attempts a rapprochement. The formal theoretical machinery of the memory model of Atkinson and Shiffrin (1969) has modular aspects which allow it to be “plugged into” an attentional theory of retardate discrimination learning. The separation of memory and learning research has historically been the result of a division of scientific labor and interest. Learning theorists usually minimize retentional effects in their experimentation, while memory researchers try to hold learning constant to study retentional effects. In our own programmatic attempts to analyze the discriminative learning processes of retardates, we were forced by the data to consider short-term memory phenomena when we changed from a Trials-to-Criterion Design with a single problem to Miniature Experimental Design with several problems concurrently trained with a small number of trials per problem. Interference and forgetting were manifested so clearly under these conditions that the theoretical problem could no longer be ignored. B. A-RTheory

In nonquantitative form the major retentional postulates may be stated as follows: 1. SHORT-TERM STORE(STS)

a. Destructive Read-In For attended dimensions, items of cue-reward information are entered into STS with destructive read-in. This property entails the erasure of all former items when a new item is entered.

b. Spontaneous Decay Item strengths in STS spontaneously decay in time, with rates controlled by item parameters.

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Quantitative statements of ( a ) and ( b ) above are given in Sections 11, B, 2 and 11, B, 5.

2. REHEARSAL BUFFER a. Entry Items in STS may be entered into a Buffer of limited capacity (equal tog, a variable quantity that may be zero).

b. Interference If the Buffer is filled, a new item has a probability (a)of replacing an old item in Buffer. Buffer dynamics are postulated in quantitative form in Section 11, B, 3.

3. LONG-TERM STORE(LTS) a. Entry Items in Buffer or STS enter LTS with probabilities related to the learning rate parameter 8. b. Buffer-LTS Interaction Items achieving a high degree of strength in LTS are neither entered nor retained in Buffer. The quantitative statement of this dynamic appears in Section 11, B, 6 . C. Justification

Many empirical effects have been uncovered in retardate discriminative learning that appear retentional in nature. A representative sample of these will be described (each briefly) and grouped into sections corresponding roughly to the major components of the memory system needed to provide theoretical accounts of the phenomena. 1. SHORT-TERM STOREA N D BUFFER

a. Decremental Effects of Intertrial Interval and Interpolations Decay and interference were demonstrated in a coordinated series of studies by Klinman (1964) who compared the amount of forgetting produced by interpolating either time alone or a retroacting item between a single training trial and a test trial. A standard, two-choice discriminative learning task was employed (Miniature Design) with moderately retarded children. The training stimuli (geometric shapes) differed in both color and form. In one condition, intertrial intervals, for different problems, were either 15 or 30 seconds of unfilled time; in another condition the 30-second intertrial

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interval was “filled” with a training trial on a different color-form problem to provide retroactive interference. An additional feature of the experiment was the inclusion of redundant and component tests. For the redundant condition the test stimuli were the same color-form patterns used on the training trial: for the component condition, the test items were one-dimensional (the color or the form of the original pattern with the other dimension constant). Figure 14 (in the “Data” panel) graphs the performances under all the conditions of the experiment with color and form test trial data averaged. There are four empirical effects of interest: (1) Time alone causes forgetting; (2) Interpolated trials produce more retention loss; (3) Component tests yield weaker performance than redundant tests; and (4)There is not much evidence of interaction of main effects. Theoretical simulation of these four effects was attempted using borrowed parameters. Stat-child performances are drawn in the “Theory” panel of Fig. 14. The three main effects and absence of interaction agree in theory and data, but the magnitudes are off. These could be adjusted considerably by parameter juggling, but we are aiming primarily here for a semiquantitative (order-of-magnitude) recovery by theory of a number of qualitative effects rather than a precise account (with many free parameters) of afew empirical findings. T o account for the temporal effects, the spontaneous decay of information in STS does the major theoretical work. The retroactively inhibiting influence of the interpolated trial is theoretically the consequence of destructive read-in to STS. On test trials, after an interpolation, only long-term strength and the rehearsal Buffer are available for responding on the test trial. The facilitating effects of redundancy in this experiment are less centrally

FIG. 14. Retention losses with component and redundant tests are compared for conditions of interpolated material and unfilled time. A-R Theory Stat-children functions are plotted at left.

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related to retentional dynamics than the other effects. These are, however, consistent with the theory as shown by the simulations, and are consequences of our attentional assumptions of parallel processing, and of our response generation rules. b. Proactive Interference and Intertrial Interval In a series of discriminative problems, each given for a small number of trials, performance is sometimes observed to be poorer on later problems than on earlier ones. This proactive interference effect tends to be greater with longer intertrial intervals. This interactive effect has been shown with college students in verbal learning experiments (see Keppel & Underwood, 1962) and also with retardates learning a series of standard two-trial discriminative problems. Marcia Knight (1968), employing a Miniature Design, varied the intertrial interval in a series of dimensionally homogeneous but discrete problems with retarded children, and found considerably more proaction with a 20-second interval than with completely massed presentation (zero intertrial interval). Her data are reproduced in Fig. 15. In theory, proactive interference is a Buffer phenomenon deriving from competition of items for entry into a filled rehearsal Buffer. The likelihood of a limited Buffer being filled increases with successiveproblems. The absence of proactive interference with massed trials derives from the assumption that with immediate testing the subjects will be responding with information in STS, which has not had time to decay. Figure 16 presents the results of a Stat-child simulation of Knight’s data using parameters within the usual range for Miniature Experiments (see

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Table 1). The agreement of theory and data is seen in three major features: (1) the absence of proactive interference in the massed trials condition; (2) the presence of PI with spaced trials, and (3) the gradual onset of the latter effect.

Delayed Response In a delayed response experiment the subject is shown the correct stimulus of two presented. A delay (of unfilled time) may then be instituted followed by a test trial consisting of the correct and incorrect stimulus. Typical results show declining accuracy of performance with increasing delays between demonstration and test. Shown in Fig. 17 are the results for a delayed response experiment with low-MA retardates on a two-choice position discrimination (House & Zeaman, 1961). Also plotted in Fig. 17 are the outcomes of a Stat-child simulation of the data. The data and theory correspond in functional form and fairly well in numerical values. To achieve this, the decay rateparameter(8) was set to 2.2, which is somewhat faster than the usual rate of 1.4. This adjustment seems reasonable since the subjects providing the data were of low mental age (MA 2-5 years) when compared to the usual groups run on retentional problems with Miniature Designs. This type of experiment provides the closest test of the STS decay principle. The interesting speculation emerging from this experiment is the inference of a need for faster decay rates for subjects of lower developmental levels, a speculation receiving some support from the independent conclusions of Spitz (1963) from his programmatic research on retardate shortc.

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Delay Interval (See )

FIG. 17. Short-term decay in data and theory. Delayed response data from House and Zeaman (1961).

term memory. It should be pointed out, however, that the recent conclusions of Ellis (1970) are contrary to this notion.

d. Concurrent Problems A Concurrent Problem Design is a special case of Miniature Design in which several problems are learned concurrently. As an illustration, consider the case of three different discriminative problems, A, B, C, in which each problem consists of a different pair of stimuli. Within a single training session the three problems can vary in order of presentation (e.g., ABCBCAABC.. . or AABBCC.. ., etc.). Several variants of this design were employed by B. J. House, A. Martin, B. McBane, and R. Brainerd(unpub1ished results, 1969). In the first variant (among others) subjects were trained to criterion on Singles (AAA. . .) or Doubles (ABAB. . .) for a fixed number of trials per day. In the Doubles Condition demands are made on short-term memory not made in the Singles. Two groups of moderate- to high-level retarded children were run under these conditions, with results shown in Fig. 18 for 2 days of practice. The “Data” panel at right reveals the following features: 1. Doubles performance is weaker than Singles. 2. The difference grows with practice. 3. A marked loss occurs between days. 4. Recovery on Day 2 is gradual but faster than Day 1 learning. The Stat-child performances in the “Theory” panel of Fig. 18 show all of these features, but the formal correspondence is not complete. The Statchild functions undergo differential forgetting between days for the Doubles and Singles, which the retardates do not. Also, the Stat-child functions have

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FIG. 18. Performances on Days 1 and 2 under Singles and Doubles Conditions for both Stat-children (with the usual parameters) and retardates.

an overall level that is too high. Aside from these discrepancies the theory is not strongly challenged by the data. Whether a small amount of parameter manipulation would eliminate the discrepancies is not yet known. The two major theoretical reasons for the observed differences lie in the domain of short-term memory. The Singles Condition permits response from STS, Buffer, or LTS, the Doubles Condition effectively eliminates the possibility of response from STS because of decay and destructive read-in between repetitions of the same problem. In a second study by House, Martin, McBane, and Brainerd, another variant of the Concurrent Problems Design was used, with either two or ten interpolated trials between repetitions of the same problem, as illustrated in the following sequence of trials: 2 N N A A B BCCBB NNB 10

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With this design, all even-numbered trials have a retentional advantage in having an immediately preceding trial on the same problem. Oddnumbered trials permit retention loss through decay and retroaction. The data of this experiment are graphed in Fig. 19 with odd and even trials plotted separately to provide an index of the effects of short-term memory. The following effects can be observed 1. 2. 3. 4.

Odd-trial performances are weaker than those of even trials. Ten interpolated trials produce more deficit than two. The odd-even differences tend to diminish over trials. The N condition function is flat and lower than other functions at the end of practice.

Theoretical simulations of this experiment were attempted with no unusual parameter settings. These appear in Fig. 20. All the main effects enumerated above are present, but the match of theory and data is poor in level and magnitudes of observed differences. Theoretically the Odd-Even differences in both conditions are caused by contributions of short-term memory on the Even trials. The 10 trials of interpolated problems would provide greater opportunity for interference with the trained item in Buffer. The two trials of interpolation are sufficient to erase the memory of trained items in STS. The gradual diminishment of OddEven differences comes about because of the cumulative growth of information in LTS in both conditions. The absence of improvement in the

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“New Problems” condition is the obvious consequence of the absence of opportunity for cumulative growth of LTS information. 2. REHEARSAL CAPACITY: THE BUFFER The Rehearsal Buffer associated with the ith dimension has a temporary limit of p i items, where p i is jointly determined by task demands and the capacity of the subject to rehearse. A major role of Buffer is to provide a theoretical mechanism for interference effects in both retroactive and proactive designs. Another role of the Buffer lies in the account it can yield of very high-level performance after a single-training trial, despite decaying STS and weakness of LTS. a. Retroaction: Similarity of Trained and Interpolated Items A retroaction design (train-interpolate-test) was employed by Klinman (1964) using a Miniature Experiment technique with moderately retarded children in the MA 6-10 year range. After a single-training trial of redundant color and form object stimuli, she interpolated a single trial of new stimulus information either similar or dissimilar in nature. The similar material was another color-form problem; the dissimilar interpolation consisted of a variety of items such as junk, dot patterns, or gray wedges. On component tests of the originally redundant color-form cues, the subjects showed greater

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retention loss after interpolation of similar than dissimilar material as shown in Fig. 21. To simulate these effects it is assumed that the dimensions of dissimilar material are different than those of the original learning. I n this case no interference in Buffer is possible, given our independent processing assumptions. This condition then becomes theoretically equivalent to the “time alone” condition of Fig. 14 already simulated. The Similar Condition should provide opportunity for interference since the training and interpolated dimensions are the same, and simulation of this condition is identical to that of the “Interpolated” Condition of Fig. 14.

b. Proaction: Similarity of Trained and Proacting Items A study by McBane and Zeaman (1970) demonstrated that the stimulus dimensions of color and form controlled the development of proactive interference in the learning and retention of moderately retarded children (MA 6-9 years). A series of six two-trial color discrimination problems was given in uniformly massed sequence followed by a seventh problem on a form discrimination. Performance declined over the course of the first six problems (proactive effect), but recovered to starting level when the problem changed to the form dimension (release from proaction). These results were replicated with a group having the reverse sequence of form-to-color. To simulate these effects the basic assumption needed is that the Buffer size of these subjects is greater than zero and somewhat less than six. Other assumptions are that attention to color and to form was very high (guaran-

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teed by pretraining in the empirical study), and that the other parameter settings typically used for Miniature Designs hold here. The simulation of the proactive effect is shown in Fig. 23 for a series of three successive twodimensional problems. If following such a series a problem featuring a different dimension were introduced, the buffer of the new dimension would be empty, and performance would equal that of the first problem in the series. There seemed little point in running new simulations to meet the precise conditions of this experiment, since we are sure we can recover the main effects with the assumptions indicated. c. Rehearsal (Buffer) Learning

A successful attempt was made to train rehearsal in a recent doctoral dissertation by McBane (1972). She used subjects in the mild and moderate range of retardation, and trained them on lists of discriminative problems of gradually increasing lengths. After pretraining on the relevant dimension (of color or form), the subjects were repeatedly tested with list lengths of one item. All subjects performing at a high level on this task were moved up to list length two. They were shown, for example, form cue A, then immediately tested with cue A versus cue B. Next they were shown the positive cue C of the next problem and immediately tested for this information with a choice between cues C and D. This sequence completed training onlistlength two. After a 20-second delay, two delayed test trials were administered (A versus B, and C versus D) for retention of the two-item list. Following successful performance on two item lists, the list lengths were gradually increased using analogous procedures until a list length was found exceeding the capacity of the subject. In this study, attention was assured because performance on immediate test following each item during training was virtually error-free. Short-Term Store was minimized or eliminated as a source of control by the delay between training and final test, and by the interpolations usually occurring between training and delayed tests. Long-Term Store contributions to performance were minimized by reuse of the same limited set of cues. The only remaining theoretical source of correct responding is from the Buffer. The finding of significance for rehearsal or Buffer learning was this: after the successful learning of each list length N, the subjects could remember, on the average, N plus i items on the next length ofN + 1 items. That is, they behaved as if they had learned to rehearse exactly N items and were forced to guess on the extra item (with probability of f of being right). At the end of repeated training on lists of length N + 1, however, they were able to remember N + 1 items, if they were not at capacity, showing that they had by training increased their temporary Buffer capacity by 1. Each increment in list length was thus accompanied by new learning until final capacity was reached.

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If the interpretation of these results is correct, then it is established that the p (temporary Buffer capacity) represents a control process rather than a structural feature. Whether p has an upper limit (with extensive training), that might qualify as a structural feature, is a separate question. Data from McBane’s thesis bearing on this issue are presented in the final section of this paper. d. Apparent One-Trial Learning If use of a Buffer is to some extent controlled by trainingvariables, then a Buffer capacity may develop during an experiment (e.g., a p = 0 becomes p = 1) with an apparent change in speed of learning. For example, House and Zeaman (1959) trained a group of moderately retarded children (MA’s 3-4 years) on a series of position reversals. After about eight reversals group performance improved to a level of approximately one-trial reversal learning. This could be interpreted as the result of the gradual acquisition of a rehearsal Buffer rather than changes in the learning rate parameter, 8.The two interpretations differ in consequences. The Buffer interpretation predicts that a 24-hour gap between trials would produce a chance-level performance; the learning-rate (0) interpretation would predict no retention loss during a day’s interval. We were prompted by this analysis to go back to the data of the House and Zeaman (1959) study and look for instances where a day’s interval occurred between successive reversals, rather than the usual 15 seconds. We found 80 such cases. After achieving a criterion of 10 successive correct responses to one position, in only 43/80, or 54% of the cases, did these subjects go to the previously correct position at the beginning of the next day’s training. In brief, the performances in this experiment were controlled not by LTS, but by some aspect of short-term memory which we infer to be Buffer capacity. In this sense, one-trial reversal learning is not learning at all (in the long-term sense) but rather an echo-box or rehearsal phenomenon.

3. CONTROL OF BUFFER BY LONG-TERM STORE The simple idea behind this section maintains that subjects do not bother to rehearse things they already know. Translating in theoretical terms, items reaching a critical strength in LTS are dropped from Buffer. Also, welllearned items do not compete for entry with those already in Buffer. As tests of these notions, several experiments with retardates are available in which the degree of training of proacting and retroacting items wasvaried. Expectation would be the more the training, the less the interference.

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a. Degree of Training of the Retroacting Items Two studies using Miniature Designs permit a roughly controlled comparison of the effects of degree of training of the interpolated item in a traininterpolate-test sequence (J. C. Campione and D. Zeamon, unpublished results, 1969; Scott, 1966). I n the Campione and Zeaman study each ofthe interpolated trials used all new stimuli. I n the Scott experiment, a single, well-learned item was used for every interpolation. The results of the two experiments are plotted. in Fig. 22 in the “Data” panel. Although the comparison of the two studies is only crudely controlled, the difference in degree of forgetting is so large that it may tentatively be attributed to the major operational difference in procedure. Despite the higher level of performance under the “New Item” condition at zero interpolations ( a measure of learning), the “New” function drops precipitously after a single interpolation compared to the “well-learned” condition. Retroaction appears to be controlled by the learned strength of the retroacting items. The Stat-child memory functions at the right of Fig. 22 start at the same degree of learning for zero interpolations, since in a properly controlled experiment this would be the case. To represent differences in strength of learning of the interpolated item, the difference in LTS strength of the positive and negative cue (APr) was made relatively large for the WellLearned item and small for the New condition. Other parameters were as usual for this type of experiment. Comparison of theory and data shows concurrence in the main effects but not magnitudes of differences. More precise parameter estimation awaits better controlled data. In qualitative terms, the Buffer dynamics operating here are straightforward. In the New condition, the interpolated items compete for entry into a Buffer that may be filled after one or two item entries, knocking out the resident trained items (with probability a)with con-

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FIG. 22. The retroactively inhibiting effects of interpolating new or well-learned material between single-training and test trials. Data are shown at left; Stat-children are at right.

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sequent decrement in retention. The Well-Learned, interpolated item has no corresponding probability of dislodging the trained item in the Buffer, so retention remains relatively high in this condition. b. Degree of Training of the Proacting Items Knight (1968) arranged a series of 15 two-trial problems in a typical Miniature Design. The problem dimensions were color and form (geometric shapes) throughout the series with both dimensions redundant. Extensive pretraining on these dimensions assured attention to these dimensions, so that over a series of different problems with color-form relevant a decremental (proactive) effect would be expected rather than an incremental (learning-set or ID-shift) effect. The novel aspect of her procedure was the introduction of a previously well-learned item several times within the series. Her results are shown in Fig. 23. The New problems show the development of proactive inhibition within each subseries. Introduction of the Old problem has two effects: performance shows no PI decrement on these problems, and performance immediately following Old problems is elevated. The latter effect is termed Proactive Release. The demonstration that A-R Theory can predict both these effects is shown on the right in Fig. 23. The explanation of the scallopped functions is as follows. With limited Buffer capacity, the later items in a subseries of New problems suffer interference; the Old item remains high in performance since response here comes from a strong LTS because the Old problem does not compete for Buffer space, the previous items already in Buffer are rehearsed for an additional trial. If this additional rehearsal trial brings the items in the Buffer to criteria1 strength in LTS, these will be dropped from the Buffer leaving room for entry of the next New problem in the Buffer without competition. c. Retroactive Interference with Items of Varying Learned Strength An increased number of training trials on the target item enhances not only learning but memory as well. Stukuls (1968) demonstrated this principle with a retroactive design. He trained moderately retarded children (MA 5-8 years) for either two or eight trials on a color-form problem, then interpolated two, four, or eight trials of interpolated material with different color-form cues. A control condition had no interpolation. Retroactive interference occurred under these conditions as shown in Fig. 24, more so after the two than the eight training trials of original learning. In theory the starting difference between the Two and the Eight Conditions is primarily due to the superior item strength in LTS after eight training trials. The increased resistance to retention loss in the Eight Condition receives an explanation in terms of Buffer dynamics. After eight training

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4. INFORMATION TRANSFER TO LONG-TERM STORE Long-Term Store is characterized as a collection of noninterfering item strengths (cue-reward associations). These enter LTS from either STS or Buffer with rates determined by the learning parameters, 0. Several experimental effects in discriminative learning yield data which depend on the nature of LTS.

a. Good Redundancy The greater resistance of redundant material to forgetting is shown in a study by J. C. Campione and D. Zeaman (unpublished results, 1969). Moderately retarded children (MA 4-7 years) were given single-training trials and then tested after varying numbers of interpolated trials on different problems using similar materials. A variant of Miniature Design was used called the Embedded Design [introduced by Peterson, Saltzman, Killner, and Land (1962) and adapted for retardate discrimination learning by House (1968)l. With this efficient technique, an interpolated problem may also serve as a trained item for later test. The use of junk stimuli (pictures of common objects) for both training and interpolated items results in retroaction functions that decline relatively slowly as interpolations are increased from one to eight. In contrast, the use of simple geometric figures differing in both color and form (as both training and interpolated material) yields a more striking drop after a single interpolation as shown in Fig. 25. To represent the multidimensional junk problem theoretically we merely increase the number of relevant dimensions in relation to the two-dimensional color-form problem. We have as yet no simulations for retroaction functions with two-versus-many relevant dimensions, but for another purpose we did compute retroaction functions for Stat-children with one-versus-two-relevant dimensions after two or eight training trials. For gross comparative purposes these are presented in Fig. 26. We attach significance to only two aspects of the simulation: the increase in performance with increased redundancy, and the faster decline in retention with less redundant material. Both effects are present in theory and data. More precise simulation remains to be done. With independent dimensions contributing to performances the probability is increased that at least one dimension will have strength in one of the memory registers. The increased resistance to retentional loss in the redundant condition derives from the fact that each additional dimension has some likelihood of having strength in LTS, thus eliminating the possibility of interference from interpolated material. b. Bad Redundancy Under some conditions redundancy facilitates performance (Good Redundancy) as demonstrated in the previous section, but under other condi-

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:

‘“t

CHANCE .................................................... ........................................................................ .................... 1

1

-

0

1

2

1

1

1

4

8

NUMBER OF INTERPOLATIONS

FIG. 2 5 . RI functions for multidimensional “junk” stimuli and for stimuli differing in only color and form. Increased redundancy of test stimuli decreases loss. Based on unpublished results from J . C. Campione and D. Zeamon, 1969.

(

1

2

4

I

NUMBER Of INlERPOLlTlONS

FIG. 26. Stat-child RI functions for one- and two-dimensional stimuli. An additional parameter is the number of training trials before interpolations.

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tions redundancy has the opposite effect (Bad Redundancy). The major empirical variable that appears to be responsible for these opposing effects is the use of two redundant dimensions vs. the use of two redundant cues on the same dimension. The former is facilitative, the latter decremental. Decremental redundancy has been reported by House (1971), Hyman (1967), and Cahn (1966). They used either (1) one positive and one negative cue per dimension or (2) two positive and two negative cues per dimension. As an illustration of the latter condition, the positive stimuluscard might be composed of a triangle and a square, with the negative stimulus a circle and a diamond. Conditions were otherwise those of standard discriminative trials in Miniature Designs. In both studies, a decremental effect was found for redundant cues with moderately retarded children. On the normal adult level, the opposing effects of redundancy (both Good and Bad) have been shown for the same subjects in a single experiment (Zeaman, Campione, & Allen, 1970). The incremental effect of dimensional redundancy has been simulated in the previous section. To show that A-R Theory can predict Bad Redundancy, Stat-children were run on original learning with one and with two cues per dimension. The outcome is graphed in Fig. 27. This theoretical result depends upon the division of the learning rate parameter in equal portions to all cues in STS or Buffer (see equation, Section 11, B, 4, b. i i ) . In this way each cue in the Two-Cue Per-Dimension problem gains LTS strength with a rate of increase only half the magnitude of that for the One-Cue-Per-Dimension problem, since it is the average rate of increment (rather than the sum of the rates) that theoretically determines the growth of cue-reward information in LTS.

c. Retention Loss over a Day With a Trials-to-Criterion Design, retention loss over a 24-hour interval is typically quite small in comparison to that observed with Miniature Designs in which a relatively small, fixed number of trials are given on each

TRIALS

FIG. 27. The theoretically decremental influence of multiple cue-pairs on the same dimension is shown for two groups of Stat-children. Bad redundancy.

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problem. The Concurrent Problems study described in Section XIV,C, 1, d shows alarge retention drop over aday when 10 trials of acquisition preceded the retention interval. Some additional results are available from data reported by Zeaman and House (1963), in which grossly comparable conditions and subjects obtained, but with 25 trials per problem on each of 2 days. The data are shown in Fig. 28. Some retention loss is observable but not the same order of magnitude as that observed in Fig. 18. The difference in retention loss is theoretically attributable to strengths in LTS, since after a day’s interval, it is assumed that STS is erased and that the Buffer is empty. All that is necessary for a simulation of this effect is the usual parameter array, which would make LTS stronger after 25 trials than after 10, with consequent increase in resistance to retention loss.

d. Gradual Learning The transfer of information to LTS is theoretically controlled by the learning rate parameter 8. Some recently collected data with retarded subjects has a bearing on the value of this parameter. It was pointed out in Section VII that the issue of Gradual vs. All-or-Nothing Learning centered on the value of 8 , and that our use of a value of .5 for second-stage learning rate put us in the Gradualist camp. In order to measure this parameter with maximum degree of directness it is necessary to insure that performance has no contributions from either STS or Buffer. One way to achieve this condition would be to train aproblem

hrront Corrc rt

Two Trial Blocks

FIG. 28. Retention loss over a day (loss of short-term memory). The subjects exhibit a drop in performance on the day following criterion. Recovery by retraining is quick.

