Advances in Psychology Volume 71 Aging and Cognition I

AGING AND COGNITION Knowledge Organization and Utilization

AGING AND COGNITION Knowledge Organization and Utilization

ADVANCES IN PSYCHOLOGY 71 Editors:

G. E. STELMACH

P. A. VROON

NORTH-HOLLAND AMSTERDAM NEW YORK OXFORD TOKYO 9

AGING AND COGNITION Knowledge Organization and Utilization

Edited by

Thomas M. HESS Department of Psychology North Carolina State University No& Carolina, U.S.A.

1990

NORTH-HOLLAND AMSTERDAM NEW YORK OXFORD TOKYO

NORTH-HOLLAND ELSEVIER SCIENCE PUBLISHERS B.V. Sara Burgerhartstraat 25 P.O. Box 2 I I , 1000 AE Amsterdam, The Netherlands

Distributors for the United States and Canada: ELSEVIER SCIENCE PUBLISHING COMPANY, INC 655 Avenue of the Americas New York. N.Y. 10010, U.S.A.

ISBN: 0 444 88369 X ELSEVIER SCIENCE PUBLISHERS B.V., 1090 All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying. recording or otherwise, without the prior written permission of the publisher, Elsevier Science Publishers B.V./ Physical Sciences and Engineering Division, P.O. Box 1991, 1000 BZ Amsterdam, The Netherlands. Special regulations for readers in the U.S.A. - This publication has been registered with the Copyright Clearance Center Inc. (CCC), Salem, Massachusetts. Information can be obtained from the CCC about conditions under which photocopies of parts of this publication may be made in the U.S.A. All other copyright questions, including photocopying outside of the U.S.A., should be referred to the copyright owner, Elsevier Science Publishers B.V., unless otherwise specified. No responsibility is assumed by the Publisher for any injury and/or damage to persons or property as a matter of products liability, negligence or otherwise, or from any use or operation of any methods, products, instructions or ideas contained in the material herein. Printed in The Netherlands

TABLE OF CONTENTS Preface and Acknowledgments List of Contributors Adult Age Differences in Activity Memory: Cue and Strategy Utilization Margaret P. Nor& and Robin L. West

vii

xiii

1

The Assessment of Qualitative Age Differences in Discourse Processing Elizabeth A.L. Stine and Arthur Wingtkld

33

Aging and Schematic Influences on Memory

93

Thomas M. Hess Metamemory in Adulthood: Differentiating Knowledge, Belief, and Behavior Christopher Hertzog. Roger A. Dtwon, and David F. Hultsch

161

Cognition and Aging: A Theory of New Learning and the Use of Old Connections Donald G. MacKag and Deborah M. Burke

213

Semantic-Memory Function and Dysfunction in Alzheimer's Disease Robert D. Nebes

265

A Developmental Approach to the Study of

Visual Cognition in the Elderly Matthew J. Sharps

297

Expertise and Aging: Life in the Lab Neil Chamess and Elizabeth A. Bosman

343

Table of contents

vi

9 Levels of Knowledge Utilization and Visual

Information Processing Willlam J. Hoyer

387

1 0 Aging and Everyday Cognitive Abilities Steven w.comelius

411

11 Affect, Control, and Real World Problem

461

Solving across the Adult Lifespan fiedda Blanchard-Flelds and Cameron J. Camp Author Index

499

Subject Index

511

During the past twenty-five years, there has been a steadily growing level of interest in the study of aging effects on cognition. Much of the work in this area has proceeded within a traditional information processing framework in which the primary focus has been on examining the efficiency of basic cognitive operations. In conjunction with relatively recent developments in cognitive and developmental psychology, however, there has been an increased emphasis on examining cognitive abilities in relation to both the background knowledge possessed by the individual (and their ability to access and use this information) and the speciflc contexts of performance. Specifically. investigators have begun to pay more attention to the role that stable or developing knowledge systems play in determining performance and age differences therein. There is accumulating evidence that the nature of aging effects on cognitive performance is dependent upon the type of task-relevant knowledge that the individual brings into the testing situation. For example, task-relevant expertise in older adults has been found to be associated with high levels of performance in spite of declining levels of efficiency in more domain-general operations. Apparently, individuals can use their experience and knowledge in some cases to maintain performance and/or develop compensatory mechanisms for aging-related changes in more general ability systerns. In a related vein, other investigators have examined the speciflc contexts in which different-aged adults function. Of primary interest here is the notion that development during adulthood is associated with changes both in experiences and in the demands placed upon a n individual's cognitive system, and that age differences in performance need to be interpreted within the context of these changing demands. The efficiency of particular cognitive skills at any point in the lifespan should be directly

vlii

Preface

related to their relevance to the individual's specific life circumstances. Thus, the form of any age function relating to performance will be dependent upon the relation of the specific skill being tested to the general life contexts of the age groups included in the study. The present volume consists of eleven chapters that dfscuss theory and research relevant to the just-discussed issues, with an emphasis on the examination of adult age differences in the representation, organization, and utilization of knowledge in relation to cognitive performance. The authors are all active researchers in the field of aging, and represent a variety of theoretical perspectives relating to the study of aglng and cognitive abilities. Consistent with this diversity, the chapters deal with a wide range of cognitive skills, methodologies, and subject populations. The first four chapters explore various aspects of memory performance. Norris and West discuss research examining adult age differences in memory for activities. They argue that, in contrast to studies using more traditional laboratory tasks, examinations of activity memory have a greater degree of ecological validity due to the practical significance of this skill in everyday life. In accordance with the current focus, their review of the literature indicates that age differences in 'activity memory are moderated by the type of tasks and stimulus items used. Stine and Wingfield examine the evidence for qualitative age differences in discourse processing through the use of relative memorability analyses, in which the recall of specific text units is compared across age groups. Based upon their work, they conclude that there is little evidence for qualitative change with age in the nature of discourse representation, but that the emphasis on speciflc processes across text types may change in conjunction with age-related variations in working memory efficiency. Hess then examines age differences in the extent to which the knowledge possessed by the individual influences memory performance. Using a schema-based framework for interpreting the relevant research, he argues that aging is associated with an increase in the influence of knowledge structures on retention. This increased influence appears to be related both to a greater dependence upon

Preface

ix

the support aspects of knowledge in response to declining general skills and to older adults' greater reliance on knowledge systems in editing memory output. In the fourth chapter, Hertzog. Dixon. and Hultsch explore the concept of metamemory a s it relates to aging and memory. They challenge the utility of the traditional view of metamemory as knowledge of memory functioning. Instead, they propose that metamemory may be better conceptualized using the notion of self efficacy. in which the individual's beliefs about his or her memory abilities is a n important predictor of performance. The next three chapters deal with issues of information access and representation, broadly defined. Mackay and Burke attempt to use Node Structure Theory to explain aging effects on memory performance. They examine age differences in the ability to create and access connections within a memory representation, and propose that a single mechanism--an impairment in the priming of memory nodes--can account for a variety of the aging effects on memory observed in the literature (e.g.. the relatively greater problem that older adults have in accessing new versus old information), In the next chapter, Nebes explores the hypothesis that Alzheimer's disease is associated with a loss of information from semantic memory. He concludes that the basic contents of semantic memory are preserved in Alzheimer's patients, but that the ability to access information in this system is impaired, with successful retrieval being dependent upon the demands of the task. In Chapter Seven, Sharps examines visual cognitive abilities and aging. He advocates the use of methodologies that allow more complete understanding of the conditions under which aging effects in performance will or will not be observed. His review of the research on visual cognition suggests that age differences in the represenation and processing of visual information vary as a function of a variety of task and stimulus factors, such as degree of practice and familiarity. The next two chapters explore issues of cognitive aging in relation to expertise. Charness and Bosman examine the effects of practice in both cognitive and motor domains. They conclude that extensive practice can result in maintenance of skill with age, primarily through the development of compensatory mechanisms.

X

Preface

They also argue, however, that aging-related changes in "hardware" set limits on the extent to which older individuals can benefit from experience. Hoyer examines the interaction between aging and expertise in the realm of visual information processing. He discusses this interaction at several levels of analysis, and attempts to specify the mechanisms through which relevant prior knowledge operates to counteract aging-related impairments that occur in visual cognition. The final two chapters deal with cognitive abilities in everyday contexts. Cornelius examines people's implicit theories of academic and everyday intelligence in relation to traditional ability measures and to development in adulthood. He argues that traditional ability tests that are used in many studies of intellectual development are more reflective of academic intelligence, which is valued most in early adulthood. In contrast, everyday intelligence is seen as increasing in importance with age during adulthood. Unfortunately, this factor is not reflected in traditional ability measures, which leads to a biased picture of intellectual skill in adulthood. Blanchard-Fields and Camp further discuss issues of everyday cognitive skills in their examination of real-world problem solving. They argue that there are qualitative differences in the manner in which different-aged individuals solve problems, and that changes in problem-solving performance can be best understood by examining variations in how individuals interpret and approach problem situations. ACKNOWLEDGMENTS The completion of a project such as this one does not come about solely through the efforts of one individual. First, I would like to thank the contributors to the volume for their hard work and excellent chapters, and for their indulgence of my novice (approaching expert) editor behavior. I would also like to thank George Stelmach (Series Editor) for his assistance in the initial development of this project, and K. Michielsen at North-Holland for his patience and encouragement throughout this endeavor. In a more general frame, I gratefully acknowledge the financial support for my work provided over the years by the National Insitute on

Preface

xi

Aging. Finally, on the homefront, my sincere thanks go to Elisa Fortenberry at North Carolina State University for her expert editorial assistance In putting the fhal product together. And last, but definitely not least, I would like to thank my family-Erica, Stephanie, and Peter--for their support and understanding throughout this project.

T.M.Hess

This Page Intentionally Left Blank

LIST OF CONTRIBUTORS Fredda Blanchard-Fields, Department of Psychology, Louisiana State University, Baton Rouge, Louisiana 70803-5501, U.S.A. Elizabeth A. Bosman, Psychology Department. University of Waterloo, Waterloo, Ontario N2L 3G 1, Canada Deborah M. Burke. Department of Psychology. Pomona College, Claremont. California 9171 1. U.S.A. Cameron J. Camp, Department of Psychology. University of New Orleans, New Orleans, Louisiana 70148. U.S.A. Neil Charness, Psychology Department, University of Waterloo, Waterloo, Ontario N2L 3G 1, Canada Steven W. Cornelius, Department of Human Development and Family Studies, Cornell University, Ithaca. New York 14853, U.S.A. Roger A. Dixon, Department of Psychology, University of Victoria, Victoria. British Columbia V8W 2Y2. Canada Christopher Hertzog, School of Psychology. Georgia Institute of Technology, Atlanta, Georgia 30332-0 170. U.S.A.

Thomas M. Hess. Department of Psychology, North Carolina State University. Raleigh, North Carolina 27695-7801. U.S.A. David F. Hultsch, Department of Psychology, University of Victoria, Victoria, British Columbia V8W 2Y2, Canada William J. Hoyer, Department of Psychology, Syracuse University, Syracuse, New York 13244-2340, U.S.A.

Donald G. MacKay, Psychology Department, University of California, Los Angeles, Los Angeles, California 90024.U.S.A. Robert D. Nebes, Western Psychiatric Institute and Clinic, University of Pittsburgh, Pittsburgh, Pennsylvania 15213. U.S.A. Margaret P. Norris, Department of Psychology, University of Florida, Gainesville, Florida 3261 1, U.S.A. Matthew J. Sharps, Department of Psychology, School of Natural Sciences, California State University - Fresno, Fresno, California 93740-0011. U.S.A. Elizabeth A. L. Stine, Department of Psychology, University of Kansas, Lawrence, Kansas 66045.U.S.A. Robin L. West, Department of Psychology, University of Florida, Gainemille, Florida 3261 1, U.S.A. Arthur Wingfield, Psychology Department, Brandeis University, Waltham, Massachusetts 02254-9110,U.S.A.

Aging and Cognition. Knowledge Organization and Utilization Thomas M. Hess (Editor) Q Elsevier Science Publishers B.V. ~orth-HolfandJ.1990

CHAPTER ONE

ADULT AGE DIFFERENCES IN ACTMTY MEMORY: CUE AND STRATEGY UTILIZATION Margaret P. Nor& and Robin L. West University of Florida

SUMMARY

Activity memory represents a n important new paradigm in cognitive gerontology because it includes tasks that have ecological validity for older adults and tasks that are not a s strongly influenced by strategic processing as traditional verbal memory tasks. This review of the literature, including new data, reveals that the magnitude of age differences in activity memory is strongly influenced by the types of tasks and items that have been employed in the literature. In addition, the impact of motor and object cues, and organization are discussed, with a n emphasis on the notion that age differences may be controlled by the interaction of these task characteristics. Activity memory provides a generally familiar context for learning and it is d e c t e d by the ease of remembering item-specific information. Consistent with the traditional verbal memory literature, age Merences can be explained by the degree to which an activity memory task supports or guides strategic processing. Until recently, the typical mode of representation in memory experiments was based on verbal encoding of words. Because of this tradition, our knowledge of age differences in memory abilities is largely limited to verbal memory tasks such a s word list recall, paired associate learning, and prose recall. These tasks have laid a

2

Norrls and West

strong foundation for understanding memory processing among older adults. Recently, cognitive gerontologists have felt the need to expand task domains, particularly to include nonverbal memory tasks that might be part of the everyday activities of older adults. One fruitful new task domain, to be reviewed here, is activity memory. Activity memory research represents an important new paradigm in cognitive psychology, with considerable heuristic value. R. L. Cohen (1981)has pointed out that investigation of alternative memory tasks such as activity memory may enhance our understanding of memory processes. In order to test the generality of established laws about memory, R. L. Cohen investigated memory for actions and did not find evidence for prirnacy, active attempts to memorize, or effects due to different orienting tasks. He concluded that commonly accepted memory laws about serial position, strategies, and levels-of-processing may be unique to verbal recall (R L. Cohen, 1981). It is clear that traditional verbal memory tasks may differ in many regards from other types of memory. Biiclunan and Nflsson (1984).for instance, have argued that verbal recall and memory for activities are substantially different in terms of stimulus properties. Unlike verbal memory tasks, recall of activities involves multimodal cues because several sensory systems can be involved, including auditory, visual, tactual, gustatory, and olfactory. The investigator can manipulate many modalities of information. Traditional verbal memory tests, on the other hand, are typically unimodal, involving auditory or visual systems. Activity memory research is also valuable because traditional verbal methods of assessing memory may be an inadequate analogue of normal memory functioning and may have poor ecological validity (Neisser, 1978; Poon, 1980). Limiting investigations to verbal memory may tell us little about memory performance outside of the laboratory. Memory for activities, on the other hand, has important practical significance. Recall for what one has done, or what one needs to do is a memory demand that is frequently encountered in everyday life. For example, common memory tasks may include remembering to take medication, or recalling whether or not the bills have been paid.

Actlulty Memory

3

The ecological validity of activity memory appears to be particularly relevant to research on aging. Studies show that memory for names and faces, and memory for activities are among the most common problems identified by elderly adults (Cavanaugh, Grady, & Perlmutter, 1983; Chaffin & Herrmann. 1983). Furthermore, it has been argued that traditional laboratory recall tasks may bias results in favor of younger adults because these tasks are less familiar to older adults (Erickson, Poon, & Walsh-Sweeney. 1980: West, 1986). As a result, patterns of age differences may vary with activity memory studies (e.g., Backman & Nilsson, 1984;Padgett & Ratner, 1987).Thus,investigations with the activity memory paradigm are valuable for verifying whether older adults' secondary memory deficits are limited to verbal recall. It is evident that the investigation of activity memory has important implications both in terms of expanding our knowledge of memory processes in general, and in illuminating aging effects. This chapter will review the research on adult age differences in activity memory, to determine whether or not there is consistent evidence for secondary memory deficits in this alternative domain. The following factors will be discussed the trpes of tasks and items employed, the influence of motor and object cues, and the influence of strategic processes such as organization. The discussion focuses on the impact of these factors on adult age differences in memory. TASKS AND ITEMS A common to-be-remembered item in the activity memory

literature is a discrete one-step action. Series of such actions are often presented in lists. Many authors have investigated Subject Performed Tasks (SPTs) such a s "cross your fingers" or "put the stamp on the book" (Backman & Nilsson, 1984. 1985;R L. Cohen, 1981, 1988;Dick & Kean, 1989;Glover, Timme. Deyloff & Rogers, 1987;Helstrup, 1986, 1987;Nilsson & Cohen, 1988).and similar lists of simple actions (G. Cohen & Faulkner, 1989;Guttentag and Hunt, 1988). Another measure is memory for simulated everyday events such as preparing to go on a trip or taking a tour of a building (Norris & West, 1988;Padgett & Ratner. 1987:Ratner & Bushey. 1984). Finally, recall of cognitive activities such as serial-learning

4

Nor& and West

tasks. WAIS items, and word-picture naming tasks have been investigated by Kausler and his colleagues (Kausler & Hakami, 1983;Kausler, Lichty & Davis, 1985;Kausler, Lichty & Freund, 1985; Kausler. Lichty. Hakami 8t Freund, 1986;Kausler & Phillips, 1989; Lichty. Kausler & Martinez, 1986). Effects of Aging Adult age differences do appear to vary a s a function of type of to-be-remembered item, BBckman's research has compared recall of SPTs to comparable verbal tasks such as sentence recall (recall of the same SPT items without motor action) or word recall (recall of the same nouns as appeared in SPT items). A consistent age by item type interaction has been found such that age differences were eliminated during SPT recall, but remained in the comparable verbal tasks (BBckman, 1984, 1985;Backman 8t Nflsson, 1984, 1985). G. Cohen and Faulkner (1989)investigated age differences in the recognition of actions similar to SPTs. Their activities, however, were limited to the placement of objects (examples: "put the stamp on the book," "put the spoon next to the toothbrush) whereas most SPT studies have included a variety of actions such as "smell", "fold, "look", and so on. Consistent with the earlier SPT data, no age differences occurred in the recognition of performed activities (G.Cohen 8t Faulkner, 1989). In contrast, Guttentag and Hunt (1988)found that young adults recalled substantially more performed actions than older adults. They employed a list of SFTs in which no objects were involved (e.g.. "shake your head yes", "touch your knee"). One possible explanation for these discrepant results is that no object cues were provided. Another distinction is that this investigation involved incidental recall whereas the studies finding no age differences employed intentional recall (Bilckman, 1985;B~ckman&Nflsson. 1984,1985:G. Cohen & Faulkner. 1989). Although intentionality has not been systematically examined in SFT studies, there is consistent evidence that intentional and incidental recall of cognitive activities do not differ (e.g. Kausler & Hakami, 1983). Another possible reason for the discrepant results in this study is list length. Guttentag and Hunt (1988)used lists of 24 items,

Acttufty Memory

5

whereas Backman's studies employed lists of 12 items. Age difllerences in SPT recall have been found with longer lists (R L. Cohen, Sandler. & Schroeder. 1987). A dissimilar dependent measure in the activity memory literature is recall of simulated everyday activities. This has been referred to as "went memory" (Padgett and Ratner, 1987). Rather than discrete one-step actions like SPTs. event memory typically requires the recall of a series of related actions. The complex events that have been studied include clay making (Padgett & Ratner, 1987: Ratner & Bushey. 1984).taking a tour of a building (Padgett & Ratner, 1987).preparation for vacation travel (Norris & West, 1988). and wrapping a parcel (Hashtroudi. Johnson, & Chrosniak. in press). With event memory, the overall event includes component actions which need to be recalled. The component actions are often organizable into categories such as "get the ingredients" for the clay making (Ratner & Bushey, 1984)or "pack a toiletry bag" for the travel preparation task (Norris & West, 1988). Age differences in event memory have varied as a function of organization and motor cues, as noted in later sections of this paper. Kausler and his colleagues have investigated age differences in cognitive activities. They have used a variety of cognitive tasks including perceptual-motor, verbal learning, semantic memory, and problem-solving tasks, and also, several tests from the Reference Test for Cognitive Factors, such as, Card Rotation or Maze Tracing (Ekstrom, French, Harman, & Derrnen, 1976). Their results have consistently shown that recall of cognitive activities is age-sensitive whether tested with incidental or intentional recall (Kausler & Hakami, 1983:Kausler, Lichty. & Davis, 1985:Kausler. Lichty. & Freund, 1985;Kausler et al., 1986;Kausler & Phillips, 1989:Lichty et al.. 1986). The previous evidence, then, was inconsistent, with age difllerences varying a s a function of item type. A recent study in our laboratory investigated these item type differences by comparing recall of cognitive activities and SPTs. Slxteen items (half SPTs and half cognitive activity items) were presented to younger and older adults. Presentation time was also varied. The to-beremembered activities were all performed and then tested with verbal free recall. SpTs were significantly easier for older adults to

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and West

recall than cognitive activities (see Table 1). A significant age by item type interaction also resulted from substantially greater age differences in recall of cognitive activities than recall of SPTs (Norris & West, 1989). This item type effect could explain why age differences have been prominent in studies of cognitive activity recall (e.g., Kausler et al., 1986)but not in studies of SPT recall (e.g., BBchan, 1985). In summary. various types of measures have been employed in the activity memory literature. Age differences in recall appear to vary as a function of item type and/or task type. While there is evidence that age differences are eliminated when testing for the recall of discrete one-step actions (BAclanan, 1985;BBckman & Nilsson. 1984,1985;G. Cohen & Faulkner, 1989).recall of discrete actions may be age-sensitive under certain conditions such as when long lists are used or when object cues are not provided. Event memory shows a complex interaction between age dmerences and presentation conditions (Norris & West, 1988;Padgett & Ratner, 1987;Ratner & Bushey, 1984).and recall of cognitive activities appears to be age-sensitive. Potential Explanatory Variables What variables account for the item type differences in aging studies? A number of factors could be controlling the outcome across studies because investigators using differing item types have often varied other characteristics as well, such as list length, familiarity, presentation time, and types of cuing. One candidate is list length. Age differences appear to occur more consistently with long lists (R. L. Cohen. Sandler, & Schroeder, 1987;Guttentag & Hunt, 1988;Kausler. Lichty, & Freund. 1985;Lichty, Bressie, & Krell, 1988).The use of strategic processes such as organization, verbal association. and visual imagery may be particularly effective when memorizing long lists. Age differences in recall may be more pronounced with longer lists because young adults are able to spontaneously use these strategies. R L. Cohen and his colleagues found significant age dmerences on an SFT list with 37 items but not on one with 14 items (RL. Cohen, Sandler, & Schroeder, 1987).At the same time, their study did not

Actioity Memory

7

replicate the usual significant age by item type interaction (significant age effects for words and not SPTs) for the 14-item list (R. L. Cohen. Sandler. & Schroeder. 1987). There are no other studies including a direct manipulation of list length so it is dimcult to determine its exact influence on age-related differences. However, across studies, list length does not consistently predict outcome a s older adults have sometimes performed as well as younger adults on lists of 32 SPTs (Dick & Kean, 1989). and have performed worse than younger adults on lists including only 12 cognitive activities (Kausler & Hakami, 1983; Kausler & Phillips, 1989). Nevertheless, list length could still affect performance in interaction with presentation time or other stimulus properties, such as item familiarity. When list length is varied, total presentation time changes as well. It is possible that this time variable explains the discrepant findings in the literature. In Kausler's investigations, total presentation time ranged from 30 to 90 minutes due to activity durations of 45 seconds per activity or longer. In contrast. the SPT studies conducted in BBckman's laboratory have had subjects perform activities for 5 seconds, with a total time of only 60 seconds in most studies (e.g., Bsckman. 1985). This short presentation time would result in at least five items remaining in primary memory at the time of test (see Glanzer. 1972). The longer presentation time, on the other hand, would probably permit subjects to retain no more than one activity name in primary memory. Such presentation differences could account for the fact that investigators using short intra-item intervals have not found age dmerences in activity memory (e.g., B~ckman& Nilsson. 1984). whereas those using longer intervals have (e.g., Kausler & Hakami, 1983). Presentation time may also be a n influential factor in the nonsignificant age by item type interaction found by R L. Cohen and colleagues (R. L. Cohen, Sandler, & Schroeder, 1987). The nonsignificant interaction was due to the elimination of age differences in the word recall list, as well as the SPT list. The authors suggested that their presentation time of 3 seconds per word could account for their failure to find the age by item type interaction. Their total presentation time was therefore shorter

a

No&

and West

than the total presentation time in Backman's (e.g., B&3unan. 1985). Although the time difference does not appear to be a sizable one, Cohen's older subjects may have been able to recall more items from primary memory than BBckman's subjects, and thus performed as well on the word list a s the SFT list (R.L. Cohen. Sandler, & Schroeder, 1987). Clearly, older adults can perform better when recalling from primary memory than from secondary memory (Fozard, 1980). A study conducted recently in this laboratory addressed this question by varying presentation time (see Table 1). Eight SFTs and eight cognitive activities were presented with intra-item intervals of 8 seconds (approximately 4 minutes total time) or 45 seconds (appraximately 14 minutes total presentation time). With respect to presentation time, a significant rate by item interaction was found. The source of this interaction was a significant time effect for the SFTs and not the cognitive activities. This is consistent with an earlier finding that presentation time did not affect recall of cognitive activities (Kausler, et al., 1986). although presentation rate differences between 1.5, and 10 second intervals have not been found with SPTs (RL. Cohen, 1985). In the present study, recall of SFTs was significantly higher than recall of cognitive activities with slow presentation, whereas performance on the two item types was comparable with the more rapid presentation rate. This interaction did not vary by age group (see Table 1). This evidence indicated that the effects of presentation can vary in accordance with other experimental variables such as item type. The results of this study, as well a s the inconsistent effects of list length in the literature, suggest that these two stimulus characteristics -- list length and presentation time -- can influence recall in interaction with other factors (e.g.. item type), but may not always directly predict age Werences (see Norris 81West, 1989). Another possible explanation for discrepant results for SFTs and cognitive activities concerns the familiarity of the tasks employed. Kausler and his colleagues have suggested that age deficits may be pronounced in his research because of the artificial nature of the laboratory tests that subjects perform (Kausler. Lichty, & Davis, 1985). Similarly, Backman argues that SFTs are ecologically valid because they require encoding of meaningful

Activity Memory

9

Table 1

Mean Number of Items Recalled as a Function of Presentation Rate and Item ZlJjIe

SPT Items

Group

Cognitive Activities

Slow

Fast

Slow

Fast

Younger

6.4

5.1

5.2

4.7

Older

4.9

3.7

2.9

2.8

Both

5.5

4.4

4.0

3.7

Overall

Overall

Younger

5.7

5.0

Older

4.3

2.8

Both

5.0

3.9

objects and actions, which would facilitate processing by older adults (Bilckman & Nilsson, 1984). For example, clapping ones' hands or looking in the mirror (Biickman & Nilsson. 1984) are arguably more familiar tasks than performing the Object Assembly test or producing exemplars of a semantic category (Kausler & Hakami. 1983). In fact, in one investigation of cognitive activities, age differences appeared to be less prominent for a set of cognitive activities that included simple mathematics, a more familiar activity than letter cancellation or verbal learning (Kausler & Hakami. 1983). On the other hand, attempts to manipulate familiarity directly have not consistently shown that recall of

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Norrls and West

SPTs varies as a function of familiarity (R. L. Cohen. Peterson & Mantini-Atkinson. 1987;Helstrup, 1986, 1987;Lichty et al., 1988; Nilsson & R. L. Cohen, 1988). Also, if familiarity were controlling the outcome vis a vis age daerences. event memory studies ought

not to show age differences because the to-be-remembered events are generally very common everyday activities (e.g., Norris & West, 1988).In fact, event memory often does demonstrate age Werences (e.g., Padgett & Ratner, 1987). Overall, familiarity per se does not stand out as a consistently strong explanation for variations across studies, but it could still influence performance in interaction with other factors such as presentation time. Although more study is still warranted, it appears that neither list length, presentation time, nor familiarity can alone account for age differences that vary as a function of item type. At this point, there is no single, clear explanation in the literature. One possibility that has not yet been examined is that recall of cognitive activities places a greater demand on working memory. Subjects are required to recall a task label or description for the cognitive activities, (e.g., "incomplete words". '"word-picture naming"). In contrast, when a person recalls an SFT, they recall the specific action phrase that defined the act they performed, (e.g.. "fold your arms". "stretch your legs"). Thus, recall of cognitive activities generally requires the subject to translate the actions into an unfamiliar label or description, placing a greater demand on working memory. No such transformation is required in SPT recall because the task labels are highly farniliar phrases. When tobe-remembered items require transformation or translation into some kind of coding system, older adults are at a disadvantage (Craik. 1986). This factor needs further investigation. Finally, discrepant findings for different types of activity memory may be due to the kinds of cues that are available. Age differences were eliminated in those experiments in which both motor and visual cues were provided to the subjects, whereas the motor involvement in Kausler's cognitive tasks is mostly limited to paper and pencil activity. Motor activity appears to facilitate the processing of older adults in most of the activity memory studies (e.g, BSckman. 1985;Norris &West, 1988).Visual cues, provided by objects, may also play a role because simple objects have generally

Actlufty M e m o y

11

not been present in the studies which investigated age differences in verbal recall. It has been argued that age differences are eliminated in activity recall precisely because multimodal cues are provided (Bi-ickman, 1985:Bi-iclunan & Nilsson. 1984,1985).The importance of these two particular types of cues will now be discussed. MOTORCUES Motor Encodhg Cues The presence of motor cues is a particularly important distinction between activity memory and verbal recall. Motor cues are always present in action lists but are never presented in verbal recall tasks. The significance of motor cues for recalling SpTs has been supported by findings that older adults were not as adept a s younger adults in recalling sentence descriptions of SPTs (Bi-ickman 8t Nilsson, 1984,1985).although they did recall enacted SPTs as well as the young. Additional evidence for the importance of motor cues comes from Kausler's studies using cognitive activities in which motor action was mostly limited to using a pencil and paper. These studies found age daerences in activity recall (Kausler & Hakami, 1983;Kausler, Lichty, & Davis, 1985: Kausler, Lichty. & keund. 1985;Kausler et al., 1986: Kausler & Phillips, 1989).except in one Lichty study using a list that included 12 motor tasks only (Kausler 81Lichty. 1988). Saltz' work has also suggested that motor cues are beneficial for older adults (Saltz. 1988).His study examined age differences in the motor processing of sentences, that is, the recall of sentences in which the verbs were acted out by the subjects. For example, half of the subjects would enact "eating" when presented the sentence 'The squirrel was eating green acorns". Recall was cued with the sentence verbs. They found that age dmerences were reduced, but not eliminated, when the subjects enacted the sentence verb. This recall task falls along a continuum between activity and verbal recall tasks, because the to-be-remembered item is a sentence that includes an action, not just an action phrase. This may explain why they found only a reduction, and not an elimination of age differences in recall.

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N o r i s and West

The role of motor cues has also been investigated in the event memory literature. Age differences in recall were eliminated when subjects performed actions in preparation for a vacation (Norris & West, 1988).and when subjects went on a tour of a building (Padgett and Ratner, 1987).However, age differences in recall remained on a clay-making event (Padgett & Ratner, 1987;Ratner & Bushey, 1984). In these studies, list length varied from 24 to 42 items. There are no studies that have examined recall for events using shorter lists. It is reasonable to speculate that age differences in event recall have been magnifled due to list length. Another study presents contradictory evidence for the motor hypothesis (Lichty et al., 1986). Subjects were tested for recall of motor activities such as cutting shapes, connecting rings, and clay modeling. They were also given cognitive activities to recall such as estimation of length, incomplete words, and word search. Younger adults recalled both types of activities better than older adults, and the authors concluded that motor involvement was an unimportant predictor of the magnitude of age differences in activity memory (Lichty et al., 1986). However, later analysis revealed that the age differences in recall of both the cognitive tasks and the motor tasks could be attributed to only four of the twenty-four items (Kausler & Lichty. 1988). The importance of motor cues can also be addressed by a large body of literature which compared enacted activities to imagined. planned, or watched activities. This is an important comparison because watched or imagined actions provide many of the rich visual and kinesthetic cues present in performed actions, but they do not provide motor cues. Younger adults recall actions which they imagine performing as well as they recall actions that are actually performed (BBckman & Nilsson, 1985;Helstrup. 1986, 1987:Saltz & Donnenwerth-Nolan, 1981). In contrast, older adults may benefit from motor cues, and perform more poorly when such cues are not available. Age differences in recall have been found when subjects were given action sentences to recall with instructions to imagine themselves performing each action (BBckman & Nflsson, 1985: Guttentag & Hunt, 1988). These age differences in recall were eliminated when motor cues were provided (BBclunan & Nflsson. 1985).but not when a long list of

Activity Memory

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items without objects was used (see page 6) (Guttentag& Hunt, 1988). With event memory, there was no age by event type interaction for recall of performed as opposed to imagined events. Younger adults generally remembered more details about events of both types (Hashtroudi et al., in press). Similarly, Kausler and colleagues found that planned and performed activities were less often recognized by their older adults than their younger adults, with no interaction of age and performance condition (Kausler. Lichty, & Freund, 1985). Other investigators have compared subject-performed tasks to experimenter-performed, or watched, tasks. R L. Cohen and his colleagues have typically found no differences in recall between watched or performed activities for younger adults (R. L. Cohen, 1981, 1983;R. L. Cohen & Bean, 1983;R. L. Cohen, Peterson & Mantini-Atkinson. 1987). However, watched activities, even when embedded in a complex sequential event like making clay, are not recalled a s well by older adults a s activities that are actually performed (Norris & West, 1988;Padgett & Ratner, 1987). On the other hand, recognition testing can eliminate age differences in remembering watched actions (G. Cohen & Faulkner. 1989). Overall, these data suggest that degree of motor activity predicts age differences in free recall. Age differences in recall typically remain when actions are only watched or imagined, suggesting that the motor modality is most important for reducing age deficits. There are exceptions to this statement (see, for instance, Guttentag & Hunt, 1988;Kausler & Lichty, 1988)but the exceptions may be explained by other variables, such a s list length and item familiarity, which may interact with motor cues. When studies are placed on a continuum reflecting degree of motor involvement, those that involve complex to-be-remembered items with minimal motor activity show age differences, with the age gap decreasing a s conditions approach the other end of the continuum--simple motor actions. Motor Encoding and Retrieval One valuable aspect of research on activity memory is that it may be able to shed light on the dmerential impact of encoding and

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retrieval deficits in older adults because motor cues can be manipulated at both stages of processing. Geropsychologists have attributed age deficits on standard memory lists to encoding and retrieval deficits in the elderly (Kausler, 1982). and their differential influence has been debated (see Poon, Walsh-Sweeney, & Fozard. 1980). R. L. Cohen (1981.1983)maintains that encoding mechanisms do not appear to be important in SFT recall. His evidence for this includes the absence of rehearsal and the failure to find orienting task Werences (R L. Cohen, 1981).Kausler and his colleagues have also shown that activity recall is not affected differentially by incidental and intentional recall instructions (e.g.. Kausler & Phillips, 1989). Kausler has concluded that activity memory is independent of rehearsal which occurs during encoding. Hence, the age decline in recall of cognitive activities has been attributed to a retrieval deficit in the elderly (Kausler, 1985). In contrast, Backman and Nilsson (1984, 1985) have emphasized the importance of encoding. An encoding deficit in the elderly is implied in their proposal that older adults are able to compensate for their memory deficits in SPT recall tasks because SPTs provide rich multimodal cues for individuals, thus removing the requirement for the subjects to generate such cues for themselves. The improvement from non-guided memory tasks (e.g., word recall) to guided memory tasks (e.g., SPT recall) may be less pronounced for younger adults because they are able to spontaneously recode sentences, words or imagined actions to other modalities by carrying out organization, imagery, and verbal mediation. Older adults are not able to spontaneously perform these strategic operations, and require the multimodal information in SPTs to support their recall (Backman & Nilsson, 1985). By virtue of the fact that verbal free recall is used in all conditions, most SPT studies do not reveal the role that retrieval could play as the source of older adults' difficulties. Thus, explanations have focused on the fact that SFTs permit older adults to compensate for their strategic encoding deficits. One method which is used to address the encoding versus retrieval issue is to employ recognition tests. In this case, the recognition findings are not definitive because age difllerences occur

Actfufty Memory

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in recognition of performed activities sometimes (Kausler, Lichty & Freund. 1985).but not always (G. Cohen & Faulkner. 1989). In

general, however, ceiling effects confound studies of activity recognition (Kausler & Lichty. 1988). In most of the extant literature, motor cues were provided only during encoding (BBckman, 1985:BBckman & Nilsson. 1984,1985; R. L. Cohen. 1981). That is, the items were presented with motor cues by having the subjects perform the tasks as the experimenter read the items. Recall, however, was a verbal description of the tasks. This procedure does not allow for an investigation of the influence of motor cues during retrieval. The designs employed by Norris and West (1988)and Salk (1988)manipulated motor cues during both encoding and retrieval to study the impact of motoric processing in both phases of memory. These task conditions were compared: a) verbal encoding/verbal retrieval, b) verbal encoding/motor retrieval, c) motor encoding/verbal retrieval, and d) motor encoding/motor retrieval. In both studies, the presence of motor cues during retrieval did not eliminate age differences. In contrast, age dnerences were reduced in the motor encoding/verbal retrieval condition (Norris and West, 1988). These data are consistent with the findings in SPT studies because motor encoding/verbal retrieval is the typical SPT condition (e.g., BBckman & Nilsson. 1985). This pattern was also seen in a study comparing children and young adults in sentence recall. Motor enactment at input improved recall for both groups. In contrast. motor enactment during retrieval did not significantly benefit either age group (Salk & Dixon, 19821. General conclusions about the age-related impact of motoric cues await further investigation. In particular, there is a need for more studies varying motor cues at both encoding and retrieval with different item types. Research with cognitive activities has shown clearly that retrieval operations are important in understanding age differences in activity memory (Kausler. 1985). Others have argued that motor encoding facilitates older adults' recall of SPTs (e.g.. B~ckman.1984).When motor cues at encoding and retrieval are manipulated, it appears that motor encoding/verbal retrieval is the condition least likely to show age differences. At this point, then, there is insufficient evidence to

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argue that motor cues will always improve older adults' performance. Older adults may perform well on SpTs because of the combined effect of using motor encoding with verbal retrieval on highly familiar, simple actions. Together, these conditions may provide the supportive guidance required for older adults to perform well (Perlmutter & Mitchell, 1982). OBJECTCUES The use of external objects is another important distinction between traditional verbal recall and activity recall. Activity memory studies have typically used lists in which some items required the use of objects (e.g. smell the soap) and some items did not (e.g. yawn). In contrast, traditional verbal lists do not include objects. It is possible that older adults' memory performance is improved on activity memory tasks because the objects seen during encoding provide visual cues. Research with younger adults has addressed this issue. Some studies have compared recall of SpTs with objects to recall of SPTs which were mimed, that is, objects were imagined but were not present. The findings are mixed, with symbolic performance leading to recall that is sometimes worse and sometimes equivalent to SPTs with objects (Helstrup. 1986. 1987). Several studies have investigated whether motor cues alone or the combination of motor and visual cues are important in activity recall. The recall of SPTs with objects present was compared to the recall of SPTs without objects. No differences in recall were found in some studies (BWcman & Nilsson, 1984;R. L. Cohen, 1988;R L. Cohen, Peterson. & Mantini-AtMnson. 1987, Experiment 1). although in one case, items without objects yielded better recall than those with objects (R L. Cohen, Peterson, & Mantini-Atkfnson, 1987,Experiment 2). Furthermore, in one study, recall probabilities were calculated separately for the action component and the object component of the SpTs; the results showed that a high recall probability for the action component was more predictive of item recall than a high recall probability for the object component (R. L. Cohen. Peterson, & Mantini-Atkinson. 1987). These results suggest that the motor cues are the critical variable in SPT recall. However, these data

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17

were collapsed over age groups, and therefore do not address the question of whether object cues are important in eliminating age differences in SFT recall. In order to test whether object cues alone will eliminate age differences in recall, young and old adults were tested for recall of SFTs and sentences with objects present (BAckman, 1985). The young adults recalled both types of stimuli equally well, whereas the older adults recalled SPTs better than sentences with objects present. B2kkman (1985) concluded that the presence of objects during encoding plays a minor role with respect to the lack of age differences in SFT recall and that the essential task properties for eliminating age differences were the motor cues provided by the performance of the task items. However, it is just as likely that the combined effect of visual and motor cues was important for accurate SFT recall, as no condition provided motor cues without any objects. A recent study in our laboratory investigated the influence of object cues in SFT recall, Older and younger adults were given action lists to recall with the presence or absence of visual and organizational cues. The following four lists were presented under two conditions (verbal encoding/verbal retrieval or motor encoding/verbal retrieval): a) organized list with objects present (categories included actions with office, kitchen, toiletry, and sewing items). b) unorganized list with objects present, c) organized list without objects (categories included hand, feet, torso, and mouth actions), and d) unorganized list without objects. Both age groups performed significantly better with objects than without objects, but the age by object cue interaction did not approach significance, suggesting that the visual cues provided by objects are not important in eliminating age differences in SPT recall. However, object cues did interact significantly with condition (verbal versus motor encoding) and with list organization (see Table 2). These interactions were due to the greater impact of objects when other cues--motor encoding cues and list organization--were not present. In summary, those studies which have tested young and middleaged adults have produced contradictory results. Some have found no dif€erence in recall between those items which use objects and

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Table 2 Mean Number of Items Recalled as a Function of Test Condition. Obfect Cues, and Organization Verbal Condition Organized Group Younger Older Both

Unorganized

Object

No Object

Object

No Object

10.0 8.2 9.1

9.9 7.4 8.6

10.8 7.8 9.3

9.0 5.9 7.4

Overall

Overall

9.9 7.7 8.8

9.9 6.8 8.3

Younger Older Both

SPT Condition

Organized Group Younger Older Both

Younger Older Both

Object No Object 11.5 9.0 10.2

11.6 10.0 10.8

Unorganized Object 12.1

9.5 10.8

No Object

11.4 8.4 9.9

Overall

Overall

11.5 9.5 10.5

11.7 8.9 10.3

Activity Memory

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those that do not. Others have found that object cues sometimes facilitate and sometimes impair recall. Although the elimination of age differences in SFT recall can not be attributed to the provision of object cues, there is evidence to suggest that the presence of objects has other important interactive effects. Object cues improve recall in the absence of other cues, but not when other cues are present. There are two important implications from this cue interaction. First, it suggests that the visual cues provided by objects are less powerful relative to motor and organizational cues. It is possible that object cues do not consistently eliminate age Merences in recall because they are less robust. Second, previous findings on the impact of object cues may be inconsistent because the effects of cuing interact with other test variables. In terns of the aging literature, there is evidence that object cues alone are not sufficient to eliminate age differences in activity recall. Our recent data also show that object cues are not influential in eliminating age differences in SIT recall even when combined with motor and organizational cues. These findings indicate that, overall, motoric processing is the more important variable for eliminating age deficits in recall. STRATEGIC PROCESSING IN ACTIVITY MEMORY

In addition to the influence of visual and motor cues, there has been considerable investigation of the impact of strategic processing on activity recall. It is possible that activity memory, unlike verbal memory, is recalled without the benefit of strategic processing. Verbal recall is thought to be strongly influenced by strategies. Thus,verbal recall favors younger adults who are able to spontaneously use organization, visual imagery, verbal association, etc. It has been argued that age differences in SFT recall are eliminated because SPT recall is nonstrategic (R. L. Cohen, 1983,1984). Several pieces of evidence have been cited to support the notion that SPT recall is nonstrategic or automatic: a) subjects report no attempt to memorize during SPT presentation (RL. Cohen. 1981).b) young children, older adults, and educable mentally retarded adults, who presumably have strategy deficits, are not penalized in

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tests of SPT recall (Backman, 1985;Backman & Nilsson, 1984, 1985;R. L. Cohen & Bean, 1983;R. L. Cohen & Stewart, 1982).c) a levels-of-processing effect has not been found in SPT recall (R. L. Cohen, 1981). d) SPT recall was less impaired than word recall under divided attention conditions (R. L. Cohen. 1988;Bilckman, Nilsson, & Chalom, 1986).and e) practice effects are minimal (Kausler & Lichty, 1988). The strategic processes that are most studied in the activity literature are rehearsal and organization. There is agreement that primacy effects are not seen in SPT recall (Backman & Nilsson, 1984,1985;R L.Cohen. 1981. 1983).This isviewed as evidence that SPT recall does not rely on rehearsal strategies (Rundus & Atkinson, 1970;Atkinson & Shiffrin, 1971). An exception to this, however, comes from evidence that primacy effects in SPT recall are seen when serial recall is tested rather than free recall (Helstrup. 1987). This suggests that subjects can be induced to use rehearsal for SPT memory, although they may not spontaneously do so. There is also evidence that cognitive activities, like SPTs. are encoded without rehearsal. Kausler and his colleagues have consistently found that incidental recall was as proficient as intentional memory for cognitive activities. This also provides definitive evidence that activity recall is independent of rehearsal (Kausler & Lichty, 1988). The use of organization in activity memory has also been investigated. Evidence for the use of organization has cast doubt on the notion that SPT recall is nonstrategic in all respects. Among young adult subjects, it has been found that nonorganizable lists cause greater impairment in SPT recall than in sentence recall (Backman et al.. 1986).Backman and Nilsson (1984,1985)suggest that the multidimensional task properties of SPTs enhance the detection of superordinate categories for older adults and this may account for the lack of age differences in SPT recall. However, if this hypothesis were correct, the age by task interaction found on overall performance should also be found on measures of organization, and that was not the case in two studies (Backman & Nilsson. 1984, 1985). Although SPTs were organized to a greater extent than verbal tasks, providing evidence that SPTs are not

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entirely nonstrategic, the elimination of age differences could not be attributed to the use of organization by the older adult group. A study that examined memory for cognitive and motor activities (Lichty et al., 1986) also did not find a relationship between organization and recall. Although they found no age differences in the use of organization. the younger adults recalled more of the activities than the older adults (Lichty et al.. 1986). However, in this study and the ones mentioned above, only two superordinate categories were included. With only two categories, the potential for organization was necessarily limited, which may account for no association between organization and aging in these studies. The role of organization has also been studied in our laboratory. Older and younger adults were given four SFT lists to recall, two lists that could be organized into four semantic categories and two that could not be organized systematically. (Organizability was also crossed with the presence of visual cues-see Table 2). There were main effects for age and for organization. Also, a significant age by organization interaction resulted from the older adults benefitting more from the organizational cues than younger adults. Organization has also been examined with event memory. When motor cues were varied during encoding and retrieval, younger adults made greater use of organization than older adults in all conditions except the one condition--motor encoding/verbal retrieval--in which no age differences in recall occurred (Norris & West, 1988). In contrast to previously mentioned studies (Bi4ckman & Nilsson, 1984. 1985; Lichty et al.. 19861, this list included seven superordinate categories. It is possible that the relationship between organization and recall is more evident when the lists employed are highly organizable. Another event memory study had mixed results. Padgett and Ratner (1987) found no age differences in recall of the component actions in a tour-taking event, but the young recalled more than the old on a clay-making event. Both events were presented in a n organized structure, however, the items in the clay-making event also were presented in a logically sequential order. The authors interpreted this a s evidence that the younger adults benefitted more

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from the logical relationships inherent in the clay-making event (Padgett & Ratner, 1987). At the same time, there were no age differences in the recall of the superordinate category actions for both events, suggesting that the organized structure of the to-beremembered items was retained by the older group as well a s the young (Padgett & Ratner, 1987:Ratner & Bushey, 1984). In summary, there is evidence to suggest that activity recall is nonstrategic with respect to rehearsal. This suggests that age differences in activity recall may be eliminated, in part, because the types of strategic processing employed by younger adults in wordlearning tasks are less meaningful when learning activities. On the other hand, memory for actions is apparently not all together different from memory for verbal material. This is demonstrated by the evidence that categorical organization can enhance recall of activities. Organization appears to have a greater influence on performance when the organizational structure is more prominent. It appears that subjects can be induced to use organization in activity recall when the material is highly organizable and that age differences in recall may be eliminated under these conditions. CONCLUSIONS Although it has been commonly accepted that older adults perform more poorly on memory tasks than younger adults, activity memory studies reinforce the notion that age-related memory declines may not be pervasive. A review of the literature revealed that the magnitude of age differences in activity recall is influenced by motor and organizational cues, but apparently not by object cues. The motor cues provided during encoding typically eliminated the age deficit in SFT and event recall, although this finding did not extend to cognitive activities in which the motor cues were limited largely to manipulating paper and pencil. Further evidence for the importance of motor cues came from studies that demonstrated that younger adults consistently recalled watched and imagined activities as well as performed activities, whereas older adults recalled more performed activities than watched or imagined ones. In addition, motor cues at encoding may be more important in

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23

eliminating age differences than motor cues at retrieval (this conclusion is made with caution, however, due to limited data). It is important to recognize that the influence of motor cues on age differences does not stand in isolation. The effectiveness of motor cues does not depend on visual cues. At the same time, motor cues may be especially effective when an organizational structure is provided by the to-be-remembered items. In spite of consistent evidence favoring the notion that motor cues facilitate recall by older adults, motor cues do interact with other variables. Therefore, the benefits of motor cuing for older adults may be lost when other test conditions, such as lengthy presentation times, long lists, or unfamiliar task labels. favor young adults. Item type effects appear to have a strong impact on age differences in activity recall. The earlier discussion of item type focused on three domains -- SPTs. event memory, and cognitive activities. The importance of item type in predicting the magnitude of age differences in activity recall is further demonstrated by individual item analyses conducted by Kausler and his colleagues (Kausler & Lichty, 1988). They found that the magnitude of the age differences varied substantially from item to item, regardless of whether the tasks were cognitive or motor in nature. In fact, observed age differences in the recall of twelve motor and twelve cognitive tasks were due to sizable age dmerences on only four of these twenty-four items (Kausler & Lichty. 1988). The age differences were not significant on the remaining items, and on several items, the older adults recalled more than the younger adults. The authors further point out that some activities were substantially more memorable than others. regardless of age. These individual item differences have rarely been examined although one study found that item recall probabilities were not correlated with rated familiarity or vividness (R. L. Cohen, Peterson, & Mantini-Atkinson, 1987). Individual action items vary along numerous dimensions, in spite of many similarities between the different task types (see Kausler & Lichty, 1988). The importance of these dimensions of difference is not yet fully understood. Even within the tasks categorized as SFTs, there is considerable variation among items on many potentially influential factors: number and kind of body

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movements required, presence of objects, use of isolated a s opposed to repetitive motions, number and kind of mental operations required. familiarity of the to-be-performed activities, and so forth. More systematic analyses of such item characteristics are needed. The existing literature, reviewed here, has explored only a few factors that may influence patterns of age differences. Models for understanding the activity memory data have focused both on encoding and retrieval processes. Our conceptualization combines the models of others with an overall emphasis on contextual issues. The contextual model proposes that retention depends not only on current cognitive processes, but also on the context in which information was learned. According to that model, recall will improve when the to-be-remembered information is presented within a meaningful general context (Hultsch & Deutsch. 1981). There is evidence to suggest that age differences in recall are eliminated when familiar materials are used within a familiar context (Botwinick & Storandt, 1980: Hultsch & Dixon, 1983: Poon & Fozard, 1978). Hence. age differences in SPT recall may be eliminated, in part, because the actions to be recalled can be associated with meaningful everyday settings. In addition. simple motor actions may elicit related contextual information that is distinctive to specific items. making those more memorable. This item-specific information is likely to be processed by older adults. and hence, to improve their level of recall. There is evidence to suggest that successful memorizing by older adults is particularly dependent on the provision (by the experimenter) of item-specific cues that are well integrated with the to-be-remembered items (Burke & Light, 1981). Older adults are thought to be deficient in their spontaneous use of strategies such as rehearsal, organization, and association (Poon, 1985)that would result in memory traces including such cues. Thus, older adults' recall memory is enhanced when the task properties provide integrated item-specific information (e.g., Park, Smith, Morrell, Puglisi. & Dudley, 1987). Consistent with this interpretation. age differences do not occur in activity recall when the task conditions provide subjects with multimodal cues, but remain when the task requires subject-generated strategies. Activity memory tasks that

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25

provide motor, visual and/or organizational cues, can be viewed a s guided memory tasks. Individuals are induced to attend to and register cues on such tasks [B~ckman& Nilsson, 1985).and such tasks are less likely to result in age differences in memory performance (Craik. 1986). A similar model has been proposed by Kausler and his colleagues (Kausler & Lichty. 1988). They suggest that information processing requirements are reduced for the encoding of activities. They argue that the activation or initiation of an action sequence automatically creates a memory trace. Their model suggests that there is information automatically processed during the performance of an activity. Hence, when older adults perform the activity they process information that is otherwise not processed during unguided memory tasks. The automatically-encoded information improves the level of activity recall for older adults. At the same time, the model of Kausler and his colleagues suggests that retrieval of activities remains effortful [Kausler & Lichty, 1988). One aspect of their model is particularly intriguing. Retrieval remains effortful because the context-specific information processed at encoding is not necessarily available at retrieval. Hence, age differences in recall may exist. despite encoding of item-specific information, because older adults may not be as efncient as younger adults in the effortful retrieval of that item-specific information (Kausler & Lichty, 1988). DiMerences in retrievability of such detail may vary as a function of item type. and hence, account for the age differences in recall. These notions about retrieval also fit the evidence concerning object cues. Performance may be better without objects when kinesthetic cues (e.g.. moving an arm) processed at encoding are associated with environmental cues (one's arm) that are also available at retrieval. As a n addendum to their model, action familiarity could enter in as an influential factor. When an activity is highly familiar, the regeneration of cues at retrieval may proceed more easily for older adults. When items are less familiar (that is, the general context is one of performing an unfamiliar action), item-specific information that could enhance recall may be less likely to be processed by older adults and/or may be less readily available to the older adult at retrieval. This hypothesis has not had sufficient study.