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for just one trial per day, embedded within a series of other problems. This radical spacing of trials was employed by Sperber et al. (1972) using retardates in the 5-1 1 year MA range. Training was continued for 16 days using a Miniature Design with average performance reaching approximately 75% correct for the group. The best method of assessing 8 value from these data uses a Backward Learning Curve analysis. Subjects who learned(seven consecutive correct trials) are first segregated. Next we look at precriterion performance level of these subjects. The trial immediately preceding criterion cannot be counted since this by definition of criterion must be an error trial. The trial preceding criterion by two averaged 60% correct, which was reliably higher than the trial preceding it (which in turn was below chance). Postcriterion responding averaged 96% correct. To drive performance from chance to 96% in three trials requires a 8-value of approximately .65, a number close enough to our previously assumed value of .5 to satisfy our semiquantitative requirements.

XV. RESPONSE GENERATION A. The Issue

In the two-choice situation, there are only two possible overt responses. The problem of generating overt responses from the covert response strengths is more complicated for multiple-look theories than for one-look, but all theories must make some provision. I n the end, they all generate some strength or preference for the positive stimulus and for the negative stimulus from which the overt response isgenerated. At one extreme thematching rule dictates that the probability of generating the correct overt response (P +) is equal to the relative strength of the positive stimulus (W +). That is, the probability is the ratio of the strength of the positive stimulus to the sum of the strengths of both stimuli. At the other extreme the maximizing rule says that the stimulus with the higher strength is chosen 100% of the time. Between these two extremes, function rules have been proposed which relate the relative strength of the positive stimulus to the probability of a correct response with a mathematical rule which is neither matching nor maximizing. The ramp function has been used by Lovejoy (1968) and by Sutherland and Mackintosh (1971). Under this function rule, it is proposed that there is a threshold, k, such that when W + is less than k, then P + = 0; when W + is greater than 1 - k, then P + = 1.00; and for values of W + between k and 1 - k, P + is a linear function of W + which rises from zero to one. The matching rule and the maximizing rule are special cases of the ramp function, as may be seen by considering the cases for k = 0 and k = .5, respectively.

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B. Alternative Theoretical Positions

Among the one-look models, only Lovejoy has proposed a ramp function with k = .2. Other one-look models in general use a matching rule, including those of Zeaman and House (1963), several linear models (see Atkinson, Bower, & Crothers, 1965), and Luce’s (1959) Theory of Choice. Multiple-look theories have not been so consistent. House and Zeaman have a matching rule, Spence has a maximizing rule, as does Bower (1967) for his multicomponent memory trace model. Trabasso and Bower (1968) have a matching rule for their hypothesis sampling model. The lack of consistency in such closely related theories suggests that the ramp function may hold in general with the parameter, k, changing with experimental condition or subject population, or both. C. Statement of Our Theoretical Position

A-R Theory uses the matching rule [Luce’s (1959) Rule], at this time for both covert and overt response generation, with the stipulation that this theoretical stance amounts to the assertion that we use aramp function with k = 0. We look forward to incorporating k as a response strategy parameter whose value may be affected by individual or experimental differences. To generate an overt response from the covert responses to the positive and negative stimuli, we simply compute the probability, P + , as the ratio of the number of positive covert responses, N(r), to the total number of covert responses, N(r) + N(f). This rule has been stated in Section 11, A, 2, d. D. Justification of Our Position

1. EMPIRICAL All of the parameter estimations in the current version of A-R Theory have assumed k = 0. This may turn out to be reasonable given the kinds of experiments which have been simulated. The major effects of learning and transfer in the Trials-to-Criterion Design or in the Miniature Experiment Design, except for retention effects, have been generated by matching models of Zeaman and House (1963) and House and Zeaman (1963). Many of them have also been handled by Lovejoy’s model with k = .2. Although the A-R model with k = 0 does well with many experiments, refinements of estimation could show differences. There are particular tasks which seem likely to yield larger values for k. These are in general the whole stimulus or component testing after a Demonstration Trial. The high performance level on these (Martin, 1970) suggests maximizing.

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Another possible experimental way of getting at k is the transitivity design of Campione (1969b). Campione found that when attention to relevant dimensions was properly controlled, the Choice Rule of Luce holds for cuepreferences of retardates in two-choice discriminations. If Cue B is preferred over Cue A, and Cue C is preferred over B, then transitivity implies that C will be preferred over A. Luce’s Rule permits quantitative predictions of the extent of the preference of C over A from a knowledge of the A-B and B-C preferences. Campione found such predictions to hold with good precision for the typical cues used in retardate discriminative learning. An indirect method of demonstrating that transitivity of cues holds for our subjects comes from an experiment in which retardates were totally unable to learn a problem set requiring nontransitivity. If subjects are trained to prefer Cue A over B for one discriminative problem, and B over C in another, then transitivity predicts that A will be preferred to C. An attempt may be made to countertrain this tendency by rewarding C over A. The problem has been called a Conditional Reaction. When Zeaman and House (1962) trained these three (nontransitive) problems concurrently (A > B, B > C, C > A), no evidence of any learning whatsoever was found after 600 trials of training for moderately retarded children with MA’s up to 6 years. 2. THEORETICAL A model with a variable k parameter, free for fitting, would be the most general theory with respect to response generation rules. Our adoption of the matching rule, representing the special case of k = 0, was based on simplicity and goodness-of-fit for the data on hand. Later generalizations of A-R Theory will likely include the k parameter if empirical grounds emerge for its inference. XVI. CONTROL PROCESSES AND STRUCTURAL FEATURES

A. The Issue

Atkinson and Shiffrin (1969) have distinguished two general types of theoretical parameters, those representing fixed untrainable capacities of the subject (structural features), and those which are adjustable by experiential factors (control processes). The distinction is of singular importance for any research program which seeks to discover the relation of intelligence to processes such as learning, memory, and attention. If intelligence isviewed asa stable trait, for which there is ample evidence in our retardate population (Fisher & Zeaman, 1970), then we should look for parameters reflecting structural features rather than control processes to relate to intelligence. In order to carry out such a search it is first necessary to have a theory which

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yields parameter estimates of the various subprocesses. Next, it is necessary to collect evidence that will help in the classification of the parameters as fixed or adjustable. Most of the research presented in this paper has been directed toward the first step of constructing and testing a theory of retardate learning, memory, and attention, but we do have some evidence and some speculations on the classification of our theoretical parameters as those reflecting control processes and structural features. B. The Parameters

1. T H ELEARNING RATEPARAMETERS The two learning rate parameters, Ooa and Ors and the two extinction rate parameters, Ooe and Ore, are the traditional candidates for relation to intelligence given the frequency with which intelligence has included learning ability as one of the defining attributes. The speed of solution of discriminative problems does correlate with both MA and IQ in our retarded population (House & Zeaman, 1960;Zeaman & House, 1966),but this raw fact does not specifically implicate learning rate parameters. One of the contributions of our earlier model (Zeaman & House, 1963) was the separation of attentional and learning components of empirical discriminative learning functions. Using the technique of plotting backward learning curves, empirical learning functions have a generally ogival shape as shown in Fig. 29.

IY U

I

I

s #

1 so

- ?o

AT1E N110 N

TRIALS

FIG.29. Graphical estimates of theoretical parameters Po and 0 as length ofinitialplateau and slope of transition zone, respectively.

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Mary Ann Fisher and David Zeaman

The length of the original plateau is a measure of the initial probability of attending to the relevant dimensions, the slope ofthe transition from chance to 100% is the measure of learning (and extinction) rate. Wide differences in retardate intelligence and wide differences in problem difficulty produced no appreciable changes in the O parameters as inferred from slope differences. This led us to a “O-invariance” hypothesis which held that learning rates in two-choice discriminations were not related to intelligence (or anything else that we could find). The learning rate parameters of A-R Theory are not precisely the same as those of our initial models, because of the introduction of retentional dynamics. They are, however, related. If during the typical Trials-to-Criterion Design, the Rehearsal Buffer is not used(as there is reason to believe) and if decay STS is assumed to be a fixed quantity, then the slopes of the backward curves are still the best indices of the O parameters, as before. The best evidence we have for the 0-invariance hypothesis within the frame of A-R Theory may be adduced from a recent experiment by Sperber ef al. (1972) described in Section XI, C, 4, d. In this experiment, short-term memory contributions were minimized by a one-trial-per-day spacing, and attention (Po) was maximized by extensive pretraining (and concurrent training on other problems within a Miniature Design). In this situation errors are almost exclusively controlled by 8 parameters. Each subject in the experiment was trained on eight separate problems so relatively stable estimates could be obtained of individual performances. If total errors under these conditions are, as we theorize, the best empirical index available for inferring individual 8 values, and if fairly wide individual differences exist in error scores, we are in a position to test the relation of differences in O to differences in intelligence. Mean error scores for the 18 retardates in this experiment ranged from 25 to 68. Mental ages ranged from 5.5 to 1 1 .Oyears, IQs from 41 to 74. A simple test of the relation of intelligence and learning was made by making a median split of the group into High- and Low-MA groups. The mean errors for the Lows was 43.3, compared to 45.0 for the Highs, a trivial difference in the wrong direction. Virtually identical results obtained for the IQ split. Consequently we conclude that there is little support in these data for a relation of learning and intelligence in simple discriminative learning with memory and attention controlled. We do not abandon our 8-invariance hypothesis for this population and this task. One caution should be observed in interpreting the 8-invariance hypothesis. The empirical measurements of 0’s by slopes of backward curves and total errors are not very precise. Small differences in 8 , say to the order of . l , would be hard to detect empirically, but over a lifetime of learning experiences such a small difference may cumulate to a large difference in discriminative knowledge. All that we can reasonably conclude at present is

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that large differences in learning rates have not been observed within the fairly wide differences in retardate intelligence. Learning rate is viewed as a structural feature, but it is not as sensitively related to intelligence (if at all) as we had originally hoped. 2. ATTENTION PARAMETERS a. Initial Po The starting probabilities of attention to the relevant dimension (Po,, o) was found, in our earlier papers, to relate fairly well to measures of intelligence (House & Zeaman, 1963; Zeaman & House, 1963);but this parameter can not readily be viewed as a structural feature. What dimension (color, form, position) a subject tends to look at upon entering a discrimination learning session is very much a control process. It is adjustable. After training on a particular dimension, the subject transfers his high attention to the next problem to be solved, as has repeatedly been shown in intradimensional shift experiments. Why then should initial Po’s correlate with intelligence? One answer may simply be general transfer. The dimensions of color and form, typically made relevant, gradually gain salience over, say, position (a favorite dimension) due to cumulative extralaboratory experience. This might account for the influence on Po of MA but not IQ. Another factor may be responsible. In the attentional theories of Lovejoy (1968), Sutherland and Mackintosh (1971), and Trabasso and Bower( 1968), attention to dimensions has some fixed component not subject to experimental change. With such systems the saliencies of various dimensions could in part be viewed as structural features. Retardates just do not have strong native tendencies to observe the fussy dimensions of color and form that experimenters tend to make relevant, preferring instead to observe more gross dimensions such as position. While experience can temporarily modify these attentional proclivities, there is some spontaneous regression when problems are changed or get difficult. It would be no great problem to incorporate within A-R Theory the Lovejoy notion of a partially fixed component of attention, and this has been left open as a possible future line of theory revision. b. Breadth of Attention In A-R Theory multiple-looking is possible, and some retardate datasupport the argument that they can attend to more than one dimension on a trial. It is tempting to speculate that the breadth of attention may be related to developmental level, or at least the upper limit on breadth of attention may be. The data presented in Section XI1 suggested that higher-MA subjects showed more evidence of multiple-looking than lower-MA ratardates.

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The trouble with this speculation within the context of A-R Theory is that breadth of attention here is merely the product of the independent probabilities (EPoi) of looking at the various ( i ) single dimensions. If the likelihoods of looking at single dimensions represent control processes, the products of these could hardly be a structural feature. To pursue the argument further, we speculate on the possibility of an upper limit on breadth of attention as a capacity factor related to intelligence. A-R Theory, with its independent observing response probabilities, rules out this possibility. But this apparent weakness may be a strength. If the results of an experiment testing for upper limits or capacities of multiplelooking cannot be simulated with A-R Theory, we would have defined a discrepancy score which would assess the degree of competition between attentional probabilities when multiple-looking capacities were approached; that is, a theory-data discrepancy score could be used to define a limit on capacity for broad attention. The kind of experiment needed here is one which is not often run. Typical discriminative learning experiments put no demands on broad attention. Rather, it is the opposite. With one dimension relevant, narrow attention is ultimately required. With redundant relevant dimensions, broad attention is not required either. Only when single-trial training is given on redundant dimensions and testing is done for the components is it the case that broad attention is demanded for successful solutions. If, with gradually increased numbers of relevant dimensions, at some point diminishing returns were observed with component testing, we might be able to infer a capacity factor (or structural feature) for breadth of attention. Such an experiment, with adequate control of retentional factors, may be feasible (with a Demonstrational-Trial technique) but has not yet been run. 3. RETENTIONAL PARAMETERS

a. Buffer Size Although Buffer size is a limit, it is not regarded as a fixed capacity, since evidence has been presented that it can vary with training (Section XI, C , 2, c). It is best viewed as a temporary limit. Here again, though, we may speculate on an upper limit of rehearsal capacity with optimal training. McBane (1972) made a search for such upper limits in an experiment described earlier in Section XI, C , 2, c. She inferred Buffer capacities by controlling attention, STS, and LTS and then finding the upper limits of item list lengths that could be remembered by rehearsal memory. These upper limits were related to the developmental levels of her subjects. Table 111 summarized her results. The High Group consisted of eight mildly retarded subjects (Mean IQ = 74, Mean MA = 10.8 years). The Low Group subjects

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TABLE 111 AVERAGE LISTLENGTHCAPACITIES FOR TWO GROUPS OF RETARDATES, WITH COLOR OR FORMRELEVANT Dimension Form

Color

Mean

High group Low group

5.3

4.2 2.0

4.8

2.1

Mean

4.0

2 .o

2.3

( N = 8) were moderately retarded (Mean IQ = 50, Mean MA = 6.2). The High Group after intensive training rehearsed over twice as many items as the Low Group (a reliable difference), with form being easier than color. Two additional observations of interest in this context were (1) the fact that‘ none of the subjects in this experiment had the slightest difficulty in remembering list lengths of five items when these consisted of previously Well-Learned items (providing additional evidence that, in the experiment proper, they were responding out of the limited memory store of Buffer rather than the unlimited LTS); and (2) that interrogation of the subjects on their methods of remembering suggested that they were using visual rehearsal (“I keep pictures in my head”) rather than verbal rehearsal. The tentative conclusion to be drawn from McBane’s research is that the upper limit of the Buffer capacity with extensive training is a structural feature related to developmental level. Since MA and IQ were confounded in this experiment, further research will be necessary to separate these variables.

6. Decay Rate, S The spontaneous rate of decay of information in the STS is controlled by the theoretical parameter, S. This parameter is not subject to change by any of the training techniques we have used, so it is regarded as a measure of a structural feature rather than a control process. For all of the experiments in which STS was assumed to play a role, we have used a constant value of the decay parameter despite wide changes in the nature of the training conditions. Sensitivity of decay rate to changes in developmental level is very much a matter of theoretical and empirical dispute. In the work of Spitz (1963) and the early theorizing of Ellis (1963). decay rate was assumed to covary with intelligence, although, as has been pointed out, Ellis’s later theory and data has suggested a decay rate invariance across normal-retardate comparisons (Ellis, 1970). The inclusion of Memory Span tests in many intelligence tests implies that

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some aspect of short-term memory in related to intelligence. To the extent that performance on such tests is related to the rate of spontaneous decay of the individual items within the span, we might assume that our 6 parameter should be related to intelligence. Within the context of our discriminative learning experiments, the only suggestive evidence we have adduced on this point (see Section XIV, C, 1, c and Figs. 8 and 9) was the faster rate of decay for lower-MA than higher-MA subjects in experiments providing adequate measures. Since we have thus far adopted only a semiquantitative approach to parameter estimation, and since none of our studies has been directed specifically to the assessment of relative decay rates in subjects of varying intelligence, our position is open. We believe that spontaneous decay is an innate capacity of the organism that may be related to intelligence. A-R Theory merely tells us how to measure the stuff, what variables to control for (attention, learning, and rehearsal), and how to control them. c. The Interference Parameter, a The interference that occurs when new items compete for space in afilled rehearsal buffer is controlled by the parameter, a. On the basis of results with adult normal subjects, it appears that a is a control process, representing as it does a strategy or decision to rehearse new items or old items when capacity factors prevent doing both. Atkinson and Shiffrin (1969) have shown that instructions to the subject can control their decisions to rehearse new rather than old material. For most of our simulations, we have used a value of .5 for a,implying that for most tasks retardates are indifferent with respect to the rehearsal of new rather than old times. But the control-process nature of a was shown within our retardate data domain by the need of a much higher value of a for a task which required for successful performance a high probability of rehearsing new information. When training consists of a series of ID-ED shifts, it is profitable for subjects to rehearse new material as soon as the shift starts (see Sections XI1 and XIII). A high value of a would thus be adaptive. We do not believe it a coincidence that simulation of these data required an a of .9. The Lewinian concept of retardate “rigidity” may have some relevance in the context (Kounin, 1941). If a rigid subject preferred to rehearse old rather than new material, an a value less than .5 would be required. In general, our simulations do not bear out this notion. Also, the controlprocess nature of this parameter makes it apoor candidate for relation to the stable trait of intelligence.

d. Implications for Retardation There are at least two ways in which A-R Theory can be of help in the study of mental retardation. First, the theory can, if it is well-confirmed,

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tell us how a retardate learns, extinguishes, transfers, remembers, and attends to some simple kinds of discriminative information. In this sense, the distinction between control process and structural feature is relatively unimportant. The theory tells us what variables to manipulate to control performance and what the nature of the control will be. Although ourgoals are not primarily applied, the theory is available for use in the solutionof practical problems which call for the learning of simple discriminative problems by retardates. I n another chapter in this volume, Marc. W. Gold reports a number of successful applications of Attention Theory to the solution of applied problems in retardation. A second way in which A-R Theory relates to retardation depends upon the distinction between control process and structural feature. Since individual differences in intelligence are highly stable traits in our retardate population, only stable parameters, those representing structural features, are meaningfully relatable to intelligence. The parameters of A-R Theory which qualify as structural features are 0’s (learning and extinction parameters), 6 (short-term memory decay rate), and maximum p (upper limit of rehearsal capacity). Of these, the learning rate parameters are empirically unrelated to intelligence, leaving only the two retentional parameters as viable candidates. If retardation can be related to large individual differences in a few basic processes, rather than small, hard-to-detect differences in agreat many processes, our current analyses suggest that these will be in the domain of memory rather than learning, extinction, or attention. REFERENCES Anderson, D. R. The effects of prior training on redundancy learning in children. Unpublished doctoral dissertation, Brown University, 197 I. Atkinson, R. C., Bower, G. H., & Crothers, E. J. An introduction to mathematical learning theory. New York: Wiley, 1965. Atkinson, R. C., & Shiffrin, R. M. Human memory, a proposed system and its control processes. In K. W. Spence & J. T. Spence (Eds.), The psychology of learning andmotivation: Advances in research and theory. Vol. 2. New York Academic Press, 1969. Pp. 89-195. Belmont, J. M. Long-term memory in mental retardation. In N. R. Ellis (Ed.), International review of research in mental retardation. Vol. 1. New York: Academic Press, 1966. Pp. 219-225. Belmont, J. M., & Butterfield, E. C. The relations of short-term memory to development and intelligence. I n L. P. Lipsitt & H. Reese (Eds.), Advances in child development and behavior. Vol. 4. New York: Academic Press, 1969. Pp. 29-82. Bower, G. H. A multicomponent theory of the memory trace. In K. W. Spence & J. T. Spence (Eds.), The psychology of learning and motivation: Advances in research and theory. Vol. I. New York Academic Press, 1967. Pp. 299-325. Brown, A. The stability of dimensional preference following oddity training. Journal of Experimental Child Psychology, 1970, 9, 239-252. Bush, R. R., & Mosteller, F. A. mathematical model for simple learning. PsychologicalReview, 1951,58, 313-323.

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Bush, R. R., & Mosteller, F. Stochastic models for learning. New York Wiley, 1955. Cahn. T. I. The role of redundancy in discrimination learning by normal and mentally retarded children. Unpublished doctoral dissertation, University of Connecticut, 1966. Campione, J. C. Intra- and extradimensional shifts in retardates as a function of dimensional preference. American Journal of Psychology, 1969, 82, 212-220. (a) Campione, J . C. Transitivity and choice behavior. Journal of Experimental Child Psychology, 1969, 7, 387-399. (b) Campione, J. C., Hyman, L., & Zeaman, D. Dimensional shifts and reversals in retardate discrimination learning. Journal of Experimental child Psychology, 1965, 2. 255-263. Campione, J . C., & Wentworth, C. Differential cue habit strength as adeterminant ofattention. Journal of Experimental Psychology. 1969, 82, 521-53 1 . D’Amato. M. R., & Jagoda, H. Analysis of the role of overlearning in discrimination reversal. Journal of Experimental Psychology, 196 I , 61,45-50. Dickerson, D. J. Irrelevant stimulus dimensions and dimensional transfer in the discrimination learning of children. Journal of Experimental Child Psychology, 1967, 5, 228-236. Dickerson, D. J., Wagner, J. F., & Campione, J. Discrimination shift performance of kindergarten children as a function of variation of the irrelevant shift dimension. Developmental Psychology, 1970, 3, 229-235. Eimas, P. D., & Shepp, B. E. Retardate discrimination learning following differential conditioning of the choice-point stimuli. Child Development, 1964, 35, 685-693. Ellis, N. R. The stimulus trace and behavioral inadequacy. In N. R. Ellis (Ed.), Handbook of mental deficiency. New York McGraw-Hill, 1963. Pp. 134-158. Ellis, N. R. Memory processes in retardates and normals: Theoretical and empirical considerations. In N. R. Ellis (Ed.), International review of research in mental retardation. Vol. 4. New York: Academic Press, 1970. Pp. 1-32. Estes, W. K. Learning theory and the new “mental chemistry.” Psychological Review, 1960,67, 207-223. Estes, W. K. Reinforcement in human learning. I n J. T. Tapp(Ed.), Reinforcement andbehavior. New York Academic Press, 1969. Pp. 63-94. Estes, W. K. Learning theory and mental development. New York Academic Press, 1970. Estes, W. K., & Burke, C. J. A theory of stimulus variability in learning. PsychologicalReview, 1953,60. 276-286. Feldstein, J. H., & Witryol, S. L. The incentive value of uncertainty reduction forchildren. Child Development. 197 I , 42, 793-804. Fisher, M. A,, Martin, A,, McBane. B., & Zeaman. D. Breadth of retardate attention. Unpublished manuscript, University of Connecticut, 1969. Fisher, M. A , , & Zeaman, D. Growth and decline of retardate intelligence. InN. R. Ellis(Ed.), International review of research in mental retardation. Vol. 4. New York Academic Press, 1970. Pp. 151-191. Gulliksen, H., & Wolfle, D. L. A theory of learning and transfer: 1. Psychometrika, 1938.3, 127-149. Guthrie, E. R. Association by contiguity. I n S. Koch (Ed.), Psycho1ogy:Astudyofascience. Vol. 2. New York McGraw-Hill, 1959. Pp. 158-195. Harlow, H. F. Learning set and error factor theory. I n S . Koch (Ed.), Psychology: A srudyof a science. Vol. 2 . New York: McGraw-Hill, 1959. Pp. 492-537. House, B. J. Recalls versus trials as factors in serial verbal learning of retardates. Psychological Reports, 1963, 12, 931-941. House, B. J. Discrimination learning without overt response or reward in retardates. American

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Journal of Mental Deficiency, 1964,68, 734-740. (a) House, B. J. Oddity performance in retardates: I. Acqu on and transfer. ChildDevelopment, 1964, 35, 635-643. (b) House, B. J. Effects of similarity of discrimination problems on learning and retention in retardates. Journal of Experimental Child Psychology, 1968, 6, 57 1-584. House, B. J. A decremental effect of redundancy. Journal of Experimental Child Psychology, 1971, 10. 403-412.

House, B. J., & Zeaman, D. Reward and nonreward in thediscrimination learning of imbeciles, Journal of Comparative and Physiological Psychology, 1958, 51, 614-618. House, B. J., & Zeaman, D. Position discrimination and reversals in low grade retardates. Journal of Comparative and Physiological Psychology, 1959, 5, 564-565. House, B. J., & Zeaman, D. Visual discrimination learning and intelligence in defectivesof low mental age. American Journal of Mental Deficiency, 1960, 65, 51-58. House, B. J., & Zeaman, D. Effects of practice on the delayed response of retardates. Journal of Comparative and Physiological Psychology, 196 I , 54, 223-229. House, B. J., & Zeaman, D. Reversal and nonreversal shifts in discrimination learning in retardates. Journal of Experimental Psychology, 1962, 63, 444-45 1. House, B. J., & Zeaman, D. Miniatureexperimentsin retardatediscrimination learning. In L. P. Lipsitt & C. C. Spiker (Eds.). Advances in childdevelopment andbehavior.Vol. 1. New York Academic Press, 1963. Pp. 313-373. Hull, C. L. Principles of behavior. New York Appleton, 1943. Hyman, L. M. The effect of redundant patterns on retardate discrimination learning. Psychonomic Science, 1967, 9, 195-196. Kendler, H. H. Environmental and cognitive control of behavior. American Psychologist, 1971, 26,962-973.