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Can it be said that older adults' secondary memory deficits are limited to verbal recall tasks? Even though the pattern of age changes in activity memory has not always conformed to that observed with verbal recall, the evidence thus far does not support such a strong statement. It is important to note that studies of activity memory have often validated earlier evidence obtained with more traditional paradigms. For instance. age differences in memory are less apparent when older subjects are induced to use organizational strategies while learning verbal materials (Hultsch & Deutsch, 1981). This finding is essentially replicated in the activity memory literature. List length effects can occur with SPTs (RL. Cohen, Sandler, & Schroeder. 1987) a s well as with word recall. Changes in stimulus characteristics -- bimodal presentation of sentences (Biickman, 1986) or use of a meaningful encoding context with spatial infomation (Waddell & Rogoff, 1981) have provided supportive guidance for the information processing of older adults and permitted them to compensate for encoding deficits, just as the multimodal properties of SpTs provide supportive guidance for compensation in a similar manner (Backman, 1984). Age differences in activity memory performance appear to vary a s a function of primary and secondary memory demands. just a s they do with word recall (Fozard, 1980). Traditional verbal recall studies consistently demonstrate that older adults perform worse than younger adults when the test conditions do not provide adequate cues (Perlmutter & Mitchell, 1982). and the activity memory literature also demonstrates the value of cuing for older adults. At the same time, activity memory research provides u s with a paradigm to expand our understanding of memory and aging. The relevant stimulus properties are not the same for word recall and activity recall. Activity memory studies have provided new data on the influence of multimodal cues: the investigation of modality cues is an important area of research which the traditional verbal recall literature cannot readily address. Activity memory also represents a task which is not influenced in the same way as verbal recall is influenced by strategic processing. In addition, activity memory research has valuable practical significance since memory for activities has been identified as a common problem for elderly

--

Activity Memory

27

adults. Thus, it is especially useful for the study of memory and aging. Investigations of activity memory may continue to shed new light on age-related changes in cognitive processing. ACKNOWLEDGMENTS

This work was supported by a grant from the National Institute of

Mental Health (MH09542)and a grant from the National Institute on Aging (AGO6014). REFERENCES

Atkinson. R. C.. & Shiffi-in. R. M. (1971).The control of short-term memory. S c i e n t f l American. 224,82-90. Backman. L. (1984).Age differences In memory performance: Rules and exceptions. Unpublished doctoral dissertation. University of Umea, Sweden. B~ckman,L. (1985).Further evidence for the lack of adult age differences on free recall of subject-performed tasks: The importance of motor action. Human Learning,4,79-88. B ~ c h a nL., (1986). Adult age differences in cross-model recoding and mental tempo, and older adults' utilization of compensatory task conditions. Experimental Aging Research 12, 135-140. Backman, L., & Nilsson. L-G. (1984).Aging effects in free recall: An exception to the rule. Human Learning. 3,53-70. BBckman, L., & Nilsson. L-G. (1985).Prerequisites for lack of age differences in memory performance. Experimental Aging Research 11.67-73. B~ckmanL., Nilsson, L-G.. & Chalom, D. (1986).New evidence on the nature of encoding action events. Memory & Cognitioa 14. 339-34.6. Botwinick, J., & Storandt. M. (1980).Recall and recognition of old information in relation to age and sex. Journal of Gerontology. 35.70-76. Burke, D.M., & Light, L. L. (1981).Memory and aging: The role of retrieval processes. Psychological Bulletin, 90. 5 13-546. Cavanaugh, J. C., Grady, J. G., & Perlmutter, M. (1983).Forgetting and use of memory aids in 20- to 70-year olds' everyday life. International Journal of Aging and Human Development. 17. 113-122. Chaffin. R., & Herrmann. D. J. (1983). Self reports of memory abilities by old and young adults. Humn Learning, 2,17-28.

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and West

Cohen, G.,& Faulkner. D. (1989).Age differences in source forgetting: Effects on reality monitoring and on eyewitness testimony. Psychology and Aging. 4, 1-8. Cohen, R. L. (1981). On the generality of some memory laws. Scandanavian Journal of Psychology, 22, 267-281. Cohen. R. L. (1983).The effect of encoding variables on the free recall of words and action events. Memay & Cqgnition, 6. 575582. Cohen. R L. (1984).Individual differences in event memoqy: A case for nonstrategic factors. Memory & Cognition, 12. 633-641. Cohen, R L. (1985).On the generality ofthe laws of memory. In L.G. Nilsson & T. Archer (Eds.). Perspectives on learning and memory (pp. 247-277).Hfflsdale, NJ: Erlbaum. Cohen, R. L. (1988). Metamemory for words and enacted instructions: Predicting which items will be recalled. Memory & Cognition. 16.452-460. Cohen, R. L., & Bean, G. (1983).Memory in educable mentally retarded adults: Deficit in subject or experimenter? Intelligence. 7.287-298. Cohen, R. L.. Petersen. M.. & Mantini-Atkinson, T. (1987). Interevent differences in event memory: Why are some events more recallable than others? Memory & Cognition, 15, 109118. Cohen, R. L., Sandler. S. P.. & Schroeder, K. (1987).Aging and memory for words and action events: Effects of item repetition and list length. Psychology and Aging, 2,280-285. Cohen, R L.. & Stewart, M. (1982). How to avoid developmental effects in free recall. Scandanavfan Journal of Psychology. 23. 9-16. Craik, F. I. M. (1986).A functional account of age differences in memory. In F. Klix & H. Hagendorf (Eds.),Human memory and cognitive capabilities: Mechanisms and performances (pp. 409422). North-Holland: Elsevier Science Publ. Dick, M. B., & Kean, M. C. (1989).Memory for action events in Alzheimer-type dementia: Further evidence of an encoding failure. Brain and Cognition 9,71-87. Ekstrom, B. R., French, J. W.. Harman, H. H., & Deman. H. (1976). Manual for kit offactor-referenced cognitive tests. Princeton, NJ: Educational Testing Service. Erickson. R. C., Poon, L. W.. & Walsh-Sweeney, L. (1980).Clinical memory testing of the elderly. In L. W.Poon, J. L. Fozard, L. S. Cermak, D. Arenberg, & L. W. Thompson (Eds.), New dfrections in memory and aging: Proceedings of the George A. Talland Memorial Conference (pp.379-402).Hillsdale, NJ: Erlbaum .

Actfulty Memory

29

Fozard, J. L. (1980). The time for remembering. In L. W. Poon (Ed.), Aging in the 1980s (pp. 273-290). Washington, DC: Amerlcan Psychological Association. Glanzer, M. (1972). Storage mechanisms in recall. In G.H. Bower (Ed.). The psychology of learning and motivation Wol. 5. pp. 67193). New York Academic Press. Glover, J. A., TLmme. V.. Deyloff. D., & Rogers, M. (1987). Memory Journal of Educational for student-performed tasks. P ~ y ~ h o l o g79.445-452. y, Guttentag. R E.. & Hunt, R. R (1988). Adult age differences in memory for imagined and performed actions. Journal of Gerontology: Psychological Sciences. 43. 107-108. Hashtroudi. S..Johnson, M. K., & Chrosniak. L. D. (in press). Aging and qualitative characteristics of memories for perceived and imagined complex events. Psychology and Aging. Helstrup, T. (1986). Separate memory laws for recall of performed acts? Scandinavian Journal of Psychology. 27. 1-29. Helstrup. T. (1987). One, two. or three memories? A problemsolving approach to memory for performed acts. A c t a PSyChOlOgica. 66. 37-68. Hultsch. D. F. (1969). Adult age differences in the organization of free recall. Developmental Psychology. 1, 673-678. Hultsch, D. F.,& Deutsch, F. (1981). Adult development and aging: A lge span perspective. New York: McGraw-Hill. Hultsch, D. F., & Dixon. R. A. (1983). The role of pre-experimental knowledge in text processing in adulthood. Experimental Aging Research 9. 17-22. Kausler, D. H. (1982). Experimental psychology and human aging. New York: John Wiley. Kausler. D, H. (1985). Episodic memory: Memorizing performance. In N . Charness (Ed.), Aging and human performance (pp. 101141). Chichester, England: Wiley. Kausler. D. H.. & Hakami, M. K. (1983). Memory for activities: Adult age differences and intentionality. Developmental P~y~hOlogy, 19.889-894. Kausler, D. H.. & Lichty. W. (1988). Memory for activities: Rehearsal-independence and aging. In M. L. Howe & C. J. Brainerd (Eds.), Cognitive development in adulthood (pp. 93131). New York Springer-Verlag. Kausler. D. H.. Lichty, W., & Davis, R. T. (1985). Temporal memory for performed activities: Intentionality and adult age differences. Developmental Psychology, 21. 1132-1138.

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Kausler. D. H., Lichty, W.. & Freund, J. S. (1985). Adult age Werences in recognition memory and frequency judgments for planned versus performed activities. Developmental P ~ y c h o w21,647-654. , Kausler, D. H., Lichty, W., Hakarni. M. K.. & Freund. J. S. (1986). Activity duration and adult age differences in memory for activity performance, Journal of Gerontology, 1 , 80-8 1. Kausler, D. H., & Phillips, P. L. (1989). Instructional variation and adult age differences in activity memory, Experimental Aging Research, 14, 195-199. Lichty, W., Bressie, S., & Krell, R (1988). When a fork is not a fork Recall of performed activities a s a function of age, generation and bizarreness. In M. M. Gruneberg, P. E. Morris, & R N. Sykes (Eds.). Practical aspects of memory: Current research and bsues, [vol. 2, pp. 506-511). Toronto: John Wiley & Sons. Lichty. W.,Kausler, D. H., & Martinez, D. R. (1986). Adult age differences in memory for motor versus cognitive activities. ExperimentalAging Research. 12.227-230. Neisser. U. (1978). Memory: What are the important questions? In M. M. Gruneberg, P. E. Morris. & R. N. Sykes (Eds.), Practical aspects ofmemoy (pp. 3-24). London: Academic Press. Nilsson, L-G., & Cohen, R L. (19881. Enrichment and generation in the recall of enacted and non-enacted instructions. In M. M. Gruneberg, P. E. Morris,& R N. Sykes (Eds.),Pmcticd aspects of memory: Current research and issues. (Vol. 1, pp. 427-432). Toronto: John Wiley & Sons. Norris, M. P., & West, R L. (1988, August). Age dinerences in activity memory. Paper presented at the meeting of the American Psychological Association, Atlanta. Norris. M. P., & West, R. L. (1989. July). When do older adults recall perjiormed actions as well as younger adults? Paper presented at the Conference on Action Memory, Toronto. Padgett. R J.. & Ratner, H.H. (1987). Older and younger adults' memory for structured and unstructured events. Eqerimental Aging Research. 13,133-139. Park D. C.. Smith, A. D., Morrell. R W..Puglisi, J. T., &Dudley, W. N. (1987, May). Eflects ofperceptual and semantic contextual integrations ofpicture memory in the elderly. Paper presented at the Cognitive Aging Conference, Atlanta. Perlmutter. M., & Mitchell, D. B. (1982). The appearance and disappearance of age differences in adult memory. In F. I. M. Craik & S . Trehub (Eds.),Aging and cognitiueprocesses (pp. 127144). New York Plenum Press.

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Poon, L. W. (1980).A systems approach for the assessment and treatment of memory problems. In J. M. Ferguson & C. B. Taylor (Eds.). The comprehensive handbook of behavioral medlclne (Vol. 1, pp. 191-212).New York Spectrum. Poon. L. W. (1985). Differences in human memory with aging: Nature, causes, and clinical implications. In J. E. Birren 81K. W. Schaie (Eds.). Handbook ofthe psychology ofugfng (2nd ed.. pp. 427-462).New York Van Nostrand Reinhold. Poon, L. W..& Fozard, J. L. (1978). Speed of retrieval from longterm memory in relation to age, familiarity, and datedness of information. Journal of Gerontology, 33. 71 1-717. Poon, L. W.. Walsh-Sweeney, L., & Fozard, J. L. (1980).Memory skill training for the elderly: Salient issues on the use of imagery mnemonics. In L. W. Poon. J. L. Fozard, L. S.Cemak, D. Arenberg. & L. W. Thompson (Eds.), New directions in memory and aging: Proceedings of the George A. Talland Memortal Confeence (pp. 461-484).Hfflsdale. NJ: Erlbaum. Ratner, H. H.. & Bushey. N. (1984,August). Adults’ event recall: Putting memory in context. Paper presented at the meeting of the American Psychological Association. Toronto. Rundus. D.. & Atkinson, R. C. (1970).Rehearsal processes in free recall: A procedure for direct observation. Journal of Verbal Learning and Verbal Behavior, 9, 99-105. Saltz. E. (1988).The role of motoric enactment (m-processing) in memory for words and sentences. In M. M. Gruneberg, P. E. Morris, & R. N. Sykes (Eds.). Practfcal aspects of memory: Current research and tssues (Vol. 1. pp. 408-414).Toronto: John Wiley & Sons. Saltz, E., & Dixon. D. (1982).Let’s pretend: The role of motoric imagery in memory for sentences and words. Journal of Experimental Child Psychology. 3 4 , 77-92. Salk, E., & Donnenwerth-Nolan, S. (1981).Does motoric imagery facilitate memory for sentences: A selective interference test. Journal of Verbal Learning and Verbal Behavior. 20.322-332. Waddell. K. J., & Rogoff, B. (1981).Effect of contextual organization on spatial memory of middle-aged and older women. Developmental Psychology. 17, 878-885. West, R. L. (1986).Everyday memory and aging. Developmental Neuropsychology, 2.323-344.

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Aging and Cognition: Knowledge Organization and Utilization

Thomas M . Hess (Editor) 0Else~k Sden~eP L c b U ~ h e rB.V. ~ North-HOllandl. 1990

CHAPTERTWO

THE ASSESSMENT OF QUALITATIVE AGE DIFFERENCES IN DISCOURSE PROCESSING Elizabeth A. L. S t h e and Arthur Wingfield Brandeis University

SUMMARY It is generally the case that older adults remember less from what they read and listen to than do their younger counterparts. The question remains open, however, as to whether these quantitative age differences are also accompanied by qualitative differences. We address this problem in two parts. First, the issue of whether younger and older adults remember different kinds of information is considered by reviewing data on age Werences in the levels eft”ect (the tendency for gist information to show a higher probability of recall than detail) as well a s by examining results from relative memorability analyses (in which the probabilities of recall of individual text units by young and old are directly compared). Second, the issue of whether younger and older adults depend on different sorts of contextual or linguistic cues, or rely on different processing strategies in understanding and remembering discourse is considered by examining evidence for four different hypotheses of qualitative age differences in discourse processing. It is argued that while the qualitative structure of language processing mechanisms is preserved across age, working memory limitations that accompany advanced age may in themselves result in a qualitatively different balance of these processes, or they may necessitate that certain processes take precedence in later adulthood.

34

StineandWinQpeld

Quantitative memory declines in later adulthood are welldocumented (cf. Burke & Light, 1981). even when the to-beremembered materials are a s ecologically valid a s spoken and written discourse (e.g., Cohen, 1988; Stine. Wingfield. & Poon. 1989). There remains considerable controversy, however, as to whether these quantitative declines are accompanied by qualitative changes as well. In other words, older adults frequently remember less, but do they remember different19 Our goal here will be to explore this question, by suggesting how one might go about answering it, as well as a by providing a current position on the basis of extant data. QUANTITATIVE VERSUS QUALITATIVE AGE DWFERENCES By way of defining the research problem, we begin by first considering what is meant (perhaps, not so obviously) by the contrast between a quantitative and a qualitative difference. According to Webster's New World Dfctionary, to quantify is 'Yo determine or express the [amount] of; [to] measure," and to qualify is "to describe by giving the [characteristic elements, attributes] or characteristics of." Conceptually then, a quantitative difference is a difTerence in amount, whereas a qualitative difference is a Werence in kind. It would be misleading, however, to assume that a qualitative analysis precludes the use of quantitative measurement (to the contrary, we promise to use numbers extravagantly). Consider the importance of measurement in assessing the quality of an empirlcal object or a theoretical system. If we assume that the quality of a n entity may be expressed as a collection of features (e.g., Dersky, 1977),each one having some scale of measurement, then we may express this quality as a vector of quantities corresponding to the feature set. Minimally, such a vector of featural measures would consist of zeroes (i.e., "feature is absent") and ones (i.e.. "feature is present"). So we could say that two things are qualitatively different if one contained one or more features which the other did not, or in other words, if the patterns of zeroes and ones in their feature vectors were different. Such a pattern might emerge if we were to model the cognitive processing for a given task as a collection of processing mechanisms.

Suppose, for example, that we could represent the task of remembering a list of words a s (ITEM ENCODING, INTENTEM CHUNKING, CHUNK RETRIEVAL, ITEM RETRIEVAL). If we presented a list of apparently unrelated words (e.g.. frog, grass, train, bell. .I to two groups of subjects, giving the Experimental Group an organizational orienting task (e.g.. to categorize the list into things that are green, things that make noise, etc.) that we did not give to the Control Group, we would find that the Experlmental Group would remember more words than the Control Group (cf. Einstein h Hunt, 1980, Experiment 2). We might attribute this recall Merence to qualitative differences in processing. in which the processing of the Experimental Group consists of all four processing components (and hence, represented a s ( 1 . 1 , l . l ) ) and the processing of the Control group consists of only two of the four he., (1.0.0.1)). At a slightly more sophisticated level, the values in the feature vector could express how much of a feature were present. For example, we could introduce a second Experimental Group who received the organizational cues, but who were also subject to some condition (e.g.. sleep deprivation) which adversely affected all processes equally. We might represent the efficiency of their processing operations as (.8,.8,.8,.8), So this group would differ quantitatively but not qualitatively from the first Experimental Group. Thus, we could say that two things are qualitatively different if one contained relatively more or less of a feature than another, or in other words. if the values of their feature vectors were not scalar multiples of one another. So for example, in our organization experiment, the Control Group was probably engaging in some kind of (subjective) organizational processing, so w e might more accurately model their processing operations as something like (1*.2,.2,1). The point here is that questions about quality are inevitably reducible to questions about measurable quantities. This, by no means, trivializes our original goal of exploring qualitative age differences, but rather facilitates it. This will be our approach in untangling the different meanings of "qualitative age differences." It seems to u s that one of two things is typically intended by asking whether there are qualititative age differences in discourse

36

StlneandWiq@ld

memory. First, we could be asking about the extent to which younger and older adults remember the same kinds of information. In this case, the elements of our feature vectors would represent particular pieces of information (e.g.. propositions or story nodes), or particular kinds of information (e.g., main points or minor details), and our task would be to compare the feature vectors of young and old. This is an empirical issue. If we choose to classify these items by type, this classification may be theory-driven, but having done this, whether or not the recall protocols of younger and older adults contain the same kinds of information is simply an empirical fact. The existence of qualitative dnerences in recall may or may not co-occur with quantitative Merences. For example, it may be that even though older adults remember less quantitatively, their qualitative recall could be virtually indistinguishable from that of younger adults. That is. older adults remember less, but the deficit may be distributed equally among different kinds of information contained in the text. On the other hand, it may be that the quantitative memory declines in later adulthood are accompanied by the absence of a particular type of information in the recall protocol. A second intent of the question of qualitative age differences in discourse processing could be whether younger and older adults differ in the way they go about processing discourse. In other words, do older adults rely on different sorts of linguistic information or utilize alternative processing strategies? This is a very different question from the first. In this case, the elements of the feature vectors of young and old are cognitive processes. This contrasts with the first case in which the feature vectors contained empirical text units: here the features being compared are theoretical entities. So for example, in our word memory experiment, assuming we represent the processing of younger adults as (1~1.1.1). we might represent the hypothesis that older adults are only 80% as effective at item retrieval but otherwise as emcient as young by (1,1,1,0.8). Like the issue of quality of recall, however, the issue of quality of processing is also distinct from the issue of quantitative age difference. For example, it may be that even though older adults

Qualitative Age Dlffeences

37

remember less, the processing mechanisms in comprehending and remembering discourse may be qualitatively the same, just uniformly slower or less reliable. On the other hand, it could be that quantitative memory decline goes hand in hand with a change in the way information is processed, as would be the case, for example, if age declines in auditory or visual acuity induce a greater reliance on top-down contextual processes. To further c l a m the issues at hand, we might also point out that these two different approaches to the question of qualitative age differences in discourse memory are distinct. For instance, one might observe qualitatively similar performance between young and old, but qualitatively different processing mechanisms. In fact, Salthouse (1984) has discussed the value of a research strategy, "molar equivalence - molecular decomposition." which takes advantage of this principle. As Salthouse (1984) found among expert typists, it may be found in some cases in discourse processing that age-related qualitative change in cognitive mechanism enables qualitatively similar performance. That is. limitations in one part of the processing architecture may be overcome by the older adult who is able to develop m e r e n t ways of using that processing architecture. One corollary to this principle is that one might observe qualitatively different recall performance between young and old accompanied by qualitatively similar processing mechanisms, which could be the case if the older adult did not develop alternative processing strategies to overcome processing limitations. Thus, the existence of qualitative age differences in the empirical arena does not in itself entail the existence of qualitative age difTerences in process. This is not to say that qualitative age differences in process are inaccessible to study. As we will show, interpretation of age daerences in performance in terms of process depends upon one's model of the cognitive system. Our goal in this chapter will be to tackle these two distinct questions. First, we consider whether younger and older adults tend to remember the same kinds of information from prose. While we begin by treating this as the strictly empirical question that it is, we will be able to interpret these data in terms of modem discourse theory. Having done this, we will, in the subsequent section, consider whether younger and older adults process discourse

38

smandwingfleki

differently by entertaining four alternative hypotheses for qualitative age dnerences in processing mechanism. DO OLDER ADULTS REMEMBER DIFFERENT INFORMATION?

For the most part, the question of whether younger and older adults remember different information from discourse has been addressed by exaznining whether there is differential recall of major and minor points of a text across age. Consider the three conceivable answers to this question. The first is often the last bastion of hope for the optimist facing a literature replete with quantitative age declines: perhaps older adults remember less information, but maybe what they are forgetting is simply the trivial detail, while retaining the more important elements reflecting the gist of the discourse. This would be good news indeed, suggesting a functional adaptation to memory loss. On the other hand, the bad news of quantitative age declines could be worse: in addition to older adults remembering less information, they might be unable or less able to discriminate between the important and the trivial, producing a recall protocol with a disproportionate amount of trivial detail. A third possibility is that younger and older adults would show similar distributions of major and minor points in their recall. It is generally the case that a reader or listener is more likely to remember the more important, "higher level" points from a passage than the "lower level'' detail. This leuets effect has been found through various operationalizations of level of importance, including formal prose analysis systems as well a s experimenter or subject ratings. When applied to questions of adult age differences. the issue becomes whether older adults show a sharper discrimination between higher and lower level information than do younger adults (i.e., an "increased levels effect"), a decreased discrimination between higher and lower level information (i.e,, a "decreased levels effect"), or a pattern similar to that found for the young (i.e.. the "same levels effect"). Table 1 summarizes a number of studies which have examined this issue. Immediately apparent are the striking diversity of findings, which cannot be easily accounted for in terms of variability in prose or subject characteristics or by the way text units were analyzed. While some studies have reported

Qualitatiw Age Di@kences

39

that older adults show the same recall advantage for main ideas over detail as younger adults do, others have found that older adults are relatively better at remembering the main ideas, and still others have reported that older adults are relatively more likely to recall lower-level details. We reiterate that "relatively" is a key word here, since both younger and older adults are more likely to remember the major points of a text over the rninor detail, suggesting that both young and old to some extent organize the text, or show some appreciation of text structure. This is an important point. We know of no research at all suggesting that healthy older adults do not discriminate between major and minor points. Thus, the question is one of degree: to what extent do older adults differentiate between the more and less important elements in their recall protocols relative to their younger counterparts? To this point in the argument in discussing whether younger and older adults remember different kinds of information. we have not yet attempted to distinguish clearly between the discrimination among item types in the recall protocols and the cognitive processes underlying this discrimination. This will be addressed in the next two sections. The Discrimination among Text Elements Because we want to isolate the phenomenon before developing a theoretical interpretation, we will first adopt a purely empirical approach in discussing the discrimination among text elements in discourse. In keeping with the traditional empirical definition of discrimination, that "[aln organism is said to discrfmfnate between two stimuli when it behaves differently in the presence of each" (Reynolds, 1975, p. 45), we could say: A dlscrfmfnatfonis made between two text elements when one is remembered and the other is not. We explicitly do not intend for discrimination to refer to an active. effortful choice among units. We, of course, do not necessarily deny the existence of such processes, but to simplify our present discussion, we will use the term discrimination only in its empirical sense. A sensible working hypothesis is that a discrimination among text units occurs when these units are

Table 1 Summary of Studies Testingfor Age X Units Interaction ~~

Passage Characteristics #/

?Lpe

word Length

Modality

Units Analysis System

Subjects

Age X Units Interaction?

Constraining Condition?

Increased levels e&t for 0

...when Ss were instructed

Decreased levels e&t for 0

...when Ss were instxucted

Byrd (1985): 12aa

A

m

Listened: oral recall

Kintsch

25 Y (1826 yrs); 25 0 (64-70 yrs); matched on Mill Hill

to give verbatim recall

to Summarize

&hen (1 979): 1 N

"300

Constituent Listened facts (A 120 vd; ("S " v oral recall

40Y (1829yrs); 400 (65-95yrs); high and low educ'l

~ m z E z * * ] on lwelgrpsmatched WAIS Vac

Same levels effect for Y and 0

Decreased l m l s effect for 0

...when Y and 0 were lower in educational level

36 Y (20-39yrs); 36 M (40-57yrs):

Increased levels effect for 0

...WhenY and owere high

36&(EEoT$erbal grpsmatchedon Voc KFlu-

Decreased levels effect for 0 in vocabulary level

...when Y and 0 were lower

[y=O for highverbal;

OcY for low verbal) Dimn, Hultsch, Simon, & von Eye

6Ex

W3

M

written

...whenY and 0 were high

in educational level

(1984): Kintsch

recall

in vocabulary level

Table 1 (continued) ~~

~

Passage Characteristics #/

Type

word Length

Modality

Units Analysis System

Subjects

Age X Units Interaction?

Constraining Condition?

Decreased levels effect h r 0 & M

...but due to dflemms in

Same units effects for Y and 0

...regardless of recall

D h n , Simon, Notoak, & Hultsch (1 982): 5 Ex

"180

Reador listened; written

Kintsch

d

Ha~-ker,H&y. 4Ex

"400

& Walsh (I 982): Study

Read; oral vs. written

d

30 Y (18-32yrs): 30 M (34-56yr~); 300 (60-81yrs): matched on Voc KFRT

variability,not means

I:

Kintsch 38 Y (18-24yrs); (kinds of 32 0 (66-79 p) propositions)

modality

Hcuker, Hartley. & Walsh (1 9821: Study 2:

4Ex

"400

Read

Kintsch

24 Y (18-26yrs): students; E%276yrs1; on Shipley-Hartford Y crawl scrace

0

high

dump seat

-----> sump deat

2

moderate

tool carts

-----> cool tarts

4.5'

low

Intended

Error

Note: Distance represents the number of connections intervening between a node activated in error and the first uncommitted node that it conjointly primes. The arrow stands for "was misproduced as". The asterisk indicates an ambiguity with respect to level (see text for explanation).

cool tarts in the sentence, 'They were moving tool carts down the assembly line", an uncommitted or novel proposition node becomes primed because the speaker is unlikely to have a committed node representing the proposition, "They were moving cool tarts down the assembly line." Thus, the priming on this uncommitted node will be extremely weak because about four other committed nodes intervene between the nodes activated in error (again the nodes representing /s/ and /d/) and the uncommitted node at the proposition level, s o that this error is very likely to pass undetected. As noted in Table 3, however, the level of the uncommitted node is ambiguous in this example: if the speaker lacks a committed node for the phrase, cool tarts, then commitment of a novel phrase node rather than a novel propositional node is called for.