Kendler, H. H., & Kendler, T. S. Vertical and horizontal processes inproblemsolving. Psychological Review, 1962, 69, 1-16. Keppel, G., & Underwood, B. Proactive inhibition in short term retention of single items. Journal of Verbal Learning and Verbal Behavior, 1962, 1, 153-162. Klinman, C. Short term memory in discrimination learning of retardates. Unpublished doctoral dissertation, University of Connecticut, 1964. Knight, M. The effects of intertrial interval duration on short-term retention of a two choice visual discrimination task by retarded children. Journal of Experimental Child Psychology, 1968,6, 241-253.

Kounin, J . Experimental studies of rigidity: I. The measurement of rigidity in normal and feeble-minded persons. Character and Personality, 1941,9, 251-273. Krechevsky, I. “Hypotheses” in rats. Psychological Review, 1932, 39, 5 16-532. Lashley, K. S. Brain mechanisms and intelligence: A quantitative study of injuries to the brain. Chicago: University of Chicago Press, 1929. Lashley, K. S., & Wade, M. The Pavlovian theory ofgeneralization. PsychologicalReview, 1946, 53,12-87.

Levine, M. Hypothesis behavior by humans during discrimination learning. Journal ofExperimental Psychology, 1966, 71, 331-338. Lockard, J. S. Choice of a warning signal or no warning signal in an unavoidable shock situation. Journal of Comparative and Physiological Psychology, 1963, 56, 526-530. Losty, B. Stimulus integration and novelty as factors in the discrimination learning of retarded children. Unpublished doctoral dissertation, University of Connecticut, 197 I . Lovejoy, E. Attention in discrimination learning. San Francisco: Holden-Day, 1968.

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Luce, R. D. Individual choice behavior: A theoretical analysis. New York Wiley, 1959. Mackintosh, N. J. Incidental cue learning in rats. Quarterly JournalofExperimenraIPsychology, 1965, 17,292-300. Martin, A. The effect of the novelty-familiarity dimension on discrimination learning. Unpublished doctoral dissertation, University of Connecticut, 1970. McBane, B. Short term memory capacity and parallel processing. Unpublished doctoral dissertation, University of Connecticut, 1972. Medin, D. L. A scanning model for discrimination learning. In W. K. Estes, G. A. Allen, E. Ligon, D. L. Medin, D. Robbins, & G. L. Wolford, Communications in mathematical psychology. Rockefeller University, New York,October 1968-September 1969. Norman, D. A. Models of human memory. New York Academic Press, 1970. Peterson, L. R., Saltzman, D., Killner, K., & Land, V. Recency and frequency in paired associate learning. Journal of Experimental Psychology, 1962,63, 396-403. Polson, P. G., & Greeno, J. G. Non-stationary performance before all-or-none learning. Psychological Review, 1969, 76, 227-231. Prokasy, W. F. The acquisition of observing responses in the absence of differential external reinforcement. Journal of Comparative and Physiological Psychology, 1956,49, 131134. Reese. H. W. The perception of stimulus relations: Discrimination learning and transposition. New York Academic Press, 1968. Restle, F. The selection of strategies in cue learning. Psychological Review. 1962, 69, 11-19. Rock, I. The role of repetition in associative learning. American Journal of Psychology. 1957, 70, 186-193. Ross, L. E. Classical conditioning and discrimination learning: Research with the mentally retarded. In N. R. Ellis (Ed.), Infernationalreview ofresearch in mental rerardation. Vol. I . New York Academic Press, 1966. Pp. 21-54. Scott, K. G. Some parameters of short term recall. Unpublished doctoraldissertation, University of Connecticut. 1966. Scott, K. G., & Scott, M. S. Research and theory in short-term memory. In N. R. Ellis(Ed.), International review of research in mental retardation. Vol. 3. New York Academic Press, 1968. Pp. 135-162. Shepp, B. E. Some cue propertiesof anticipated rewards in discrimination learning of retardates. Journal of Comparative and Physiological Psychology, 1962, 55, 856-859. Shepp, B. E. Some cue properties of incentives: Discrimination of distinct rewards by retardates. Journal of Comparative and Physiological Psychology, 1963, 56, 1078-1080. Shepp, B. E. Some cue properties of rewards in simultaneous object discriminations of retardates. Child Development, 1964, 35, 587-592. Shepp, B. E., House, B. J., & Zeaman, D. Contiguity and imbeddedness factors in the discriminative learning of retardates. Journal of Experimental Child Psychology, 1967. 5, 604-611.

Shepp, B. E., & Turrisi. F. D. Learning and transfer of mediating responses in discriminative learning. In N. R. Ellis (Ed.), International review of research in menfal retardation. Vol. 2. New York Academic Press, 1966. Shepp, B. E., & Turrisi, F. D. Effects of overtraining on the acquisition of intradimensional and extradimensional shifts. Journal of Experimental Psychology, 1969, 82, 46-5 1. Shepp, B. E., & Zeaman, D. Discrimination learning of size and brightness by retardates. Journal of Comparative and Physiological Psychology, 1966, 62, 55-59. Siegel, A. W., & Stevenson, H. W. Incidental learning: A developmental study. ChildDevelop-

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ment, 1966,37,811-818. Spence, K. W. The nature of discrimination learning in animals. Psychological Review, 1936, 43,427-449. Spence, K. W. Behavior theory and learning. Englewood Cliffs, N. J.: PrenticeHall, 1960. Sperber, R. D., Greenfield, D. B., & House, B. J. Curvilinear effects of distribution of trials in retardate memory and learning. In D. Zeaman, learning and transfer in mental defectives. Progress Report No. 6, 1972, University of Connecticut, Research Grant M-1099,National Institute of Mental Health, U.S.Public Health Service. Spiker, C. C. Application of Hull-Spence theory to the discrimination learning of children. In H. W. Reese (Ed.), Advances in child development and behavior. Vol. 6. New York Academic Press, I97I . Spitz, H. H. Field theory in mentaldeficiency. I n N. R. Ellis(Ed.), Handbookofmentaldeficiency. New York McGraw-Hill, 1963,Pp. 1 1 4 0 . Stevenson, H. W. Latent learning in children. Journal of Experimental Psychology, 1954.47, 17-21. Stukuls, I. Discrimination learning and effects of proactive and retroactive interference on the retention of mental retardates. Unpublished doctoral dissertation, University of Connecticut, 1968. Suchman, R. G., & Trabasso, T. Color and form preferences in young children. Journal of Experimental Child Psychology, 1966,3,177-187.(a) Suchman, R. G., & Trabasso, T. Stimulus preference and cue function in young children’s concept attainment. Journal of Experimental Child Psychology, 1966,3, 188-198. (b) Sutherland, N. S., & Holgate, V. Two cue discrimination learning in rats. Journalof Comparative and Physiological Psychology, 1966,61,198-207. Sutherland, N. S., & Mackintosh, N. J. Mechanismsofanimaldiscrimination learning. NewYork: Academic Press, 1971. Terrace, H. S. Discrimination learning with and without “errors.’ Journal of the Experimental Analysis of Behavior, 1963,6, 1-27. Tolman, E. C. Purposive behavior in animals and man. New York Century, 1932. Trabasso, T., & Bower, G. H. Attention in learning: Theory and research. New York: Wiley, 1968. Witryol, S. L., Lowden, L. M., & Fagan, J. F. Incentive effects upon attention in children’s discrimination learning. Journal of Experimental Child Psychology, 1967,5, 94-108. Wolff, J. L. The role of dimensional preferences in discrimination learning. PsychonomicScience, 1966,5455-456. Wolff, J. L. Concept-shift and discrimination-reversal learning in humans. Psychological Bulletin, 1967,68.369-408. Wolford, G . , & Bower, G. H. Continuity theory revisited Rejected for the wrongreasons? Psychological Review, 1969.76, 515-518. Wyckoff, L. B. The role of observing response in discrimination learning: I. Psychological Review, 1952,59,431-442. Zeaman, D., Campione, J., & Allen, M. Opposing effectsof redundancy in retention of averbal discrimination. Journal of Verbal Learning and Verbal Behavior, 1970,9,607413. Zeaman, D., & Denegre, J. Variability of irrelevant stimuli. JournalofExperimentalPsychology, 1967,73,574-580. Zeaman. D., & House, B. J. Approach and avoidance in the discrimination learning of retardates. Child Development, 1962,33. 355-372. Zeaman, D., & House, B. J. The role of attention in retardatediscrimination learning. InN. R. Ellis (Ed.), Handbook of mental deficiency. New York McGraw-Hill, 1963. Pp. 159-223.

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Zeaman, D., & House, B. J. Therelation ofIQ and learning. In R. M. Gagne(Ed.),Learningand individuul dixerences. Columbus: Merrill, 1966. Pp. 192-212. Zeaman, D., House, B. J., &Orlando, R. Useofspecial training conditions invisualdiscrimination learning with imbeciles. American Journal of Mental Deficiency, 1958, 63, 453-459. Zeaman, D., Thalier, C.. & House, B . J. Variability of irrelevant stimuli in discrimination learning of retardates. Journal ofExperimentol Gild Psychology, 1964, 1, 89-98.

Studying the Relationship of Task Performance to the Variables of Chronological Age. Mental Age. and I&

.

WILLIAM E KAPPAUF UNIVERSITY OF ILLINOIS AT URBANA.CHAMPAIGN

I1 . V.

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CHAMPAIGN. ILLINOIS

................................................................. 258 A . Background .............................................................. 259 B . Plan and Organization .................................................... 261 C . A Preview of Principal Findings .......................................... 262 A Developmental Population for Research on CA, MA. and IQ .... 263 Two-Dimensional Maps of the CA. MA. IQ Domain ......................... 264 Critique of Harter's Interpretation of Her Data ............................... 264 Intercorrelations and the Factor Space A . Relationships in the IogCA. IogMA. 1 .......................... 267 B . Relationships in Other Forms of the CA. Mk.IQ Space ...................272 C . Implications for the Analysis of CA. MA. and IQ Effects .................. 274 Response Surfaces and the Ruled Surface Model ............................. 274 274 A . Procedures for Plotting Response Surfaces ................................ B . The Ruled Surface Model for Response Surfaces .......................... 275 C . Testing the Ruled Surface Model ......................................... 277 D . Interpretation When the Ruled Surface Model Applies on the IogCA. IogMA. IogIQ Grid ........................................ 277 E . Interpretation When Some Other Grid Is Required to Make the Ruled Surface Model Acceptable ............................... 280 Procedure for Deriving and Plotting Iso-Performance Contours ............... 280 A. Selecting the CA. IQ Grid ................................................ 281 B . Entering the Data ... ..................... C . Interpolation and Plott Analysis of Harter's Data Using Iso-Performance Contours ..... A . The 1965 Study .......................................................... 284 B . Need for Cross-Validation ... ............... 290 C . The 1967 Study ................................. Appraisal of the Graphic Approach in the Analysis of 293 Response Surfaces ...........................................................

1. Introduction

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William E. Kappauf A. Comparison with Alternative Procedures ................................. B. Questions about Domain and Grid Details ................................ . C. Properties of the Iso-Performance Contour Diagram ........ D. Empirical Curve-Fitting and Theory ...................................... Some Comments on the Research Literature ................................. A. Interpreting the Role of CA ............................ B. Some MA Issues .................................... , and IQ .............................. The Design of Experiments on A. Some Shortcomings of Factorial Designs with ..................................... Analysis of Variance B. Design for Iso-Performance Contour Analysis ............................. The Problem of Correlated Variables in Other Areas of Research ......... ................................... Summary and Conclusions ............................. ................ ........ Appendix ................................ ...................................... References .....

293 295 296 297 300 300 301 303 303 306 309 310 312 315

I. INTRODUCTION

The recent literature contains a number of papers which discuss methodological issues in research on retardates and the relative merits of different experimental designs (e.g., Baumeister, 1967; Ellis, 1969; Haywood, 1970; Heal, 1970; Stanley, 1967b; Zigler, 1969). There is concern over etiological questions, over the interpretation of data, over the homogeneity of groups of subjects, over methods of analysis. The present paper resembles these in being methodological and in having implications for the conduct of programmatic research on retardates, but it has been written primarily as a supplement to this previous literature. It addresses itself to issues and procedures which appear not to have been considered fully in the context of retardate research. The primary object of this paper is to call attention to our need for ways of obtaining a better quantitative understanding of the manner in which performance at any chosen task depends upon CA, MA, and IQ. That the methods used heretofore in research on retardates and normals have not provided sufficient insights in this regard is evidenced by the fact that, in spite of the relative abundance of such studies, we still have no general quantitative theory for relating performance to CA, MA, and IQ. Formal strategies of experimental design and analysis, or correlational and multivariate procedures, might appear to offer the needed advances, but for research into the dependence of performance on CA, MA, and IQ they typically cannot be so well suited or so informative as designs and graphic data-handling procedures which focus specifically on examining and exploring the very form of that functional dependence. Old and familiar advice,

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which bears regular repetition, is that we should always take a good look at a careful plot of our experimental data. And this, in a word, is the theme of this paper. A return from more formal statistical procedures to direct graphical analysis in studies of performance in relation to CA, MA, and IQ can teach us much about that relationship and should help to reduce confusions in the interpretation of data. If we further assume a curve-fitting approach in organizing the data, we should be guided both toward realistic models for describing task performance as a function of CA, MA, andIQ and toward ways of assembling new data which will facilitate the evaluation of these models. In the following discussion of problems related to the collection and plotting of data on CA, MA, IQ, and performance, most of the concepts and procedures will, and should, have a familiar ring. But they seem not previously to have been discussed in a way which bears specifically on the CAYMA, IQ issue which has been central to much of the past research on retardates. Hence they have been drawn together here. Hopefully the resulting package will have something useful to say for the design and analysis of future experiments aimed at improving our understanding of the performance of retardates in comparison with the performance of normal and gifted individuals. A. Background

This paper had its beginnings in 1968 when students in an experimental design course brought to the writer’s attention two studies which Harter (1965, 1967) had conducted to assess the contributions ofMA and IQ to performance in a learning-to-learn situation. These studies are of special interest because they represent the first uses of a two-way factorial design in research with retardates. The design involved levels of MA and levels of IQ. Harter’s principal conclusions from her work were: (1) that significant independent effects on learning-set formation are present for both IQ and MA; (2) that the interaction effect of MA and IQ is also significant; and (3) that the dependence of learning-set formation on CA is negligible. In her analysis of the data, the MA and IQ effects were assessed by analysis of variance procedures, and the CA effect by determining the extent of the correlation between CA and learning-set score. Harter’s adoption of multigroup designs was a major step forward in a field where typical designs have been more restricted and less ambitious: i.e., two-group comparison designs involving a retardate group and a normal group of either the same average CA or the same average MA. Even Denny’s (1964) recommendation of a three-group study, in which retardates would be compared with normals of matching CA as well as with normals of the

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same MA, appears not to have been pursued. Harter’s choice of a factorial design was associated with her interest in extending the scope of her studies to high IQ levels, where data on learning-set formation had been lacking. Her data are therefore more comprehensive and informative than the data of most other studies, and they deserve careful attention as indicative of the considerable merit of broader range studies of the sort recommended by Heal (1970) and in the present paper. In spite of the merits of Harter’s data, there are some unhappy shortcomings in her interpretation of them as summarized above. These arose out of the special state of affairs which surrounds CA, MA, and IQ data and which has led other investigators as well into similar errors when interpreting the relation of CA, MA, and IQ to an experimental criterion measure. This special condition, well recognized but not always easy to cope with, is the interdependence of these three variables. No matter how they are scaled, they reflect only two sources of variation. All information that is contained in the three is contained in any two of them alone. The effects of this interrelationship pervade research design, data description by means of graphs, and data interpretation by all techniques. At the design level, it means that these variables can never be accommodated in a three-way orthogonal design. Nor can we study the relationship of any one of them to performance while holding both the others constant. At best, we can study the relation of performance to one of them (say MA) while holding another (say IQ) constant), but in doing this we must be willing to allow the third (in this case CA) to vary with the first. Harter’s design uses two variables but, as she recognized, it faces the same problem. She put it this way in the introduction to her first paper( 1965)“. . . no study has yet employed a design in which both IQ and MA were varied independently, a procedure which is possible, provided one is unconcerned with the relationship which each of these variables has to CA [p. 321 .” At the level of the schematic or graphical representation of data for CA, MA, IQ, and a criterion, the interdependence of CA, MA, and IQ means that all three can be plotted in a two-dimensional grid. Performance at the criterion task can therefore be represented as a function of all three variables by preparing a chart or figure which depicts variation in a total of three dimensions. A three-dimensional plot will handle all four variables. And at the level of data interpretation, the interdependence of CA, MA, and IQ has two especially important consequences: (1) If one of these three variables is related to some performance measure of interest, then at least one of the others is also related to that performance. (2) In most situations, task performance will be related, not to two, but to all threevariables. These constraints stem from the factor structure of theCA, MA, IQ space. Indeed,

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if we examine Harter’s results in factor perspective, removed from the context of the analysis of variance which she used, it becomes clear that the effects which she observed for MA and IQ are not independent, and that the CA effect is far from negligible. B. Plan and Organization

Pursuing these points, part of this paper is concerned with (a) a specific critique of Harter’s analysis, and (b) a review of the sources of problems which have been encountered in previous attempts to attribute performance changes to differences in CA or in MA or in IQ. The remainder of this paper is built around (c) the proposal that studies of the so-called “effects”’ of CA, MA, and IQ should be planned as multigroup studies which will permit an extended mapping and analysis of the three-dimensional surface which represents the regression of task performance on CA, MA, and IQ. A good model for this surface is a requisite for theory development. This surface may be referred to in various ways: as a three-dimensional psychometric function, as a regression surface, or as a response surface. We shall use the latter term, “response surface,” which comes from the recently developed field known as response surface methodology (see Box, 1954; Box & Wilson, 1951; Box & Youle, 1955).Verygenerally defined, aresponse surface is a surface which portrays performance change over the domain of a set of n experimental variables. In an analysis of variance such as Harter’s, the test for interaction effects asks whether irregularities of various kinds occur in the response surface. Conventional multiple regression techniques, on the other hand, view the response surface as a plane. Quite certainly the regression of task performance vs. CA, MA, and IQ, scaled in any conventional way, is never a plane over the age and IQ range of interest to develop‘Throughout the remainder of this paper the word effect will always be placed in quotation marks when referring to the “effects” of CA, MA, or IQ on performance. The Harter studies and all others which would look at the relation of CA, MA, and IQ to performance are associational, correlational, or status studies rather than experiments in the usually accepted sense (see Stanley, 1967a; Underwood, 1957). Subjects have not been assigned at random to conditions, nor have variables been manipulated. Only associational information is forthcoming from these studies. Our quotation marks around “effects” recognize this state of affairs. To be most proper one would avoid speaking of effects, but it is obviously a verbal convenience to use a term such as “MA effects” instead of more appropriate but cumbersome expressions as “relations of M A to performance” or “change in performance with MA.” In this vein, it should be noted that Humphreys and Dachler (1969) refer to a design such as Harter’s as a “pseudo-othogonal” design. Recognition of the correlational, multivariate character of these studies suggests further that in interpreting data we not overlook the potential role of other traits which happen to be correlated with the variables under study, i.e., CA, MA, and IQ.

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mental psychologists: there must always be regions in the domain where performance levels off or begins to do so. Quite certainly, also, interactions must be the rule. On the other hand it seems areasonable possibility that the response surface may be a “ruled surface.” This is a surface which is generated by the translation of a straight line, that is, by the movement of a line so that it always remains parallel to its original position. In the present paper we shall consider procedures for fitting a monotonic horizontally ruled surface to response surfaces relating performance to CA, MA, and IQ. We shall also explore the implications which an interest in response surface analysis has for experimental design and data collection. In its organization, this paper mixes methodology and content in what is hopefully a comfortable and logical order. This first half of the paper is centered around the Harter studies which are reanalyzed here. Methodological questions are discussed as each becomes important either for an understanding of the limitations of the original analysis or for the development of the new analysis. The second half of the paper deals with an assessment of the new procedures and with the implications of the present analysis both for (a) the interpretation of the role of CA and MA in performance and (b) the design of future experiments. Although the first half of the paper(Sections 11-VIII) forms adefinite unit, the following breakdown may be of use to the reader: Sections 111, IV, VIII, and X are specifically concerned with review and discussion of studies and issues from the literature. Secions, 11,111, and V provide background for the criticism of conclusions drawn in reports of these previous studies. Sections VI, VII, IX, and XI discuss the proposed graphic procedures for analyzing data in response surface form and for evaluating the ruled surface model. C. A Preview of Principal Findings

We have already noted in subsection A above some of the conditions which follow from the interdependence of CA, MA, and IQ. Thesections which follow make those observations explicit and extend them. It is found that previous arguments which have minimized the role of the CA variable in performance at various learning tasks have been based on data for nonrepresentative samples of the developmental population. When the total population is considered, CA and IQ are the obviously “natural” factors, and MA is the variable which may be eliminated from the discussion if one desires. Harter’s results can be plotted as a function of CA and IQ, and it is shown that a particular combination of CA and IQ scales can be found such that the performance or response surface is well fitted by a monotonic horizontally ruled surface. This model, therefore, provides a parsimonious

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description of the performance of her subjects as a function of CA and IQ. The outcome of this graphic approach and that of the original analyses of variance thus differ considerably. It has just been suggested that a critical step in approaching our general problem is that of identifying or defining the population of individuals whose CA, MA, and IQ measures will concern us. We begin with this. I I . A DEVELOPMENTAL POPULATION FOR RESEARCH O N CA, MA, AND IQ

Within the research literature on learning, memory and other tasks in relation to growth and intelligence, one does not find a formal definition of the developmental population. There is typically no need to define this natural population, and except for occasions when a test is being standardized, there is little research concern about sampling it representatively. Most studies deal with more limited school or grade populations, and when CA and/or MA and/or IQ have been involved as variables, investigators have preferred either a controlled-sampling design or an available-subjects design to a design based on broad, representative sampling. In this paper, however, we want to consider the entire developmental population, and so we must decide what our “working” population will be. We shall refer to this population as the CA, MA, IQ domain for our inquiry. According to our usually accepted model for mental growth, an individual’s general intelligence advances until he reaches a chronological age of 15-20 years, after which time it is more or less stable. We quantify his standing at any time in terms of an MA measure. We estimate his average rate of mental growth to any particular CA by his IQ. We conceive thedistribution of IQ’s at every chronological age to be the same, and will here presume that they are distributed normally with the same mean (100) and the same standard deviation (16) at every CA. If in studying performance at various tasks as a function of mental development we would eliminate those low CA levels where IQ measurement is uncertain, and if we would work to CA levels not much above 15 years, then it appears reasonable to set bounds on the chronological age dimension of our CA, MA, IQ domain at 3 and 16 years. Let us further assume, as a matter of considerable convenience for some calculations which will appear below, that the distribution of chronological ages between these limiting ages is rectangular. Given the foregoing CA, IQ conditions, and given that the IQ’s are ratio IQ’s as we shall presume for most of this paper, the distribution of mental ages over the domain is of course fully determined. Thus for the discussions which follow, we are assuming that theCA, MA,

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IQ domain of interest for developmental performance studies is defined by a rectangular distribution of CA’s from 3 to 16 years and a normal distribution of ratio IQ’s (100, 16) at every CA.* 111. TWO-DIMENSIONAL MAPS OF THE CA, MA, IQ DOMAIN

Let us now plot this domain and observe the CA, MA, IQ relationships within it. In rectangular coordinates, three representations of the domain are possible. These are shown in Fig. 1. From the explicit interdependence of CA, MA, and IQ given by the ratio formula, we recognize that in a rectangular grid based on any two of these variables, the third can always be plotted as a function of the others. Thus in diagram A, the dashed lines show selected levels of MA plotted as a function of CA and IQ. In diagram B, the dashed sloping lines show selected levels of IQ as a function of CA and MA. And in diagram C, the dashed lines represent equal CA values as a function of MA and IQ. Following the language of the cartographer, we may refer to these dashed lines as iso-MA lines, iso-IQ lines, and iso-CA lines in the three successive diagrams. Given these added lines, each diagram becomes in fact a three-way grid instead of a two-way grid. Hence for any point in these diagrams we can read the triplet of CA, MA, and IQ values associated with that point. Or to put it oppositely, we can plot the set of CA, MA, and IQ values for any subject in a single point. In each of the three diagrams of Fig. 1, the CA, MA, IQ domain which was chosen above lies within the heavily marked boundaries. For purposes of graphical representation only, it was necessary to set limits for the IQ scale, and these are shown as 50 and 150. Having these diagrams in hand, we are ready to make anew inspection of some of Harter’s data. IV. CRITIQUE OF HARTER’S INTERPRETATION OF HER DATA

In each of the diagrams in Fig. 1, the data for Harter’s 1965 study have been entered numerically in the manner of a cartographer entering elevation numbers on a map. The nine bold numbers shown within each diagram are rounded values of the average performance measures for the nine groups of subjects in the study. The learning-to-learn task was scored in termsof problems to criterion. Higher scores were obviously poorer scores. In each It is recognized that some past studies of performance in relation to CA, MA, andIQ have used subjects beyond CA 16 in retardate groups, but interest in these studies has not been strictly developmental.

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0 3 4

6

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FIG. 1. Three maps of the CA, MA, IQ domain using linear scales on the orthogonal axes. I n each of them, two variables define the orthogonal grid while the third variable, which is a direct function of the other two, can be scaled by using a third (dashed) set of grid lines which are loci of uniform values of that third variable. Rounded values of the average performance score for each group of subjects in Harter’s (1965) study have been entered as the bold numbers within each diagram. See text for discussion.

diagram, the average number of problems to criterion for each group has been entered at the location which represents the average CA, average MA, and average IQ of that group. For Harter’s MA x IQ design, the MA levels approximated 5,7, and 9 years, while the IQ levels approximated 70,100, and 130. This is seen most clearly in diagram C . The reader may verify the plotting by noting that in each diagram the number 24 is plotted for the group with MA = 7, CA = 7, and IQ = 100.

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Diagram C in Fig. 1 portrays the data in the array as treated in Harter’s analysis of variance. There is an IQ “effect”: performance changes with IQ at each MA level. There is also a change in performance as MA varies at each IQ level. And the MA x IQ interaction is apparent. Diagrams A and B, however, look at the data in ways which the analysis of variance did not. I n A we see that performance improves with IQ when CA is held constant, but also that it improves with CA when IQ is held constant. Similarly in diagram B we observe improvement with MA when CA is fixed, but also a drop in proficiency with increasing CA when MA is held constant. We can also see from diagram A or B why Harter found that the correlation of CA with performance was negligible: average performance was best at the lowest and highest CA’s, and poorest at mid-CA. Clearly this correlation measure was conditional upon the particular nine MA, IQ groups which filled Harter’s factorial design. The alternative factorial designs, CA x IQ and CA x MA, did not interest Harter, but the implication of diagrams A and B is that either of these other designs would have disclosed a clearcut “effect” of CA. In sum, a look at the three plots of Harter’s data in response surface form indicates that there is as much reason to accept and report a CA “effect” on performance as there is to speak of an MA “effect” or an IQ “effect.” Of course there are some problems here. The CA “effects” in diagram A are identical with the MA “effects” which Harter reported. And the CA “effects” in diagram B are identical with the IQ “effects” recorded in her paper. Thus, the “effects” which we read for and ascribe to CA turn out to be familiar ones which we have seen before. And what “effect” we ascribe to CA varies with the method of diagramming the data (A vs. B). Is CA picking up components of the “effects” of the other variables? Or do the “effects” of the other variables merely reflect components of the CA “effect”? Is there a nonarbitrary coordinate arrangement which should be used for plotting the data and which will resolve this dilemma? In point of fact, the confusion of the CA and MA “effects” in diagram A and that of CA and IQ “effects” in B are associated with relationships among the partial correlations with the performance measures. We shall return to this below. More immediately, our need for an appropriate, nonarbitrary coordinate arrangement suggests that we examine the factor structure of the CA, MA, IQ domain and use a vector or factor diagram. V. INTERCORRELATIONS AND THE FACTOR SPACE

Figure 1 provides some quick information about the factor structure ofthe CA, MA, IQ domain which we have chosen for these discussions: (1) Diagram A shows that the correlation between CA and IQ is zero, as indeed it

267

TASK PERFORMANCE A N D CA. MA, A N D IQ

must be for the general population as long as there is a consistent distribution of IQ’s at every CA. This correlation will remain zero no matter how we might transform the CA scale or the IQ scale. Hence two “natural” factors of the CA, MA, IQ domain, no matter how it is scaled, are a CA-factor and IQ-factor. As factors, their vectors are orthogonal, and thus the question about the nonarbitrary coordinate system can already be answered The grid which we use should be a CA, IQ grid of some sort. (2) Diagrams B and C show that the correlations of MA with CA and with IQ are both positive, as indeed must apply for the developmental population. Thus, in the factor space, the MA vector is separated by less than 90”from the CA vector and from the IQ vector. (3) A visual comparison of digrams B and C indicates that the correlation of CA with MA must be larger than the correlation of IQ with MA. The MA vector must therefore be closer to the CA vector than to the IQ vector. [For an introduction to factor and vector concepts, see Cattell (1952) and Guilford (1954a).] In later sections of this paper which concern curve-fitting problems, we shall explore various transformed scales for CA and IQ. Of all the ways in which CA, MA, and IQ measures might be scaled, logarithmic scaling for all three produces the most unique relationships among the three variables. We shall therefore examine first the logCA, log MA, log IQ space. Note that we have used “CA, MA, IQ domain” to refer in a general way to the developmental population. We shall use “CA, MA, IQ space” to refer to the space defined by raw scores for CA, MA, and IQ, just as we have now used “logCA, logMA, logIQ space” to refer to the space of logarithmic measures for the three variables. For the general space, where the form of measure is not specified, we shall write “C’A, fQ space.”

m,

A. Relationships in the IogCA, IogMA, log10 Space

1. LINEARD EPENDENCE

The ratio formula that IQ IogIQ

=

=

lOOMA/CA leads to the relationship

log 100 + IogMA

-

logCA

=

2

+ lOgMA - lOgCA

(1)

We thus have linear interdependence of logCA, logMA, and logIQ: any one is a linear function of the other two. There are two immediate consequences of this observation: a. In diagrams corresponding to those of Fig. 1 but having logarithmic instead of linear scales on both ordinate and abscissa, the grid line for any given value of the third variable is always a straight line, and the set of these grid lines is a progression of parallel lines. The latter form a clearly directed scale with lines spaced as logarithms of the values of that third variable. This

268

William E. Kappauf 0

A MA

IP

‘I

MA

FIG.2. Three maps of the CA, MA, IQ domain using logarithmic scales on the orthogonal axes. In each, the grid lines representing uniform values of the third variable now comprise a set of parallel lines, and the scale for the third variable has a clear, specificdirection. Thelarge numbers within each diagram are the rounded performance measures for the nine groups of subjects in Harter’s (1965) study.

is illustrated in Fig. 2. The direction of the third scale is normal (perpendicular) to the inserted grid lines. Note that when the directions of the three scales for each diagram are compared, as they are in the set of small vectors associated with each diagram, the MA vector always falls between the other two. b. If we form the matrix of IogCA, logMA, and IogIQ values for all subjects, the rank of that matrix is 2. Therefore the values of logCA, logMA, and IogIQ comprise a perfect two-factor space. Given this, the MA vector must lie in the same plane with the orthogonal vectors for CA and IQ. What we do not know immediately, of course, is the specific location of the MA vector in relation to the CA and IQ vectors. This depends on the

TASK PERFORMANCE AND CA, MA, AND IQ

269

logCA, logMA, and logIQ, logMA correlations. These correlations for the general developmental population, and in particular for the population represented by our CA, MA, IQ domain, do not appear in the literature-or more properly, did not appear in those sources which the writer searched for them. They can, however, be obtained from sets of scores appropriately generated by computer. 2. COMPUTER-DETERMINED CORRELATIONS A program was prepared to generate CA, MA, IQ, IogCA, logMA, and logIQ values for an empirical sample of 10,408 “subjects” well distributed over the CA, MA, IQ domain. At each of 1301 chronological age levels in the series 3.00, 3.01, 3.02, . . . 15.98, 15.99, 16.00, the computer generated eight random normal deviates for a distribution with u = 16. From these deviates, IQ’s were determined. From each pair of CA and IQ values, the computer found, in turn, logCA, IogIQ, logMA, and MA. Means, standard deviations and intercorrelations were then computed for the six variates. The data which pertain to the logCA, logMA, logIQ space are summarized in Table I. The expected value of rloCAloglQ was of course zero. The value obtained for the generated sample was - .0121. The value ofrlogCAlogMAwas .9396, a value which exceeds every guess-timate the writer has ever obtained for this correlation from students and colleagues. r]ogIQlogMAwas.3309. Thus the MA vector is considerably closer to the CA vector in the factor space than it is to the IQ vector. The angle separating the CA and MA vectors, as estimated from this set of data, is 20.1”. 3. THESTANDARDIZED logCA.logMA,logIQ GRID

The obtained intercorrelations determine the plot of the logCA, logMA, logIQ space which is diagrammed in Fig. 3. This plot and the direction ofthe MA vector depend, of course, on the CA range which was chosen for this analysis. To have chosen a narrower CA range would have decreased the correlation between logCA and logMA, and would have increased the angular separation between the CA and MA vectors. The selection of 16 as the value for a,Qinfluenced the values on the IQ and MA scales but not the intercorrelations, since the latter do not depend 00 this scale factor. The factor plot shown in Fig. 3. uses logCA, logMA, and logIQ scales on which oloScA,ulogMA, and uloglQare equivalent distances. Since ulogMA is greater than ulogCA, the MA scale is more compressed than the CA scale. As in Figs. 1 and 2, the triplet of CA, MA, IQ values for agiven individual can be represented here by a single point. Perpendiculars dropped from a point to each of the three scales identify the CA, MA and IQ values associated with that point.

270

William E. Kappauf TABLE I

ESTIMATES OF

Measure p

IogCA

IogCA IogMA

IogMA

PARAMETERS OF THE LOGCA, LOGMA, LOGIQ SPACE, BASED ON 10,408 COMPUTER-GENERATED CASES

Obtained value ,9375

Comment The antilog of this value is 8.66 years, which is the geometric mean of the initial rectangular distribution of CA’s. The arithmetric mean is 9.5 years.

,1964 ,9323

.2081

must be less than 2, piogMA must be Because plogIQ less than p ],,&A. Here, mlogMAis less than p above. The geometric mean of the empirical MA’s was 8.56. The arithmetic mean was 9.504. This is expected to be larger than slogCA because ~l~~~

=

w.Here, PCA. MA

IogIQ

1.9948

ploglQmust be less than log Mean mloglQ =

IogIQ

IogCA IogMA r l ~ g M AIoglQ

IogCA IogIQ

.07 I2

,9396 . 3309 -.0121

=

ur

-

2

+ mlogMA

,2090.

rCA. MA

- mlogCA =

IQ which is 2.0. 1.9948

,001

4. FACTOR REPRESENTATION OF MA

In the logCA, logMA, IoglQ space, the correlation of IogMA with IogCA or the CA-factor is .9396, and therefore the CA-factor accounts for (.9396)2 or .88 of the variance of logMA. Similarly the IQ-factor accounts for(.3309)* or the remaining .12 of the variance in IogMA.’ 5. RELATIONS AMONG PARTIAL CORRELATIONS

Because of the linear interdependence of IogCA, logMA, and IogIQ, the ’The reader may be concerned that the domain which we have chosen here includes some individuals with MA’s as low as 1.5 years and others with presumed MA’s as high as 24 years. Figure 3 does not show the distribution of subjects over the domain, but in point of fact only 48 of the 10,408 generated CA, MA, IQ combinations involved MA’s of less than 2.5 and only 25 involved MA’s of 20 or more. If the “subjects” with these extreme MA’s are dropped from consideration, or if they are assigned limiting MA’s of 2.5 and 20, as was done in a portion of the computer run. the correlations reported here are affected very little, and the change in the factor structure of the score space is of no consequence.

TASK PERFORMANCE AND CA, MA, AND IQ

FIG. 3. The CA,

27 1

scales.

partial correlation of any of these with a second when the third is partialled out is +1 .OO.Using the form rab,ctorepresent the correlation of a with b when c is partialled out, we have: TlOgCA logMA, IogIQ = + 1.00, rloglQ logCA, logm= - 1 .OO, and r l o g ~logIQ, ~ logCA = 1 .OO.This is exactly what is implied by the linear grid lines of uniform values for the third variable in each of the diagrams in Fig. 2. Now because logCA and logMA are perfectly correlated when logIQ is loglQandrl,,,,, have the same partialled out, it must be true that rlogCAZ,

+

William E. Kappauf

212

rloglQ Z, b g M A = -rlogCA Z, 1ogMA. And rlogMA Z, logCA = first of these statements accounts for the fact that CA and MA “effects” read exactly the same in diagram A of Fig. 2 when IQ level is fixed. And the second indicates why CA and IQ “effects” read alike in diagram B of that figure when MA level is fixed.‘

rlogIQz, logCA. The

. . .

B. Relationships in Other Forms of the CA, MA, IQ Space

Of course CA, MA, and IQ measures are most commonly dealt with as “raw” values rather than in logarithmic form, Hence it is a proper question to ask how the CAYMA, IQ space compares with the logCA, logMA, logIQ space. We shall make that comparison here, but at the same time will consider a series of “mixed” spaces (e.g., logCA, logMA, IQ; CA, MA, logIQ; etc.) which will concern us later. 1. ABSENCE OF STRICT LINEAR DEPENDENCE

In any space other than the logCA, logMA, logIQ space, strict linear dependence among the CA, MA, and IQ measures no longer exists. This has several consequences: (a) On newly scaled CA, IQ grids, iso-MA lines do not plot as straight lines as they did in Figs. 2 and 3. (See Appendix Figs Al-A4 for examples.) (b) Partial correlations among CA, MA, and IQ measures are no longer of necessity f1.00, although they may be close to these values. (c) Partial correlations for predicting a criterion performance measure will not be exactly equal in pairs (as discussed in Section V, A, 5, just above), although they will be very nearly so (see House & Zeaman, 1960). (d) The dA, Ith,iQ space is no longer aperfect two-factor space: a third, though relatively unimportant, factor appears. This factor is evaluated below.

2. CORRELATION AND FACTOR DATA From the computer runs which were described in Section V, A, 2, data were obtained for these new spaces as well as the log, log, log space. Table I1 summarizes the computer findings. The only scale forms considered here are CA and logCA, MA and logMA, ‘These relations among partial correlations in this particular problem derive from a more general condition. If among n measures listed in a matrix, there is a subset of these measures, say measures a, 6, c, . . . j , which are linearly dependent, then rob$ , . , , , , , n = k1.00, and r Z o C , , , , . = krzbc,, , , , n . The same holds for all pairs of measures in the subset. (L. Tucker, personal communication.)

,,

,,

273

TASK PERFORMANCE AND CA, MA, AND IQ

TABLE I1 CORRELATIONAL AND FACTORINFORMATION ABOUT THE CA,MA,IQ Dohlllm WHEN THE THREEVARIABLES ARE VARIOUSLY SCALED Correlations between measures for

Scales for CA

MA ~

IogCA CA logCA CA logCA CA IogCA CA

IQ

CA and IQ

CA and MA

IQ and MA

.939 ,916 ,939 .916 397 .918 ,897 .918

.335 .363 .333 .360 .360 .333 .363 .335

Proportion of MA variance not associated with CA- and IQ-factors

___

IogMA MA logMA MA MA logMA MA logMA

-

.01I" -.012" -.Oil"

-.0120 -.011"

-.OP -.011"

-.01Y

.ooo .021

.oo1

.023 .059 .039 .056 .038

Note: Correlations are averages of values obtained in three independent computer runs, with 10,408 cases generated in each run. 'Expected value of r = .OO.

IQ and logIQ. The first set of results to be noted, one which is not shown in the table, is that for our chosen CA, MA, IQ domain with CA ranging from 3 to 16 years, rCAlogCA = .979, rMAlogW= .970 and rlQ 1ogIQ = .993. The relation between the raw values of these variables and their logarithms is curvilinear, but over the ranges of values for the domain, that curvilinearity does not reduce the correlations much below 1.00. Hence the primary relations noted above for the logCA, logMA, logIQ space may be expected to apply to a close approximation in spaces where one or more of the measuring scales has been changed. As Table I1 shows, the correlations between CA and MA measures remain consistently high, and those between IQ and MA remain in the mid . ~ O ' S . ~ As noted above, except with full log scaling, the CA, Ikl,IQ space is not a perfect two-factor space. The last column of the table shows, however, that the third factor never accounts for much of the variance of the MA measures. In particular, if MA is arbitrarily scaled in the same way that CA is(cases in upper half of Table 11), as it can be for this factoring problem, the third factor never accounts for much more than 2% of the variance. of thf MA measures. Given these simple scale transformations then, the CA, MA ,fQ 'The intercorrelations which Harter (1%5) reported over her nine groups of subjects which ranged in nominal MA from 5-9 years were these: CA VS. IQ, -.71; CA VS. MA, 64;andIQ vs. MA, .03. In our computer run we selected a subregion of the CA, MA, IQ domain which was intended to duplicate Harter's. We eliminated all "subjects" with MA's less than 4.75 years and greater than 9.25 years. The obtained computer correlations were: CA vs. IQ, -.675; CA vs. MA, t.716; and IQ vs. MA, -.014; all in good agreement with the above.

274

William E. Kappauf

space remains “very nearly” a two-factor space. The effect of the presence of the third factor on the partial correlations is illustrated in the following values computed from the correlations in Table11for the case of raw CA, MA, and IQ measures: rCAMAJQ= .988; r]QMA.CA = .933; rCA]Q,m= -.922. C. Implications for the Analysis of CA, MA, and IQ Effects

Because CA and IQ are independent over the CA, MA, IQ domain and account for all or essentially all of the MA variance, performance at any criterion task can be completely described in terms of its dependence on CA and IQ. It is not necessary to refer to MA. If performance improves with CA, i.e., if there is a CA “effect,” then an MA “effect” will be observed also. If performance improves with IQ, then an MA “effect” must be present in the data. If both the CA-factor and the IQ-factor are represented in the factor structure of a task, then the observed MA “effect” will be a composite of the CA and IQ “effects.” To be somewhat more specific about these matters, let us return to out discussion of response surfaces. VI. RESPONSE SURFACES AND THE RULED SURFACE MODEL A. Procedures for Plotting Response Surfaces

There are three common procedures which we can use for charting threedimensional response surfaces. One of these is to scale the experimental variables on a two-dimensional grid, and to enter the performance measures numerically at those locations within the grid which mark the experimental conditions. This is the procedure which was used in Figs. 1 and 2. The second procedure is to construct a perspective or isometric three-dimensional drawing showing not only the set of elevated data points but also asystem of lines connecting them to form a surface diagram. Such drawings are occasionally found in the psychological literature (e.g., Blough, 1969; Stevens, 1960; Weiss, 1972; Young & Trafton, 1964).The third procedure is to represent the surface in terms of “equal-elevation,” or “equal-response,” or “equalperformance” contours which are plotted across the two-dimensional grid. The cartographer’s use of equal-elevation contours in depicting terrain irregularities is the familiar case. For psychologists the use of equal-response contours has special significance in that each contour depicts a trade-off relation between the experimental variables. The contour connects all X, Y points which are associated with the same response and thus shows all possible trade-offs between variable X and variable Y in determining that particular level of response. In

TASK PERFORMANCE AND CA, MA, AND IQ

275

some experiments, equal-response contours are found directly through the experimental operations themselves [e.g., equal-loudness contours as determined by Robinson and Dadson (1956) and taste isohedons for the rat as determined by Christensen (1962) and by Kappauf, Burright, and DeMarco (1963)l. In other experiments, equal-response contours are derived from data which are not originally in equal-response form [ e.g., auditory isohedons as plotted by Guilford (1954b) and equal-warmth contours calculated by Stevens and Marks (1971)l. The charting procedure which is described in this paper uses equalperformance contours derived from a plot of performance measures which have been entered numerically on the CA, MA, IQ grid. We shall call the contours “iso-performance contours.” With CA and IQ scales as the coordinate axes of the grid, each contour will represent a trade-off relation between CA and IQ in the determination of performance. B. The Ruled Surface Model for Response Surfaces

Given either the original set of raw data or a set of iso-performance contours, it is reasonable to ask whether the form of the response surface can be specified. The procedures of response surface methodology offer one approach to this problem, dealing with the original data and a surface-fitting technique within an analysis of variance schema. An alternative approach can be developed working from iso-performance contours and asking whether the contours themselves can be described by a simple equation. In particular, if the iso-performance contours all turn out to be straight lines, then at each performance level avery simple trade-off relation exists between the experimental variables. The analyses described here are based upon isoperformance contours and their object is to determine whether a set of parallel linear contours can be fitted to the data. The procedure entails graphic, empirical curve-fitting of the sort so thoroughly and skillfully described by Lewis (1960) for two-dimensional problems. It employs scale transformations as necessary in order to achieve the intended fit. Our general expectation in most studies of performance as a function of an intensitive variable is that performance will change monotonically over the range of that variable. In the present two-factor situation, it is a reasonable expectation that performance will change monotonically (if at all) with changes in IQ at constant CA, and will change monotonically (if at all) with changes in CA at constant IQ. The resulting response surface would be one which proceeds monotonically in the direction of one or both factor axes. Let us call this a monotonic surface. One of the simplest forms of monotonic surface, other than a plane, is a ruled surface where the generating lines or “rulings” are horizontal. We

William E. Kappauf

216

may call this a monotonic, horizontally ruled surface. The horizontal rulings correspond of course to equal performance contours when we are thinking of the surface as a response surface. We therefore have this criterion: If the iso-performance contours which describe a response surface are both straight and parallel (or essentially so), then the response surface is a monotonic, horizontally ruled surface. The direction perpendicular to those parallel contours is the direction of greatest slope of the response surface. Components of that slope associated with CA and with IQ can be determined by relating this slope direction to the direction of the CA and IQ vectors. In general it is our expectation that the direction of greatest slope will be in the 90" quadrant bounded by the CA and IQ vectors, which is to say that we expect performance to improve with both IQ and CA, but the model is not limited to this situation. Small sections of three horizontally ruled surfaces are shown in Fig. 4. A few successive positions of the generating line are shown in each diagram. I n diagram A, the surface is a plane, but the height of the plane is everywhere the same and so the response or performance measure, Z, is not dependent on X and Y. In diagram B the surface is a sloping plane. Z changes monotonically with values of Y but is independent of X. B, therefore, is a monotonic horizontally ruled surface. C is also. In C, the surface is ogival in shape and performance score, Z, increases with both X and Y. The successive positions of the horizontal generating line are in fact the isoperformance contours on the surface, but it is their projections in the X,Y plane that we draw and label with Z values (Z,, Z,, etc.) in any simple twodimensional representation of the surface. Given a horizontally ruled surface such as B or C, projections of the iso-performance contours all have as their

f

FIG.4. Some horizontally ruled surfaces.Each of the surfaces(A, B, and C) has been formed by the translation of a horizontal straight line.

TASK PERFORMANCE AND CA, MA, A N D IQ

277

equation Y=mX+bi

(2)

where the slope, m, is the same for all lines because they are parallel, and where b varies from contour to contour. The “profile” of the surface can be obtained by plotting Z as a function of b. A monotonic, horizontally ruled surface is a three-dimensional extension of our familiar monotonic model for a psychometric function in two dimensions. It has special appeal as a model for response surfaces relating performance to CA, MA, and IQ because it implies linear trade-offs between CA and IQ measures in the determination of performance on the experimental task. C. Testing the Ruled Surface Model

Given the foregoing criterion of straight and parallel iso-performance contours, all we need do to test the monotonic, horizontally ruled surface model as descriptive of a particular set of data is to plot a set of contours for those data and observe whether or not they are straight and parallel. Details of this plotting procedure will be discussed in Section VII. Now the model as described above does not specify the particular CA, IQ grid on which the iso-performance contours will be plotted. In this respect the model is a general one-it could apply with any grid, a grid with logCA vs. logIQ, or CA vs. IogIQ, or CA vs. IQ, etc. Testing the model therefore consists of plotting iso-performance contours on various grids to determine whether there is one on which the contours satisfy the criterion. Rejection of the model follows when no grid can be found on which the iso-performance contours are suitably straight and parallel. The procedures which are followed here in manipulating the CA and IQ scales from grid to grid to fit model to data correspond to those illustrated and discussed by Lewis( 1960) and Mueller (1949) for two-variable problems. D. Interpretation When the Ruled Surface Model Applies on the IogCA, IogMA, IoglQ Grid

Suppose now that a set of iso-performance contours which we have plotted on a logCA, logMA, logIQ grid do satisfy the criterion. They are straight and parallel and we accept the response surface to be a horizontally ruled surface. How do we interpret this outcome in terms of CA “effects,” MA “effects,” and IQ “effects?” Since the specific interpretation depends upon the orientation of the isoperformance contours and the surface, Fig. 5 has been prepared to cover

278

William E. Kappauf B

MA

CA

2 = t (CAI

2 = t (10)

C

ia

D

I?

MA

CA

t 2 = t (log D-KIogCAl

2

f (MA)

FIG. 5. Iso-performance contours representing a series of monotonic, horizontally ruled response surfaces. Each diagram shows the IogCA, IogMA, logIQ space, with the axes for CA, MA, and IQ intersecting at the joint mean for the three log scales. Each contour(bo1d line) links CA, MA, IQ points in the domain where performance at the task under study is at agiven constant level, Z,.

extreme and general cases. The separate diagrams in the figure show four hypothetical, illustrative surfaces. All are monotonic, horizonally ruled surfaces. Iso-performance contours are straight and parallel in each case. Performance is the Z-variable, and so the separate contours are labeled Z , , Z,, Z,, or Z, to indicate different levels of performance, The rectangular ground for each diagram is a reduced representation of the IogCA, IogMA, logIQ space of Fig. 3. The IogCA axis, the logIQ axis, and logMA vector axis are shown in each case. Their point of intersection is the joint IogCA mean, logMA mean, logIQ mean, corresponding to the joint CA, MA, IQ geometric mean. In each diagram, the direction normal to the iso-performance contours is the direction of greatest slope of the response surface.