Cognition and Aging

257

The New Prediciton: Age and the Detection of Speech Errors From the Strength-of-Priming condition and the examples above it is clear that probability of error detection is directly related to strength of priming. This means that a deficit in the transmission of priming will reduce the probability of error detection. This means that, all other factors being equal, errors will be detected with higher probability in young than in older adults under the Transmission Deficit hypothesis. CONCLUSIONS Although we have applied the NST and the Transmission Deficit hypothesis to only a few cognitive aging phenomena in the present paper, the theory cuts across paradigm-specific boundaries and seems applicable to a wide range of tasks, some of which are new or relatively unexplored within the field of cognitive aging, for example, time-compressed speech perception. Moreover, we have only spelled out some of the predictions that follow from the theory: there are others. For example, the NST predicts that effects of ambiguity on errors induced by delayed auditory feedback (see MacKay, in press) should decline with age, and so should "perception without awareness" or subliminal perception effects (see MacKay. 1990) and the verbal transformation effect (see MacKay, 1987). At this stage, however, testing or even spelling out all of these novel predicitons may not be as important as addressing some of the other goals underlying development of a theory: to organize and integrate the existing literature in the research traditions of the field, and to establish priorities for future research within those traditions (see Salthouse, 1988). ACKNOWLEDGMENTS The authors thank Donald Kausler. Thomas Hess and two anonymous reviewers for helpful comments on earlier versions of this paper, and Nancy Woolf for providing neurophysiological references bearing on the Transmission Deficit hypothesis. Portions of this chapter were presented at the Cognitive Aging Conference in Atlanta, April, 1988. Support for this research was

258

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provided in part by grant number AGO2452 from the National Institute on Aging. REFERENCES Anderson, J. R. (1983). A spreading activation theory of memory. Journal of Verbal Learning and Verbal Behaulor, 22, 261-295. Aston-Jones, G., Rogers, J., Shaver, R D., Dinan, T. G., & Moss, D. E. (1985). Age-impaired impulse flow from nucleus basalis to cortex. Nature, 318,462-464. Balota, D. A., & Duchek, J. M. (1988). Age-related differences in lexical access, spreading activation, and simple pronunciation. P~y~hology and Aging, 3, 84-93. Birren, J. E. (1965). Age changes in speed of behavior: Its central nature and physiological correlates. In A.T. Welford & J. E. Birren (Eds.), Behaulor, aging and the nervous system (pp. 191216). Springfield. IL: Charles C. Thomas. Bowles, N. L.. Obler, L. K., & Poon. L. W. (1989). Aging and word retrieval: Naturalistic. clinical and laboratory data. In L. W. Poon. D. C. Rubin & B. A. Wilson (Eds.), Everyday cognition in adulthood and late lge. Cambridge: Cambridge University Press. Bowles, N. L., & Poon, L. W. (1985). Aging and retrieval of words in semantic memory. Journal of Gerontology. 40, 71-77. Burke, D. M., & Harrold, R. M. (1988). Automatic and effortful semantic processes in old age: Experimental and naturalistic y approaches. In L.L. Light & D.M Burke (Eds.),Language, m and aging (pp.100- 116). New York Cambridge University Press. Burke, D. M. & Light, L. L. (1981). Memory and aging: The role of retrieval processes. Psychologtcal Bulletin, 90, 5 13-546. Burke, D. M.. White, H., & Diaz, D. L. (1987). Semantic priming in young and older adults: Evidence for age constancy in automatic and attentional processes. Journal of Experimental Psychology: Human Perception and Perfonnunce, 13, 79-88. Burke, D. M., Worthley, J. S. & MacKay, D. G. (1989). On the ttp of the tongue: Why do wordjhding impatrments increase with age? Manuscript submitted for publication. Burke, D. M., & Yee. P. L. (1984). Semantic priming during sentence processing by young and older adults. Developmental Psychology, 20,903-910. Cerella, J., & Fozard, J. L. (1984). Lexical access and age. Deuelopmental Psychology, 20,235-243.

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Graf,P., & Schacter. D. L. (1985). Implicit and explicit memory for new associations in normal and amnesic subjects. Joumal of Experimental Psychology: Learnfng Memory and Cognitton. 1 1. 501-518. Hess, T. M. (1984). Effects of semantically related and unrelated contexts on recognition memory of different -aged adults. Journal of Gerontology, 39,444-45 1. Hess, T. M., & Higgins, J. N. (1983).Context utilization in young and old adults. Journal of Gerontology, 38, 65-71. Horn, J. L. (1982). The aging of human abilities. In B. Wolman (Ed.), Handbook of developmental psychology (pp. 847-870). Englewood ClifTs. NJ: Prentice-Hall. Horn, J. L., & Cattell, R. B. (1966). Age differences in primary mental ability factors. Journal of Gerontology, 21, 2 10-220. Howard, D. V. (1983). The effect of aging and degree of association on the semantic priming of lexical decisions. Experimental Aging Research, 9,145-151. Howard, D. V. (1988a). Aging and memory activation: The priming of semantic and episodic memories. In L.L. Light & D.M Burke (Eds.), Language, memory and aging. (pp.77-99). New York: Cambridge University Press. Howard, D. V. (1988b). Implicit and explicit assessment of cognitive aging. In M. L. Howe & C. J. Brainerd (Eds.), Cognitive Development in Adulthood: Progress in cognfttve development research (pp.3-37). New York Springer-Verlag. Howard, D. V., Heisey, J. G.,& Shaw, R. J. (1986). Aging and the priming of newly learned associations. Developmental P~ychol~gy, 22, 78-85. Howard, D. V., Lasaga, M. I., & McAndrews, M.P. (1980). Semantic activation during memory encoding across the adult lifespan. Journal of Gerontology,35, 884-890. Howard, D. V., McAndrews, M. P., & Lasaga, M. I. (1981). Semantic priming of lextcal decisions in young and old adults. Journal of G ~ ~ ~ n t o l36, o g707-7 ~ , 14. Howard, D. V., Shaw, R S.,& Heisey, J. G.(1986).Aging and the time course of semantic activation. Journal of Gerontology, 41, 195203. Huttenlocher, J., & Kubicek, L. F. (1983).The source of relatedness effects on naming latency. Journal of Experimental PSyCholOgy, 9, 486-496. Jones, G. V. (1985). Deep dyslexia, imageability, and ease of prediction. Brain and Language, 24, 1- 19.

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Aging and Cognition. Knowledge Organization and Utilization

Thomas M . Hess (Editor) 0 Elsevier Science Publishers B.V. (North-HolZandl, 1990

CHAPTER SIX

SEMANTIC-MEMORY FUNCTION AND DYSFUNCTION IN ALZHEIMER'S DISEASE Robert D. Nebes

University of Pittsburgh

SUMMARY

Unlike the normal old, demented patients with Alzheimer's disease show severe deficits on many tests of semantic memory. It has been suggested that Alzheimer's disease causes an actual loss of semantic knowledge in these patients and that this constitutes one of the primary psychological impairments of the disease. Even the severe episodic memory problems found in Alzheimer patients have been attributed to their inability to encode the semantic features of stimuli. This chapter reviews the performance of Alzheimer patients on dmerent aspects of semantic memory as seen in tests examining their word finding abilities, and their knowledge of the semantic attributes, associates and category membership of concepts. The effect that semantic context has on cognitive processes such as lexical and semantic priming and memory encoding is also reviewed. Evidence is presented suggesting that semantic knowledge remains intact in Alzheimer patients, but can only be accessed and used under certain conditions. Memory problems are common both in normal older persons and in demented patients with Akheimefs disease. The memory impairment found in Alzheirner patients, however, is not only much more severe than that found in the normal old, but may also be more extensive, involving memory processes that are relatively

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spared by normal aging. In particular, it has been suggested that, unlike normal aging, Alzheimer's disease disrupts the structure and function of semantic memory. This impairment of semantic knowledge has been postulated to actually cause many of the other cognitive deficits seen in the dementia associated with Alzheimer's disease. The present chapter will review the literature in this area, and will examine whether the semantic deficits found in these demented patients reflect an actual loss of semantic information (a disruption of semantic structure) or whether they are due to an impairment in the patients' access to, or ability to use, what is essentially an intact semantic structure (for a more detailed review, see Nebes. 1989). We will show that in certain situations, Alzheimer patients can not only access appropriate semantic information, but can also use this information to facilitate their performance on a variety of cognitive tasks. Finally. since Alzheimer patients appear to be more impaired on some semantic tasks than on others, we will examine whether concepts such as automaticity, implicit memory,or environmental constraint might be useful in explaining this variability. The concept of semantic memory (memory for meaning) has been most extensively articulated by Tulving (1984). who distinguished it from what he called episodic memory (memory for events) on a variety of characteristics. Episodic memory is a record of unique events in an individual's experience, encoded in relation to a particular time and context. These memories make up an autobiographical record of events in an individual's Me. It is this type of memory that allows people to describe what happened on a television show they saw several weeks earlier, or to recall a list of words they heard in a memory test. In the case of remembering a word list, the subjects have seen those words thousands of times before: what they are remembering is the event - the fact that those words were seen at a particular time and in a particular context. Episodic memory is usually examined though tasks in which subjects are presented with words, pictures, stories, etc., and are later asked to recall or recognize this material. By contrast, semantic memory is thought to consist of a hierarchically organized body of knowledge involving facts, concepts, their meanings and associations, as well a s the rules for manipulating these symbols

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and concepts. Information in semantic memory is organized conceptually without reference to the time and context in which it was learned. Semantic memory is typically assessed by testing an individual's knowledge of vocabulary. word associations, category membership, concept attributes, facts, etc. While there is strong evidence that most older persons show a significant impairment in episodic memory (Poon, 19851, their semantic knowledge appears to be well preserved (Howard, 1988). By contrast, it is commonly held (Bayles 8r Kasznlak. 1987) that one of the primary cognitive deficits in the dementia associated with Alzheimer's disease is an impairment in demented patients' knowledge of concept meaning. The evidence for such a semantic decrement is described below. SEMANTIC DEFICITS IN ALZHEIMER'S DISEASE Word Finding Problems Patients with Alzheimer's disease have a major problem generating specific words, such a s the names of objects, or concepts. This word finding deficit is evident early in the disease, both in patients' spontaneous speech and in tasks that require them to produce a speciflc word, such a s the name of a common object. The magnitude of this word finding problem is highly correlated with the overall severity of a patient's dementia. The spontaneous speech of demented patients is often tangential and relatively empty of meaning. They have difficulty generating the exact word needed in a particular context and thus, their speech contains few speciflc referents, being instead full of indefinite terms such as "stuff' and "things". An example given by Bayles (1982) is of a patient asked to describe the use of a bathtub, who says 'Well I see now, yeah, well you go into the bathtub and you don't have any problems here or there. You have got that over there though on that". It should be noted that, while empty of meaning, the speech of demented patients has relatively normal syntax and grammar. Alzheimer patients also show major deficits when asked to name common objects. While some studies (e.g., Barker & Lawson, 1968) claim that this anomia reflects a problem in perception (i.e., the patient misperceives the object and thus misnames it), most

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researchers now feel that the source of the naming problem is semantic. They argue that the patients' knowledge of the semantic features associated with a given concept is either lost or inaccessible and thus, the patient has difficulty matching the attributes of a presented stimulus with those of the appropriate semantic concept, Evidence for such a semantic deficit includes the fact that Alzheimer patients make primarily semantic errors when they misname objects (Bayles & Tomoeda, 19831, calling an item by the name of its superordinate category or by the name of another member of the same category (for example, calling a trumpet a musical instrument or calling a saw, a hammer). Alzheimer patients usually cannot recognize the name of the item they cannot name on sight (Flicker, Ferris, Crook & Bartus, 1987). suggesting that the semantic information for that particular item may be lost rather than being merely inaccessible. These patients have particular trouble recognizing the correct name of a pictured object if the distractors are other members of the same category (Huff,Corkin & Growdon, 1986). That is, if shown a hammer, they are much less likely to pick out the word "hammer". if the distractors are %aw" "screwdriver" and "chisel" than if the distractors are "comb" "shoe" and "truck". A common interpretation of these findings is that the patients have lost their knowledge of the specific features and attributes that are essential for distinguishing closely related concepts, although they retain enough semantic information to determine the object's overall category. Thus, when they misname an object they call it by its category name, or by the name of another object in that category. A similar explanation is given for the trouble demented patients have in naming a concept upon hearing its definition (Rissenberg & Glanzer. 1987). Another way to examine demented patients' word finding abilities is through tests of verbal fluency. Here, the subject is given the name of a semantic category (e.g., animals or words and is asked to generate as many beginning with the letter '3') examples as possible from that category within a given time period (60 to 90 seconds). Verbal-fluency tasks are very sensitive to early dementia, and show a strong correlation with dementia severity. Ober et aL(1986) found that even mildly demented subjects were

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severely impaired in the rate at which they produced examples from a category, with most of their responses occurring within the first few seconds. Alzheimer patients not only made fewer responses overall, but they had more perseverations and gave more noncategory responses. One important aspect of the results in the Ober et al. study is that while the demented patients gave many fewer responses than did the normals, they did not just generate the most typical (for semantic categories) or most frequent (for letter categories) items in a category. Rather, the demented patients' responses covered the entire range of response typicality and word frequency, That is, for a category such as birds, while they were more likely to say "robin" or "sparrow". like normals. they also produced some atypical examples such as "penguin". This suggests that the demented patients had not lost the less typical or less frequent words from their lexicon. and thus, the overall structure of their categories remained intact. Knowledge of Concept Meaning Another area of research on semantic abilities in dementia has investigated what these patients know about a semantic concept's attributes. associations and category membership. The most obvious way to determine what information patients have about a particular concept is to ask them by giving them a vocabulary test. Alzheimer patients do quite poorly on vocabulary tests, whether it is a verbal definition task, such a s the vocabulary subtest of the Wechsler Adult Intelligence Scale WAIS). or a recognition test, such as the Peabody Picture Vocabulary test. Their performance also steadily declines as their dementia progresses (Bayles h Kasmiak, 1987, pp 76-77). Thus, Alzheimer patients appear to have lost knowledge of word meaning, at least when this knowledge is assessed by their ability to carry out a directed search for the meaning of a word. Demented patients also have difficulty in the Similarities subtest of the WAIS, in which they have to say how two concepts are similar (e.g.. "How are a table and a chair the same?'). Instead of responding with an abstract generalization that relates the two concepts (e.g.. for table and chair saying that they are furniture), demented patients are more likely to give a concrete

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point of similarity (e.g.. 'They both have legs.") or to say how they differ (e.g., "You eat off one and sit on the other."). Thus. it appears that demented patients may be unaware of the nature of the semantic relationships between different concepts. Another approach used to examine concept meaning involves presenting subjects with a stimulus concept and asking them to generate associatims. Here, semantic structure is reflected in the nature of the associations produced. Most normal individuals tend to produce mainly paradigmatic associations, that is. items related to the stimulus concept in meaning (e.g.. items from same category, synonyms, or antonyms). Alzheimer patients not only produce many fewer paradigmatic associations than do the normal old, but they also give many more idiosyncratic responses, that is, words with no obvious relationship to the stimulus ( G e m , Shindler & Hier, 1984). This pattern of results has been interpreted a s showing an impairment in the network of semantic associations in Alzheimer patients, in that a stimulus word is not as likely to evoke a semantically-associatedword in these individuals. Salmon, Shimamura, Butters and Smith (1989) used an associative - priming paradigm to assess the integrity of semantic associations between ditrerent concepts in Alzheimer patients. In this procedure, subjects are presented with pairs of weakly related words and are asked to make some decision about them. Later, as part of what the subjects think is a totally dflerent task, they are given a series of stimulus words in a free association task and for each stimulus word are asked to say the first word that comes to mind. Embedded within the series of stimulus words are the first words from the previously presented word pairs. The question here is whether prior presentation of the two words a s a pair acts to prime (i.e.. activate) the associative link between them, thus making subjects more likely (in comparison to a control condition in which there is no prior presentation of the word pair) to emit the second word of the pair when they see the first word in the free association task. Salmon et al. (1989) found that Alzheimer patients were significantly less likely than normals to show such associative priming. That is, prior presentation of an semantically associated pair of words did not change the likelihood that the demented patients would emit the second word of the pair when shown the

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flrst in a free association task. The results of a control condition embedded within the main task suggest that the superior associative priming seen in the normals is not due to their using a conscious recall strategy that is unavailable to the dememted patients. Salmon et al. argue that these results are evidence for an impairment in the network of semantic associations between concepts in Alzheimer patients. There have also been several studies that have directly examined Alzheimer patients' knowledge of the specific attributes that make up the meaning of a concept. Martin and Fedio (1983) showed photographs of common objects to Alzheimer patients and had them sort them into general categories, which the patients did quite adequately. Martin and Fedio then asked them direct questions about the photos. Demented patients could accurately answer questions about the superordinate and specific category of the objects (e.g., Is it man made? Is it a tool?), but were much less accurate in answering questions about the objects' specific attributes (e.g., Is it made of metal? Is it used to cut? Does it have moving parts?). They concluded from these results that while Alzheimer patients retain general information about a n item's category membership, they have lost their knowledge of, or access to, those semantic attributes that are necessary to determine concept meaning. Flicker et al. (1987) gave subjects 25 items and asked them both to name the objects and to pick out the eight objects they would use for a particular chore (e.g., cooking dinner). While the demented patients did have less trouble picking out objects needed for a given task than they did producing the objects' names, the patients were significantly impaired on both tasks. Flicker et al. concluded that demented patients have difficulty accessing specific attribute information about a concept from semantic memory. Use of Semantic Structure in Episodic Memory Finally, it has been suggested that a semantic impairment may be at least partially responsible for the deficit Alzheimer patients have in episodic memory. Weingartner et al. (1981) tested subjects' memory for lists of 20 words. One list (random) consisted of

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randomly selected words, while a second set (unclustered) consisted of 10 words from each of two categories all intermixed. A third list (clustered) was also made up of 10 words from each of two categories, but here, the words were presented grouped by category. Weingartner et al. found that the recall of normal persons improved if there was a semantic structure present in a list. Thus, their memory for the clustered list was better than for the unclustered list, which was in turn substantially better than for the random list. In contrast, the performance of the Alzheimer patients was equally poor on all three lists; the semantic structure of the lists apparently having no effect on their memory performance. Even when the lists were presented multiple times, demented patients showed no tendency to use the semantic structure inherent in the lists to improve their recall. The Alzheimer patients also did not show any consistent organization in their recall. That is, unlike normals, they did not recall items from the same category as a group, wen after having seen the same list SIX times. summary The most common interpretation of the studies summarized above is that while demented subjects retain information about the general category to which a concept belongs, they have either lost, or have difficulty accessing, information about the specific attributes and features of concepts. This semantic defect is seen to have widespread effects. It causes defective episodic memory because the demented patients do not encode semantic attributes. The patients have dimculty retrieving the names of objects or exact referents in spontaneous speech because they do not have available the specific information that would allow them to differentiate closely related referents and thus to chose the appropriate word. Their deficits in vocabulary and verbal comprehension tests could be explained along the same lines. There are however, other experiments suggesting that patients with Alzheimer's disease can access and use semantic information, including specific semantic features and attributes, at least under certain conditions.

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PRESERVED SEMANTIC FUNCTION IN ALZHEIMER'S DISEASE Knowledge of Concept Meaning A recent study by Grober, Buschke. Kawas and Fuld (1985) suggests that knowledge of the specific attributes of concrete stimuli is actually preserved in demented patients, but that the organization of these attributes is disrupted. In this task, subjects were shown a target concept in the form of a word (e.g., "airplane"). They were then given a list of stimulus words (e.g., shoe, fly, pflot. desk, radar, milk, etc.) and asked to check off those words that were "related to" the target. Grober et al. found that demented patients responded correctly to 95% of the stimulus words, somewhat less than the 98% accuracy of the normal old, but stfll quite good. A second experiment, however, suggested that the demented patients were less aware than normals of the relative importance of the various attributes. Subjects were given word triplets, all of which were related to a single target concept, but which varied (according to norms) in their relative importance to the meaning of that target (e.g., for "airplane" - they might get "luggage", ''fly'. "radar"). Subjects were to pick out the word most important to the meaning of the concept first, and then the next most important word. Grober et al. found that demented patients were significantly worse than normals in discriminating among the attributes on the basis of their importance. They suggested that whfle Alzheimer patients have not lost their knowledge of concept attributes, the organization of these attributes is disrupted, the patients being relatively unaware of the relative importance of the various aspects of a concept's meaning. Such a disruption of attribute organization could produce many of the same cognitive deficits as an actual loss of those attributes. For example, if, in order to remember a concept, an individual must encode its semantic features, then any disorganization of these features could impair his or her episodicmemory performance. When given a word such a s "tiger" to remember, whfle a normal individual would encode distinctive features such as '*cat","stripes': and "large". a demented patient might encode less relevant attributes such a s "whiskers", "fur'; and "tail". which would not clearly specify the target concept. The

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demented patient's episodic memory would thereby suffer as a result of a semantic disorganization. One difficulty with the Grober et al. study is that it defined related attributes rather loosely, in that not only were distinctive physical features and actions involving the target concept given as related words, but also words that were just generally associated with the target (e.g.. for "airplane" the stimuli "sky" and luggage"). We recently carried out a study (Nebes & Brady. 1988) that differentiated between the various types of related words. Subjects were given a concrete noun as a target concept. They were then shown a series of ten stimulus words. We recorded the time it took the subjects to decide whether or not each stimulus word was related to the target. Of the five stimulus words that were actually related to a given target concept, one was the target's category, another a generally associated word, a third a prominent physical feature (a distinctive adjective or part), a fourth a function (a distinctive use or action involving the target), while the fifth was the target word itself a n identity relation. For example for the word "shirt" the category was "clothing", the associate was Yie", the action was "wear", the feature was "collar", and identity was "shirt". There were also five unrelated words interspersed among the related ones. If demented patients are differentially impaired with regard to the distinctive features and actions of concepts, then they should be slower and less accurate in making decisions about these types of stimulus words than about words involving a category, associate or identity relationship. The results are shown in Figure 1. While the demented patients were slower to make decisions than were the normals, the magnitude of this group difference was no greater for decisions about a physical feature or action than it was for decisions about a category or a general associate. In fact, the greatest difference in response time between normal and demented subjects was for decisions about the category of a target word. As in the Grober et al. (1985)study, the demented patients were very accurate in this type of decision, correctly identifying related words over 96% of the time. Thus, like Grober. we found no evidence that the field of semantic attributes, at least for these concrete concepts, was in anyway constricted or diminished in Alzheimer patients.

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Nor, was there any evidence for a specific impairment or loss of knowledge of the physical features and actions of concepts. In a study just completed, we attempted to directly test Grober et al.'s hypothesis that Alzheimer patients are unaware of the relative importance of the different attributes of a concept. Here, we used a procedure similar to that in the study just described. The subjects were given a target word followed by a stimulus word and they were to decide whether or not the two words were related. Unlike the previous study, the important stimulus variable in this experiment was not the nature of the attributes (i.e., physical feature, action, etc.) but rather, their relative dominance or salience with respect to the concept. We first carried out a nonning study in which we gave the target nouns to normal older persons and asked them to generate as many attributes as they could to each noun. We then selected high, medium, and low dominance attributes, based on the percentage of the norming sample who gave a particular response. High dominance attributes were those that over 45% of the subjects in the norming sample generated, while medium dominance attributes were generated by 20 to 30%. and low dominance attributes by less than 10%. For example, for the concept "elephant" the high, medium, and low dominance attributes selected were 'Yrunk", "ivory" and "memory". If Alzheimer's disease does disrupt the organization of concept attributes according to their importance or salience, then the time it takes Alzheimer patients to decide that a given attribute is related to a concept should not vary a s a function of the rated dominance of that attribute, while in normals it should. A preliminary analysis of the results (see Figure 2)shows that the time Alzheimer pattents took to decide that a given attribute was related to a target concept was aEected by attribute dominance to the same degree a s was that of both normal-old and normal-young individuals. The question then arises a s to why Alzheimer patients show sensitivity to attribute saliency in this task but not in that of Grober et al. (198517 One possible explanation is that in the Grober et al. task, the patients had to make a decision based on a direct comparison of the relative importance of multiple attributes (i.e., which of these three is most important). By contrast, in our study their knowledge of attribute saliency was derived indirectly from the

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relative speed with which they made a simple decision are these two words related or not. Thus, whether or not the semantic organization of concept attributes appears normal in Alzheimer patients may depend on how access to this information is tested. A similar explanation may account for why, in the Martin and Fedio (1983)study, Alzheimer patients were apparently unaware of the

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physical features and functions of objects. In the initial experiment in the Grober study and in our two studies, subjects had only to decide whether or not a concept and an attribute were related, while in the Martin and Fedio study they were asked a direct question about a concept (e.g., Is this item made of metal?) which required them to search for, and to make a decision about, a speciflc bit of information. Again. the manner in which demented patients' semantic knowledge is tested may be crucial in determining whether or not they succeed. There is also evidence that the structure and organization of semantic categories remains relatively intact in Alzheimer patients. We noted earlier that when demented patients are asked to generate members of a given semantic category, they produce many fewer items than do normals, but their responses contain low and medium tgpfcdity (dominant) items in roughly the same proportion as do the responses of normals (Ober et al., 1986). That is, their responses cover the whole range of typicality for members of a category, and thus, there is no evidence that they have lost the less typical category members. This was confirmed in a study from our lab (Nebes, Boller & Holland, 1986) in which we measured the speed with which subjects decided whether a particular word was a member of a given category. We varied the typicality of the items (i.e.. how commonly normals generate that item as a member of that category) and found that not only were demented patients quite accurate in making category decisions, but their knowledge of the relationship between an item and its category showed a similar structure to that of normals. That is. high typicality members were responded to faster than were low typicality members. While the demented patients took longer to respond than did normals, they were not disproportionately slower in responding to the less typical category members than to the more typical ones (see Figure 3). One line of evidence suggesting that the network of associations between semantic concepts remains at least partially intact in Alzheimer patients comes from studies using semantic priming. This approach is based on a model that views semantic memory as a hierarchical network of conceptual nodes. Presentation of a concept, for example by means of its name, activates not only its node, but also other concept nodes associated with it through a

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variety of relationships. This spread of activation briefly increases the accessibility of these related concepts, allowing them to be processed more rapidly if they occur soon after a concept to which they are related. In the semantic-priming paradigm, the time a subject takes to process a given stimulus is measured under two conditions: a) when the preceding stimulus (the prime) is semantically related to the item being processed, and b) when it is unrelated. Normals generally process a word faster if it is preceded by a semantically related concept (e.g.. they can process "doctor" faster if it follows "nurse" than if it follows "shoe"). Since this task does not require the subject to engage in any intentional search for, or use of, semantic associations, we felt it might be a good measure