279

TASK PERFORMANCE AND CA, MA, AND IQ

In diagram A, task performance changes with changes in IQ and is completely independent of changes in CA. The position of the MA vector, however, indicates that for this task, performance will always be observed to vary with MA as well as with IQ. .33 is the correlation between logIQ and logMA and is the cosine of the angle between the IQ and MA vectors. Hence, over any short distance, say that between successive iso-performance contours, the rate of change of performance as a function of MA will be .33 times as large as the rate of change of performance as a function of IQ: that is, the change in performance associated with advancing 3 small-unit distances along the logMA scale will be the same as that associated with advancing one of those unit distances along the logIQ scale. To describe this particular surface and others like it, where performance is some function of IQ, we may write Z =f(IQ). In diagram, B, the contours describe a monotonic, horizontally ruled surface where performance varies with CA and not with IQ: 2 =flCA). Performance is dependent upon the (1og)CA-factor and not upon the (1og)IQfactor. Again the position of the MA vector dictates that experimental observations will always show task performance varying with MA, as well as with CA. The “apparent MA effect” in any local portion of the domain will be .94 times as large as the CA “effect,” .94 being the value of the correlation between logCA and logMA. In diagram C, the iso-performance contours progress in a manner which indicates that task performance is dependent on both the CA and IQ factors. 2 =fllogIQ - klogCA). A response surface of this sort implies CA “effects,” “apparent MA effects,” and IQ “effects”-all three. Rate of change in performance associated with advancing MA will be a weighted sum of the rates of change in performance associated with advancing CA and advancing IQ: dZ d[MAI

--=

dZ dZ .94 d [CAI .33-d [IQI

’

(3)

where [CAI, [MA] and [IQ] imply that CA, MA, and IQ have each been expressed as logs and standardized. It may be of interest to note a consequence of this relationship: that the “apparent effect” of MA will exceed the CA “effect” whenever the IQ “effect” exceeds. 18 times the CA “effect,” and will exceed the IQ “effect” whenever the CA “effect” exceeds .71 times the IQ “effect.” Diagram D concerns the very special case where performance at the task advances directly with changes in MA. The iso-performance lines and the iso-MA lines are parallel. I n factor language we would say that with respect to the (1og)CA- and (1og)IQ-factors, the factor composition of the task matches the factor composition of logMA. Such a task could well be used as an item on a test to measure MA. We may observe, as we did above, that the

280

William E. Kappauf

“apparent MA effect” on this task is the vector sum of the CA “effect” and the IQ “effect”: i.e., that Z = f(log1Q-klogCA). Of course it will sometimes be convenient and more meaningful to describe a research outcome such its that shown in diagram D as one which shows a “true MA effect” or a “simple MA effect,” and write 2 = f(MA). When we do so, we must remember the component character of the MA “effect” and that we are not introducing an MA factor, unless we are ready to abandon the CA and IQ factors and designate the “effects” of both CA and IQ as “apparent effects.” In all of these illustrations, the iso-performance contours (not the surface itself) have an equation of the form logIQ = m(1ogCA)

+b

and hence performance is some function of logIQ

-

(4) m(1ogCA).

E. Interpretation When Some Other Grid Is Required to Make the Ruled Surface Model Acceptable

When the ruled surface model is found acceptable on some grid other than the logCA, IogMA, logIQ grid, we know immediately that there isno possible orientation of the response surface where performance changes can be interpreted in terms of a “simple MA effect.” The iso-MA lines on these other grids are not themselves straight (see Appendix Figs. Al-A4) and hence cannot parallel the iso-performance contours (as was the case in diagram D of Fig. 5). With any of these other grids, acceptance of the model always implies a description of performance in terms of a composite of CA and IQ measures. The individual contours of the set all have an equation of the general form

fdIQ)

=

m.f,(CA)

+b

(5)

wheref, andf, express the scale transformations used on the grid for IQ and CA respectively. VII. PROCEDURE FOR DERIVING AND PLOlTING ISO-PERFORMANCE CONTOURS

When we wish to derive a set of iso-performance contours from an array of data values, three principal steps are required: (a) a specific CA, iQ grid must be selected; (b) the data must be entered on thegrid; and(c) some form of interpolation must be employed in order to locate the path of each iso-performance contour across the field of data points. Details of this procedure will be described here with reference to Fig. 6, which presents iso-

TASK PERFORMANCE AND CA. MA, AND IQ

28 1

performance contours for the data of Harter’s (1965) study plotted on a logCA, logIQ grid. A. Selecting the

&, Ih Grid

The most interesting grid with which to start an analysis is the logCA, logIQ grid because of the unique set of iso-MA lines which it contains, permitting the most convenient assessment of the hypothesis that performance differences arise from a “simple MA effect.” Figure 6 uses this grid. Scales in raw values as well as log values are shown on both ordinate and abscissa. Subsequent grids, if needed in the attempt to find a ruled surface condition, are chosen on the basis of the outcome of the preceding plot(s). B. Entering the Data

For each group of subjects, find CA (the arithmetic mean of their CA’s) and (the arithmetic mean of their IQ’s). Plot t h e C A , W point for each group on the chosen grid. The nine filled dots in Fig. 6 are located at the CA, TQ points for the groups in Harter’s study. Enter the average performance score for each group adjacent to its CA, point. The small numbers in Fig. 6 are the group performancescores. They have been rounded, but only for purposes of representation here. It should be observed that there are alternatives to the use of arithmetic means for CA and IQ as here proposed. Basically we have three options: (a) to disrzgard trgnsformation scales on the chosen grid, calculate geozetic means (CA and IQ) of the raw CA and raw IQ values, and plot the CA, IQ point for each group using the raw CA and IQ scales on the chosen grid; (b) to work from the transformation scales as used for CA, or IQ, or both, to calculate the arithmetic means of the transformed values of CA and of IQ (trCA a n d w , and plot thetrCA,rnpoint for each group using the scales of transformed values on the chosen CA, IQ grid; or (c) to disregard the transformation scales, calculate the simple arithmetic mean of the raw CA and IQ values, and plot the CA,IQ point for each group using the raw CA and IQ scales on the grid. The use of geometric means has merit because of the fact that geometric mean IQ equals 100 times geometric mean MA divided by geometric mean CA. A corresponding relation does not hold exactly for any other set of means. Thus it is only with geometric means that “mean” CA, “mean” IQ and “mean” MA plot exactly as a single point on any of our three-way grids. The use of= a n d m has merit because the plottedtrCA,EIC point for a group of subjects properly locates the “average individual” in that

William E. Kappauf

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group in terms of the scales of the chosen grid. Of course, new values of for every new grid and set of scale transformations which are explored.

trCA and/or trig have to be calculated

TASK PERFORMANCE AND CA, MA, AND IQ

283

For the level of graphical analysis described in this paper, however, it is not critical to attempt to capitalize on the above advantages of either geometric means or means of transformed values. If each group of subjects is respectably homogeneous in CA and in IQ, it will make little difference whether we use procedures (a), (b), or (c): the obtained means will be so nearly the same that the obtained response surface (even neglecting plotting errors) will not be affected observably. The following illustrative comparisons of (a) and (c) are relevant: If the age span for a group of subjects happens to be as great as two years, and if the CA distribution within that span is rectangular, then the arithmetic mean CA will exceed the geometric mean CA by at most .06 years. If the IQ range for agroup of subjects is 20 IQ points, and if the distribution over this range is again rectangular, then the difference between arithmetic and geometric means is less than .2 IQ units over the 130-150 range, and is about .4 IQ units over the 50-70 range. Hence the use of simple arithmetic means for CA and IQ should always be acceptable. C. Interpolation and Plotting

a,

Connect the TQ points to form a mosaic of triangles. First connect the two points which are closest together, then the next closest pair of points, etc. Never draw a new line which intersects any already drawn. Continue until all areas in the mosaic are triangles and until the exterior border of the mosaic has no concavities. See the finely dashed lines in Fig. 6. The obtained triangles represent facets or small triangular plane surfaces, which touch each other and together form the observed response surface (in the manner of a geodesic dome). It will be recognized that any set of scattered points can be connected in pairs by a series of nonintersecting lines which will eventually form a mosaic of nothing but triangles. But starting with any given set, it is possible to form many different mosaics. The only way to insure a unique solution to the triangulation problem, as mathematicians call it, is to introduce one or more rules of procedure. In the case of the present contour analysis, our purposes seem to be satisfied best under the rule that we draw admissable connecting lines in the mosaic in order of their length. By working from the shortest to progressively longer lines, we keep the individual facets relatively smaller and more compact, and this limits the smoothing which they introduce. The criterion that there be no concavities in the perimeter of the final mosaic assures us that all possible triangles have been formed. For a more or less “rectangular” 3 x 3 array of points, there will typically be eight triangles, but possibly more. For a more or less rectangular 4 x 4 array of CA,m points there will be some 18 triangles and possibly more. In Fig. 6, nine triangles were formed.

m,m

284

William E. Kappauf

Select the performance levels (Z-values) which will be used for the isoperformance contours. Equally spaced Z-values, while not essential, have merit in that the relative spacing of the successive contours will suggest changes in steepness of the response surface. Performance levels of 15,25, 35, and 45 were chosen for Fig. 6. For each particular 2-value, interpolate on every mosaic line which spans that Z-value to locate the CA, IQ positions where that Z-contour crosses those lines. Thus, in Fig. 6, four interpolations established the Z = 15 contour, nine established the 2 = 25 contour, etc. Each interpolation is made in terms of graphical distances on the grid being used, i.e., by measuring the lengths of the mosaic line involved and dividing it into the same fractional parts that the contour Z-value divides the difference between the Z-values (nonrounded) for the data points at the two ends ofthe mosaic line. Thus, the Z = 15 contour crosses the topmost dashed line in the figure at a point which is to the right of the data point for 2 = 16.0 by 1.0/5.2 of the distance between that data point and the data point where Z = 10.8. Connect the interpolated CA, IQ points to form the iso-performance contours. These are the four bold lines in Fig. 6. Check the obtained contours for accuracy. Note especially whether two or more contours which cross the same facet are parallel across that facet, as they should be when properly drawn. VIII. ANALYSIS OF HARTER’S DATA USING ISO-PER FORMANCE CONTOURS A. The 1965 Study

The iso-performance contours in Fig. 6, as already noted, represent Harter’s (1965) data. On a logCA, logIQ grid, iso-MA lines are straight, and two dashed, illustrative lines for MA = 3 and MA = 16 have been included in the comers of Fig. 6 to aid interpretation. 1. INTERPRETATION

OF

FIG. 6

From an examination of Harter’s data in this response surface plot we may draw the following conclusions: (1) Learning-set formation in Harter’s situation improved in a general way with advancing MA, but it was not a simple function of M A the iso-performance contours in the figure are not straight and are not parallel to the iso-MA lines. (2) Learning-set formation did not change solely as a function of CA or solely as a function of IQ, but was a function of both. (3) Learning-set formation improved mono-

285

TASK PERFORMANCE AND CA, MA, AND IQ

tonically with CA and monotonically with IQ over the range ofCA, IQ conditions examined in the study. (4) The response surface plotted with respect to the IogCA, logIQ grid is neither a plane nor a horizontally ruled surface. ( 5 ) The response surface is of such a form that a CA x IQ interaction would be expected in studies using CA x IQ factorial design, an MA x IQ interaction would be expected in studies using an MA x IQ design, and a CA x MA interaction would be expected in studies using a CA x MA design (for elaboration, see Section XI, A).

2. FITTING A RULEDSURFACE TO

THE

DATA

The regularity of the iso-performance contours in Fig, 6 suggests that the response surface might be transformed into a horizontally ruled surface if plotted with respect to a grid with new CA and/or IQ scales. The logIQ scale compresses the higher IQ values and is thus contributing to the flattening of the iso-performance contours at high IQ levels in Fig. 6. Similarly the IogCA scale works to turn the contours down sharply at the right. All of the iso-performance contours should be straighter if we shift to a logCA, IQ grid or a CA, logIQ grid, and may be straighter still if we go to a CA, IQ grid. Figure 7 is a replot of the data on a CA, IQ grid. The iso-performance contours are much straighter, as expected, but are not quite parallel. A further shrinking of the left side and expansion of the right side of the CA scale can be accomplished by using a CA scale in the form - log(KCA), where K is some constant larger than 16 (the upper limit of our CA range). Such a scale with K = 19 is used in Fig. 8. Here the iso-performance contours are both acceptably straight and acceptably parallel. Hence we have found that the response surface for Harter’s 1965 data can be described as a monotonic, horizontally ruled surface when plotted on a grid which is scaled as -log( 19-CA) vs. IQ.6 The transformation of CA values to -log( 19-CA) deserves comment. Under this transformation, CA is scaled backward from 19. High CA’s beget low values of (19-CA) and low CA’s high ones. The negative sign attached 61t has been noted by Mueller (1949) and others that transformations frequently work at cross-purposes, that different transformations are required to accomplish different results with the same data. Thus, eliminating interactions (Bogartz & Wackwitz, 1970; Lindquist, 1953) and achieving homogeneity of variance may require different transformations. In the present analyses we have another example: log transformations simplify the CA, MA, IQ space, but a different set of transformations for CA and IQ is required to portray in a simple way the dependence of Harter’s performance measure upon CA and IQ. MA and task performance are different functions of CA and IQ and it takes different transformations to show each most clearly.

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to the log value merely reverses the plotting scale so that CA = 3 is represented at the left of Fig. 8 and CA = 16 at the right in a manner consistent with the CA scales in previous figures. The use of scale transformations of the type (K - X ) or log (K - X) is not without precedent (Bousfield, 1934; Hull, 1943; Stephan, 1931), and the scaling of CA backward from a level which may be thought of as “maturity” is not without theoretical interest. These matters will be discussed more fully in Section IX, D.

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3. EQUATIONS OF

THE

ISO-PERFORMANCE LINESIN FIG.8

The fitted, straight, and parallel iso-performance lines in Fig. 8 are described by the common equation Y = mX + b, they all have the same slope m, and they differ only in the value of b. Hence the response surface can be

288

William E. Kappauf

completely described by citing the value of m and showing the manner in which the performance measure, 2, varies with changes in b. In the case of the surface defined by the fitted lines in Fig. 8, Y = b when X or log(l9-CA) = 0, i.e., when CA = 18. Inspection ofFig. 8 indicates that the four fitted iso-performance lines, when extended, will all reach the ordinate line for X = 0 at negative values of Y. To determine the values of b for each of the fitted lines we need to identify two points on one of the lines to provide slope information and one point of each of the other lines. Slope is determined with greatest precision by using maximally separated points. In Fig. 8, maximum separation occurs for the points where the line fitted to the 2 = 15 contour intersects the left border and the lower border of the figure. Based on visual readings to the nearest unit on the IQ scale and the nearest .01 on the log scale, these points are ( - 1.20,144) and( -.58,50). The slope is therefore(50 - 144)/[-.58 -(-1.20)] = -94/.62 = -152,whichistosaythatfor every unit increase in the value of - log( 19 - CA), e.g., from - 1.2 to - .2 as CA advances from 3 years to 17.4 years, there is a 152 unit decrease in IQ. The fitted lines thus have an equation of the form Y = -152X+b (6) or IQ = -152 (-log [19-CA]) + b (7) Hence b = IQ - 152 log [19-CA] (8) (Although the third digit in 152 is not a “significant digit,” it will be retained here in order to avoid misinterpretations which might possibly occur if the number were rounded to 150. The 2 is shown in italics to indicate that only the 1 and 5 are significant digits.) Reading the intersection of each of the fitted iso-performance lines with the lower border of the figure permits the calculation of b for each line by substituting the intersection-point values in Eq. (8). From these calculations we obtain the following equations for the four fitted iso-performance lines: Line for 2 = Line for 2 = Line for 2 = Line for 2 = 4. THEPROFILE OF

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RESPONSE SURFACE

A graph of values of 2 as a function of b is given in Fig. 9. This plot depicts the “profile” or changing slope of the fitted ruled response surface. Literally,

TASK PERFORMANCE AND CA.

289

MA, AND IQ

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this graph shows the way in which performance varies with IQ, given CA = 18, but because we have a horizontally ruled surface it describes the variation in performance with IQ at any CA. More generally, it shows the form of the line of intersection of the fitted surface with any vertical plane which cuts the family of fitted iso-performance lines. Hence it depicts the line of steepest descent of the response surface, i.e., the intersection of the fitted surface with a plane which is perpendicular to the family of fitted iso-performance lines. But it also describes the manner in which performance varies withCA! By finding scales which transform the response surface into a horizontally ruled surface, we have found those unique and interesting conditions where performance improvement with CA and performance improvement with IQ both follow the same function. Had this profile line turned out to be a straight line, then the fitted response surface would have been a plane. (See, for example diagram B in Fig. 4.) As it is, the profile line is not far from a straight line, implying that when the CA, MA, IQ space is scaled as in Fig. 8, the response surface is only slightly bowed-concave upward-over the region which Harter (1965) explored in her study. The curvature of this fitted surface will not (and could not!) be defended as statistically significant, but it will be accepted here because it is accommodated by our a priori model which anticipates a gradual approach to a performance limit at high IQ and high CA levels. This model and these data will be considered further in Fig. 11.

290

William E. Kappauf

5. REVIEW AND COMMENT We have thus observed that a. Iso-performance contours for Harter’s (1965) data can be fitted very well by a family of parallel straight lines if the data are plotted on a grid with IQ vs. -log( 19-CA). (See Fig. 8.) b. The response surface defined by these parallel fitted lines is slightly concave upward. (See Fig. 9.) c. The fitted response surface is described by the relation of the performance measure, 2, to the Y intercepts, bi, of the fitted iso-performance lines. Each bi, in turn, is a simple linear function of IQ and log(19-CA). d. Because of the fact that performance improves with increases in CA and in IQ, improvement in performancemust also beassociated-though not in any simple manner-with increases in MA. e. If the scope of the chosen CA, MA, IQ domain is taken as a basis for judgment, Harter’s measure of learning-set formation changed more rapidly in the CA dimension than in the IQ dimension. The slope of the fitted isoperformance lines on the standardized grid of Fig. 8 is steeper than 45”: to advance from the iso-45 line to the iso-15 line one need advance only 1.5 standard score steps in CA, but as much as 2.8 standard score steps in IQ. f. The curve fitting operations described here stopped when an acceptable fit appeared to have been attained. Some other scale, say -log( I8 -CA) or -log(20-CA), might have produced a result as satisfactory or better than that shown in Fig. 8, but such additional scales were not tried. As in all empirical curve-fitting, other “solutions” are not ruled out by one “success.”

B. Need for Cross-Validation

In the above transformation search for a set of scale conditions which would provide linear, parallel iso-performance contours, we have been working with observed mean scores for each of Harter’s groups of subjects, and not with true mean scores for these groups. The search procedure has been entirely empirical and the outcome, satisfying as it is for this particular batch of data, requires cross-validation before it can be accepted as having more general significance. In her 1967 study, Harter used the same learning-set task and scored it in the same way, and so her 1967 data deserve examination for crossvalidation purposes. The following analysis is legitimate as a cross-validation attempt since the writer did not examine these data at all until the analysis of the 1965 results had been completed. Disappointingly, the new data, in two sets, provide only six data points to define each response surface-a condition which severely restricts the number of triangular facets available

TASK PERFORMANCE AND CA, MA, A N D IQ

29 1

for contour mapping. The new measures are also less reliable (see Section VIII, C) than the 1965 data. They are therefore of somewhat limited usefulness for our intended cross-validation check, but nevertheless here they are.

C. The 1967 Study

Of the 16 groups in this study, 12 are of interest to us here. They were divided into two sets of six groups each. Each set of six groups comprised a factorial array, two levels of MA by three levels of IQ, and so the study really consisted of two 2 x 3 factorial experiments involving MA and IQ. In one of these experiments, subjects were tested under the “standard” condition, which was the same as that used in the 1965 study. In the other experiment, subjects were tested under a “social” condition where special social reinforcements were added. Two basic conditions did change from the 1965 study. One of these was a change from 10 problems to 25 problems in each daily session. The other was a change from the use of one experimenter to two experimenters, each of whom worked with half of the subjects in each group. Although Harter found that there was no statistically significant experimenter effect, the variability of subjects within groups on problems to criterion was greater for the 1967 subjects than for the 1965 subjects.’ This could have resulted from the new massing condition or a small experimenter effect or both, but its effect was to increase the standard errors of the new performance measures as compared with standard errors for the 1965 data. The new data for the “standard” condition prove to be not very informative. First, performance did not improve monotonically with IQ at either of the MA levels, perhaps reflecting the sampling errors just discussed. The effect of this was a small depression in one portion of the response surface. But second, when the data are examined on any CA, IQ grid, the available triangular facets fail to provide enough information on isoperformance contours which are independent of one another (see Section IX, C). Were one to choose the grid which appears best to favor linearity of the major contour it would be the CA, IQ grid, but little confidence attaches to this choice. ’At the writer’s request, Dr. Susan Harter kindly made available a set of photocopies of the summary data sheets for her 1965 study and for the social groups in the 1967 study. On these sheets were recorded the CA, MA, IQ, and criterion scores for each subject. Within-groups variability on the criterion increased, as would generally be expected, with groups average score in both sets of data, but the rate of increase was greater for the social groups. In spite of the fact that the social groups reached criterion in fewer trials than the groups in the 1965 study, their average within-groups variability was greater.

292

William E. Kappauf

The data for the six “social” groups are plotted in Fig. 10. The grid here is the same -log( 19- CA), IQ grid used in Fig. 8, and the iso-performance lines which were fitted to the data in Fig. 8 have been reproduced here for comparison with the newly observed iso-performance contours. There are some irregularities in the new contours, but the general slope IS0

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TASK PERFORMANCE AND CA. MA, AND IQ

293

of the new contours is not unlike that of the contours for the 1965 experiment: the CA scale looks good and the value ofm appears not unsatisfactory for these data. A general comparison of the Z-levels of the new iso-performance contours with those for the former experiment indicates that the new groups performed at better absolute levels: they reached the learning criterion in fewer trials than the earlier groups of subjects had. This we would expect from the new and higher incentive levels. In spite of the fact that these new data are really too limited for good response surface analysis, it is encouraging to find that the two 1967 experiments point to the same grids (CA, IQ and -log[19 - CAI, IQ) which drew our attention in analyzing the 1965 data (Figs. 7 and 8). In that respect, at least, the cross-validation is successful. Of course it is tempting to discount the new “standard” data and emphasize the outcome for the new “social” groups. What Fig. 10 implies is that the social condition influenced problems to criterion, but that it did so without modifying the trade-off relationship between CA and IQ in determining learning-set performance. This is to say that the social-standard variable changes the “level” of the ruled surface and its rate of climb but not its orientation in the -log( 19-CA), IQ space. This is an interesting kind of result to be pursued in other test situations: i.e., to determine whether experimental parameters merely affect level, or both level and orientation of the response surface. IX. APPRAISAL OF THE GRAPHIC APPROACH IN THE ANALYSIS OF RESPONSE SURFACES A. Comparison with Alternative Procedures

The graphic procedures which have been illustrated here consist on the one hand of procedures for plotting and interpreting the response surface in terms of the CA, MA, and IQ variables, and on the other hand of procedures for examining the suitability of the monotonic, horizontally ruled surface as a model for the observed response surface. Considered overall, this approach may well seem unsophisticated in these days of elaborate multivariate, computerized analysis. It entails hand-plotting and the computation of more interpolated iso-performance points than there are original data points. It presumes reliable data, and reasonable concurrence of the raw data with the model which holds that task performance changes monotonically with CA, MA, and IQ. It is subject to the known weaknesses of trial-and-error curve-fitting which is done by eye. It seems a comedown from the formal computational procedures of correlational analysis, or analysis of variance, or response surface methodology.