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of the intactness of semantic associations in demented patients. We have carried out several priming studies. In the most recent, subjects were given a series of words and we measured the time it took them to respond to each word as a function of whether the preceding word (the prime) was semantically related to it or not. We used two difYerent tasks - word naming and lexical decision (Nebes. Brady & Huff, 1989). If there is an impairment in the network of semantic relationships between concepts in Alzheimer patients, then we would expect semantic priming to be reduced or eliminated in these individuals. However, as shown in Figure 4, if anything, the priming effect was larger in the demented patients than in the normal young or old, for both the naming and lexical-decision tasks. Thus, while demented patients may have difficulty explaining the nature of the relationship between a table and a chair (Similarities subtest of the WAIS), they are aware of this relationship at some level, since they process the word "chair" faster if it is preceded by "table" than if it is preceded by an unrelated word, such a s "mountain". How then can we reconcile these findings with the previously mentioned associative priming data of Salmon et al. (1988). One important difference between the semantic-priming and associative-prfmingparadigms is the demand for lexical search in the latter. In semantic-priming tasks, the effect of the prime is measured by a change in the speed or accuracy with which subjects process a presented word. By contrast, in associative-priming tasks, the effect of the prime is measured by a change in the likelihood that the subjects will emit a given word in a free association task. Therefore, successful associative priming requires more than just activation of a semantic node and the spread of this activation to related nodes; it requires lexical search. Thus, rather than dysfunctional semantic associations, an impairment in lexical search may be the cause of Alzheimer patients' fallure in associative priming. Use of Semantic Context and Information The performance of demented patients can also be facilitated by more complex semantic contexts such a s those provided by a sentence. In a semantic-priming task (Nebes et al., 1986). subjects

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listened to a sentence in which the final word was missing. At the point in the sentence when the find word would have been heard, subjects instead saw a target word which they were to read aloud. The context of the sentence was either congruous with this visual word (e.g., the subject heard 'The child was born with a rare -'I

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and then saw "disease"), or was incongruous (e.g., 'When you go to followed by "disease"). These conditions were bed turn off the compared to a neutral condition in which the sentence provided no contextual information ('They said it was the -"). If demented patients are unable to use the semantic context provided by a sentence, then the speed with which they read the target word should be unaffected by the nature of the preceding sentence. It was not. A congruous sentence facilitated (i.e., speeded up) reading of the target word (in comparison to the neutral condition)just as much in the demented patients as it did in the normal old and young. The inhibition produced by an incongruous sentence (in comparison to the neutral condition) was even larger in the patients than in the normals. These results suggest that the semantic information present in the sentence must have been encoded and comprehended at some level in order for it to have affected the patients' behavior in this manner. Further analysis of the sentences showed that the priming effects produced by sentence context in this task could not be attributed merely to the presence in the sentence of a single word highly associated with the target. Instead, the effect of sentence context appeared to due to the meaning conveyed by the sentence as a whole. A companion task to the previous one examined the effect that sentence context had upon Alzheimer patients' ability to carry out a directed search of their lexicon (Nebes et al., 1986). Again, subjects heard an incomplete sentence and at the point where the final word would normally have occurred, they heard a tone. This was their signal to complete the sentence with a single word. In this task, subjects had to use the semantic-syntactic context of the sentence to guide their search through their lexicon for an appropriate word to complete the sentence. The sentences varied in the degree of selection constraint they imposed on this final word. Some sentences were very constraining, in that relatively few words would sensibly complete the sentence (e.g., "Father carved the turkey with while others were much less restrictive (e.g.. 'They went to a -."I, in that they could be completed by a large see the famous number of words. Normal young and older persons completed the high constraint sentences faster than they did medium or low constraint sentences. The demented patients were -I'

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disproportionally slower than the normals on the medium and low constraint sentences. In fact, the patients actually had a great deal of difficulty with any sentence that did not provide a high degree of constraint, often being unable to produce an ending within the 10 second time limit. The patients were much better. both in terms of accuracy and speed of response, if the sentence context was highly constraining. Thus, if anything, Alzheimer patients were more sensitive to the semantic context of the sentences than were normals. Therefore, the word-finding deficit previously shown for Alzhefmer patients was also evident in this task. but it could be ameliorated to a degree, if the patients were provided with a highly constraining semantic context that guided their search of their lexicon for the appropriate word. In a study still underway. we followed up on this last task by investigating whether the degree of constraint present in a sentence also d e c t e d the time subjects took to judge whether a final word made sense in the context of that sentence. The subjects heard a sentence in which the final word was presented visually. and they had to say yes or no as to whether this visual word provided a sensible completion to the sentence (e.g., "He mailed the letter without a stamp. vs. The wealthy child attended a private hand"). Again we varied the constraint of the sentences. We found that the decision time of Alzheimer patients was affected by sentence constraint to the same degree as was that of normals (see Figure 5). That is, like normal young and old subjects, demented patients detected an appropriate completion of a high constraint sentence faster than they did a low constraint sentence. Thus, they responded "yes" to "He scraped the cold food from his plate." faster than they did to 'The surface of the water was very smooth". These last three studies demonstrate that complex semantic context does affect the speed with which Alzheimet patients can: identify a word, make a decision about the contextual relevance of a word and search their lexicon for an appropriate word. Thus. whatever problems demented patients have on semantic tasks. their performance is sensitive even to complex semantic information conveyed by whole sentences.

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Use of Semantic Context in Episodic Memory Finally, two studies from our lab suggest that the presence of semantic structure in verbal material can facilitate Alzheimer patients' episodic memory for this material, probably by improving encoding. The first study (Nebes et al., 1984) examined how accurately subjects could recall lists of words that differed in the amount of language structure present in the list. The lists varied in how closely they approximated English text, that is, the degree to which they conformed to the constraints of English syntax and semantics. The lists ranged from a zero-order approximation words selected totally at random (e.g.. day, angel, error, view, wire, park, rail, belt) - to lists with a moderate (fifth-order)approxtmation (e.g., to, ask, for, is. to, earn. our, living) in which there is some language structure, to actual text (e.g.. it, was, a, warm, day, in. July, when). The more closely a word list approximates a natural sentence, the easier it is for normals to recall it (Miller 81 Selfridge, 1950). Higher order-of-approximation lists are more likely to have embedded within them meaningful groupings of words (chunks) that allow subjects to encode the words in terms of well-learned language patterns. In the Nebes et al. (1984) study, task difficulty was individually equated for normal and demented subjects by first determining how long a list of random words had to be before a particular subject recalled only 25% of them. This list length was then used for all the varying approximations to text that were given to that particular subject. Obviously, since demented patients have a poor episodic memory, this meant that the lists given to them were shorter than were those given to the normals. However, we did not analyze the absolute number of words recalled in this task, but rather the percentage of a list that a subject recalled a s a function of order of approximation. Results showed that a s approximation-to-text increased, the percentage of the list recalled also increased, and this increase was virtually identical for normals and for demented patients. It thus appears that patients with Alzheimer's disease can use the language structure present in text to facilitate their memory for that text. However, there was a major confound in this task. As approximation to text increases, not only are word lists more likely to form semantically coherent phrases,

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but they are also more likely to conform to normal syntactic patterns. It is known (Marks & Miller, 1964) that both syntactic and semantic structure can facilitate recall. Since syntax is relatively well preserved in demented patients (Hier, Hagenlocker & Shindler, 1985). the improved memory of Alzheimer patients for the higher orders of approximation might be due to their use of syntactic rather than semantic structure. This confound was not, however, present in a followup study (Nebes. Brady & Jackson. 1989) in which subjects were given seven-word sentences that were either normal, bizarre (i.e.. they portrayed unlikely events), semantically anomalous 0.e. * they portrayed impossible events that violated semantic constraints), anagrams (i.e.. sentences whose word order was disarranged), or random word lists which had neither semantic nor syntactic structure. For example, a normal sentence was "Five girls swam in the shallow pool"; a bizarre sentence was 'Three bugs jumped over the rotten meat": a semantically anomalous sentence was Many carrots sang to the sickly ashtrays"; an anagram was "Ship near sunken two floated ducks the): while a random-word list was "Dentist town a the decided tender broken". Again, overall memory performance was equated between the normal old and the patients prior to testing. In this case, we varied the duration of an interference period following presentation of random-word lists until we found a duration that produced 25% recall accuracy. An interference period of this duration was then used with the various sentence types. Since the only difl'erence between the normal, bizarre, and semantically anomalous sentences is the amount of semantic structure present in the sentence (all of them have normal syntax). if demented patients cannot use semantic structure to improve their recall, but instead rely on syntactic structure, there should no dflerence in their recall accuracy for these three types of sentence. From the data shown in Figure 6 it is clear that the pattern of recall accuracy across the various sentence types was very similar in normal and demented subjects. Recall accuracy improved as the amount of semantic information in the sentences increased (i.e.. from semantically anomalous, to bizarre to normal sentences) and this was equally true in elderly normals and in demented patients. The mechanism by which semantic structure

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facilitated memory perfonnance also seemed to be the same in normals and in demented patients. Semantic structure appears to provide a basis for subjects to organize a string of words into chunks (meaningful phrases), thus allowing more efffcient encoding of the words into memory. If we look at the number of words m a w up a recall "chunk" (defined as a sequence of correct words recalled in the same order a s they were presented). it is clear (Figure 7 ) that a s the semantic structure of the sentences increased, so too did chunk size and that this was equally true of both normal and demented subjects. Thus, demented patients do appear capable of using the semantic structure present in text to

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improve their episodic memory and the mechanism by which semantic information af€ects their memory is the same as in normal individuals. The question now becomes why can demented subjects use semantic structure in these sentences, but not in the categorized word lists of Weingartner et al. (19811. One possibility is that Alzheimer patients benefit from the semantic information present in sentences, because reading connected text is such an overlearned automatic sklll in most persons. Demented individuals may fail to encode semantic information only if the situation requires that they self-initiate a novel coding scheme, such a s grouping words by

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membership in a semantic category. Demented patients may be able to effectively encode semantic information only to the extent that their encoding is induced and directed by the stimulus material itself through overlearned patterns of processing.

SUMMARY OF RESULTS There is no question that demented patients have trouble generating an appropriate word, both in spontaneous speech and in tasks that require them to name an item upon seeing its picture or upon hearing it deflned. However, it also appears that this wordfinding problem can be reduced if an adequate stimulus context is provided to guide or constrain the patient's search for a suitable word, a s in the sentence-completion task. In situations in which subjects must generate their own lexical-search strategy with minimal contextual guidance (e.g., a verbal-fluency task), the wordfinding performance of demented patients is deficient. As to what demented patients know about the meaning and associations of a particular concept, the answer appears to depend on just how you ask them. For example, if you test their knowledge of an item's superordinate category by asking them to generate as many items as possible from a given category (e.g., furniture), or to tell you how a table and chair are alike, they do poorly. If, on the other hand, you ask them to sort items by category, or to make a decision as to whether a given item belongs to a particular category, they do quite well. Similarly with associations. If asked to generate associates, demented patients are less likely than normals to come up with a paradigmatic (i.e., semantic) associate. This could indicate that such semantic associations are lost in Alzheimer patients. However, if you examine their knowledge of associations by indirect means, such as semantic priming, it is clear that the network of associations between the different concepts remains relatively intact. In terms of their knowledge of the attributes of a concept, when demented patients are directly asked about the specific physical features and functions of objects, they are often unable to correctly answer the question. However, if they are just asked whether or not a specific attribute is related to a given concept, they are very accurate. In all of these tasks, it appears that the

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situations that give the demented patients the most difficulty are those in which they must carry out a self-directed search of their semantic memory for a specific piece of information. The preciseness of the search seems crucial. The effect that semantic context has on episodic memory in demented patients also depends on the experimental situation. When the semantic structure present in a set of words consists only of the words being segregated into several categories, demented patients do not use the semantic structure to improve their memory encoding. When, however, the semantic structure is inherent in connected text, they do. Similarly. connected text also had a strong priming effect in demented patients, even greater than that found in normals. Since reading text is a highly overlearned skill for most persons in our society. the patients' use of the semantic information in text may be more automatic than it is in situations where they must first notice and then use the semantic structure in a more novel setting, such a s categorized word lists.

INTERPRETATION Given the variability in the test results described above, how are we to conceptualize the nature of the semantic deficit in Alzheimer's disease? First of all, is semantic information actually lost in Alzheimer patients or are their semantic impairments due to other cognitive deficits that limit their ability to access and appropriately use semantic information? Certainly many investigators (e.g., Bayles & Kaszniak, 1987:Salmon et al., 1986) feel that Alzheimer's disease produces a fundamental disruption of semantic information. To determine whether information is really lost or merely inaccessible is, of course, extremely difficult. However, to the extent that demented patients can access or use semantic information under some conditions but not under others, this would suggest that at least some semantic information remains intact in Atzheimer patients. The tasks on which demented patients appear most impaired are those that require them to carry out a directed search of their semantic memory for a specified piece of information (e.g., verbal fluency, object naming, generating associates, etc.). However, it is unlikely that we can attribute all

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semantic problems in Alzheimer's disease to a reMeuu.2 denit, as the performance of demented patients can differ greatly between conditions that make similar demands on retrieval. For example, demented patients can answer direct questions about whether a particular object belongs to a certain category, but not similar questions about the object's physical properties and functions (Martin & Fedio. 1983). Another possibility is that rather than being lost, or relatively inaccessible, semantic information is disorganized (e.g., the semantic attributes of a concept no longer being organized according to their relative importance), leading to ineffective use of this information (Grober et al., 1985). However, there is also evidence that the overall organization of at least some components of semantic memory remains intact in Alzhiemer patients (Ober et al.. 1986: Nebes et a]., 1986). Many of the studies just reviewed seem to suggest that the presence or absence of a semantic deficit in demented patients depends greatly on the nature of the task. It may therefore be more useful to determine under what conditions Alzheimer patients can access and use semantic information and under what conditions they cannot. The question then becomes are there any untfying concepts that might explain why demented patients can apparently retrieve and use semantic information in certain tasks and not in others. For example. can we use the concept of automaticity? Jorm (1986) and Nebes et al. (1984) suggested that if the semantic operations involved in a task make heavy demands on attentional capacity, then Alzheimer patients will show a deficit. However, if access and use of semantic infomation is relatively automatic, they will perform normally. While this is a very appealing concept, there is no direct evidence for it in the literature. The concept of automaticity has been most clearly conceptualized in restricted experimental paradigms: in visual and memory search by Schneider and Shrif€rin (1977). in memory encoding by Hasher and Zacks (1979). and in semantic priming by Neeley (1977). Of the studies described in this review, only the semantic-priming procedures have any well defined criteria for determining whether subjects are using automatic or attentlon-dependent processes. We had predicted in our priming studies (Nebes et al., 1984; Nebes et al., 1986: Nebes et al., 1989a) that demented patients would show

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semantic priming resulting from an automatic spread of activation, but not priming dependent upon attentional processes. These two components of priming have been differentiated in a number of studies in normals through the presence or absence of priming inhibition (Neely, 1977) or through the use of a word-naming versus a lexical-decision paradigm (Seidenberg,Waters, Sanders & Langer, 1984). Unfortunately, the predictions that spring from these earlier studies with normals were not supported by the results with Alzheimer patients, If we accept the criteria that have been laid down for differentiating automatic from attention-dependent priming, it appears that both types of priming occur in Alzheimer patients. Thus, there is no strong evidence that demented patients can access and utilize semantic information only through automatic processes. Another theoretical construct recently advanced by Craik (1984) to explain the effects that normal aging have on cognition, might also be of use in understanding the pattern of semantic deficit in Alzheimer patients. Craik suggested that the amount of age deficit seen in a given task is a function of the degree to which the required cognitive operations are self-initiated versus being driven by the task and stimulus materials (i.e., the amount of environmental support provided). It may be that in tasks in which demented patients must self initiate and organize the retrieval and use of semantic Information, their performance is defective, while in tasks in which their processing is strongly constrained and guided by the external task situation, they perform fairly normally. The most obvious support for this view comes from the sentencecompletion task (Nebes et d., 1986) and its followup task. Here, the amount of constraint present in an incomplete sentence certainly had a major effect on demented patients' ability to complete the sentence with an appropriate word or to judge whether a presented word sensibly completed the sentence. It is possible to also categorize at least some of the other semantic tasks used with Alzheimer patients in terms of the amount of environmental support they provide (e.g., verbal fluency has little support, while category decision has a great deal). It is clear, however, that this conceptualization cannot explain the entire pattern of semantic test results in Alzhiemer patients. For example, an associative-priming

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task does not seem to provide any less semantic guidance than does a semantic-prlming task using single words, and yet Alzheimer patients perform abnormally on the first and normally on the second. Another potentially useful concept is impZicit memory. As recently reviewed by Schacter (19871,implicit memory is evident when previous experiences facilitate performance on a task that does not require conscious intentional recollection of those experiences. This is contrasted to explicit memory, which does involve intentional recollection (e.g., typical recall and recognition tasks). There is a growing literature showing that even amnesic patients who are grossly impaired on traditional measures of explicit memory perform normally on measures of implicit memory (Graf, Squire & Mandler, 1984). Many of the semantic tasks that Alzheimer patients perform successfully, could qualify as measures of implicit memory (e.g., semantic priming). Even the superior performance that Alzheimer patients show in remembering sentences as compared to random words might involve implicit use of their knowledge of the semantic relationships expressed in the sentences. However, Alzheimer patients do not necessarily perform normally on all of the tasks that are presently classified as measures of implicit memory. For example, Alzheimer patients do not show normal associative priming (Salmon et al.. 1988). Therefore, the implicit memory concept alone cannot totally account for the pattern of semantic-memory performance in Alzheimer's disease. At present, there does not seem to be any one simple explanation for the variability in demented patients' performance on measures of semantic memory. We may have to look for combinations of factors (e.g., automaticity plus environmental constraint) or it may turn out that semantic memory is comprised of multiple components, some of which are impaired in patients with Alzheimer's disease, while others are spared. REFERENCES Barker, M. G., 81 Lawson. J. S. (1968).Nominal aphasia in dementia. British Journal of Psychfairy, 114, 1351-1356.

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Bayles, K. A.. & Kaszniak, A. W. (1987). Communication and cognition in normal aging and dementia. Boston: College -Hill press. Bayles. K. A., & Tomoeda, C. K. (1983). Confrontation naming in dementia. Brain and Language, 19.98- 114. Craik. F. I. M. (1984). Age differences in remembering. In L. R. Squire & N. Butters (Eds.). Neuropsychology of m y (pp. 312). New York Guilford Press. Flicker, C., Ferris, S. H., Crook, T.. & Bartus, R. T. (1987). Implications of memory and language dysfunction in the naming deficit of senile dementia. Brain and Language, 31, 187200.

Gewirth. L. R., Shindler, A. C., & Hier, D. B. (1984). Altered patterns of word associations in dementia and aphasia. Brain and Language, 21.307-3 17. Graf, P., Squire, L. R., & Mandler, G. (1984). The information amnesic patients don't forget. Journal of Experimental Psychology: Learning Memory and Cognition, 10, 164- 178. Grober. E., Buschke, H., Kawas, C., & Fuld, P. (1985). Impaired ranking of semantic attributes in dementia. Brain and Language, 26, 276-286. Hasher, L. & Zacks. RT. (1979). Automatic and effortful processes in memory, Journal of Experimental Psychology: General., 108, 356-388.

Hier, D. B.. Hagenlocker, K.,& Shindler, A. G. (1985). Language disintegration in dementia: Effects of etiology and severity. Brain and Language, 25, 117- 133. Howard, D. V. (1988).Aging and memory activation: The priming of semantic and episodic memories. In L. L. Light & D. M. Burke (Eds.), Lunguage, memory, and aging (pp 77-99). New York: Cambridge University Press. Huff, F. J., Corkin, S., & Growdon, J. H. (1986). Semantic impairment and anomia in Alzheimer's disease. Brain and Language, 28,235-249. Jorm, A. F. (1986). Controlled and automatic information processing in senile dementia: A review. Psychological Medicine. 16, 77-88.

Marks, L. E., & Miller, G. A. (1964). The role of semantic and syntactic constraints in the memorization of English sentences. Journal of Verbal Learning and Verbal Behavior, 3. 1-5. Martin, A., & Fedio, P. (1983).Word production and comprehension in Alzheimer's diesease: The breakdown of semantic knowledge. Brain andLanguage, 19, 124-141.

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Miller, G. A, & Selfridge. J. A. (1950).Verbal context and the recall of meaningful material. Amer[cal Journal ofp~ychology~ 63, 176185. Nebes, R.D. (1989)Semantic memory in Alzheimer's disease. P ~ y ~ h o l ~ gBulletin., i ~ a l 106,377-394. Nebes. R. D., Boller, F., & Holland, A. (1986).Use of semantic context by patients with Alzheimer's disease. Psychology and Agfng. 1 . 261-269. Nebes. R. D.. & Brady. C. B. (1988).Integrity of semantic fields in Alzheimer's disease. Cortex, 24,291-300. Nebes, R. D., Brady, C. B., & Huff, F. J. (1989a).Automatic and attentional mechanisms of semantic priming in Alzheimer's disease. Journal of Clinical and Experimental Neuropsychology, 1 1 , 219-230. Nebes. R. D.. Brady, C. B., & Jackson, S.T. (1989b).The effect of semantic and syntactic structure on verbal memory in Alzheimer's Disease. Brain and Language, 36, 301-313. Nebes, R. D., Martin, D. C., & Horn, L. C. (1984).Sparing of semantic memory in Alzheimer's disease. Journal of A b n o M P ~ y ~ h o l ~93, g y ,321-330. Neely. J. H. (1977).Semantic priming and retrieval from lexical memory: Roles of inhibitionless spreading activation and limited-capacity attention. Journal of Experimental Psychology: General, 106, 226-254. Ober. B. A., Dronkers. N. F., Koss. E., Delis, D. C., and Friedland, R P. (1986). Retrieval from semantic memory in Alzheimer-type dementia. Journal of Clinical and Experimental Neuropsychology. 8.75-92. Poon, L. W. (1985).Differences in human memory with aging: Nature, causes, and clinical implications. In J. E. Poon, & K. Warner Schaie (Eds.), Handbook of the psychology of aging (pp. 427-462). New York Van Nostrand Reinhold Co. Rissenberg, M., & Glanzer. M. (1987).Free recall and word finding ability in normal aging and senile dementia of the Alzheimer's type: The effect of item concreteness. Joumal of Gerontology,42, 318-322. Salmon, D. P., Shimamura. A. P.. Butters, N.. & Smith. S. (1988). Lexical and semantic priming deficits in patients with Alzheimer's disease. Journal of Clinical and Experimental Neuropsychology. 10. 477-494. Schacter, D. L. (1987). Implicit memory: History and current status. Journal of Experimental Psychology: Learning, Memory, and Cognition, 13, 501-518.

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Schneider, W., & ShifMn, R.M.(1977). Controlled and automatic human information processing: I. Detection, search and attention. PsychoZogfcaZ Revfew, 84, 1-66. Seidenberg. M. S., Waters, G. S.. Sanders, M., & Langer. P. (1984). Pre- and postlexical 'loci of contextual effects on word recognition. Memory and CognUf.on, 12,315-328. Tulving, E. (1984). Precis of "Elements of episodic memory." The Behavioral and Brain Sciences, 7, 223-268. Weingartner, H., Kaye, W.. Smallberg, S.A., Ebert, M.H., Gilin, J.C., & Sitaram, N. (198 1). Memory failures in progressive idiopathic dementia. Journal o f A b m a l Psychologg, 90, 187- 196.

Aging and Cognition: Knowledge Organization and Utilization Thomas M. Hess (Editor) 0 Elseuim Science F.zLbZi~her~ B.V. (Abrth-Holland), 1990

CHAPTER SEVEN

A DEVELOPMENTAL APPROACH TO VISUAL COGNITION IN THE ELDERLY Matthew J. Sharps

California State University - Fresno

SUMMARY Significant age-related influences on visual cognitive abilities are commonly reported. I t is argued that methods derived from developmental theory and findings may be useful for the study of these influences. Such “ageby-task’’ methods involve the systematic and simultaneous manipulation of task-related and subjectrelated variables. Examples of the utility of these methods are drawn from the spatial perspective-taking and spatial memory literature. The application of this approach to problems of mental imagery, within a mental image rotation framework, is also demonstrated. A review of literature on mental image rotation and aging indicates that performance may depend upon a variety of subject- and task-related factors, including stimulus characteristics. A new experiment addressing some of these factors is reported. Subject age is shown to interact significantly with specific characteristics of the stimulus items employed. The results indicate that an age-by-task approach to problems of aging and mental imagery may lead to more comprehensive understanding of the factors influencing performance than would otherwise be possible. Visual cognition, or visual information processing, has been defined as the entire process by which human beings receive visual information and adjust their behavior on the basis of that

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information (Spoehr & Lehmkule, 1982). A variety of visual cognitive abilities are included within the sphere of activities involved in knowledge utilization (see Lachman & Lachman, 1980). including the use of visual characteristics of stimuli to organize encoding and retrieval, the ability to judge similarities and differences among stimulus items, and the ability to judge the appropriateness of stimulus organization to various real-world and experimental contexts (e.g., Biederman, 1977). An understanding of the principles underlying aging and visual cognition is therefore important for the development of knowledge utilization theory. Numerous studies have demonstrated age-related declines in specific areas of visual cognition. Such declines are accepted a s essentially axiomatic in a number of functional areas, including the ability to manipulate images in mental %pace" (e.g., Gaylord & Marsh, 1975).the ability to remember spatial relations (e.g.. Light & Zelinski, 1983;Pezdek, 1983).and the speed of cognitive functions (e.g., Birren. 1974). Cognitive declines with age have been documented so thoroughly that few investigators question their existence or importance; current research tends to address the severity or impact of given deficits, rather than their existence. As new information about aging and cognition accumulates, however. it is becoming more critical to focus attention on the abilities retained by the elderly, as well as upon the declines that occur with age. It is necessary to examine not solely what the elderly tend to do when compared with young adults, but also what they can do, given the appropriate circumstances. It is therefore important to develop and employ experimental methods which permit the analysis of the abilities retained throughout the lifespan. One set of methods which has proven to be highly useful for such analyses derives from the developmental theory of Gollin (e.g, 1965. 1981,1984,1985;Gollin & Saravo, 1970).Research designs in both developmental and nondevelopmental research often involve only one level of either subjects or tasks (Gollin & Saravo. 1970,p. 59). Subjects of different ages may be tested within only one task framework, or subjects of the same age may be tested using several tasks. Gollin proposes that more comprehensive information may be obtained through the use of experimental designs involving the

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systematic variation of both subject and task characteristics within the same experimental framework, This age-by-task approach "mandates a research methodology that seeks to access the central processes available to organisms, to plot their polyphasic relations over ontogenesis, and to spec@ the successive configural characters of organism-environment patterns.. .The essential feature of those methods is the recognition of the constructive. organizational character of central processes, their patterned interrelations and variation during ontogenesis, and their species-specific qualitative and temporal properties" (Gollin, 1981, p. 246-247). It is especially important to note the phrase "central processes available to organisms" in the above. Within Gollin's research framework, the investigator selects task characteristics and organismic characteristics (such a s age) according to theoretical considerations, and varies them systematically in an age-by-task manipulation. If these variables are properly chosen, the investigator may obtain a n understanding not only of what individuals of a given age tend to do on a given task, but also of what they are able to do when task circumstances are reconfigured. It becomes possible to isolate specific characteristics of the task environment which are optimal or suboptimal for the performance of individuals of dflerent ages. Gollin's approach has been employed in a number of areas in comparative and developmental psychology, including the developmental analysis of learning in rats (e.g., Rudy, Vogt, & Hyson, 1984). the study of the development of conceptual-verbal mediational systems in young children (e.g., Gollin & Garrison, 1980). and other areas of child development research. A particularly pertinent example of these applications stems from research on visual cognition in children, specifically in the area of spatial perspective-taking. The original studies of spatial perspective-taking (Piaget & Inhelder, 1967. original study 1948) involved the "three mountain task." in which children were asked to examine an array composed of three papier-mache mountains which differed in several features. A doll was also placed at the array, but at a different orientation from that of the child. The child was then asked to choose the perspective which represented

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the doll's "view" of the array. Several kinds of perspective representation were used in these experiments. It was found that younger children tended to make "egocentric" responses, choosing perspectives which represented the view that they themselves saw, rather than choosing the view that represented the doll's true "viewpoint." F'rom these results, Piaget and Inhelder (1967) further observed that the ability to engage in nonegocentric spatial perspective-taking improved over the course of child development. According to Piaget and Inhelder. the possession of virtually no ability to take perspective (around age 4) gives way to an evident recognition of some need for perspective-taking. followed by actual attempts to separate viewpoints. Around the age of 9 or 10 years, children were observed to achieve a more complete understanding of spatial perspective-taking, and were in general able to employ perspective-taking abilities similar to those of adults. These findings gained broad acceptance, and were widely replicated in subsequent years (see Laurendeau & Pinard, 1970). However, further studies reflned these ideas. Spatial perspectivetaking abilities were shown not only to depend on the age of the child, but also on the characteristics of the tasks employed to test them (e.g., Borke, 1975; Fishbein, Lewis, & Keiffer, 1972; Gzesh & Surber, 1985: Huttenlocher & Presson. 1979; Masangkay, McClusky. McIntyre. Simms-Knight, Vaughn, & Flavell. 1974; Olson, 1970 Presson, 1980: Shantz &Watson, 1970). For example, Brodzinsky, Jackson, and Overton (1972). using a task framework similar to the three-mountain paradigm, showed that masking stimulus arrays during the child's attempt to judge perspective improved perspective-taking performance. Walker & Gollin (1977) found that masking of a dollhouse array "reduced egocentric errors among 4-year-olds, producing a pattern of responses more typical of that observed among older children" (p. 343). The complexities of the child's perspective and of the doll's line of regard (e.g., corner versus side views of dollhouse arrays) have also been shown to interact with the ages of the children studied (Schachter & Gollin, 1979; Walker & Gollin, 1977): younger children tend to have more difficulty with perspective-taking when dealing with more complex views, a s well as with doll positions from which the doll's "view" is more complex.

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A later study (Gollin & Sharps, 1987) demonstrated that the availability of strategy, in the absence of any physical alteration of the stimulus materials, also influenced spatial perspective-taking in young children. When children were asked first to generate an egocentric view of a dollhouse array, and then to demonstrate the doll's view, young children were able to respond nonegocentrically. The salient findings of this research, for present purposes, may be summarized succinctly: spatial perspective-taking in children was not shown to be a function of subject age alone. Rather. it was shown to be an interactive function of subject age and task type. The performance of younger children, in whom refined spatial perspective-taking abilities were not expected, could be enhanced significantly, either by altering the physical characterstics of the stimulus array, or by altering the strategy with which the child approached the problem. These results further indicated that an investigator might also flmft the performance of younger children, by manipulating strategy or stimulus characteristics to make perspective-taking more difficult. This is a critical polnt. If experimentation on spatial perspective-taking had remained within the strict parameters of the traditional three-mountain task, it might have been assumed that young children were simply incapable of perspective-taking. If, on the other hand, research in this area had begun and ended with task frameworks which were optimal for the performance of younger children, the actual organismic changes that occur through the course of child development might never have been detected; currently, it might be believed that development produces no qualitative changes in the young child's perspective-taking abilities. The use of a wide range of tasks, and of systematic age-by-task analyses (e.g., Schachter & Gollin, 1979; Walker & Collin, 1977). however, has precluded these conclusions; it is now understood that spatial perspective-taking depends both upon age and task characteristics, rather than upon either alone. Precisely the same type of issue arises with research on the visual cognitive abilities of young and elderly adults. In general, experimental paradigms in this area have not systematically manipulated age as a variable against task types. This raises the same problem obsenred in studies of spatial perspective-taking: any

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given study, no matter how well-designed. provides only information about the performance of older people within the range of tasks examined. Without specific attention to task selection, critical issues of plasticity and of the availability of abilities are left unevaluated. We can best address these issues by including a spectrum of experimental tasks, selected systematically against the variables of interest, and administering this systematic series of tasks to samples drawn from across the adult lifespan. One area of aging research within which these developmental methods have been useful is the study of memory for spatial relations, Spatial memory is obviously of considerable importance to living independently, a concern to the majority of the aged. Much research on spatial memory has employed some variant of a paradigm in which a group of items (such as toy objects, pictures. letters or printed words) are arranged in an array in some sort of context (such as a room, a map. a matrk of boxes, or a model town). The m a y of items is presented to the research subject for encoding. After some period of time, the subject is asked to demonstrate memory for the locations, and in some cases the identities, of the items employed. The kinds and scales of the task contexts used in this work have been extremely variable. Reviewers (e.g.. Weatherford. 1985) have distinguished to some extent between large- and small-scale spaces, and Siegel, Herman, Allen, and Kirasic (1979) have shown that one may cautiously generalize between studies employing test spaces of dif€erent scales. However, no systematic evidence concerning the extent of such generalizability is presently available. A number of studies have been focused upon the developmental course of spatial memory across the adult lifespan. Perlmutter, Metzger, Nezworski, and Miller (1981)examined the memory of young and elderly adults for the locations of buildings on a schematic map. Age-related declines in spatial memory were observed: sixty-four year-olds recalled locations significantly less accurately than did twenty year-olds. Park, Puglisi. and Lutz (1982) examined young and elderly subjects' recall of the left-right positions of pictures presented singly or in pairs. Age-related declines were also observed in this study. Similar results were obtained by Park, Puglisi. and Sovacool (1983)in a study of

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memory for line drawings and printed words located on a large card, and by Pezdek (1983)in a study of memory for items placed in a six-by-six square matrix. Other investigators also observed agerelated declines in spatial memory using schematic maps (Light & Zelinski. 19831, chess problems (Charness. 1981). urban landmarks (Evans. Brennan, Skorpanich. & Held, 1984). slides of a building interior (Weber. Brown, & Weldon. 1978), and the Tactual Performance Test of the Halstead Neuropsychological Battery (Moore, Richards, & Hood, 1984). These studies, taken in combination, seem to provide overwhelming evidence for agerelated decline in spatial memory. However, in a few studies, a somewhat different pattern emerged. McCormack (1982)found no difference in spatial memory between young and elderly subjects in a study of memory for the location of words printed in vertical arrangements or in quadrants on a large card. Waddell and Rogoff (1981) conducted a study in which middle-aged and elderly women were asked to remember the locations of small objects, which were placed either in an array of cubicles or in a realistic, small-scale panorama. Elderly subjects exhibited significantly poorer spatial memory performance than did middle-aged persons in the array condition, but did not do so in the panorama condition. This study provided evidence that the relationship between aging and spatial memory may not be fixed and determinative. Rather, the characteristics of the task employed may differentially influence the performance of young and elderly subjects. Results consistent with this conclusion were obtained (Sharps & Gollin, 1987a) in a study of memory for the locations of objects placed in constrasting contexts. This study explicity employed Gollin's age-by-task model. A large room was furnished with unconventional "structures," including cable-spools, piles of boards, piles of fabric, and so on. The unconventional context was intended to obviate the potential influence of the experiences of young and elderly subjects with different kinds of real-world spaces. A precise. black-and-white schematic map of that room was drawn. Subjects were asked to remember the locations of common objects placed either in the room or on the map. Within the map condition, elderly subjects performed at significantly lower levels

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on this task than did college-aged control subjects, a finding consistent with most of the literature in this area. However, within the room condition, the spatial memory of the elderly was significantly enhanced relative to that of the younger subjects. This indicated that spatial memory in young and elderly adults was in fact task-dependent; some characteristics of the task contexts employed differentially influenced the memory performance of the two age groups. A follow-up experiment was conducted, using table-sized arrays in which the structures were again blocks, piles of fabric, and so on. These arrays varied in the "visual distinctiveness" of component "structures," from a black-and-white schematic map on which the structures were merely line drawings, to a "painted model" on which structures were three-dimensional and differently colored. The "room" condition of the previous experiment was also replicated. It was found that elderly persons performed at significantly lower levels than did young subjects when the objects to be remembered were placed on the schematic map. However, the performance of the elderly improved significantly, both absolutely and relative to that of younger subjects, when color, dimensionality, or both were added to the spatial memory arrays (Sharps & Collin, 1987a). These results demonstrated that age-related deficits in spatial memory are more complex than might at first be apparent. It would appear that the age-related declines generally obsenred in spatial memory may be increased within more visually diverse task contexts, and reduced within contexts whose elements are less visually distinctive. Evidence is now emerging, both from the author's laboratory and from others (e.g.. Park, Cherry. Smith & Lafronza, in press), that these specific beneficial effects of contextual distinctiveness on the spatial memory of the elderly may be confined to specific procedures or populations. For example, no such effects are observed when items to be remembered are identifiably related by category (Sharps, 1990). However, when the procedures and samples of Sharps and Gollin (1987a) were employed, and an age-by-task analysis was conducted, spatial memory performance was shown to be a function both of age and task type, This indicates that studies of aging and spatial memory may benefit from specific consideration and systematic variation

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both ofthe ages of the subjects employed and of the tasks used to test them. Similar benefits of the use of age-by-task methods may be observed in other areas of aging and visual cognition as well, including the study of mental imagery abilities and the influence of the aging process on these abilities. In recent years, the study of mental imagery has become a particularly active area, in part because of the interest intrinsic to the subject, and in part because mental imagery paradigms may be used to address a variety of issues, such as the rate at which cognitive processes occur. Many of these issues are critical in the psychology of aging, and numerous investigations of the relationship of the aging process to mental imagery performance have been made. However, the bulk of the investigations reported in the literature have not systematically evaluated the influences of age- and task-related factors against each other. Since Gollin's age-by-task methods have been shown to be of use in the closely-allied area of aging and spatial memory research, it was felt that such an approach to aging and mental imagery might also be productive. What follows is a brief review of some of the most important findings, for present purposes, in the area of aging and mental imagery. Special attention is given to the study of mental image rotation, one of the most productive research frameworks employed in the area. A new experiment on aging and mental image rotation, based on this review and employing the age-by-task method described above, is also reported. MENTAL IMAGERY: BACKGROUND AND PERTINENT FINDINGS

Scholarly attention to mental images dates back at least to the time of Aristotle. Mental imagery was a major focus at the advent of scientific psychology, as well: Wundt (e.g.. 1894) regarded an understanding of mental imagery as crucial to comprehension of the elements of consciousness which constituted the subject matter of the structuralist school. However, imagery fell from favor within the mainstream rather quickly. The study of imagery was especially shaken by the idea of "imageless thought." As is well known, Watson attacked the idea of "mind" in a seminal paper

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(1913). The process of thinking, in Watson's view, could most parsimoniously and accurately be considered without reference to the idea of images: within Watson's formulation, imagery was subsumed by subvocal thinking, The images which become subjectively evident when one thinks about specific experiences or events were. for Watson, the result of being able "to carry on a conversation about (events) either to ourselves. ,. or with someone else" (Watson, 1928,p. 77). Watson furthermore held that, since images could not be proven to exist. they were therefore either nonexistent or unimportant for a science which must focus on the objectively verifiable alone. As Kosslyn (1980)wrote, Watson "seems honestly to have believed that imagery was simply talking to oneself" (p. 455). The behaviorist perspective advocated by Watson dominated experimental psychology through the middle years of this century, and, not surprisingly, thoughout this period little empirical interest was paid to questions of mental imagery. However, with the rise of modem cognitive psychology in the latter half of the century, more references to the subject began to appear once again. For example, work by Paivio on imagery and verbal processes, culminating in the dual coding theory (see Paivio. 1971, 1986,for review discussions), focused attention on evidence for the existence of imagery a s a process functionally autonomous from. if interactive with, verbal cognition. There are major differences between the mental imagery research of the present time and that of the turn of the century. In part as a result of the behaviorist emphasis on strict scientific method, post-behaviorist researchers have paid far more attention to methodology than previously, as well as to the creation of more objectively verifiable methods of measuring performance on mental imagery tasks. One of the most important of these methods has been the use of mental chronometry, the measurement of how much time is required to perform a given cognitive manipulation. An excellent example of the use of mental chronometry is seen in the work of Kosslyn and colleagues (e.g., Kosslyn, 1973;Kosslyn. Ball, & Reiser, 1978)on the scanning of images. Kosslyn's work demonstrated that the time required to scan an image varies a s a function of the distance to be scanned. This research was criticized

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on the grounds that results might have reflected the subjects' tacit beliefs or knowledge about scanning rates, rather than the process of scanning itself (e.g. Pylyshyn, 1981; Intons-Peterson, 1983). However, these criticisms were answered by subsequent research (e.g., Reed, Hock, & Lockhead. 1983) in which "tacit knowledge of scanning rates" could not reasonably have affected performance. The bulk of the available research seems to support Kosslyn's contention that subjects scan images in a manner analagous to that in which they scan percepts. This research has contributed substantively to the view that images are not merely manifestations or special cases of verbal activity. Another use of mental chronometry in the study of imagery is to be found in the work of Shepard and colleagues. In 1971. Shepard and Metzler presented a mental chronometry paradigm involving the mental rotation of images. The stimulus materials employed were pairs of abstract figures. each composed of ten white cubes, arranged in configurations involving different right-angle turns (see Figure 1). The two figures were either identical in configuration or were stereoisomers, and were rotated relative to one another. Angles of rotation were varied systematically. and images were rotated either in the picture plane or in depth. The pairs of figures were shown sequentially to adult subjects, who were asked to decide whether the figures were the same or were difTerent (stereoisomers). The reaction times of subjects in this experiment increased as a function of angular rotation, both for picture plane and depth rotation, providing evidence that subjects do in fact treat mental images a s though they are "real." The manipulation of mental images was shown to be a process that takes time, and subjects required more time for tasks requiring more manipulation. Further studies (Cooper & Shepard, 1973a,b),in which subjects saw rotated alphanumeric characters, and were required to determine if a given character was "normal" or a mirror image of the normal configuration, supported this hypothesis: the average time to make this determination increased with increasing angular departure from the character's normal orientation. However, when subjects were provided with information on the upcoming character and its orientation, reaction times dropped to about 400 milliseconds

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Figure 1.

figures.

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A Shepard-Metzler item, requiring rotation in depth of cube

regardless of orientation. Subjects reported that, when provided with this information, they prepared for the rotated stimulus items by "imagining" normal versions of the characters rotated into the orientations provided, and were then able to test the match of character to orientation. The results of these studies, and of subsequent research employing a wide variety of stimulus materials and paradigm variations (e.g.. Cooper, 1975, 1976;Cooper & Podgorny. 1976; Corballis. 1986;Corballis, Nagourney, Shetzer, & Stefanatos. 1978; Corballis. Zbrodoff, & Roldan, 1976; Eley. 1982; Kubovy & Podgorny, 1981; Metzler & Shepard. 1974; Petrusic, Varro, & Jamieson, 1978: Steiger & Yuille, 1983;Tapley & Bryden, 1977: White, 19801, were consistent with subject self-reports of the rotation of images. Mental image rotation appears to be a real-time process, within which rotations through larger angles require more time than rotations of smaller magnitude.

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The work of Shepard. Cooper and colleagues provided more than validative evidence for the real-time nature of mental imagery processes. The mental image rotation (MIR) paradigm also provided an excellent method of examining issues in the study of aging and mental imagery. A variety of studies (e.g.. Elias & Kinsbourne, 1974:Plude. Milberg, & Cerella, 1986;Salthouse, 1987) have focused on questions of imagery, spatial abilities involving imagery, and aging. Generally, some age-related declines in performance have been observed. For example, there is considerable evidence for declines in cognitive speed with advancing age (Birren. 1974).probably due to a general age-related slowing of the central nervous system (also see Cerella. 1985. and Salthouse, 1982, 1985). Specifically, Birren holds that the aging process is accompanied by a generalized, physiologically-mediated slowing of central nervous system functioning. The behavioral artifacts of this slowing are expected to include diminished speed of behavior and diminished efficiency of performance in other task contexts involving speed requirements. Mental image rotation procedures have been used to address both cognitive speed and the accuracy of decisions made under speeded conditions. The results have in general agreed with Birren's hypothesis. However, the results of these studies have not been entirely consistent. The most critical findings, for present purposes, are reviewed below. Gaylord and Marsh (1975)presented young (20year-old) and elderly (65-72year-old) male subjects with Shepard-Metzler cube figures on a tachistoscope. Depth rotation figures were employed. There were significant declines with age in both the accuracy of decisions and the speed at which they were made. Although several possible interpretations of these data could be made, these findings are consistent with Birren's (1974)hypothesis of generalized CNS slowing. Jacewicz and Hartley (1979)provided data which have been interpreted as conflicting with the work of Gaylord and Marsh, and with the speed-loss hypothesis. They presented young (22 year-old) and older (56year-old) English-speaking subjects with letters from the familiar Roman or from the Greek alphabet. In each trial, a letter was presented in its normal orientation. This was followed by the presentation either of the same letter or of its mirror image,

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rotated in the picture plane with reference to normal orientation. The experimental design allowed the separation of 'basic speed" (obtained from the latency of responses when two objects are presented at the same orientation) from the rate of actual image manipulation (rotation). The letters were rotated at angles varying from zero to 180 degrees. When the familiar Roman letters were employed as stimulus items, the performance of young subjects did not differ from that of the elderly, in basic speed or in rate of image rotation. When unfamiliar Greek letters were employed, the elderly were slower than the young subjects in their basic speed. However, the rate of manipulation did not differ with age. Decision accuracy did not dmer significantly between age groups. The results of this experiment were construed as failing to support the notion of generalized CNS slowing with age, and as a failure to replicate the work of Gaylord and Marsh (1975). These findings were strongly criticized by Cerella. Poon, and Fozard (19811, who employed the stimulus materials of Jacewicz and Hartley (1979) to test, in a standard mental image rotation task, a population more similar to that of Gaylord and Marsh (1975). It was noted that Jacewicz and Hartley employed elderly experimental subjects who were currently enrolled in college classes, and who were on average younger than those employed by Gaylord and Marsh. Cerella et al. (1981) tested elderly subjects ranging in age from 66 to 77 years, recruiting not from college classes but from Boston area housing projects. Although decision accuracy did not differ significantly between age groups, this study resulted in a n imposing 96% age-related decline in speed of response. Cerella et al. concluded that the failure of Jacewicz and Hartley to find age differences in their procedures resulted from their use of "unusually young and active" subjects (p. 621). Cerella et al. further concluded that their findings provided strong support for the generalized CNS slowing postulated by Birren (1974). It is important to note that subject characteristics were not manipulated in the work of Cerella et al. The idea that differences in the activity level and education of specific subject groups influences performance on imagery tasks remains hypothetical; controlled studies of specific subject-related variables would be necessary to test this hypothesis. However, considered together

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with the studies of Gaylord and Marsh (1975) and Jacewicz and Hartley (19791, these results indicate that subject-related variables may be an important point for future study, and may have profound influences on cognitive functioning generally and mental imagery particularly. A variety of influences, including demographic variables, life-style, or health-related factors, may have contributed to differences in performance between the populations of Cerella et al. and Jacewicz and Hartley. Furthermore, Cooper (1982) has shown that there are important individual Werences in the cognitive style with which problems of mental image rotation are approached: different individuals tend to take either a n analytic or a wholistic approach to MIR problems, which influences performance significantly. In light of these results, it is clearly prudent within any given experimental framework to consider the possibility of subject-related influences on performance. Like Cerella et al. (1981). Berg, Hertzog, and Hunt (1982) provided strong support for generalized CNS slowing. "Palmer figures", which are stick-like configurations generated by connecting points on a 3 x 3 dot matrix (see Palmer. 1977). and which are rotated within the picture plane, were employed as stimulus items in a mental rotation task. Significantly increased reaction times with age were observed. However, no age differences were obsenred in error rates. The Primary Mental Abilities Figures Test (PMAF). a test of spatial ability, and the Nelson-Denny Vocabulary Test (NDV), a test of verbal ability, were also administered. Reaction times and the slopes of reaction time/rotational angle functions were significantly correlated with performance on the spatial abilities test. but not with performance on the verbal test. Subjects in this study were tested over four consecutive days. Significant effects of repeated exposure to the stimulus materials were observed: reaction times and the slopes of reaction time/rotational angle functions decreased for both young and elderly adults, although age differences were neither eliminated nor systematically reduced. The repeated exposure of the stimulus items in this study occured over a period of four days; this research did not address putative effects of long-term familiarity or practice

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on performance, Therefore, these results should not be construed as ruling out possible age-differential effects of longer-term familiarity. However, within the parameters of this study, the findings of Berg. Hertzog 'and Hunt indicated that age-related daerences in mental rotation reaction times did not result from the novelty or unfamiliarity of the stimulus items. As noted above. these results are consistent with the generalized speed-loss hypothesis of Birren ( 1974). Herman and Coyne (1980)addressed mental image rotation from a somewhat different perspective. They asked subjects in three age groups (20-, 60-, and 70-year olds) to engage in a spatial perspective-taking task, specifically the determination of the locations of target objects from imagined points of reference. Subjects were also asked to imagine the rotation of a n array of objects relative to their present position. Interestingly, no age difference was found in the rotation task. However, the spatial perspective-taking task produced better performance in the young than in the older subjects. This indicated that age differences in mental Imagery abilities were task-dependent. If the two tasks employed in this study had produced the same pattern of results for young and elderly subjects, this work might have been considered support for the idea of a unitary cognitive process of mental imagery, within which age-related deficits could be safely charted. Instead, the disparate pattern of results actually obtained indicates that the constellation of abilities which constitute mental imagery are just that: a constellation of cognitive abilities, rather than a unitary process. The findings of Herman and Coyne (1980)regarding task dependency also reinforce the idea that, even in the absence of evident subject-related factors such as those cited by Cerella et al. 11981).conflicts of results are not necessarily irreconcilable unless they result from precisely the same procedures. Evident discrepancies between the findings of different studies may arise as a function of differences in the experimental tasks employed. It is therefore important to test. systematically, the influences of various task types against the influences of aging within the general area of mental imagery. It should be pointed out that this

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type of analysis is exactly what Collin's developmental, age-by-task approach is designed to accomplish. Krauss. Quayhagen. and Schaie (1980) used several tasks to address mental imagery abilities. Elderly subjects (aged 64 to 76 years) were tested with the standard, paper-and-pencil Spatial Relations Test of the Primary Mental Abilities (PMA) test (Thurstone. 1962, revised edition), with slide projector versions of the PMA test. and with a mental image rotation test involving "Attneave-Arnoult" (AA) stimuli. These stimulus items are irregulary shaped, two-dimensional, faceted solid black figures, generated and used by Cooper (e.g.. 19751, and derived by the method of Attneave and Arnoult (1956). Along with the speed of mental rotation, memory for the test stimuli was also evaluated. The results of the AA stimuli test indicated that memory for test stimulus items was important for performance at higher levels of MIR performance, although less so for subjects who performed more poorly. In other words, memory for items was a better predictor of performance in the upper portion of the performance curve than in the lower portion. It was also found that subjects experienced more difficulty with the paper-and-pencil PMA than with the projector versions: although the proportion of correct responses to the number of items attempted did not differ significantly between the PMA task types, the absolute number of correct responses was significantly higher in the projector conditions, indicating that performance was inhibited by the "mechanical barriers present in paper-and-pencil tasks" (p. 205). This study sewed as additional evidence that the manifestation of imagery abilities is task-dependent. Clarkson-Smith and Halpern (1983)tested three age groups of women (aged 18-28, 50-60, and 70-80 years of age) in a mental image rotation paradigm using "semi-abstract" figures, drawings representing a swan, a boat, a face or a witch on a broom. Meaningful or nonmeaningful labels were assigned to the figures. The effect of meaningful labels was to decrease errors in decision for older subjects, indicating that verbal mediation may be used to compensate for age-related deficiencies in spatial abilities. However, older subjects in this study did make more errors than did younger subjects. This finding is congruent with the results of

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Gaylord and Marsh (1975),who found that more errors were made by elderly than by young subjects when Shepard-Metzler cube figures were employed. However, these findings differ from others In the literature (e.g.. Berg et al.. 1982: Cerella et al., 1981;Jacewicz & Hartley, 1979). As discussed above, the results of these latter investigations indicated that young and elderly adults did not tend to differ significantly in the accuracy of their rotation-based decisions. The results of Clarkson-Smith and Halpern (1983) and of Gaylord and Marsh (1975),when compared with other research in the area, indicate that both the accuracy of mental image rotation decisions and the speed of mental rotation are influenced by task characteristics. Sharps and Gollin (1987b).using Shepard-Metzler cube figures rotated in depth, addressed the effect of speed requirements on the speed and accuracy of mental image rotation judgements in young and elderly adults. Mental image rotation tasks in general require subjects to work as fast as possible. In this study, young and elderly adults were asked to work either as rapidly as possible, a s accurately as possible, or to balance speed and accuracy. It was found that when asked to work a s quickly a s possible, elderly adults performed at the same rate of speed as young subjects, but made significantly more same/different judgement errors. When asked to respond accurately, without reference to speed, elderly adults responded with the same decisional accuracy a s young subjects, but required more than twice as much time on average to reach these decisions. When asked to balance speed and accuracy, the elderly responded with the same decisional accuracy a s younger persons, although, again, older individuals took longer on average to make these judgements. Interestingly, the elderly performed at the same level in both the accuracy and speed/accuracy conditions, although they used twice a s much time to arrive at decisions in the former condition. Subjective self-reports Indicated that older subjects used more caution in the accuracy condition; in the absence of speed requirements, they reported taking additional time to check their work. The results of this study are consistent with Birren's (1974) speed loss hypothesis, in that the elderly exhibited slower reaction times than the young when speed requirements were imposed.