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William E. Kappauf

But while all these statements are true, the method has compensating merits. It forces the investigator to become involved in taking a first-hand look at the data rather than just processing it by routine methods. It offers built-in protection against taking a nearsighted look at data for only a part of the CA, MA, IQ domain, because it uses grids which span the entire domain of interest in developmental research. It recognizes that linear models for CA “effects,” MA “effects” or IQ “effects” are unrealistic. It considers a model which is less restrictive than the general linear model: a model which suggests that a simplified trade-off relation exists between CA and IQ in the determination of performance, but which admits a curvilinear dependence of performance on each of these variables and their combination. It goes beyond a null hypothesis assessment of fit of model to data and looks for a seemingly “best” fit. If we apply multiple regression procedures to CA, IQ, and performance data we have a numerical goodness-of-fit criterion (least squares), but all that we can obtain is information about the slope of the plane of best fit to the data and the direction of that slope. A factoring of performance scores along with some desired set of transforms of CA, MA, and IQ values will do no more: it permits us to locate the performance test vector in the factor space and observe whether it is closest to the CA, MA, or IQ vector, but from this we learn nothing about rates of change of slope of the response surface or where in the domain these changes occurred. By working with iso-performance contours, on the other hand, we get a description of the response surface “as it is” or as best we can know it from the data on hand. And by working with a horizontally ruled surface model which admits a curvilinear profile for the surface, we accommodate to “end-of-scale” effects rather than worry about them as sources of spurious plateaus or interactions. The present procedures conceptually resemble most closely the procedures found in response surface methodology. This methodology is concerned with fitting complex surfaces to the data of experiments where several experimental variables have been employed either in factorial or in some modified, incomplete factorial array. Representative, informative papers in this field include those of Box (1954), Box and Wilson (1951), Box and Youle (1959, Hill and Hunter (1966), Meyer(1963), and Williges andSimon (1971). Our problem of describing or predicting performance from CA and IQ is simpler than most problems dealt with by response surface methodology. We have but two predictor variables rather than many. This makes it possible to tackle our curve-fitting task somewhat informally by means of scale transformations instead of by more forceful methods using complex polynomial equations and numerical criteria. Thus, while the present paper has adopted the term “response surface” as a convenient descriptive term for regression surface, the methods outlined here are not to be found in current response surface methodology.

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It has not been done here, but it should be apparent that the present methods can be made more formal if and when this seems desirable in terms of their usefulness and frequency of application. For one, the plotting procedures with varying scale transformations can be computerized. For another, the methods can be extended to include goodness-of-fit tests to assist in the comparative evaluation of different grid arrangements and in assessing seeming differences between the results of different experiments.

B. Questions about Domain and Grid Details

The graphical procedures described in this paper are general: they are not restricted either to the particular 3/16-year CA range chosen for the CA, MA, IQ domain, or to the present grids where the IQ scales are cut arbitrarily at 50 and 150, where oIo = 16, and where equal standard deviation distances determine the CA and IQ dimensions of the figures. The use of standardized scales on the grids is not essential, but it should be noted that this follows convention in factor analysis diagrams, and may in the long run have merit in assuring that neither the CA nor the IQ scale will beunduly compressed to the detriment of an effective plotting and interpretation of the iso-performance contours. If a developmental population spanning a wider CA range is appropriate for certain studies, grids for this new population condition can be prepared: the correlation between CA and MA will be larger than was found here, and the MA vector will move closer than 20” to the CA vector in the IogCA, logIQ grid. oCAwill also increase, a change to be noted if one wishes to preserve the standardized feature of the scales on the present grids. The averaging and plotting of IQ values, as well as the use of straight facet lines for interpolation, presume that the intelligence test used in gathering the research data has provided IQ’s which have the same mean and variance at every chronological age level, as is the case with deviation IQ’s (Pinneau, 1959). This paper began with the stricter condition, namely that the IQ’s would not only have consistent means and variances but that they would also be ratio IQ’s. This was an important condition for our initial argument that CA, MA, and IQ values could be represented by a single point in a two-dimensional but three-way grid. We can back away somewhat from this aspect of our model now, if we wish. Once we observed that CA and IQ are the naturally orthogonal variables, we adopted the position that the trade-off relations which we should look for in trying to understand task performance are relations between CA and IQ, rather than relations between CA and MA or between IQ and MA. We are thus committed to transformvariations of the CA, IQ grid, and henceforth our interest in literal or precise MA values wanes. The uniform-MA lines on our present grids were

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drawn to show MA values when MA is exactly equal to IQ(CA)/ 100. If the latter happens not to be exactly true, as when we have deviation IQ’s, the MA lines provide only an approximate MA scale, but they can still serve their primary purpose: namely, to provide a general reference for judging whether or where the iso-performance contours indicate that task performance can be described as a “simple function’’ of MA. C. Properties of the Iso-Performance Contour Diagram

Since the present graphic methods depend on the use and interpretation of iso-performance contours, it is important to recognize the following properties of the iso-performance contour diagram: 1. The mosaic of triangular facets which is obtained to represent the response surface will vary somewhat with the rules which are applied when drawing the facets. The rule recommended here, i.e., starting with the shortest facet edge and drawing progressively longer ones in order, provides one particular set of facets and interpolated contour points. A slightly different set of facets and interpolated points will be obtained if a different rule for creating facets is followed. 2. Transformations of scale modify the apparent shape of the response surface. This is reflected in the fact that scale transformations modify the shapes of individual facets and may also affect their configuration and distribution. Note that the long thin triangle on the left in Fig. 6 has been replaced by a similarly long thin triangle on the right in Figs. 7 and 8. 3. The transformation scales for CA and IQ which are used on any particular grid determine the shapes of the obtained iso-performance contours, but the investigator’s choice to standardize or not standardize the grid scales influences only the visually perceived slope of each contour. 4. Two or more iso-performance contours which cross the same facet run parallel to each other within that facet. While such contours provide redundant information about contour direction on that facet, at least two are needed if facet slope is to be apparent. 5 . The diagram shows change of slope of the response surface only if the slopes in “neighboring rows” of facets across the surface can be compared. Thus, detection of a slope change requires at least two contours through one “row” of facets and one or two contours in a contiguous “row” (see Fig. 7, Z = 15 VS. Z = 25, 35, 45). 6. No matter how many interpolated iso-performance points are calculated or how many contours are drawn, the total information in the diagram is always limited by the number of original data points. 7. The reliability of the average performance measures, i.e., the individual data points, is a function not only of error of measurement for the performance task itself but also of the tolerated heterogeneity of subjects

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within groups with respect to CA and IQ. (See Section XI, B, 5.) 8. Unreliability of the average performance measures will tend to have a relatively greater effect on the path of iso-performance contours in those portions of the CA, IQ domain where the slope of the response surface is low (i.e., where dZ/db is low). Oppositely, reliability of the path of iso-performance contours will generally be greatest in those portions of the CA, IQ domain where the slope of the response surface is greatest. It would be desirable if the ratio of the standard error of each mean performance measure to the local slope of the profile of the surface were roughly constant. 9. Any one iso-performance contour followscorresponding paths through corresponding facets on each successive grid which is tried in evaluating a given batch of data. The task of interpolating along facet lines on each new grid can therefore be abbreviated by borrowing on calculations made for previous figures. It will be noted that some of these properties are important for experimental design, others for how we derive the contours and how far apart we space them. D. Empirical Curve-Fitting and Theory

In the course of checking whether a monotonic, horizontally ruled surface could be fitted to Harter’s data, we manipulated and transformed the CA and IQ scales in a trial-and-error way until an appropriate combination of grid scales was found. This is a case of empirical curve-fitting, and of the use of transformations for simplifying data description (see Mueller, 1949). The slope value of - 152 and the value of 19 in CA measures scaled as log( 19 - CA) are empirical constants, not constants dictated by theory. As a matter of fact there appears to be very little quantitative theory about the development of learning ability or other performance as a function of CA, MA, and IQ. About all we have are two general kinds of ideaswhich might be construed as theory. One is that performance should improve monotonically with CA, and/or with MA, and/or with IQ. We started with this premise in Section VI, B. The other is that learning rate in particular should vary simply with MA. This will be discussed in Section X, B. And then of course there is the implied theory, whenever correlational procedures are used, that the dependence of performance on the experimental variables is linear. In the present development, acceptance of the use of a basic CAJQ grid opened up the possibility of conceiving a relatively simple model for the surface relating performance to CA and IQ. Thus the monotonic, horizontally ruled surface model is an attempt at a more specific statement about the response surface, at a more specific theoretical formulation. Harter’s data make the model look very reasonable for the learning-set task.

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More complete testing of the model, of course, requires that data be collected over an even wider segment of the CA, MA, I Q domain than was sampled by Harter. A perspective drawing of an extended response surface which illustrates the model is shown in Fig. 11. This figure is an all-toogenerous extrapolation of Harter’s (1965) data as suggested by the monotonic, horizontally ruled surface model. It hypothesizes what the response surface for Harter’s task might have been like if data had been collected for groups distributed over the entire CA, MA, IQ domain. The minimum possible performance score on the learning-set task (problems to criterion) was 5, and one subject achieved this score. The highest observed scores were in the 60’s. The illustrative surface sketched here flattens out in the region of high IQ and high CA. It rises steeply in the region of low IQ and low CA. That portion of the total surface which is represented by Harter’s 1965 data is marked by the four heavy lines corresponding to the data portions of the fitted iso-performance lines of Fig. 8. Had the investigator imposed some limit on testing, say at 90 problems, the surface would truncate at that level as suggested in the upper left. Note that the ruled surface model implies that improvement in performance follows the same curve as a function of the CA measure as it does as a function of the IQ measure. This is a feature of the model which has been noted earlier (Section VIII, A, 4). As is pointed out by Hill and Hunter (1966) and Mueller (1949) among

IQ

CA FIG.11. A perspective illustration of a monotonic horizontally ruled responsesurface. The surface which was fitted to Harter’s (1965) data has been liberally extended tosuggest ageneral model which spans the entire CA, IQ domain. The four straight lines fitted to the data in Fig. 8 are included here, and the bold portions of these lines represent the region over which Harter actually collected data.

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others, empirically fitted functions do not in themselves establish theory, but the character of those functions will often cast light on the dependencies involved and suggest theoretical points to be tested. Of particular interest in the present case is the CA scale which provided the empirically successful fit of model to data (Figs, 8 and 10): CA scaled as -log(19 -CA). This representation of CA parallels transformations which are occasionally met in the literature. Stephan (1931), in a correlational problem, found that the analysis of the data was considerably more informative when based on values of log( 100-percent) than when based on lodpercent). Bousfield (1934), who first developed equations to describe eating behavior in animals, found that the rate of food consumption of cats and of chickens at any moment during eating is dependent upon a simple quantity here written as (L - E), where L is the animal's limit of food consumption, the total amount he will have eaten at satiation, and E is the cumulative amount of food already eaten. Similarly, Hull (1943) described inhibitory potential as an inverse function of (B - W) where B is the physiologicallimit of work and W is the amount of work already done: inhibitory potential grows quickly as W approaches B. In the backward learning curve, learning rate is seen asvarying backward from the time of mastery as defined by the learning criterion. In the context of Bousfield's limit of food consumption and Hull's physiological limit of work, in particular, the constant 19 in (19 - CA) stands as a limit-a maturity limit or a CA limit beyond which experience might be expected to have no influence on the learning-set task. The result suggests that learning-set formation depends, in parallel fashion, upon a logarithmic measure of years remaining to maturity and upon IQ. The fact that the number 19 happens to be in the range normally thought of as marking the end of mental growth makes it doubly interesting. To summarize, we have a general model which has passed one test, but in view of the restricted crossvalidation which is available, the empirically successful constants and empirically successful scale forms on the grid should at this point only be taken as suggestive of theory and of points requiring further study. Models provide ways of organizing data, but they are also useful guides for the design and development of new experiments. See, for example, the three-dimensional graphic models proposed by Osgood (1949) and by Weiss (1972). Given the present model some obvious research questions are the following: Will the model apply for other tasks? How will the specific form of the model differ for different tasks as regards the CA scale, the IQ scale, and the value of the slope factor m which represents the orientation ofthe surface? Can learning or memory tasks be classified or grouped on the basis of the form of the fitted model? Is age from maturity a factor in other tasks as Harter's data suggest it to be for learning-set formation? It will be interesting to pursue these questions.

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X. SOME COMMENTS O N THE RESEARCH LITERATURE A. Interpreting the Role of CA

In this paper, we have dealt with CA and IQ as the naturally orthogonal variables and have emphasized CA over MA. The reader may have found this surprising in view of statements in the literature which specifically discount the role of CA in certain learning tasks (Harter, 1965; House & Zeaman, 1960; Zeaman & House, 1967). The following quotations indicate the form of the argument against CA, and apparently only Wischner( 1967) has hinted disapproval of i t a. “The partial r’s . . . show that M.A. and IQ are independently related to learning rate provided that C.A. can be ruled out as a relevant variable. Evidence can be found in two places in our data weighing against C.A. as a variable affecting learning first, the raw correlation of C.A. with error score is low (.26) and in an unexpected direction; second, holding C.A. statistically constant does not affect the correlation between M.A. and errors. With C.A. varying, M.A. correlates - .55 with errors. With C.A. fixed, M.A. correlates - .54 with errors. Such a state of affairs could come about in two ways. Either C.A. controls an entirely different portion of the learning variance than M.A., or C.A. is not a relevant variable. The latter appears more reasonable given all the data. It is also true that other investigators have not reported C.A. as a relevant variable, while at the same time reporting M.A. and IQ as correlates of visual discrimination learning. “If C.A. is not a relevant variable, the interpretation of the partial correlations of M.A. and IQ with learning becomes straightforward. With either held constant statistically, the other still correlates significantly with learning, thus establishing the independent relation of both M.A. and IQ to learning ability [House 8c Zeaman, 1960, pp. 56-57] .” b. “The near-zero correlation discovered is a critical finding since the interpretation that IQ and M A independently contribute to LS formation is based on the assumption that CA is unrelated to LS. In view of the negligible relationship obtained between LS and CA, one may conclude that variability in CA was neither a contributing nor a contaminating factor, and that interpretations based solely on IQ and MA are justifiable [Harter, 1965, p. 401 .”

In each of these passages CA is acknowledged as a confounding variable in the study, but is then inferred to be irrelevant. In both cases, thearguments about CA are based upon correlation measures. What the investigators have seemingly done is to argue about the relation of CA to performance as if their correlations of CA with performance (.26 for House andzeaman; .04 for Harter) were good estimates of population correlations. This they cannot be, because they were clearly not based on representative samples of the general population of children. The comment in (a) above that the .26 correlation between CA and error score was in the unexpected direction holds if we are thinking about the general population where error scores should go down with advancing CA, but a mapping of the CA, MA, and IQ ranges of House and Zeaman’s subject group on a CA, IQ grid suggests that this was not an unexpected value for their group. Nor does the computation

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of partial correlation coefficients permit better inferences about the general population, for these too apply of necessity only to the experimental population. The degree to which the experimental groups studied by Harter and by House and Zeaman differed from our model population (Section 11) is best indicated by the following intercorrelations for CA, MA, and IQ: (a) r M C A was .64 for Harter and - .12 for House and Zeaman as compared with + .92 for the model population (Table 11); (b) their values of r M A I Q were .03 and .73 as compared with .36 for the model population; and their values of rc--lQ were -.71 and -.69 as compared with -.01. (See also footnote 5, p. 273.) In general, the dependence of learning or other task performance on CA cannot be inferred properly from correlational information based upon nonrepresentative samples of the population. Argument about the “effects” of CA, MA, and IQ must proceed from their interdependence in the entire developmental population, and this leads us to the position that the “effect” of CA cannot be disregarded. B. Some M A Issues

Not a few experiments in the literature indicate that when a group of normal subjects is matched in MA with a group of retardates, the retardates do less well than the normals do at a learning task (e.g., Girardeau, 1959; House & Zeaman, 1958). This says, in our present jargon, that an isoperformance contour for the task in question does not overlay or follow the iso-MA line defined by the two groups on any of our CA, IQ grids. Harter’s (1965, 1967) results were like this (see Fig. 6): (a) among groups of subjects matched in MA, performance was poorer the lower the IQ; and (b) the isoperformance contours did not parallel the iso-MA lines. But there are also other experiments which have led to the conclusion of no difference between the learning performance ‘ofretardates and normals when they have been matched on MA (e.g., Ellis & Sloan, 1959). Reviewers vary in the interpretation which they place upon segments or the entirety of these data. Thus, Stevenson (1963), in summarizing the mixed findings on discrimination learning, concluded that ‘‘. . . The possibility that normal and retarded S’s of comparable mental age differ in rate of discrimination learning cannot be discarded [p. 4271” Denny (1964) observed that: “A mixture of results evolves from such studies. Many of these studies indicate that the learning differences between the normal and retarded are slight or non-existent; a few indicate superiority for the mentally retarded; and the remaining minority indicate inferior learning performance by the retarded [p. 1011.” For verbal learning, Zeaman and House (1967) recognize a dif-

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ference between MA-matched groups: “IQ and verbal learning performance are positively correlated, in both paired-associate and serial-position tasks, for subjects of equal MA [p. 2021 .” They see a similar relation applying for simple discrimination tasks and learning-set formation. Most recently, Estes ( 1970) summed up his review with some tentative conclusions, among them the suggestion that quantitative differences in rates of acquisition tend to disappear when MA is equated. Given that the literature represents a broad mix of studies, using tasks of varying character and complexity and using retardates of varying CA levels, it is clear that differences among the results of different studies could have arisen from any of several sources, among them being (a) real task differences, (b) procedural differences, (c) Type I and Type I1 errors associated with random errors in the data, and (d) MA x IQ interactions. The results of Harter’s (1965) study call our attention to the latter. In those data, retardates and normals performed equally well at MA-9, but not at MA levels 7 or 5. This is a very unique form of the MA x IQ interaction among all possible forms that it might have taken. When Fig. 6 above is reexamined the interaction is seen to be of a sort that, although the isoperformance contours did not parallel the iso-MA lines over their entire course, they did parallel the MA lines through a portion of their course, namely in a portion of the retardate range. Perhaps there are other learning and memory tasks, even many, which like Harter’s are not a “simple function” of MA over the entire CA, MA, IQ domain but which approximate a “simplc function” of MA over a portion of the domain. This would say that at least some of the differing outcomes of individual studies with MAmatched groups may have been a function of the particular part of the response surfaces which each sampled. Thus, only a more complete mapping of the response surface for each different learning task can provide the full answer to general questions concerning the equivalence or difference of MAmatched groups at that task. For any task where the response surface is of complex form on the logCA, logIQ grid, a study using two groups of subjects or even three can never be adequate to handle the question. A fair amount of theoretical debate now swings in part on aspects of this MA issue (see Ellis, 1969; Zigler, 1968). Having good response surface information on more learning and memory tasks will certainly not be without effect on this discussion, for such information should do much to clarify the particular problems which need debating. Response surface considerations suggest a way of accounting for one other finding about MA reported by House and Zeaman (1960). I n their study of visual discrimination learning in retardates, they found that the regression of the criterion on IQ and that on CA were both acceptably linear, but that the regression of the criterion on MA departed significantly

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from linearity. This general kind of result is to be expected for data analyzed in terms of raw CA, MA, and IQ measures. Consider the CA, IQ grid shown in Appendix Fig. A3. The iso-MA lines are curved on this grid. Should task performance be linearly related to CA over some range of CA values and linearly related to IQ over some range of IQ values, then the curvature of the iso-MA lines dictates that the relation of task performance to MA will be curvilinear. In general it appears that, except in the logCA, IogMA, IogIQ space, the regression of performance on MA must differ in curvilinearity from the regression of performance on either CA or IQ.

XI. T H E D E S I G N OF EXPERIMENTS O N CA, M A , A N D I Q

A. Some Shortcomings of Factorial Designs with Analysis of Variance

In the planning of experiments on task performance as related to CA, MA, and IQ, there are several shortcomings of traditional factorial designs which should be kept in mind. The first of these is that freedom in laying out a factorial design is always restricted when correlation exists between the variables included in the design. In the case of CA and IQ which are uncorrelated or orthogonal, a factorial design is always admissable and can be used to cover the entirety or any subregion of the CA, IQ domain. But the correlation of + .36 between MA and IQ over the CA range from 3 to 16 means that there is, for practical research purposes, a restricted range of available MA values at any IQ level, and a restricted range of available IQ values at any MA level. Reference to Fig. I , diagram C, or Fig. 2, diagram C, will make this clear. There is therefore a limit to the span of MA levels which can be used in a MA x IQ factorial experiment once the span of IQ levels has been decided upon, and vice versa. This restriction becomes exceedingly severe for MA x CA factorial designs. The correlation cited in Table I1 between CA and MA is + .92. If 140 and 70 are taken as practical limits for group average IQ’s, practical in terms of one’s being able to locate suitably large numbers of subjects for all groups, then possible CA x MA designs can bedeveloped only over very confined regions. Examples are: 3-4.2 years on both CA and MA, or 5-7 years on both scales, or 8- 1 1.2 years, or lO-l4years(see Fig. 2B). Thus among possible factorial designs, the MA x IQ design has practical limitations and the CA x MA design may never prove useful. The second shortcoming of traditional factorial design is that the analysis of variance, which provides the primary motivation for employing the design in the first place, is hardly ever going to be informative. Given suitable pilot

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work with a particular task, an investigator can anticipate significant main effects. H e can also anticipate interactions on several grounds. There is proper concern in the literature that interactions between CA, MA, IQ and other variables in various factorial designs can arise out of “floor” and/or “ceiling” effects occurring when the scale for measuring criterion performance is inadequate to handle the full range of proficiency levels for the different groups of subjects (e.g., Baumeister, 1967; Ellis, 1969). But with regard to the variables of CA, MA, and IQ themselves, it is possible to make a completely general statement about the occurrence of interactions among them. It is this: The only condition under which no interactions will ever be found among CA, MA, and IQ is when the response surface plotted with respect to the logCA, logIQ grid is a plane. Under all other conditions, at least one of the interactions from among CA x MA, MA x IQ, and CA x IQ will be real. We can be more specific than this. To do so, we must enumerate the different possible conditions and consider them one by one. The following statements assume that the response surface is plotted with respect to the logCA, logIQ grid, and they cover all cases where this surface is not a plane and where the indicated factorial designs span as much ofthedomain as they can. (1) If the response surface is a horizontally ruled surface of the sort shown in diagram A of Fig. 5 , where performance varies with IQ but is not alinear function of logIQ, then aCA x MA interaction must exist for any CA x MA design. This is illustrated in Fig. 12 as discussed below. (2) And (3) which follow are obvious parallels to (1). (2) If the response surface is a horizontally ruled surface of the sort shown in diagram B of Fig. 5 , where performance varies with CA but is not a linear function of logCA, then an MA x IQ interaction must exist for any MA x IQ design. (3) If the response surface is a horizontally ruled surface of the kind shown in diagram D of Fig. 5, where performance varies directly with MA but not as a linear function of logMA, than a CA x IQ interaction must exist for any CA x IQ design. (4)If the response surface is a horizontally ruled surface of the kind shown in diagram C of Fig. 5 , where performance varies similarly with both CA and IQ (see Section VIII, A, 5 ) but not as a linear function either of logCA or of logIQ, then an interaction exists for any factorial design which samples the CA, MA, IQ domain, whether it be a CA x MA, and MA x IQ, or a CA x IQ design. ( 5 ) If the response surface is not a horizontally ruled surface, but performance is an additive function of an IQ “effect” which is not a linear function of logIQ and a CA “effect” which is a linear function of IogCA, then as in (1) above a CA x MA interaction must exist for any CA x MA design. (6) If conditions are as in (5) but the I Q “effect” is a linear function of IogIQ and the CA “effect” not a linear function of logCA, then as in (2) above an MA x IQ interaction must exist for any MA x IQ design. (7) If performance is an additive function of a CA “effect” and an IQ “effect,”

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where these are not linearly related to logCA and logIQ respectively, then a CA x MA interaction exists for any CA x MA design, and a MA x IQ interaction exists for any MA x IQ design. (8) If performance is not an additive function of CA and IQ “effects” and does not follow a horizontally ruled surface with respect to the IogCA, logIQ grid, then as in (4) an interaction exists for any factorial design which samples the CA, MA, IQ domain. Figure 12 is presented to illustrate the first of these special conditions. Consider the numbers in the figure as “true” scores for 25 hypothetical groups of subjects. The grid is log, log, log. Performance varies with IQ only, but it does not vary linearly with logIQ. For any sampling of CA x IQ levels over the space, there is no CA x IQ interaction. And for any sampling of MA x IQ cells over the space there is no MA x IQ interaction. But for any CA x MA design (e.g., the groups with scores in parentheses), there is a CA x MA interaction. In view of the uniqueness of the conditions specified in ( I ) , (2), (3),(5), (6), and (7) above, it seems a safe bet that CA x MA, CA x IQ, and MA x IQ will regularly be found when one looks for them in reliable data. If then, we no longer need to inquire about the existence of interactions among CA, MA, and IQ, we should be ready to direct increasing attention to the form of the surface which relates performance to CA, MA, and IQ.

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B.

Design for Iso-Performance Contour Analysis

When we turn to plotting and analyzing response surfaces and iso-performance contours on CA, IQ grids, what are the implications of this new approach for experimental design and for data collection? Here are a few: 1. The design should involve the testing of separate groups, suitably spread out over the CA, IQ domain, rather than the testing of one large representative group (as wanted for correlational studies) which would subsequently be divided into subgroups by CA, IQ cells for analysis. The latter procedure would necessarily concentrate many more observations than needed in the midrange of IQ values and divert research time from the collection of enough cases at extreme IQ levels. Thus, controlled sampling is favored over some form of random or representative sampling. 2. Each group of subjects should be as large as is practical. The plea for adequate, reliable data is commonplace in discussions of experimental design, but it must be made with special urgency whenever empirical curve fitting is intended in the analysis of data. As Mueller (1949) puts it, “When sufficient information is available, these [curve-fitting] methods may be of value in determining the magnitudes of desired constants [p. 2211 .” And he then adds the emphasizing, negative statement: “Little is gained by employing these statistical methods of curve fitting if adequate information is not present .” There is a real difference between conducting an experiment to determine whether changes in performance are associated with changes in some variable, and conducting an experiment to determine by visual methods the form or shape of the function relating performance to that variable. In the latter case the experimenter typically needs more data, enough to make reasonably sure that he will not be devoting most of his efforts to fitting his model to what is actually “noise” in the data. For situations where a monotonic model appears reasonable, noise is particularly unfortunate if it obscures what is in fact a true monotonic response surface. There is never any fully effective way to recover from the effects of noise, and graphic methods are especially vulnerable in this respect. Hence the individual groups of subjects must not be too small. 3. In general, larger groups should be planned for those regions of the CA, IQ domain where the slope of the response surface is expected to be low. This is in the interest of improving the reliability of the iso-performance contours which cross there. Whereas in analysis of variance applications we are concerned that all performance means be equally reliable, in interpolation-for-contour operations the reliability of data points should be increased as the difference between neighboring data points decreases (see Section IX,C, 8).

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4. The number of groups (or data points) must probably be nine or more. For an effective analysis using iso-performance contours, not only must each group mean be as reliable as possible, but there must also be a satisfactory number of groups. It would appear that a minimum of nine groups of subjects is needed if one is to be assured of obtaining enough suitably independent iso-performance contours to compare for shape, slope and separation (see Section IX, C, 4-5). And the greater the number ofgroups, the more successful the mapping of the response surface will be. It can be anticipated, therefore, that experiments which would produce meaningful iso-performance contours will require upward of nine groups of subjects and an average performance measure for each group which, on the basis of prior testing, can be expected to be sufficiently reliable for a curve-fitting type of analysis. 5. Each group of subjects should be as homogeneous as possible in CA and in IQ. This assures greater accuracy of the group’s average performance score as an index of the true performance score associated with i t s m , Q point. The effect of heterogeneity is a smoothing effect: to use the average obtained performance score for a group as an estimate of the true performance score associated with itsCA,IQ point is to assume that the response surface is a plane over the CA, IQ region represented by that group. Gross heterogeneity of subjects within groups with respect to CA and IQ must therefore tend to smear out or broaden the steepest transition part of the response surface. Suggested as a seemingly good and not unrealistic set of bounds for intragroup heterogeneity are a limit of 1 year for the CA range and a limit of some 20 points for the IQ range of any group, In general, when intragroup heterogeneity cannot be avoided, it appears that “with-contour heterogeneity” (i.e., where the scatterplot of CA, IQ values for subjects in any group runs roughly in the direction of the expected iso-performance contours) is to be preferred to “across-contour heterogeneity” (where the within-scatterplots run normal to the direction of the expected contours). 6. For the purposes of plotting iso-performance contours, the IQ points for the different groups of subjects need not form any special rectangular or factorial array over the CA, IQ domain. The array can in fact be an “array-of-opportunity.” This means that subjects need not be sampled or assembled so that every particular group has a preplanned or prescribed (as one might strive for in as well as a preplanned or prescribed analysis of variance designs). As more than nine groups are introduced, the array will most certainly not be exactly rectangular or factorial in the above sense. See Fig. 13 for a hypothetical distribution of groups over the CA, IQ domain which would be effective for deriving a number of wellseparated, independent iso-performance contours. 7. Although there need be no special constraints on t h e m , Q a r r a y , the

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experimenter will wish to work with groups so located that there will be a good number of interpolated points per contour, i.e., that every contour will intersect a good number of facet edges. Two designs are likely to do this. One is a CA x IQ factorial design (or any approximation thereto). The other is a design such that the plot of t h e m , - values for the nine (or more) groups forms an array, one axis of which runs roughly parallel to the expected isoperformance contours and the other axis of which runs more generally perpendicular to the expected iso-performance contours. Until more specific guiding data become available, it is suggested from the inspection of Harter's data in Fig. 7, that when this design is followed groups be selected in terms of the expectation that the iso-performance contours will slope downward at about 60" to the right on the standardized CA, IQ grid. Figure I3 shows one such array. 8. In pilot work when performance measures are not refined or when groups of subjects are small, groups in t h e m , lQ array should be well separated in the expected across-contour direction, in order that group performance means will be well separated and a rough analysis may be made

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for well-separated contours. As precision of measure increases, a decrease in the separation of groups in the expected across-contour direction will reduce the smoothing effect of the interpolation-for-contour operation and improve information on the shape of the profile of the psychometric function. If he can select his groups, the investigator may wish to space them in terms of whatever transformed CA and IQ scales have proved informative in previous studies. On these transformed scales, of course, the CA measures will not be rectangularly distributed nor the IQ measures normally distributed. Hence the varying availability of subjects over the CA, IQ grid may be a factor in group selection and group size. From (3), (6), and (8) especially, it is clear that research for the purpose of mapping reliable iso-performance contours of the response surface can depart from familiar and formal designs. Whereas formal designs typically employ specially developed groups which have been equated in terms of the present response surface analysis nominal values f o r m , MA,or is less restrictive because the surface is plotted and fitted using the literal rQ locations of each group whatever they happen to be. Response surface studies will be more informative the broader the region of the CA, IQ domain (Fig. 3) they cover. Like Heal (1970) the present writer sees studies which cover the whole individual difference continuum as critically important. This implies ambitious designs, but they should be seriously considered. As experiments of wider scope are planned, it is clear that the investigator will be pressed to devise performance measures which will serve adequately for all groups of subjects. This is not a new problem (e.g., see Ellis, 1969), but is somewhat less serious for response surface studies than elsewhere because the method of analysis tolerates floor and ceiling effects if the scale of measure is not quite as adequate as one might wish.

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a,

XII. THE PROBLEM OF CORRELATED VARIABLES IN OTHER AREAS OF RESEARCH

We have been concerned throughout this paper with studies in which the three variables of interest, CA, MA, and IQ, are not mutually independent. It is worth noting that this problem of correlation among the so-called “independent” variables of a design is met in other research areas too. In the CA, MA, IQ case we are concerned with traits or characteristics of subjects. In laboratory studies we are concerned correspondingly with the characteristics of words, objects, the test environment, etc. Suppose an experiment in which we wish to control both word length and word frequency. These are word characteristics which are not independent in our

3 10

William E. Kappauf

language. If we would use a factorial design in our experiment, we must settle for an orthogonal subdomain of the total word-length,word-frequency domain. Just how restrictive this subdomain will be depends on the size of the word-length by word-frequency correlation, as we saw above (Section XI, A) where CA x MA factorial strategies became very restrictive because of the high CA, MA correlation. Similarly, if we would manipulate the size and weight of objects factorially, we are faced with the fact that small objects have an upper weight limit and large objects a lower one. We must therefore be content with running tests only over some orthogonal subdomain selected from the complete size-weight domain where correlation prevails. Similar design considerations apply for such paired but correlated experimental conditions as temperature and humidity, visual stimulus area and total luminous flux, and quantity of food and nutritive value. The final step to the laboratory version of the CA, MA, IQ problem comes quickly in some research areas. One experimenter may be interested in magnitude estimates of weight, not only as a function of size and weight, but of density also. Another would study learning as a function of intertrial interval and of delay-of-reward interval, but decides that he cannot overlook the interval between each reward and the beginning of the next trial. A third is involved in a visual experiment which concerns the light-dark ratio of a flickering light and the intensity of the light, and he wants also to consider the variable of flux per unit of time. In all these instances, the task of teasing out the relative importance of each of the three variables for an understanding of performance is the same as that in the CA, MA, IQ situation. The variables are not independent. We know that they are linearly or multiplicatively related, but we would still like to know how we can most parsimoniously describe performance in terms of them. Graphic analyses of the observed response surfaces, through the use of iso-performance contours, offer the key to this needed description, just as they do for the description of data from studies involving CA, MA, and IQ. XIII. SUMMARY AND CONCLUSIONS

This paper has been concerned with the general problem of evaluating and describing performance at experimental tasks as a function of CA, MA, and IQ. It endorses a graphic approach to this problem, based on a plot of performance measures on a grid which has scales for CA and for IQ as its orthogonal axes and which includes an inset family of iso-MA lines (Figs. 3, Al, A2, A3, A4). The form of the response surface defined by the performance measures is best appreciated by calculating a series of iso-per-

TASK PERFORMANCE AND CA. MA, AND IQ

31 1

formance contours (Section VII). Given these contours and given the background three-way grid which shows CA, MA, IQ and their interdependence, it is possible to see and describe the manner in which performance varies with CA, MA, and IQ. This description is free from errors which have attended correlational analyses of such data in the past because it recognizes the full extent of the developmental population (Section 11) and the exact character of the interdependencies among CA, MA, and IQ measures (Section V). This overall procedure is illustrated in a reanalysis of a set of data from Harter (1965) on learning-set formation in ninegroups of subjects varying in IQ from 70 to 130 and in MA from 5 to 9 (Section VIII, A, 1). The outcome differs considerably from the outcome of the original analysis. The foregoing procedures are defended as providing better information about the dependence of task performance on CA, MA, and IQ than correlational and analysis of variance procedures can provide. The implications of the graphic, response surface approach for the design of new experiments are discussed (Section XI).Among these the most critical is the requirement that enough groups of subjects from retardate to normals and above be tested to define the response surface and its iso-performance contours adequately. Nine or more groups seem essential. With a response surface plotted in convenient form it is possible to consider various models for that surface, models which would make for a better description and understanding of the dependence of performance on CA, MA, and IQ. The model for the response surface that is proposed here is a monotonic, horizontally ruled surface (Section VI, B). It can be tested for any set of data using curve-fitting methods (Section VI, C). Harter’s (1965) data are well described by this model, which leads to the conclusion that there was a simple trade-off between IQ and a measure of CA (log [19 - CAI) in the determination of performance at the learning-set task. Whether this model will serve equally well for other learning and memory tasks remains to be seen. Possibilities to be explored are that test parameters shift the level of the response surface but not its basic shape, that the tradeoff relation between CA and IQ will vary for different tasks, etc. Regardless of the eventual utility of the ruled surface model, this paper will have served its purpose if it helps to clarify certain of the problems in data interpretation which have arisen from the interrelations among CA, MA, and IQ, if it draws the attention of investigators to the advantages of and need for multigroup studies as opposed to the traditional two-groups study with retardates, and if it encourages the consideration of models for performance differences throughout the CA, MA, IQ domain.

3 12

William E . Kappauf APPENDIX

On this and the following pages are reproduced four CA. iQ grids which, along with the grid in Fig. 3, were prepared for use in the analyses discussed in this paper. All of these gridsapply to the CA, MA, IQ domain adopted here (CA’s from 3 to 16, IQ’s with Mean 100 andu = 16). and all are based on standardized scales of CA and IQ. Commercially available log-log, semilog, and rectangular graph papers can of course be used for plotting data and deriving iso-performance contours, but the scaling will often be inconvenient. If the reader anticipates that some of the present grids will be useful to him and would like to obtain a copy of each in a convenient size for plotting, he may address his request to the author at the Department of Psychology, Psychology Building, University of Illinois. Champaign, Illinois 6 1820. Plotting proceeds quickly using a tracing paper overlay.

IQ

CA FIG. Al. LogCA, IQ grid.

TASK PERFORMANCE A N D CA. MA, A N D IQ

FIG.A2. CA, logIQ grid.

313

314

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William E. Kappauf

d

rz

d

ri:

TASK PERFORMANCE A N D CA. MA, A N D IQ

315

ACKNOWLEDGMENT The author gratefully acknowledges the interest and help of William Gilbert, Charles Lewis, Keith Scott, and Ledyard Tucker, who critically reviewed parts of this material, and the assistance of William Love, who developed the program for generating the sampling data cited in this paper. Computer service was provided through a grant from the University Research Board. To Susan Harter goes special thanks for her cooperation in making it possible to examine her data in greater detail than journal editors allow their readers.

REFERENCES Baumeister, A. A. Problems in comparative studies of mental retardates and normals. American Journal of Mental Deficiency, 1967, 71, 869-875. Blough. D. S. Attention shifts in a maintained discrimination. Science, 1969, 166, 125-126. Bogartz, R. S., & Wackwitz, J. H. Transforming response measures to remove interactions or other sources of variance. Psychonomic Science, 1970, 19, 87-89. Bousfield, W. A. Certain quantitative aspects of chickens’ behavior toward food. American Journal of Psychology, 1934,46,456458. Box, G . E. P. The exploration and exploitation of response surfaces: some general considerations and examples. Biometrics. 1954, 10, 16-60. Box, G. E. P., & Wilson, K. B. On the experimental attainment of optimum conditions. Journul of the Royal Statistical Society, Series B (Methodological), 1951, 13, 1-45. Box, G. E. P., & Youle, P. V. The exploration and exploitation of response surfaces: an example of the link between the fitted surface and the basic mechanism of the system. Biometrics, 1955,11,287-323. Cattell, R. B. Factoranalysis. New York: Harper, 1952. Christensen, K. Isohedonic contours in the sucrose-sodium chloride area of gustatory stimulation. Journal of Comparative and Physiological Psychology, 1962, 55, 337-341. Denny, M. R. Research in learning and performance. In H. A. Stevens & R. Heber (Eds.), Mental retardation; A review of research. Chicago: University of Chicago Press, 1964. Pp. 100-142. Ellis, N. R. A behavioral research strategy in mental retardation: defense and critique. American Journal of Mental Deficiency, 1969, 73, 557-566. Ellis, N. R., & Sloan, W. Oddity learning as a function of mental age. Journalof Comparative and Physiological Psychology, 1959, 52, 228-230. Estes, W. K. Learning theory and mental development. New York Academic Press, 1970. Girardeau, F. L. The formation of discrimination learning sets in mongoloid and normal children. Journal of Comparative and Physiological Psychology. 1959,52, 566-570. Guilford, J. P. Psychometric methods. (2nd ed.) New York: McGraw-Hill. 1954. (a) Guilford, J. P. System in the relationships of affective value to frequency and intensity of auditory stimuli. American Journal of Psychology, 1954. 67, 691495. (b) Harter, S. Discrimination learning set in children as a function of IQ and MA. Journal of Experimental Child Psychology, 1965, 2, 3 1-43. Harter, S. Mental age, IQ, and motivational factors in the discrimination learning set performance of normal and retarded children. Journal of Experimental Child Psychology, 1967.5, 123-141. Haywood, H. C . Mental retardation as an extension of the developmental laboratory. American Journal of Mental Deficiency, 1970.75, 5-9.

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Heal, L. W. Research strategies and research goals in the scientific study of the mentally subnormal. American Journal of Mental Deficiency? 1970, 75, 10-15. Hill, W. J.. & Hunter, W. G. A review of response surface methodology: A literature review. Technometrics, 1966, 8, 571-590. House, B. J., & Zeaman, D. Comparison of discrimination learning in normal and defective children. Child Development, 1958. 29, 41 1 4 1 6 . House, B. J., & Zeaman, D. Visual discrimination learning and intelligence in defectives of low mental age. American Journal of Mental Deficieng, 1960, 65, 51-58. Hull, C. L. Principles of behavior. New York: Appleton, 1943. Humphreys, L. G. & Dachler. H. P. Jensen’s theory of intelligence. Journal of Educational P~ychology,1969,60,419-426. Kappauf, W. E., Burright, R. G., & DeMarco, W. Sucrose-quinine mixtures which are isohedonic for the rat. Journal of Comparative and Physiological Psychology, 1963, 56, 138-143. Lewis, D. Quantitative methods in psychology. New York: McGraw-Hill, 1960. Lindquist, E. F. Design and analysis of experiments in psychology and education. New York Houghton, 1953. Meyer, D. L. Response surface methodology in education and psychology. Journalof Experimental Education, 1963.31, 329-336. Mueller, C . Numerical transformations in the analysis of experimental data. Psychological Bulletin, 1949, 46, 198-223. Osgood, C. E. The similarity paradox in human learning: A resolution. Psychological Review, 1949,56, 132-143. Pinneau, S . R. Conventional and deviation IQs for the Stanford-Binet. Testing today, 1959, NO. 2, Pp. 4-7. Robinson, D. W., & Dadson, R.S. A re-determination of the equal loudness relations for pure tones. British Journal of Applied Physics, 1956.1, 166-181. Stanley, J. C. (Ed.) Improving experimental design and statistical analyses. Chicago: Rand McNally, 1967. (a) Stanley, J. C. Problems of equating groups in mental retardation research. Journal of Special Education, 1967, 1, 241-256. (b) Stephan, F. E. Alternative statements of percentage data in the fitting of logarithmic curves. Journal of the American Statistical Association, I93 I , 26, 5 8 6 I . Stevens, J. C., & Marks, L. E. Spatial summation and dynamics of warmth sensation. Perception & Psychophysics, 1971,9, 391-398. Stevens, S . S . (Ed.) Handbook of experimentalpsychology. New York: Wiley, 1960. Stevenson, H. W. Discrimination learning. In N. R. Ellis (Ed.), Handbook ofmentaldeficienry. New York: McGraw-Hill, 1963. Pp. 424-438. Underwood, B. J. Psychological research. New York Appleton, 1957. Weiss, J. M. Psychological factors in stress and disease. Scientific American, 1972, 226, 104-1 13. Williges, R. C., & Simon, C. W. Applying response surface methodology to problems of target acquisition. Human Factors, 1971, 13, 51 1-519. Wischner, G . J. Individual differences in retardate learning. I n R. M. Gagnt (Ed.), Learning and individual differences. Columbus: Merrill, 1967. Pp. 213-217. Young, P. T., & Trafton, C. L. Activity contour maps as related to preference in four gustatory stimulus areas of the rat. Journal 01Comparative and Physiological Psychology, 1964,sn.68-75.

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Zeaman, D.. & House, B. J. The relation of IQ and learning. In R. M. Gagnt (Ed.), Learning and individual dflerences. Columbus: Merrill, 1967. Pp. 162-212. Zigler, E. Mental retardation. In International encyclopedia of the social sciences. New York Macmillan, The Free Press, 1968. Pp. 226-247. Zigler, E. Developmental versus difference theories of mental retardation and the problem of motivation. American Journal of Mental Deficiency, 1969. 73. 536-556.

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Author Index

Numbers in italics refer to the pages on which the complete references are listed. Ackerman, L., 133, 134, 136, 141 Affleck. P. A,, 100, 141 Akesson, A,, 99,145 Allen, K. E., 86,92,93 Allen, M., 240,255 Allen, P., 83.94 Ambrose, A,, 8,9,50 Ames. L. B.. 37.52, 58, 94 Amsel, A,, 72,91,92 Anderson, R.D., 181,221,251 Appel, M. J., 105, 141 Atkinson, R.C., 151,166, 171, 184, 194, 223,243,244,250.251 Ayers, G. E., 101. 141 Azrin, N. H., 88, 94

Blishen, B. R.,32.50 Blomstrom, R.L.. 132,142 Blood, M. R., 137,144 Bloom, B., 2.50 Blough, D. S., 274,315 Boehm, J. J., 68,94 Bogartz, R. S.. 285,315 Bolanovich, 0.J., 119,141 Bortner, M., 22,50 Bousfield, W. A., 286,299,315 Bower, G. H., 179,181,186,188,189,196,198, 204,206,207,212,213,217,221,222, 243,247,251,255 Box, G. E. P.. 261,294,315 Brawley, E. R.,86.93 Brethower, 0. M., 136,141 Brewser, P., 104,141 Broadwell, M. M., 133,141 Brody, S., 58.93 101, 102,141 Brolin, 0.. Brotemarkle, R. A,, 154,167 Brown, A,, 181,202,205,251 Brown, J. M.,1 18, 145 Brown, J. S., 71,93 Brown, L., 117,118,141 Bruner, J. S., 3, 1 I, 16. 18,22,27,50 Bucklow, M.,137,141 Budde. J. F., 101,142 Burke, C. J., 186, 198,252 100,142 Burke, R. 0.. Burns, N. R.,73.78.96 Burright, R.G., 275,316 Bush, R.R., 183,185,196, 198,251,252 Butterfield, E. C., 58,65,94.223,251

Babbage, C., 126. 141 Bae, A. Y.,106,141 Bahrick, H. P., 156,167 108, 109,141 Bailey, J. 0.. Banks, M., 82,92 Baratz, J. C., 7,50 Baroff, G. S., 61, 81, 84, 96 Baumeister, A. A., 6 I , 69,70,7 I, 72,74, 76,77,78,80,81,82,84,85,92,93,94, 95,258,304,315 Bellamy, T., 118,141 Belmont, J . M., 223,251 Belmont, L., 15,33,50 Bereiter, C., 12, 19.50 Bergman, R.H., 109,146 Berkson, G., 57, 58,59,61,65,66,67,70, 74,75,76,17,78,79,89,90,93 Bernstein, B., 6,50 Birch, H. G., 15, 16,22,33,50 Bitter, J. A,. 119, 141 Blackman, L. S., 11 1, 120,141

Cahn, T. I.. 240.252 Campbell, N.. 114, 116,142 319

320 Campione, J. C., 180, 181, 184, 200, 205, 214. 219, 240,244, 252,255 Canter, R. R., 137,142 Carrington, J. A,, 132,142 Carrot, N. F., 132,142 Cattell, R. B., 1 1 50,267,315 Cegelka. W. J., 101. 142 Chaffin, J. O., 100,142 Chin-Quan,A., 134,142 Chione, J., 134, 139,142 Christensen, K..275,315 Cifelli, J., 120, 146 Clark, C. M., 58,93 Clark, G. M., 101. 102,142,147 Cleland, C. C.. 58,93 Cohen, J. S., 108.142 Cohen, M., 108,146 Cole,M.,11,16,18.22,50 Coleman, J. S., 17,50 Conant, E. H., 137,142 Corte, H. E., 87.93 Crandall, V. C., 36,50 Crandall, V. J., 36.50 Crannel1,C. U.,154,167 Gravioto, J., 15. 50 Cromwell, R. L., 36.50 Cronbach, L. J., 126,142 Crosson, J. E., 121, 125, 134,142 Crothers. E. J., 243.251 Dachler, H. P.. 261. 316 Dadson, R. S., 275,316 D’Amato, M. R., 200,204,252 Dallenbach, K. M., 154,167 Dalrymple-Alford. E. C., 154,167 Dart, F. E., 24,25,50 Das, J. P., 13, 15, 18,26,29,30,41,45.50, 51,52

Davenport, R. K., 59,65.67.74,75,77, 79.93,95 Davis, K.,132,142 Davis, K. V., 89. 90. 93 Davis, L. E., 136,142 deJung, J. E., 121,142 Delissavoy, V., 67, 93 Delp, H. A., 100,142 Demarco. W., 275,316 Denegre. J., 180. 182, 187, 215. 216, 255 Denenberg, V. H., 8, 10,51 Denny. M. R., 259,301,315 Deno, E., 125,142

Author Index Denova, C. C., 133,142 Deutsch, M., 9,51 Dickerson, D. J., 181,219,252 DiMichael, S. G., 102. 104, 108, 109,143 Distefano, M. K., 107,143 Doleshal. L. L., Jr., 101,143 Dolnick. M. M.. 99, 103, 143 Dubrow, M., 103,143 Dybad, G., 99,143 Dye, H. B., 12,53 Dyer. P. B.. 36,51 Easby-Grave, C., 150,167 Eastaugh, H., 134,142 Eimas. P. D., 185,252 Eisenberg. G.. 116. 148 Eldred, D. M., 119,143 Elkin, L., 108,143 Elley, W. B.,42,52 Ellis,N. R., 107,143, 153,167,223,228, 249,252,258,301,302,304.309,315 Engelman, J. 0.. 19.50 Escalona, S. K.,68,93 Eskridge, C. S., 101,143 Espeseth, V. K.,102,144 Estes,W. K.,186, 189, 190, 191, 192, 194, 198, 223,252. 302,315 Etienne, J., 100. 101. 143 Evans, G. W., 114. 143 Eysenck, H. J., 37,5l Fagan, J. F., 194, 255 Fangman, T. J., 100.144 Farber, B., 98,99,143 Farnham-Diggory. S., 25,51 Faust, M., 78,95 Feldstein, J. H., 194,252 Fernberger, S. W., 153,167 Fenrick, N., 117,141 Ferguson, R. G., 106,143 Ferster, C . B., 61,93 Feuerstein, R.. 10. 51 Firth, W. G . . 132. 143 Fishel, K. N., 105, 141 Fisher, M. A,, 180,210,244,252 Fitz-Gerald, F. L., 90.93 Fleishman, E. A,. 108. 1 I I. 128. 143, 146 Fleming, R. S., 86,93 Forehand, R., 61,69,71,72. 74,76,77. 80,81,82,92,93,94 Forrester, B. J., 19’51