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However, since the elderly were substantially slower in the accuracy than in the speed/accuracy condition, but performed at the same level of accuracy in both of these conditions, part of the observed speed loss was probably due to simple caution. These findings may help to explain some of the discrepancies among results related to age-related speed loss in mental image rotation. Evidently, observed speed loss may result from a combination of factors, such a s caution and generalized slowing, rather than from one factor or set of related factors alone. These results add to the evidence that it is important to examine the possible sources of performance differences between subjects of different ages, rather than to assume that such differences reflect the influence of particular age-related variables. Herman and Bruce (1983) also addressed the question of age differences in MIR abilities, using Shepard-Metzler cube figures as stimulus items. However, instead of the tachistoscopic presentation often employed, Herman and Bruce used the paperand-pencil version of the Shepard-Metzler test developed by Vandenberg (e.g., Vandenberg & Kuse, 1978). In this version. each "problem" consists of an original figure to the left of a vertical line, and four figures to the right of the line. Two of the figures match the original but are rotated in depth between zero and 180 degrees. The other two are foils. Five of these problems are presented on each of three pages. Subjects are provided with sample problems, and are then instructed to select the two figures which match the original as quickly as possible. In this experiment (Herman & Bruce, 1983).young adults (mean age 25.3 years) performed significantly more accurately than did elderly adults (mean age 65.3 years). Herman and Bruce noted that this result differed from those of Berg et al. (19821, Cerella et al., (1981).and Jacewicz and Hartley (1979). However, age differences in accuracy were also observed by Gaylord and Marsh (1975).as well as by Wilson, DeFries, McClearn, Vandenberg, Johnson, and Rashad (1975). who employed the Vandenberg version of the test. The evident discrepancy in results among these studies was attributed by Herman and Bruce to stimulus factors; it was noted that the investigators who observed age-related declines in accuracy employed some variant of the original Shepard-Metzler cube

316

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figures, which involve the "visualization of a three-dimensional rotation from a two-dimensional figure" (p. 84). Those investigations which involved no such declines employed stimulus materials which required only the visualization of a twodimensional rotation from a two-dimensional figure. Herman and Bruce concluded that the greater "complexfty" of the cube figures was responsible for this discrepancy in findings. This is consistent with current theory: Cerella. Poon, and Williams (1980),in a survey of the literature, found that increasingly complex tasks in general result in increasing reaction times for older individuals. probably as a consequence of the "proportional slowing of the mental functions of the elderly" (p. 332). Cerella et al. (1980)also suggested that general CNS slowing should result in the slowing of all central cognitive processes approximately to the same degree. Therefore, the response times of older persons on any given task should increase as a function of the response times of younger individuals. The results of Herman and Bruce (1983)suggest that this "complexity hypothesis of Cerella et al. applies to not only the speed, but also the accuracy of spatial information processing" (p. 841. Since abundant literature suggests that mental image rotation is task-dependent, stimulus complexity would appear to be an important task characteristic to examine. Puglisi and Morrell (1986)conducted a study which was particularly pertinent to this issue. In a standard MIR procedure, young adults (mean age 21.7years) and elderly adults (mean age 70.9 years) were presented with pairs of three-dimensional toy cowboys, either the same or mirror images of each other, by means of a tachistoscope adapted for the presentation of three-dimensional objects. Significant declines in both reaction time and decision accuracy were observed with age. Also, the best fitting linear equation for these data provided slope and intercept values for the reaction time/rotational angle function which were consistent with the complexity hypothesis of Cerella et al. (1980). These findings fit well with the hypothesis of Herman and Bruce that the complexity hypothesis extends to accuracy as well a s to speed of response. Three-dimensional cowboys, rotated in depth, are complex stimulus items by comparison with Palmer or AA figures rotated in the picture plane, and subjectively appear more similar

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in complexity to depth-rotated Shepard-Metzler cube figures. The data obtained from the cowboy stimulus materials were much more similar to those obtained with Shepard-Metzler depth items than to those derived from picture plane rotations. These data therefore supported the CNS slowing hypothesis of Birren (1974)and the complexity hypothesis of Herman and Bruce (1983). The results of studies reviewed thus far, when examined in combination, suggest that mental image rotation performance in young and elderly adults is task-dependent. The complexity of stimulus items appears to be one of the task-related factors which influence the performance of young and elderly subjects within a variety of MIR paradigms. What precisely constitutes "complexity" of stimulus items in a mental image rotation task? Several investigations have been directed toward the resolution of this issue. The complexity of AA figures, which rotate in the picture plane, is fairly easy to calculate. "Perceptual complexity depends strongly upon the number of points which determine inflections on the perimeter of the form" (Cooper, 1975.p. 23-24.Based on Attneave, 1957;Attneave & Amoult, 1956;Vanderplas & GaIvin. 1959). In other words, a star-shaped figure is more complex than a triangular figure, because more points and facets are present in the former. Cooper (1975).in a study of non-elderly adult subjects, found that whereas reaction time was a function of increasing rotational angle, the complexity of the figures employed did not influence reaction time, either in terms of the slope of the reaction time/rotational angle function or of its intercept. Cooper and Podgorny (1976)examined the mental rotation of AA figures, requiring subjects to discriminate previously learned versions of the figures from rotated distractor versions. Subjects were provided with advance information on the identity and orientation of the upcoming figure, and were instructed to prepare for the presentation of the test figure by rotating a mental image of that figure into the designated orientation. The time needed for this preparation was a function of the angular rotation of the test figure from the previously-learned orientation of that figure. However, figure complexity did not influence reaction time.

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These results differ somewhat from those of Hochberg and Gellman (1977). Using "crossbeamed" MIR stimuli (present author's designation), which somewhat resembled irregular telephone or telegraph poles, they found that reaction times varied not only with the angular rotation of the stimulus figures, but also with the presence or absence of "salient landmarks," prominent crosshatches or processes. Those figures with such landmarks had lower rotational angle/reaction time functions than those "in which these features have been made less distinguishable" (p. 25). The results were not attributed "to the greater complexity, per se. of the latter, inasmuch as Cooper (1975) found no such effects with the Attneave-Arnoult shapes" (p. 25). Rather, Hochberg and Gellman attributed these findings to the "relative inaccessibilities.. .of informative features" (p. 25). It would seem that such relative inaccessibilities might contribute to overall levels of complexity. However, whether or not inaccessibility is specifically related to complexity, the Hochberg and Gellman results demonstrate the influence of stimulus item configuration on mental image rotation. Several additional studies have clarified different facets of the complexity issue. Folk and Luce ( 1987) examined the rotation of AA figures, and found that although reaction times for dissimilar stimuli were not influenced by figure complexity. reaction times for more similar stimuli, with which discrimination should have been more difficult, increased as a function of stimulus complexity. These results were interpreted to mean that subjects rotated only incomplete images when stimuli were dissimilar, and that complexity effects resulted when subjects had to rotate entire images to come to their decisions. Bethell-Fox and Shepard (1988). using patterns of filled-in squares on 3 x 3 square matrices as stimulus items, obtained complexity effects on rotation times, although these effects were in general eliminated with practice. Yuille and Steiger (19821,using Shepard-Metzler cube figures as stimuli, found that figure complexity influenced the speed of mental image rotation. However, when featural redundancy was ignored in the generation of figures, the complexity effects were not obtained. In other words, additional complexity did not influence the speed of mental image rotation when the complicating features were not necessary to accomplish the rotation task.

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At least two studies have addressed complexity effects in mental image rotation not from the standpoint of item complexity, but rather from the standpoint of rotational complexity. Jolicoeur. Regehr. Smith. and Smith (1985) employed Shepard-Metzler cube figures in a MIR task, either in their three-dimensional forms, rotated in depth, or with their internal line segments scrambled to form two-dimensional figures, rotated in the picture plane. Threedimensional rotation was found to require significantly more time than two-dimensional rotation for angles greater than 60 degrees, although this effect was not observed for smaller angles. Shepard and Metzler (1988) compared the results of tasks employing Shepard-Metzler cube figures, rotated in three dimensions, or AA figures, rotated in two dimensions. Either both forms were present, and one rotated "into" the other (as in the task used by Shepard 81 Metzler, 1971). or a single form was rotated into congruence with a previously learned original not actually present during rotation (as in the task used by Cooper, 1975). The rate of mental rotation was found to be significantly (about three times) higher for the singlestimulus than for the dual-stimulus task. Three-dimensional shapes required more initial encoding time than did twodimensional figures, although the results suggested that once threedimensional objects were encoded. their rotation could be imagined as rapidly as the rotation of two-dimensional shapes. This study, in agreement with the work of Jolicoeur et al. (1985). indicates that the dimensionality of the mental rotation required in a given task. as well as the characteristics of the stimulus items themselves, plays a powerful role in the determination of performance. The results of the studies considered above are summarized in Table 1. An examination of this literature indicates that the methods used to establish the relationship of rotational angle to reaction time, under different subject- and task-related conditions, have varied enormously. For example, some studies have reported only reaction times, whereas others have reported findings in terms of the slopes and intercepts of reaction time/rotational angle functions. These functions are particularly important. If the speed-loss hypothesis of Birren (1974)is correct, and much evidence suggests that it is. then different permutations of subject- and taskrelated factors might be expected to give rise to different

Table 1 Summary of Studies of Mental Image Rotation Discussed in

Authors and Year Shepard & Metzler. 1971 Cooper & Shepard. 1973 a,b Gaylord & Marsh, 1975 Jacewicz & Hartley, 1979 Cerella, Poon, & Fozard. 1981 Berg, Hertz~g.& Hunt, 1982 Herman & Coyne, 1980

Stimulus or Task Type

Shepard-Metzler Alphanumeric Shepard-Metzler Alphanumeric Alphanumeric Palmer Perspective-taking Array Rotation Krauss, Quayhagen, & Schaie, 1980 Several Clarkson-Smith & Halpern, 1983 "Semi-abstract" Sharps & Gollin, 1987b Shepard-Metzler Shepard-Metzler Herman &Bruce!. 1983 Wilson et. al. , 1975 Shepard-Metzler Puglisi & Morrell, 1986 Toy cowboys

the Text [in order of appearance)

Effect of Age

Effect of Stimulus Complexity

Factors of Special Importance

---Population? Population? Familiarity Task type Task type Memory for stimuli Meaningful labels Speed requirements Speed vs. accuracy

Table 1 (continuted)

Authors and Year Cooper, 1975 Cooper & Podgorny. 1976 Hochberg & Gellman, 1977 Folk & Luce, 1987 Bethell-Fox & Shepard. 1988 Yuille & Steiger, 1982 Jolicoeur, Regehr. Smith &smith, 1985 Shepard & Metzler. 1988

Stimulus or Task Type AA AA

"Crossbeam" AA Square matrices Shepard-Metzler

? = Uncertainty

* =Quallflcation; seetext

N N ? Y

Y* Y*

Shepard-Metzler

Y*

Shepard-Metzler

Y,

&AA

Y = Significant effect N = No detected significant effect

Effect of Age

Effect of Stimulus Complexity

Factors of Special Importance

---Informative figures Similarity of figures Practice Featural redundancy Dimensionality of rotation Dimensionality of rotation

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Sharps

characteristic functions. These could theoretically be used to develop a systematic understanding of the interplay of the cognitive processes in question. Additional systematic analysis is needed to establish these functions, and the degree to which specifc processes are in fact reflected by characteristic functions. Even in the absence of such analysis, however, the following conclusions may be drawn from the findings considered:

There is abundant evidence that mental image rotation is a process which occurs in real time, and which requires more time to accomplish with increased angles of rotation. 1.

2. There are differences between the mental image rotation

abilities of young and elderly adults. For example, the elderly in general require more time than young adults to accomplish any given mental rotation task. There is much evidence in the literature to implicate a generalized central nemous system speed loss (Birren. 1974) in the mental rotation rate dnerence between young and elderly adults. 3. However, the performance of young and elderly subjects on mental image rotation tasks is in general task-dependent. Within different task frameworks, age-related differences in rotation rates are not always associated with age differences in the accuracy of judgements based on rotation. Factors which influence the rate and/or accuracy of mental rotation performance include the type of stimuli employed, the complexity of those stimuli. the dimensionality of rotation (depth versus picture plane), subject familiarity and practice with stimuli, speed requirements, and whether stimuli are to be compared with each other or with images of previously learned items. It is probable that this list is not exhaustive. The relationships of these various known influences on mental rotation to one another has not been systematically evaluated at the present time. The relationship of some of these factors (e.g., speed requirements) to the aging process has been partially clarified, but comprehensive systematic evaluations are currently lacking.

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The task-dependency of mental image rotation, and the fact that some task characteristics (e.g., speed requirements) interact with aging to influence performance, indicate that mental image rotation probably involves a cluster of related abilities, which may be brought into play as task circumstances demand and as agerelated factors permit. Identification and analysis of these abilities would shed considerable light on the nature of mental image rotation and on mental imagery generally. Examination of these abilities with reference to the aging process should also allow much more specific definition and analysis of the imagery abilities retained and lost over the course of the adult lifespan. Systematic analysis of the results of a number of experiments, addressing various facets of these issues. will be needed to form a comprehensive picture of the factors and relationships involved. 4.

A preliminary experiment addressing some of these factors is

reported below. Since speed requirements have been shown to interact with age to influence performance (Sharps & Gollin. 1987b), and since stimulus complexity has been shown to influence performance on some, but not all, mental image rotation tasks (e.g.. Folk & Luce, 1987). the work presented below addressed the interactive influences of subject age, speed requirements, and stimulus complexity on the speed and accuracy of mental image rotation. Picture plane rotation of modified, two-dimensional Shepard-Metzler cube items was employed in the rotation task. The experiment was intended to provide preliminary data on the interactions of these factors, and also to demonstrate the usefulness of the age-by-task perspective in the study of aging and mental imagery. MENTAL IMAGE ROTATION IN YOUNG AND ELDERLY ADULTS: SPEED REQUIREMENTS AND STIMULUS COMPLEXITY It was previously shown (Sharps & Gollin. 1987b) that the mental image rotation performance of young and elderly subjects was differentially influenced by speed requirements: when speed was emphasized, the elderly were able to respond as quickly a s young subjects, but were significantly less accurate in their

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judgments. When subjects were specifically instructed not to emphasize speed at the expense of accuracy, the elderly were as accurate as the young in their judgments, but were significantly slower. These findings were demonstrated using standard, threedimensional Shepard-Metzler items, rotated in depth. Age differences in cognitive functioning may involve the effortfulness of the cognitive tasks in question. In several studies (e.g.. Craik, 1986).it has been shown that more effortful tasks (e.g.. free recall) are associated with relatively greater age-related deficits than less effortful tasks (e.g., recognition memory). This may be attributed to an age-related decline in general processing resources (e.g.. Craik, 1986: Norman & Bobrow, 1975). Such a decline in central processing resources might also be implicated in the performance of young and elderly subjects on mental imagery tasks. The processing of more complex stimuli, for example, would appear to be a more effort-intensive task than the processing of simple stimuli, and might therefore be expected to produce a greater age difference in performance. (This would only be expected, of course,If levels of complexity are not so great as to force subjects to employ entirely different strategies, such as partial rather than whole rotation of stimulus items). The rotation of simpler items should be less influenced by speed requirements, which hypothetically also tap such processing resources, than the rotation of more complex stimuli. Also, more complex stimuli should become more difficult to process with increasing angles of rotation, since both increased rotation and increased complexity presumably require increased processing resources. Complexity effects are not generally observed when twodimensional AA figures are employed a s stimuli [e.g., Cooper, 1975; Cooper & Podgorny, 1976;but see Folk & Luce, 1987).This gave rise to the hypothesis of Herman and Bruce (1983)that complexity effects are largely confined to MIR tasks involving threedimensional stimuli. However, given the processing-resource considerations discussed above, it seems probable that complexity effects may be obtained from the use of more complex twodimensional stimuli a s well. Since the use of Shepard-Metzler figures has in general resulted in the observation of complexity effects, it would appear that these figures may be intrinsically more

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"complex" in some way than AA figures. Relatively complex twodimensional figures were required for the present experiment. Therefore, the two-dimensional figures used in the present experiment were modeled on Shepard-Metzler figures. The use of these stimuli provided a partial test of the Herman and Bruce hypothesis. Method The subjects of this experiment were 28 young adults (mean age 20.5 years, standard deviation 3.1 years) and 28 elderly adults (mean age 73.5 years, Standard Deviation 5.3 years). A questionnaire covering health and demographic factors was administered; all subjects reported being in good health, and no systematic demographic differences were observed between the young and elderly samples. The Vocabulary subscale of the Wechsler Adult Intelligence Scale was administered; the performance of the elderly adults in the study significantly exceeded that of young adults. 41.54)=14.18.pc.001. This finding is typical. A Snellen test of vision was also administered: all subjects exhibited visual acuity of 20/40 or better. These tests were intended as precautions against the influence on performance of population differences other than age per se. Although this battery of measures was by no means comprehensive, it was felt that major dmerences in important areas between young and elderly subjects would probably be detected by these instruments. The experiment employed a Gerbrands 3-field tachistoscope, reaction timing device and clock/counter. The apparatus was arranged so that the experimenter activated the presentation field of the tachistoscope and the timer simultaneously. The subject terminated tachistoscopic presentation and timer activity simultaneously by pressing another switch. The stimulus items employed were similar to Shepard-Metzler cube figures. being composed of squares arranged in series of rightangle turns. However. these figures were two- rather than threedimensional (see Figure 2). Rotation was to be accomplished in the picture plane. The figures were mounted on standard tachistoscope cards. Each item consisted of a rectangular black field on which

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were mounted two of these figures, either two representations of one figure, or representations of a figure and its mirror image. The figures in each item were rotated 20, 45. or 70 degrees from each other, all rotations being carried out in the picture plane. The figures also differed in complexity. As discussed above, it is difiicult to be precise concerning what actually constitutes stimulus "complexity." However, in order to decide whether figures were the same or were mirror images. subjects would have to examine the right-angle turns underlying the item configurations in making their decisions. Accordingly. complexity was defined in terms of the number of right-angle turns present in a given figure. The figures used were either "simple" (consisting of 10 squares with 2 or 3 turns), "intermediate" (10squares with 4 turns), or "complex" (10 squares with 5 turns). The procedure employed w a s similar to that of Shepard & Metzler (1971). Sample and practice items were administered to ascertain that subjects understood the task, which was to decide whether the pairs of figures were the "same" or "different" (mirror images). Subjects were asked to press the termination switch immediately on making this decision, and then to inform the experimenter of their decision. Subjects were either instructed to make their decisions a s quickly a s possible, or were instructed to balance speed and accuracy in making their judgements. This instructional manipulation was carried out between subjects. Results and Discussion There was no main or interactive effect of age or instructional condition on decision accuracy scores. This is interesting in light of previous similar research. using depth rotation of threedimensional Shepard-Metzler cube items, which provided evidence that speed requirements negatively affected accuracy of judgement for the elderly (Sharps and Gollin, 1987b). While previous experiments are obviously not directly comparable with the present one, given the use of difTerent stimulus materials, the discrepancy in the pattern of results obtained suggests that rotation in the picture plane may be "easier" than rotation in three dimensions. so that speed requirements have relatively little influence on rotation

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Rgure 2. Examples of the two-dimensional figures, similar to ShepardMetzler figures, employed in the present experiment. From top to bottom, the figures are of simple @-turn).intermediate (4-turn). and high (5-turn) complexity.

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performance of the former type. This is in agreement with the work of Jolicoeur et al. (1985)and of Shepard and Metzler (1988). The results of this study regarding reaction times are summarized in Table 2. Mean reaction times, with standard deviations, are reported. Slopes and intercepts for the reaction time/rotational angles are not reported. An examination of Table 2 will reveal that, although greater rotational angles are associated with longer reaction times overall, in some cases reaction times for 45 degree angles were the same or even shorter than those for 20 degrees. This perturbation was unexpected, and may relate to the greater “familiarity” of 45 degree angles to subjects. The question is currently under investigation. However, for the purposes of the present study, slopes and intercepts for these functions over all would not be representative of the actual data. The effect of age on reaction time was significant, Fl1.52)=16.69. p < . O O l , Elderly subjects were significantly slower than young subjects across instructional conditions. This finding is in agreement with other research (e.g., Berg et al., 1982) supporting Birren‘s (1974) speed loss hypothesis. although, a s has been discussed above and elsewhere (Sharps & Gollin. 1987b).the degree of speed loss observed with advancing age appears in part to be a function of task condition. There was also a trend, albeit nonsignificant (PI 1,52)=3.41, p=.070),toward an effect of speed requirements on rotation rate: subjects appeared to work at higher rates within the speed than within the speed/accuracy condition. The trend was nonsigdcant and very weak, whereas in previous work speed requirements made a significant difference to reaction time (Sharps & Collin. 1987b). This can probably be attributed to the use of two-dimensional rotation, rather than rotation in depth, in the present experiment. These results are consistent with the hypothesis that twodimensional rotation, requiring less in the way of “processing resources,” may be relatively less influenced by speed requirements than more complex, three-dimensional tasks. This hypothesis However, will, of course, require further empirical evaluation. evidence is accumulating rapidly to the effect dependent upon a variety of stimulus-related factors, as well as upon procedural factors such as speed requirements, Hertzog and Vernon (1990).

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Table 2 Mean Reaction nrnes (in seconds) of Young and Elderly Adults, with Standard Devfations. Rotational Angle

Complexity

M

SD

M

SD

20

3T

1.96

1.54

3.37

1.88

4T

3.09

1.63

6.04

3.26

5T

3.18

1.78

5.16

2.86

3T

1.90

0.98

3.35

2.37

4T

2.13

1.43

3.41

1.83

5T

2.45

1.40

4.43

2.84

3T

2.63

1.45

4.11

2.55

4T

3.66

2.32

6.29

4.18

5T

4.19

3.03

8.05

6.86

45

70

using two-dimensional stimulus items, recently observed that although both young and elderly respondents altered their reaction times in response to speed instructions, there was no interaction of age with instruction. In the present study, which also used twodimensional items, no significant main or interactive effects of speed requirements on rotation times or accuracy scores were observed. Both of these studies are at odds with Sharps and Gollin (1987b). in which main effects and interactions of speed requirements and age were produced for both reaction times and accuracy scores. However, recent work (in preparation) in the author's laboratory. employing three-dimensional stimulus items similar to those of Sharps and Gollin (1987b), has produced a pattern of results in agreement with the Sharps and Gollin study. These preliminary results are entirely consistent with the present thesis that mental image rotation performance depends upon a complex interplay of age, stimulus factors, and procedural demands.

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The effect of rotational angle on reaction time was significant, F(2.104)=26.41. pe.001. As has been found many times previously. greater rotational angles were associated with longer reaction times. However, there was no interaction of the influence of age with that of rotational angle. Although the elderly were in general slower than young adults, they were not placed at a relative disadvantage by increasing rotational angles. The performance of the elderly paralleled that of younger persons, the degree of required rotation notwithstanding. This indicated that increased rotation did not draw increased "processing resources." in the sense in which these have been discussed above. The interaction of complexity and rotational angle was significant, F(4.208)=5.73. pe.00 1. More complex items required more time to rotate through greater angles. This finding was consistent with the hypothesis advanced above, that more complex items may require more processing resources for rotation than simpler items. This further provides a qualification to the hypothesis of Herman and Bruce (1983) that complexity effects are more likely to be observed in three- than in two-dimensional rotation. Rotation involving the two-dimensional stimuli used in the present study exhibited significant complexity effects. This indicated that complexity effects on reaction time result from stimulus configuration as well as from the dimensionality of required rotation. Further research will be required to ascertain precisely why some types of two-dimensional stimuli are associated with complexity effects, while others are not. The work of Folk and Luce (1987).discussed above, is pertinent to this issue. The effect of figure complexity on reaction time was significant, F(2.104)=31.26, pe.001. More complex figures required more time for rotation than did less complex items. This was in agreement with most of the basic data for Shepard-Metzleritems, although not for AA items, again demonstrating the stimulus-dependency of M I R The interactive effect of age and figure complexity was also significant, F(2.104)=3.70.pc.03 (see Figure 3). This is consistent with the hypothesis of age-related depletion of processing resources: increased resource utilization, resulting from increased complexity of figures, was more deleterious for the performance of the elderly than of the young subjects. The interaction of age and

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331

6000

5000

4000

2000

!

I

I

I

SIMPLE

INTERMEDIATE

COMPLEX

STIMULUS COMPLEXITY

mure 3. Mean reactfon tlmes of young and elderly subjects, plotted against the complexity of stimulus flgures employed.

rotational angle was not signiflcant. Neither was the three-way interaction of age, rotational angle and complexity. Although increased rotational angles did not negatively affect the performance of elderly persons relative to that of young adults, the complexity of stimulus items did have such an effect. This was consistent with the hypothesis that more complex stimulus items place a greater demand on available processing resources than simpler figures. Diminished central processing resources are associated with the course of aging (e.g.. Craik. 1986). Therefore, more complex stimulus items are more difficult to work with for the elderly than for young adults. Since increased rotational angles did not result in different performance trends between young and elderly adults, however, it seems that increased rotational

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requirements probably do not draw on processing resources to the same degree, or in the same way, as increased figure complexity. It is not known at present why this should be the case: current research is focused on this issue. An additional question which arises from this work is the nature of the "processing resources" to which reference has been made. The interactive effects of complexity x angle, and of age x complexity. were significant. If, however, these effects were due to the influence of the respective independent variables on some sort of unitary bank of processing resources, one would clearly expect the age x angle interaction, and the three way interaction of age, complexity. and rotational angle. to be significant. They were not. This indicates that, with reference to mental image rotation performance, there probably is no specific reserve of unitary "processing resources" drawn on in accordance with the needs presented by specific independent variables. Rather, it is logical to hypothesize that there are a variety of such resources, which become differentially important depending upon the types of subjects employed (young or elderly, in the present instance) and upon the constellation of independent variables with which those subjects are presented. The term "processing resources" is used here as a label of convenience, to describe a group of processing-related variables whose nature and function is not currently understood. The present study gives an indication of the way in which an "ageby-task" methodology may be used to obtain information on the ways in which these variables function in different experimental contexts, employing different subject populations. The present study also demonstrates a more concrete methodological point. In this work, if simple figures alone had been used as stimulus items, the magnitude of the observed main effect of age would have been relatively small. If only more complex stimuli had been employed, a large age-related deficit in the process of mental imagery might have been erroneously postulated. It should also be noted that, depending on the task employed (see Folk & Luce, 1987), if A A figures had been used instead of the figures actually used. it is probable that no complexity effects at all would have been observed (see Cooper, 1975; Cooper & Podgorny. 1976). Other stimulus materials, such as three-dimensional Shepard-

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Metzler items, might have produced still different effects. The results of this study demonstrate that, in order to build a comprehensive model of the interaction of age. stimulus complexity, and rotational angle on mental image rotation, It is important to test these effects among a variety of systematicallyrelated stimulus types. The study of knowledge utilization is predicated upon valid knowledge of the ways in which information. including visual information. is processed. If erroneous or oversimplified models of image processing, "processing resources," or other variables critical to cognitive performance are constructed, adequate theories of the higher processes involved in knowledge utilization and actualization cannot be constructed. It is therfore critical for studies of imagery, of knowledge utilization, and of cognition generally that theories concerning the basic processes of visual cognition be formulated as accurately and comprehensively a s possible, with reference to the types of experimental and situational factors which impact on performance. and with respect to the influences brought to the research situation by different subject populations. The age-by-task perspective discussed in the present paper has been shown to be a useful instrument for the examination of these influences. Additional studies employing this perspective should clarify these issues further, a s the interactive effects of additional task-related and subject-related factors are systematically evaluated. SUMMARY AND CONCLUSIONS

The developmental method discussed in this chapter involves the systematic evaluation of age and task characteristics within the same experimental framework. This allows the investigator to examine influences on cognitive performance that would not otherwise be detected. Appropriate use of the age-by-task method may help to prevent the formulation of oversimplified or invalid conclusions about the cognitive abilities of the elderly, and may improve the accuracy of estimates of the effect that aging actually does or does not have on a given cognitive process. Furthermore, by varying task characteristics systematically along continua of

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theoretical interest, the investigator may be in a better position to assess the extent of the abilities avaftable to the elderly, as well as the performance tendencies that may be expected from elderly individuals within any single task context. The utility of developmental age-by-task methods for the study of aging and visual cognition has been discussed and demonstrated. The continued use of these methods to examine cognitive performance, across a broad spectrum of populations and paradigm types, should prove useful in the development of comprehensive theories of aging and visual cognition. ACKNOWLEDGMENTS

This work was supported by a Faculty Grant-in-Aid from the University of Wyoming. The author wishes to thank Thomas Hess of North Carolina State University, Karen Barrett of Colorado State University, and Narina Nightingale of the University of Wyoming, for their very helpful comments on an earlier draft of this chapter. REFERENCES Attneave, F. (1957). Physical determinants of the judged complexity of shapes. Journal of Experimental Psychology. 53. 22 1-227.