32 1

AUTHOR INDEX

Fowler, W., 9.51 Foxx, R. M., 88.94 Franks, C. M., 112,143 Franks, V., 112,143 Freitag, G . ,77, 87.95 Fry, C., 59.95 Fry, M., 105,143 Gaona, C. E., 15.50 Gadberry, E., 117,141 Garlick, B., 115, 116,148 Gassler, L. S., 136,143 Gates,A. I., 15,51, 154,167 Gay, J., 22,50 Gerard, M.. 58. 94 Gerjuoy, I. R., 152, 157,167,168 Gilbreth, F. B., 131, 137,143 Gilbreth, L. M., 131,137,143 Girardeau, F. L., 61,%, 301,315 Click, J. A,, 22,50 Goett1er.D. R., 154, 155, 158, 159, 160, 161,167 Gold, M. W., 122,123, 125, 128,144 Gold, V. J., 77, 87.95 Goldstein, F. J., 59.95 Collin, E. S., I I , 51 Gordon, J. E., 21,53 Gorelick, J . , 106, 108, 112,147 Gray, S. W.. 19, 20,51 Green, A. H., 67.68,94 Green, P. C., 59,74,95 Greene, R. J., 83,94 Greenfield. D. B., 180,242,246,255 Greenfield, P. M., 3,22,50 Greeno, J. G., 191,254 Greenspan, E., 105,145 Greenstein, M., 100,144 Groff, G. K., 136,144 Guess. D., 58.67.77.94 Guest, R. H., 137,144 Guilford. J. P.. 154, 167. 267. 275. 315 Guinagh, B. J., 1 I , 23.51 Gulliksen, H., 183,252 Gussow, J. D., 16.50 Guthrie, E. R., 189,252

Harris, F. R., 86,92,93 Harter, S.,259,265,268,273,281,285, 287,289,291,292,298,300, 301,302, 311,315 Hawver, D. A,, 106,107,147 Haywood, H. C., 4, 10,51,258,316 Heal, L. W., 258,260,309,316 Hebb, D. O., 4,51 Heiny, R. W., 98,144 Hempel, W. E., Jr., 108,143 Hennessey, D. E.,133, 134,144 Henze, R., 101,144 Herzberg. F., 136,144 Hew, R. D., 8.51 Hill, W. J., 294,298,316 Hoats, D. L., 83,94 Holden, E. A., Jr., 152,167 Holgate, V., 22 1,2SS Hollis. J. H., 60,61, 62, 66. 69, 70, 77, 85, 86, 87, 89, 90,94 Holmes, W. G., 138,144 Honeycutt, J. M., Jr., 138,144 Hornick, A. J., 83.94 House,B. J., 122,148, 171, 179, 180, 181, 182, 183. 184,185, 186, 187,188, 189, 190,192,195,196,l98,203,205,206, 213,215,216,218,220,222,227,228, 234,238,240,241,242,243,244,245, 246,247,252,253,254,255,256,272, 300,301,302,316,317 Howe, M. A., 132,144 Huddle, D. D., 114,144 H u h , C. L., 137,144 Hull,C. L., 185, 189, 192, 195, 196, 198, 253,286,299,316 Humphreys, L. G . , 261,316 Humpstone, H. J., 154,167 Hunt, J. G., 115,144 Hunt, J . McU., 4,51 Hunter, W. G., 294,298,316 Hutt. C., 59,78,94 Hutt, S.. 59,78,94 Hyman, L. M., 180, 181, 184. 200, 240, 252, 253

Ilg, F. L., 37,52, 58.94 Hamburger, M., 10.51 Hamerlynck, L. A,, 102,144 Hamilton, J., 83,94 Harlow, H. F., 185,252 Harrell, R. F., 15,51

Jachuck, K., 29,51 Jackson, J. S., 101,143 Jagoda, H., 200,204,252 Jenkins, W. O., 156,167

3 22 Jensen,A.R.,2,4,10,11,12,15,19,26, 33,34,37,40,43.52 Johnson, S . , 117,141 Jones, F. E.,32,50 Jones, M. B.,128144 Jones, S . E., 117,141 Kagan, J., 8,52 Kappauf, W. F., 275,316 Karnes, M. B.,99,144 Karrer, R.,67.93 Kassorla, I. C., 77,87.95 Katona,G., 151,167 Katz, E., 110,144 Kaufman, M. E., 58,62,65,66, 69,70,91,

94,95 Kazdin, A., 119,144 Keiper. R.R.,59,94 Kelly, J., 133,144 Kendler, H. H.,192,198,204,207,253 Kendler, T. S., 192,198,253 Kennedy, R.J. R., 101,144 Keppel,G., 191,226,253 Kilbridge, M. 0.. 137,142 Killner, K., 238,254 Kinsinger, J., 118,145 Kirk, S.A., 99,144 Kirk, W. B.,99,144 Klaber, M. M., 58.65.94 Klaus, R.A., 19.51 Klinman, C., 181,182,224,231,232,253 Knaus, W., 120,146 Knight, M., 182,226,236,237,253 Koechert, G. A., 109,146 Kohler, W., 151,167 Kohlberg, L., 10.52 Kokaska, C. J., 101,104,145 Kolstoe, 0.P., 100, 105,145 Kounin, J., 250,253 Krathovsky, W., 36,50 Kravitz. H., 67,68,94 Krechevsky, I., 189.253 Kubie, L. S . , 58,94 Kugel, R.,99,145 Kulka, A., 59,95 Kylen,N. G., 99.145 Labov, W., 6,52 Ladas, P.G . , 110,145 Lafond, R.,116,119,134,146

Author Index Land, V.,238,254 Lashley, K. S., 189,195,253 Lawton, D., 6.52 Lenneberg, E. H., 7.52 Lerner, J. S., 106. 145 Lesser, R..68,94 Leuba, C., 58,95 Levine. A. S., 134,145 Levine, M., 186,189, 198,253 Levine, M. J., 104.145 Levison, C. A,, 72,95 Levitt, H., 58,62,65,69,70, 91 94,95 Levy, D. M., 59,77,95 Lewis, D., 275,277,316 Lewis, M., 101,145 Lindquist, E. F., 285,316 Lipton, R.C.,65,75.96 Litrownik, A,, 57,62,78.95 Lloyd, D. F., 23.52 Loban, L. N., 132,133.145 Lockard, J. S., 194,253 Locke, B.J., 83,87,92,93 Logan, 0. L., 118,145 Lorenz, K. Z., 4,52 Losty, B., 186,253 Lourie, R.S., 58,59,67,95 Lovaas, 0. I., 57,61.62,77,78,80,81, 82, 7

84,87,95 Lovejoy, E., 179,186.188, 189,192,196,

198,206,217,242,247,253 Lowden, L. M., 194,255 Lowry, S. M., 138,145 Luce. R. D., 188,243,254 Lupton, T., 136,145 Luria, A. R.,5,25,28,45,52 MacArthur. R. S., 42,52 McBane, B.,180, 182.210,232,233.248,

252,254 McCarthy, K., 157,168 McGehee. W., 133,134,145 McIntosch, W.J., 101,145 Mackay, F. A. M., 134,145 Mackiewicz, M.. 14.53 Mackintosh, N. J., 179,186,188, 189,192,

193,194,196,198,207,212,213,217, 218,221,222,242,247,254,255 MacMillan, D. L.. 155,167 Mahler, M. S., 58,95 Mann, R..57,62,78,95 Manson, W. A., 10.52

323

AUTHOR INDEX

Marangell, F., 125,145 Maris, R. S.,63,64,69,77,95 Marks, L. E., 275,316 Martin, A,, 180, 210, 243,252,254 Martin, P. R., 153,167 Mason, W. A,, 57. 58. 59, 62. 66. 70, 73. 74. 75, 77, 79, 90, 93, 95 Mathews, M. G., 101,145 Mattos, R. L., 84,95 Maynard, H. B., 138,145 Meadow, L., 105.145 Medin, D. L., 204,218,254 Mees, H., 61,83,% Meissner, A., 101,144 Menzel, E. W., Jr., 59,74,75. 79,93,95 Meyer, D. L., 294,316 Miller. J. O., 19. 51. 52 Miller, L. E., 101,145 Miller, M., 115, 148 Mocek, E., 106,145 Monge, J. P., 131, 133. 145 Morlock, D. A,, 100, 101, 143 Morrow, R. L.. 138, 145 Moseley, A., 78, 95 Mosteller, F. A,, 183, 185, 196, 198, 251, 252 Mueller, C., 277,285,297,298, 306,316 Mulhern, T., 61,70,84,85.95 Muller, V., 101,145 Murphy, J., 67, 94 Naegele, K. D., 32, 50 Neisser, U., 151,167 Nelson, N., 102,145 Nixon, R. A,, 104,145 Norman, D. A,, 223,254 Nzimande, A., 24.53 Oberly, H. S., 154,167 O’Connor, N., 30,52 Olver, R. R., 3. 22,50 O’Neil, L. P., 1 13,145 Orlando, R., 180.218,256 Om, D. E.. 26. 52 Osgood, C. E., 299,316 Overpeck, C., 116,148 Overs, R. P., 108, 109,146 Panda, T. P., 29,30.41,51,52 Parker, J. F., 111,146

Parrish, J. M., 154,167 Passman, R. H., 86,96 Pati, G. C., 132,142 Patterson, C. H., 106,146 Patterson, 0.G., 101,146 Pauling, T. P., 137,146 Pearce, E., 1 1 7,141 Pearlstone, Z., 156, 157,168 Perkins, C. C..156,168 Perlmutter, L., 117, 118,141 Peterson, L. R., 61,85,95,238,254 Peterson, R. F., 61,85,86,93,95 Petit, T. A., 132, 146 Pidgeon, D. A., 23.52 Pietrus, J. T., 133, 134,147 Pinneau. S. R., 295,316 Platt, H., 120,146 Plowden, B. 17.52 Polson, P. G., 191,254 Porter, J., 32.50 Porteus, S.D., 106,146 Postman, D. L., 156,167 Postman, L., 156,167 Pradhan, P. L., 24,25,50 Prehm, H. J., 100,146 Prieve, E. A., 133, 134,146 Prokasy, W. F., 194,254 Provence. S., 65,75,96 Psotka, J., 158,168 Rafalski, H.,14.53 Reardon, D. M., 78,95 Redkey, H., 102,146 Reese, H. W., 184,254 Restle, F., 186, 189, 198,206,212,254 Riessman, F., 9.53, 136,146 Risley, T., 61.62, 83.95 Robinson, D. W., 275,316 Rock, I., 190,254 Rogers, C. M.. 74,75.79,95 Rohmert, W., 138, 139,146 Rohwer, W. D., 37.52 Rosenthal, V.. 67. 94 Ross, L. E., 221,254 Rothstein, J. H., 106,145 Rotter, J. B., 36, 39,53 Rummler. G. A., 136,141 Rundquist, E., 101,146 Rusalem, H., 125, 126, 146 Russell, J., 86.96 Rutherford, G., 77.94

3 24 Sackowitz, P., I18,141 Saltzman, D., 238,254 Saxon, S. V., 70,75,93 Schaffer, B., 80. 81,95 Schmidt, W. H. O., 22,23,24,53 Schroeder, S. R., 57,96 Schwab, J, L., 138,145 Scimshaw, N. S.. 21,53 Scott, K. G., 123,144, 157.168. 181. 182, 213,223,235,254 Scott, M. S., 223,254 Screven, C. C., 116,119,134,146 Sengstock, W., 101, I46 Shaefer, H. H., 87,96 Sharp, D. W., 22,50 Shelton, G., 118,145 Shentoub, S., 67,96 Shepp,B. E., 180, 181, 185,195,196,197, 200,203,204,219,220,221,252.254 Shiffrin, R. M., 151.166,171,184, 194, 223,244,250,251 Shipman, V. C., 8,51 Siegel, A . W.. 181, 221,254 Silberman, C. E., 9,53 Simmons, J. Q..61.80,81,82,84, 87.95 Simon, A. J., 133,144 Simon, C. W., 294,316 Simon, H. A., 150,167 Sinick, D., 108, 109, 146 Siperstein, G. N., I 1 1, 120,141 Skeels, H. M., 12,53 Sloan, S., 136,146 Sloan, W., 107,143,301,315 Smith, P.,134,146 Snyder, W. J.. 134, 139,142 Sommarstrom, I., 99,145 Sontag, E., 118,141 Soueif, M. I., 37, 38, 39,53 Soulairac. A., 67,96 Speiser, S., 108,146 Spence,K. W., 185, 189,192,195,196, 198,206,209.2 18,255 Sperber, R. D.. 180,242,246,255 Spiker, C. C., 204,255 Spitz. R. A. 75,96, 152, 154, 155, 156, 157, 158,159,160,161.162,164, 165,167, 227.249,255 Spradlin, J. E., 61,96, 114,143 Sprague, R. L., 89,90,93 Stanley, J. C.. 258, 261.316 Stegemerten, G. J., 138,145

Author index Steinman, W. M., 115,146 Stephan, F. E.. 286,316 Stephens, L., 83,94 Stevens, E. A,, 63.96 Stevens, J. C., 275,316 Stevens, S. S., 274,316 Stevenson, H. W., 181, 221,254. 301.316 Stewart, P. A.. 137, 146 Stone, A. A., 59, % Straka, J. A., 116. 119, 134,146 Stroop, J. R., 29,53 Stroud, R. R., 138,146 Stuckey, T., 1 15,148 Stukuls, I., 182,236,237,255 Suchman, R. G., 181,202,255 Sutherland, N. S., 179, 186, 188, 189, 192, 194, 196, 198,207,212,213,217,218, 221,222,242,247,255 Tapp, J. T., 4,10,51 Tate, B. G., 61,81,84,96 Taylor, F. W., 137,147 Teplitz, Z., 67, 94 Terrace, H. S., 185,255 Thaller, C., 180, 183, 187,256 Thayer, P. W., 133, 134,145 Thomas, B., 101,102,141 Thomas, H. P.,101,147 Thor, D. H., 152,168 Thurlow, M. L., 157,168 Tobias, J., 106, 108, 109, 110, 112,147 Tolman, E. C., 192.255 Trabasso, T., 179, 181, 186, 188, 189. 196, 198, 202, 206, 212, 213, 217, 221, 222. 247, 255 Trafton, C. L., 274,316 Tredgold, A. F., 100,147 Tuggle, G., 137,147 Tulving, E., 156, 157, 158,168 Turner, S. H., 156, 168 Turnure, J. E., 157,168 Turrentine, J. L., 133, 136,147 Turrisi, F. D., 181,200,203,204,254 Umbenhaur, G. W., 106.145 Underwood, B. J., 191, 226,253, 261,316 Urbano, R. C., 157,168 Usdane, W. M., 108,147 Van Deventer, P., 117,141 Vernon, P.E.. 3, I I , 21.53

325

AUTHOR INDEX

Vygotskii. L. S.,23.53 Wackwitz, J . H., 285,315 Wade, M., 195.253 Wagner, E. E., 106, 107,147 Wagner,J. F.,219,252 Wallace, W. H., 156,168 Warner, W. L., 32,53 Warren, S . A,, 73,78,% Webreck,C.A.. 152,154,155,158, 159, 160,161,l62,167,168 Weir, K. C., 133, 136,147 Weisberg, P., 86,96 Weiss. J. M.274, 299,316 Wentorf, 0. A., 133, 134, 146 Wentworth, C., 181. 214, 219,252 Werry, J. S., 89,90,93 Whipple, G. M., 150,168 White, B. L., 8, 10, 1 I , 53 White, G. R., 134,147 White, 0. R., 121, 134,142 White, S. H., 18,53 Whitesell, W. E., 133, 134,147 Willges. R. C., 294. 316 Williams, C. E., 108, 142 Williams. C. M., 105, 141 Williams, P., 99, 147 Wilson, K. B.,261,294,315 Winters, J. J., Jr., 152,168

Wischner, G . J.. 300,316 Witryol, S. L., 194,252,255 Wolf, K. M.,75,% Wolf, M.M., 61, 83, 87, 93. 96 Wolf, R.,36, 53 Wolfensberger, W., 99,102, 103,145,147 Wolff, J. L., 184, 200,255 Wolfle, D. L., 183,252 Wolford, G., 204,207,255 Wood-Gush, D. G. M., 4,53 Woodworth, R. S., 150,151, I 6 8 Woodyard, E., 15,51 Wyckoff, L. B., 192, 195, I%, 198,206, 217,255 Youle, P. V., 261,294,315 Young, P. T. 274,316 Youngberg, C. D., 121, 134. 142 Younie, W.J., 101, 102, 125, I47 Zeaman,D., 122,148,151,168,171,180 181,182, 183, 184,185,186,187,188, 189,192, 195,196,197,198,200,203, 205,206,210,215,216,218,219,220, 222. 227. 228, 232. 234, 240, 241, 243, 244. 245, 247,252,253,254,255,256, 272. 300, 301,302,316,317 Zigler, E., 34, 53, 258, 302, 317 Zimmerman, J., 115, 116. 144, 148

Subject Index

Ability, cognitive, see under Cultural deprivation Accountability, 127-128 Age, see under Task performance Attending, in idealized memory system, 151-152 Attention-retention theory, 169-256 background for, 171 breadth of attention in, 208-217.247-248 chaining in, 175, 198-205. control processes and structural features in, 244-251 data domain of. 178-179 feedback in, 175,217-222 generalization in, 194-198 learning in, components, compounds and configurations, 183-1 84 gradual versus all-or-nothing, 189-191 mechanism of, 19I - I94 number of processes, 185-1 87 response or stimulus selection in, 179183 S-Sversus S-R,184-185 modifiability of links in, 205-208 organizational scheme for. I7 I outline of, 171-173 quantitative statement of, 173-1 74 dynamics. 176-178 statics, 174-175 response generation in, 175,242-244 retention in, 223-242 strengths of, 187-189

Blacks, cognitive competence of, 39-40 Canadian Indians, cognitive competence of, 37-39 Caste, see also Socioeconomic status influence on cognitive competence, 2931.4042 Chaining, in attention-retention theory, 175, 198-205 Cognitive competence, see under Cultural deprivation Cognitive functions, early experience and, 8-14 Concurrent problems, 228-231 Control, in attention-retention theory, 244-25 1 Correlated variables, 309-3 10 Cues conflict and combination of, 215-215 feedback and, 218-222 Cultural deprivation, 1-53 compensatory education and, 16-20 concept of, 3-5 cross-cultural approach to, 22 effect of schooling and, 22-25 influence of caste and SES on cognitive ability, 29-3 1 intelligence and, 27-28 modes of information processing, 25-27 early experience and cognitive functions and. 8-14 ethnicity, personality and cognitive competence and, 35 caste-class comparisons, 40-42 hypotheses, 35-36 multiple correlation, 42-44 tests and experiments, 36-37

Behavior(s), facilitating acquisition of. 119-123, 330-131 modifying rates of, 114-1 19, 129-130 326

SUBJECT INDEX

white-black comparisons. 39-40 white-Canadian Indian comparisons, 37-39 industrial management and, 135-136 poverty, nutrition and cognitive ability and, 14-16 socioeconomic status and, IQ and, 3 1-32 language and, 5-8 short-term memory and, 32-35 survey of normal and retarded children and their parents, 32 structure of cognitive abilities and, evidence from cross-cultural studies, 46-48 simultaneous and successive processing factors, 44-46. Digit span, redundancy in, 158-162 Dimensional preference, in attentionretention theory, 201-202 Disadvantaged, see Cultural deprivation Discrimination learning, see Attentionretention theory Drugs, in intervention studies of stereotype, 89-90 Education, see also Schools compensatory, for disadvantaged child, 16-20 early, efficacy of, 10-14 effect of, 22-25 Ethnicity, cognitive competence and, 35 caste-class comparisons, 4 0 4 2 hypotheses, 35-36 tests and experiments, 36-37 white and Canadian Indian comparisons, 37-39 white-black comparisons, 39-40 Expectancy, parental, 36 Experience, early, cognitive functions and, 8-14 Feedback, in attention-retention theory, 175,217-222 Generalization, in attention-retention theory, 194-198 Handicapped, industrial management and, 131-133

327 Icon, in idealized memory system, 152 Industrial engineering, 136-140 Industrial management, 131-1 36 Information processing, modes of, 25-27 Intelligence, see also IQ cross-cultural definition of, 27-28 Intelligence tests, cognitive competence and, 37 in vocational habilitation, 105-106 Interference, 250 proactive, 232-233 intertrial interval and, 226-227 retroactive, 236237 Interpolations, decremental effects of, 224-226 Intertrial interval, decremental effects of, 224-226 proactive interference and, 226-227 IQ. see also Intelligence socioeconomic status and, 31-32 task performance and, see Task performance Job design, 137 Job enlargement, I37 Language, socioconomic status and, 5-8 Learning, see also Schematized learning and memory system in attention-retention theory, components, compounds and configurations, 183-184 gradual versus all-or-nothing, 189-191 mechanism of, 191-194 number ofprocesses, 185-187 response or stimulus selection, 179183 S-S versus S-R,184-185 Manual dexterity tests, in vocational habilitation, 106- 108 Memory, see also Attention-retention theory idealized system, attendingin, 151-152 icon in, 152 immediate memory in, 152-156 retrieval in, 157-1 58 storage in, 156157 short-term, socioeconomic status and, 32-35

328 Methods-time measurement, 137-140 Multiple-looking, 209-21 3 Nutrition, cognitive ability and, 14-16 Overshadowing, in attention-retention theory, 2 1 6 2 1 7 Paired associates, redundancy in, 162-166 Parents, expectancies of, 36 caste-class comparisons, 41 white and Canadian Indian comparisons, 37-38 white-black comparisons, 39 personality of, 36-37 caste-class comparisons, 41 white and Canadian Indian comparisons, 38 white-black comparisons, 39 Performance, see Task performance Personality, cognitive competence and, 35 caste-class comparisons, 41 hypotheses, 35-36 multiple correlation, 4 2 4 4 parental, 36-37 tests and experiments, 36-37 white-black comparisons, 39 white-Canadian Indian comparisons, 38 Poverty, cognitive ability and, 14-16 Productivity, 136 Redundancy, in attention-retention theory, 215-216, 238-240 in digit spans, 158-162 in paired associates, 162-1 66 Rehearsal buffer, 231-237,248-249 Response, delayed, 227-228 Response generation, in attentionretention theory, 175,242-244 Response selection, 179-1 83 Response surfaces, graphic approach in analysis of, comparison with alternative procedures, 293-295 domain and grid details, 295-296 empirical curve-fitting theory, 297299 properties of iso-performance contour

Subject Index diagram, 296-297 ruled surface model and, 275-277 interpretation when model applies, 277-280 interpretation when some other grid is required, 280 plotting response surfaces, 274-275 testing the model, 277 Retention, see Attention-retention theory; Memory Retrieval, in idealized memory system, 157-1 58 Retroaction, 231-232 Reversal effect, in attention-retention theory, 202-204 Schematized learning and memory system, 149-168 attending and, 151-152 historical aspects, 149-151 icon and, 152 immediate memory, 152-156 redundancy in, in digit spans, 158-162 in paired associates, 162-166 retrieval in, 157-158 storage in, 156, 157 Schools, see also Education vocational habilitation in, 101-102 Sheltered workshops, vocational habilitation in, 102-104 Short-term memory, socioeconomic status and, 32-35 Socioeconomic status, see abo Caste influence on cognitive competence, 2931,4042 IQand,31-32 language and, 5-8 short-term memory and, 32-35 survey of normal and retarded children and their parents, 32 Stereotypy, 55-96 correlational studies of, 64-69 intervention studies in, 69 contingent stimuli, 80-89 drugs, 89-90 noncontingent stimuli and decrease in, 76-80 noncontingent stimuli and increase in, 69-76

329

SUBJECT INDEX

research strategies for, 62-64 theory, 57-61 Stimulus, in intervention studies of stereotypy, contingent, 80-89 noncontingent, 69-80 Stimulus selection, 179-1 83 Storage, in idealized memory system, 157158 Task performance, 257-3 17 correlated variables problem and, 309310 deriving and plotting iso-performance curves, 280-28 1 entering data, 281-283 interpolation and plotting, 283-284 selecting the CA, IQ grid, 281 developmental population for research on CA, MA and IQ and, 263-264 experimental design with CA, MA and IQ. factorial design with analysis of variance, 303-305 iso-performance contour analysis, 306-309 graphic approach in analysis of response surfaces, comparison with alternative procedures, 293-295 domain and grid details, 295-296 empirical curve-fitting theory, 297299 properties of iso-performance contour diagram, 296-297 Harter’s data, 264-266 analyzed using iso-performance contours, 285-290,291-293 need for cross-validation, 290-29 I historical aspects, 259-261 intercorrelations and factor space and, 266-267 implications for analysis of CA, MA and IQ effects, 274 log CA, log MA and log IQ space, 267-272

other forms of CA. M A , IQ space, 272-274 plan and organization of study, 261-262 research literature, M A issues in, 301-303 role of CA in, 300-301 response surfaces and ruled surface model and, 275-277 interpretation when model applies, 277-280 interpretation when some other grid is required, 280 plotting response surfaces, 274-275 testing the model, 277 two-dimensional maps of CA, MA, IQ domain and, 264 Tests, cognitive competence and, intelligence, 37 personality, 36-37 in vocational habilitation, intelligence, 105- I06 manual dexterity, 106-108 Training, of proacting items, 236 of retroacting items, 235-236 in vocational habilitation, 114-123, 133135 recommendations for, 129-13 1 Transfer effects, in attention-retention theory, 199-202,213-214 Vocational habilitation, 97-148 future directions of, 131-140 historical aspects, 99-100 research in, 105-123 recommendations for, 127-131 service programs in, 101-104 recommendations for, 124-127 social perspective on, 98-99 Whites, cognitive competence of, 37-40 Work sample tasks, in vocational habilitation, 108-1 12 Workshops, vocational habilitation in, 102104

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