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Aging and Cognition. Knowledge Organizaifon and UtUizatbn Thomas M. Hess (Editor) 0 Elsevier Science Ahlishers B.V. (North-Holland), 1990

CHAPTJ3R EIGHT

EXPERTISE AND AGING: LIFE IN THE LAB Neil Charness and Elizabeth A. Bosman

University of Waterloo

SUMMARY

Why do old adults perform s o poorly with typical laboratory tasks, yet do so well in professional and everyday performance? Further, why is there such a discrepancy between the ages at which peak performances are obtained in sports versus intellectual spheres? We explore the age/skill tradeoff, and suggest how "software", knowledge acquisition, can compensate for age-related declines in "hardware", cognitive architecture. We review research on several intellectual domains, emphasizing work conducted in chess and bridge, and contrast those studies with ones dealing with more physically demanding domains, typing and athletic performance. We outline the boundary conditions for compensation within each domain, and discuss the implications for theories of compensation. THE SKIU/AGE TRADEOFF

Murrell, an industrial gerontologist, once observed: "Anyone reading the results of the laboratory experiments could be forgiven for imagining that any person who achieves the age of fifty will have become a slow, forgetful. half-blind, half-deaf, palsied character of little use in industry. In fact, many older men and women hold down jobs with

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complete satisfaction to their employer." (1965. P.449). Similarly. Talland remarked: "I am still puzzled by the contrast of the athlete who,

at thirty, is too old for the championship and the maestro, who, at eighty, can treat us to a memorable performance on the concert stage... Are our aged masters freaks of nature, paragons of self-discipline, or do they demonstrate the inadequacy of our present notions about the effects of age on human capacities?" (1965,P. 558). Are our in uffro laboratory experiments adequate indicators of

fn vim cognitive behaviofl Why is there such a great discrepancy between the performance of older people on laboratory tests of cognitive ability and their performance in their professional and everyday activities? There are four classes of easy, but inadequate answers. The first is that laboratory tests are uninteresting to older adults who don't particularly exert themselves. A variant is that older adults don't share the same cultural norms to do well on tests. The hypothesis is that age differences are due to problems with motivation. The second is that cross-sectional studies of age effects are confounded by cohort differences. Earlier born cohorts were disadvantaged at certain types of test-like tasks, (Schaie, 1983; Labouvie-Vief. 1985). The hypothesis is that age differences are due to cohort confounds. A third is that laboratory tasks don't successfully tap everyday types of behavior. The hypothesis is that tasks lack ecological validity. A fourth is that in cross-sectional research, samples of young and old are not representative and are positively biased for the young since most are college students. The hypothesis is that age differences are due to unrepresentative samples. The reasons to doubt the utility of these explanations are many. Tests of the motivation hypothesis have usually failed. When you

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reward young and old, the old do not increase their performance disproportionately compared to the young. Usually, young and old increase performance equally. (See. for example, Grant, Storandt & Botwinick, 1978 with the very age-sensitive digit-symbol substitution task). The argument also tends to lose force when the experimental tasks are ecologically sound ones being performed by professionals and serious devotees [e.g.. typing: Salthouse. 1984; bridge: Charness. 1979. 1983. 1987; chess: Charness. 1981a. 1981b. 1981~). A reason to doubt the cohort confound explanation is that

longitudinal research has shown similar trends to cross-sectional research when the time interval for the longitudinal comparison increases towards that of the typical cross-sectional comparison (Botwinick & Siegler. 1980). For instance, Schaie (1983, 1989) provides longitudinal data that show that decrements on PMA scales are observed at earlier chronological ages for greater time interval comparisons (e.g.. 28 year versus 14 year measurements). Further, time lag comparisons of young undergraduate students on nonsense syllable learning have shown few changes (Kausler, 1982). Older cohorts are sometimes advantaged compared to younger ones: see Schaie (1983) for the cases of word fluency and number skills. Further, Lehman (1953) has shown that the age of peak performance in professional achievement has not changed much over the past few centuries; if anything it has occurred earlier for more recent cohorts. Stability for the age of peak athletic performance is also the rule (Schulz & Curnow. 1988). As Kausler (1982) noted, the controversy over generalizing age differences from lab to life (ecological validity) may be based on false premises. If the same processes are utilized by subjects in "ecological" and "unecological" investigations of performance, valid inferences about processes are possible. Further, as Salthouse (1985) indicated, if you want to examine "pure" age effects, then looking at situations where knowledge could compensate for age changes is probably not a good idea: 'The basic premise of the selective expertise concept is that the relation between performance and chronological age will vary with the amount of

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experience people at each age have had exercising the relevant ability. An important implication of this proposal is that meaningful reflections of 'basic' or 'pure' aging processes must either be based on novice levels of performance, or great care must be taken to ensure that experience is equated across age groups." (P.114). Those working on psychometric intelligence measures have made much the same point. They argue that intelligence subtests that require unpracticed mental operations are probably the more valid ones to use when it is assumed that intelligence reflects native ability. (A nasty problem is that it may be the case that smart people are those who have had a great deal of useful experience. Few tasks, for them, will be truly unpracticed.) It is true that samples lack representativeness, suffering from the typical biases that volunteer samples are prey to (e.g.. Camp, West & Poon. 1989;Todd, Davis, & Cafferty. 1983). Nonetheless, in one cross-sectional study where a probability sample was obtained (Herzog & Rodgers, 1989). strong linear age decline was still observed in an ecologically sensible incidental memory measure. Further, the nature of the bias probably results in underestimates of age effects. Older adults who volunteer for experiments are generally much better educated and in better health than more representative members of their cohort. What then is the explanation for the consistent pattern of decline in laboratory cognitive performance with increased age? If we rule out experience-based explanations (disadvantaged cohorts), then maturational changes are plausible candidates. Specifically, our working hypothesis is that the "hardware" supporting cognitive operations is undergoing change, usually negative change. (Patrick Rabbitt phrased it rather colorfully at a Talland Conference one time as 'The brain rots".) Although it has been fashionable to argue against the "constant decrement'' view of aging, we want to claim that it is still the most parsimonious model for consideration. Two complementary investigative models for cognitive aging are those of information processing psychology and neuropsychological case investigation. The standard information

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processing perspective on behavior is that humans act with limited rationality because of limitations in information processing capabilities (Simon, 1969). If you want to understand human capabilities. you need to find situations where behaviors depart from perfect rationality (ideal performance). The neuropsychologist examining a patient tries to find specific problems with behavior. Amnesics look perfectly normal in standard conversations, until you probe recent memory. Dyslexics are fine, until confronted with printed language. Older people look just like younger people, until you push them to the limits with complex tasks, particularly speeded ones. Baltes and colleagues (e.g.. Kliegl, Smith, & Baltes, 1986,1989)have termed the exercise "Testing the Limits". when looking at skill acquisition for a memory task by younger and older adults. Our hypothesis is that older adults can perform more than adequately in most real world tasks because they have acquired specific knowledge (declarative, procedural: Anderson. 1983)that allows them to compensate for declines in raw hardware capability. When tasks push people to their limits, however, age decline may be demonstrated even in expert performance. The famous debate between Lehman and Dennis about age of peak professional achievement hangs on this point (see Simonton, 1988). Although Dennis succeeded in finding cases where there was little decline in productivity over the lifespan by choosing modest achievements, Lehman could point to top achievements and find consistent evidence of a peak in the thirties. A recent study of the publishing behavior of North American psychologists (Horner, Rushton, & Vernon, 1986)also shows that for those whose output is highest initially (in the 20s age range) there is linear decline across the career. Moderate publishers give the usual inverted U-shaped function with peak performance in the 30s and 40s. rather than in the 20s. A similar linear decline trend is observed for the quality of teaching by psychology professors (Homer. Murray. and Rushton, 1989). Studies of skilled performers often show that older adults perform equally to young adults. How they maintain performance in the face of documented decline in various cognitive processes thought to support behavior is an intriguing question. The study of

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compensatory mechanisms is just beginning (see Salthouse. 1989: 1990). When confronted with the wearying array of findings that show that older groups do less well than younger ones on nearly every task invented by experimental psychologists, the tendency is to assume that all older adults perform less effectively than all younger adults. Means tend to hide the extensive individual dmerences in performance in both groups. There was a striking example in our work on mental calculation (Charness & Campbell, 1988). A further look at individual data shows that a 71 year old was the second fastest individual at squaring two-digit numbers mentally in the flrst session. Not every older adult shows decline, as Schaie and colleagues have been at pains to point out with longitudinal data on psychometric abilities. A Theory of Tradeoff

How can knowledge compensate for declines in hardware? We want to draw on a n analogy with human and computer chess playing. Computer chess programs play excellent chess by doing incredibly extensive searches of parts of the game tree. (The game tree is the set of all possible legal moves from the initial position to the end of the game.) Master level programs such as "Deep Thought" can search millions of paths in seconds. In contrast, human chess players rely on extensive knowledge to control the size of the search tree, and as a result, may only look at 100 or so paths in ten minutes of search. Such knowledge ensures that the best human players can still beat the best programs (though human superiority may be challenged in the next few decades). The ability to recognize chess patterns and understand their meaning enables humans to search selectively. In its strong form. the knowledge-search tradeoff proposes that equivalent performance can be reached by fundamentally different programs. (See Newell, 1989,for a good discussion of preparation versus deliberation a s strategies for problem-solving by information processing systems). Camp (1989) gives the intriguing example of how someone can answer the information question on the WAIS about the distance between New York and Paris in two

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ways. They could know the answer (memory retrieval) or could compute it from other facts (remembering how long Lindbergh's flight between the cities took, estimating the speed of the plane, and calculating the answer), as did one older adult he tested. Let's take the slowing hypothesis (e.g.. a s explicated by Salthouse. 1985, 1988) as a good first approximation theory of how aging affects information processing. We can use the slowing parameter of 1.6 - 2.0 (Cerella. 1985) to estimate an older person's reaction time from that of a younger person. (We can also estimate processing parameters like those in the Card, Moran & Newel1 (1983) cognitive model used to predict task completion times for routine cognitive tasks such as word processing. See Charness and Bosman. 1990). The strong prediction from a n age-slowing model is that if young and old adults follow the same internal program, the young will complete the task sooner than the old. But, if the two infomation processors are using different internal programs, all bets are off for who finishes first. For tasks like simple reaction time, or choice reaction time, we can be moderately confident that the programs being followed are quite similar for young and old. We are only moderately confident, since choice of a speed/accuracy criterion is a free parameter.) Thus, those types of tasks should yield reliable age dflerences. When it comes to more complex tasks (choosing a move in chess, typing an unfamiliar passage of text), we can no longer ensure that young and old use the same program. It is always possible for an older adult to use a more efficient program, run at a slower rate, to outperform a young adult who runs a less efficient variant at a faster rate. Knowledge is being equated here with the ability to construct, compile, or operate a very efficient program. A look at how experts manage to solve problems so successfully in their domains of expertise also shows that they rely on knowledge to minimize and sometimes even bypass search through the problem space (Ericsson & Smith, in press; Chi. Glaser & Fan, 1988). Some medical diagnosis and chemical analysis programs have also evolved in this direction. The triumph of knowledge over reasoning (search) for successful artificial intelligence has been

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aptly phrased as the "Knowledge Principle" (KP) by Feigenbaum (1989):

"The Knowledge Principle states that a system exhibits intelligent understanding and action at a high level of competence primarily because of the specific knowledge that it can bring to bear: the concepts, representations, facts, heuristics, models, and methods of its domain of endeavor. A corollary of the KP is that the reasoning processes of intelligent systems are generally weak and are not the primary source of power" (P.179). Rephrasing the problem for the field of aging, we can begin to ask a different question than that motivating most of the work in the field so f a r (are there changes with age). Given that older adults can maintain very high levels of performance in the face of declines in basic information processing rates (the slowlng hypothesis), how do we adequately describe the knowledge that enables them to do it? This is of course the compensation question (see Salthouse. 1989; 1990). Human expertise spans a n enormous set of tasks. A typical dictionary of occupational classifications lists thousands of job types, and a quick perusal of the Guinness book of records indicates there are many other non-paid avocations that people are willing to devote enormous effort to. We'll review a sample of studies from two primarily intellectual (chess, bridge) and two primarily perceptualmotor domains (typing, sports). Much of the work concerning compensation has been conducted by equating young and old on some molar task (e.g., typing speed, chess ratingl and seeing how they vary on the component processes thought to underlie the task. When you select young and old to be equal, however, you do not know whether in the population as a whole there is no relation between age and skill. You may have selected only the fittest old and the less fit young. Fortunately, researchers have usually shown that expert older adults look fairly typical on domain-unrelated measures, namely, they do worse than younger experts on psychometric tests such as digit-symbol

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substitution, and worse on typical experimental tasks such a s choice reaction time and memory for list items. SEMANTICALLY-RICH DOMAINS Simon (1979)introduced the term "semantically-rich" to characterize domains where a large knowledge base was instrumental for skilled performance. Semantic memory is conceptualized a s a long-term memory store containing symbol structures: networks of interconnected idea units. (See Chang. 1986.for a review of semantic memory theories.) The key to skill, in this view, is the possession of thousands of "productions". rules for interacting with domain situations. Such "if-then" rules (e.g.. if you have a headache, then take an aspirin) enable the expert to deal smoothly with new situations that can be mapped onto existing structures. For situations where thinking is required, even for an expert, productions guide search along the most effective paths. Experts often search forward from the initial state to the goal state (in physics, Simon & Simon, 1978;in medical diagnosis, Pate1 & Groen, 1986). Such knowledge-informed search processes contrast sharply with the backwards search that results from the means-ends style reasoning that characterizes novice behavior in these situations. The expert knows that in problems of a given type, if you solve for particular unknowns in a given sequence, the answer will soon be in sight. Not all expertise involves pulling knowledge out of a hat for each occasion. Allard and Starkes (in preparation) argue that often in "open" sports skills (e.g., baseball, tennis), the expert is someone who can carry out goals in a flexible fashion. In contrast, in "closed" sport skills, where the goal and its manner of implementation in the environment is relatively constant (figure skating. archery), the winner is the athlete who can carry out wellpracticed motor programs with minimal variation. Characterizing the knowledge store of the expert is still an ongoing concern (see Charness, in preparation, for an example of categorizing chess knowledge). Estimates of extent of knowledge, such as 50,OOO chess patterns (Simon & Gilmartin, 1973)have been widely cited. Given that humans take a relatively long time to add

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new information to memory (5 - 15 seconds for rote memorization: Simon, 1974). it is clear that building such a knowledge base takes thousands of hours. When considering the factor of age, it is highly likely that age will be positively associated with experience and practice. That is, older adults will have had more opportunity to build up knowledge than younger adults. An example is vocabulary, where psychometric investigations typically reveal a positive correlation between age and word definition knowledge (e.g., Birren & Morrison, 1961). The tension between knowledge possession and its successful activation and management underlies the compensation argument. Chess Expert practitioners have done little to discourage the view that chess is the most intellectual of all games. Masters have long amazed amateurs with their ability to foresee distant checkmates. Work by psychologists in this century (see Charness, in preparation: Holding, 1985) has shown, however, that skilled perception is an important component of skilled play. It was also evident to those building chess programs that it was impossible to examine the consequences of all alternatives when planning which move to make. Rather, a limited search would have to take place. Humans are far more selective than machines, In a 10 minute problem-solving episode, where players are asked to find the best move, about 100 chess positions will be examined (Charness. 198lb). Current top-flight chess programs examine between 100,OOO and 1,000,000 positions per minute (Berliner & Ebeling. 1989). What enables the best humans to beat the fastest computers most of the time? The actual problem space of possible chess games is estimated at about positions. The fastest programs, now, and in the future, will never be able to examine all alternatives. The key is to look at the best alternatives. Humans achieve this by knowing which moves to examine, and not even generating most of the irrelevant moves. Computer programs use clever pruning and move ordering techniques to grow the smallest possible search tree,

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while still looking at all required alternatives to a (timedetermined) fixed depth.

Determinants of Skill The major marker for knowledge in chess has been de Groot's (19651 brief recall task. If you show a chess player an unfamiliar middle game position for a few seconds, their ability to reproduce the position depends strongly on their skill level. Grandmasters can place nearly all pieces (about 24)perfectly. Beginners can place 4 or 5 pieces correctly. Miller's (1956)notion of a chunk can explain these differences. With structured positions. the Master can recognize clusters of pieces (7 f 2 chunks). When randomly arranged pieces are shown briefly, master and novice alike place only 4 or 5 pieces correctly (Chase & Simon, 1973a. 1973b). With random displays. there is little opportunity. even for a master. to recognize chunks larger than a single piece. These results have been taken to show that masters have a large vocabulary of familiar chess patterns (chunks) in semantic memory. Chase and Simon hypothesized that such patterns trigger move generation processes, enabling the master to look at the right alternatives. while the novice goes merrily down the wrong path, never even generating the correct move for examination. Recent experimental research suggests that the Chase and Simon theory is probably insufficiently specified, and others have emphasized the importance of delineating the mechanisms controlling search processes (Charness, in preparation; Holding, 1985). Nonetheless, pattern recognition is seen a s the key for guiding search, both for generating base moves at the root position for analysis, and for providing evaluative information at the leaf nodes of the search tree. Tournament chess games are always conducted with time limits. In top-level tournaments, players have, on average, 3 minutes per move (40moves must be completed in the first two hours). Research has shown that players typically generate a new position for analysis every 5 - 15 seconds (they seem to spend more time evaluating than generating moves). Thus, they will probably look only at about 20 moves, including analysis moves, in an

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average position over that time interval (Charness. 1981b). In short, skilled players must very quickly recognfie the right moves to look at. Chess, at top levels, is a game of time stress, precisely, the type of working environment that older adults are advised to avoid (Welford, 1985). Nonetheless, chess is also a game requiring extensive knowledge, something that older chess players are likely to have in greater abundance than younger ones. Elo (1965, 1978) showed that the careers of chess grandmasters parallel those of other peak performers (see Lehman, 1953; Simonton. 1988). Best tournament performances are achieved in the 309 (meanage of peak is 36)with declines thereafter. The nature of the decline is quite modest, about a half standard deviation from the peak in the 30s to the low point in the 60% the age at which most players give up active tournament participation. The relatively modest decline in chess performance for Grandmasters (0.5 SO1 contrasts sharply with peak performance trends mentioned earlier. Could possession of greater knowledge be compensating for older players' declining ability t o search quickly? Charness (1981a. 1981b. 1981c) explored how age and skill jointly determined the performance of chess players on a set of chess-related tasks. The strategy adopted was to equate players varying in age on skill level, using chess rating as the criterion measure for skill, and examine how the processes thought to support chess playing varied. The main sample consisted of 34 male chess players varying in age between 16 and 64. and in skill between 1283 and 2004 rating points. Players were selected such that age and skill were virtually uncorrelated (r = ,085). A substantial number of variables were examined, but this review wffl concentrate on two subsets: search characteristics and memory indexes. Chess search varied systematically with age and with skill (see Charness. 1981b). The more skilled the player, the farther ahead they projected the consequences of a base move (the first move for their side). Also, skilled players tended to examine more moves in total (both base moves and analysis moves). Older players tended to examine fewer moves than younger players of equivalent skill level, though their depth of search was equivalent. That is, though older players were capable of looking as far ahead

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(pushed search as deeply into the tree of move possibilities), they tended to end search sooner, having examined fewer alternatives. Nonetheless, the bottom line for chess is the strength of the selected move. On that measure only skill was a significant factor. Old and young alike chose moves appropriate to their skill level. In brief, age seemed to have little impact on the quality of the move selected, though it did exert an influence on the processes responsible for move selection. In fact, the curious picture arises that older players were more efficient than younger players, choosing an equally good move with less extensive search. Older players took significantly less time, on average, to choose their move. Depth of search, a measure showing skill but not age ef'fects, is a type of working memory measure. It defines the point at which a player can no longer retain accurate information about the projected changes to a perceived chess position (the physically present one) when moves are envisioned. Because of limitations in working memory, players must return to the base position and rework their analysis, a process termed "progressive deepening" by de Groot (1978). Depth of search is controlled by move generation processes (what are the possible moves), evaluation processes (knowing the value of a given position enables players to terminate a search episode), and memory processes (keeping track of moves generated and evaluated). Apparently, such highly-practiced processes execute as smoothly in the old as in the young. (Some idea of how practiced search behaviour can be is given in Charness, in preparation. The most active Canadian chess players, usually young ones, may exhibit an upper limit of a million positions examined during search over a year of tournament play.) A direct test of evaluation accuracy showed skill but not age effects. Players were asked to evaluate endgame positions (positions with few remaining pieces) as win. draw, or loss as quickly a s possible. Even with this speeded task. no age effects were evident. More direct tests of memory efficiency yielded a different result, however. An incidental memory test for the four chess problems that players were given, following interpolated tasks, showed that older players did more poorly than equally skilled younger ones. More skilled players recalled more pieces correctly than their less-

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skilled counterparts. By using the pause structure in recall, chunk boundaries were defined. As had been shown for intentional recall of chess information by Chase and Simon (1973a). skill was associated with recalling a position as a small set of large chunks. Here, however, there was an interaction between age and skill for incidental memory chunk size. The recall advantage accruing from greater skill declined with increasing age. By about 60 years of age, there was no longer any advantage to being more skilled at chess for recalling positions as small numbers of large chunks. A direct test of intentional memory for briefly presented chess positions (Charness. 198lc) showed similar age-related deficits. The finding of age-related memory declines in chess position recall has been replicated by Pfau and Murphy (19881. The declines observed for recall of chess information can be modeled successfully by assuming that older players are slower in the pattern recognition and chunking process. Using a stochastic version of W P , a chess recall simulation by Simon and Gilmartin (1973). Chamess (1988) generated reasonable fits to the intentional recall data reported earlier (Charness, 1981~). How older chess players compensate for declining memory ability (as measured with intentional and incidental chess memory tasks) is still unclear. It is possible that the time demands are not extreme enough under normal playing conditions to influence success in problem solving very strongly. Note that for humans, who search very modestly, what gets searched, rather than how deeply search proceeds. is the critical variable. Knowledge, rather than speed (except in time pressure situations), is critical to performance. It must be admitted, though, that speed does set some constraints, particularly in terms of the rate of knowledge activation. A particularly telling experimental point is that studies of semantic memory priming (speed of activation) have shown little change with age (e.g., Balota & Duchek, 1988).though mean reaction time differences still favor the young. Still, we have to explain why Elo found that the peak tournament performance for chess players comes in the 30s rather than in the 60s at a time when accumulated chess knowledge is probably at its peak.

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Peak Chess Performance and Age As mentioned earlier, Elo (1965. 1978) examined the relationship between age and peak chess performance, showing a classical inverted-U function. A plot of that function appears in Figure 1 for relatfue performance. That is, scores are based on deviations from a player's peak performance, with age 21 set to zero. The number of players on which each point is based is: 10,51. 51, 48. 51, 50, 48, 41, 27, 14,and 9 for ages 18 through 65, respectively. Given the self-selection factors that operate, the amount of decline shown may be underestimated or overestimated because of selective attrition. Since players leave the pool for dmerent reasons (involuntary factors such as illness and death, as well a s voluntary ones). a rough test for selective attrition is to see whether the age at which players stop playing in tournaments is related to their peak absolute performance (do better players play longer) and the age at which they reach that peak (do those who peak at a young age leave earlier). Using Elo's (1965)data, players whose dropout age was artificially truncated were first eliminated (since the survey was published in 1965.recent players could not achieve true dropout ages). To estimate age at withdrawal we chose the first half decade with no rating. The regression of age at withdrawal on peak rating and year of peak rating (the interaction term made no difference) was not quite significant, p < .06,with peak age being the only significant factor. A simple regression of peak age on age of withdrawal was significant (n1.35)= 6.4,p < .02) for the 37 players:

Age-at-withdrawal= 36.3+ ,655* Age-at-Peak, SE = 6.64,$ = .16. That is. peaking later in life is associated with later withdrawal, though how skilled you are at that peak is not a factor. Filtering out players who died before age 60 only intensifies the relation between peak age and withdrawal: r (20) = .49. The framework of programs and architecture can be helpful in explaining age of peak performance. A serious player in their 30s has had about 20 years of experience (most start chess before the age

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of 10). His or her cognitive architecture is still near its peak. Memory efficiency declines from the 20s and 30s in cross-sectional studies (e.g., Hertog & Rodgers, 1989). Psychometric abilities often do not show much decline until the 60s or 70s in longitudinal studies (e.g.. Schaie. 1983. 1989). Since chess does have time constraints, a younger player may occasionally generate a slightly better move than a more knowledgeable older player who can't activate the appropriate knowledge quickly enough. One slightly better move can be the difference between winning and drawing (or wen losingl a game of chess. That is. architecture may carry more weight than knowledge when speed is a significant factor in play. If this explanation is correct, you ought to predict that various forms of chess should show earlier peaks and declines. A reasonable ordering would be: speed chess (about 10 sec/move), tournament chess (about 3 min/move), then correspondence (postal) chess (3 days/move). with the latter showing later age decline. Unfortunately, there have only recently (1988)been systematically organized speed chess tournaments and speed chess ratings, so it is only possible to look at the latter two cases. Prior to the acceptance of the Federation Internationale Des Echecs, FIDE. in 1946 as the legitimate governing body for chess by most nations, world champions have been determined in

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inconsistent ways. If we restrict examination to the championships conducted by FIDE we find the expected pattern. The mean age when someone first becomes world champion in tournament chess is 29.9 years, (SD = 6.79). for the 8 world champions starting with Botvinnik (in 1951) and ending with Kasparov (in 1984). The mean age when a player first becomes world champion in correspondence chess is 45.7 years (SD= 5.80). for the flrst 11 world champions starting with Purdy (in 1953) and ending with Baumbach (in 1988). This 16 year difference is significant statistically: t(17) = 5.48. p c .001. There are many problems with this comparison, one being the very long time period for a championship match in correspondence chess (at least 3 years, versus several months for over the board play). Even if it is assumed that the correspondence chess player has won the championship by the mid-point of the three year period, there is still a significant difference between the age of attaining the top title for these two variants of chess. There may also be self-selection factors delaying when players take up correspondence chess. Usually the champions are players who started with tournament chess, never achieved world class results, and then took up correspondence play. Nonetheless, it is clear that being young is much less of a factor in becoming world champion in correspondence chess than in regular tournament chess. One significant difference between the two forms of chess, aside from time for analysis, is style of analysis. You must do all your analysis without physically moving pieces in over-the-board tournament play. You are permitted to move pieces during analysis of positions in correspondence play. Thus, working memory (keeping track of outcomes, visualizing future positions) is less stressed in correspondence play. During postal play the player can rely more on external memory (written notes). There is corroborative experimental evidence that time to choose a move is an important factor in quality of play. In a recent study, Calderwood, Klein, and Crandall (1988) have shown declines in move quality with speed pressure, with less-skilled players more hurt than highly skilled ones. A n extension to look at the age factor is needed. Such a possibility exists in tournament chess in future years, if so-called "active chess" (averaging 30 seconds/move)

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becomes rated independently of standard tournament chess. Comparisons between ratings under the two time limits ought to reveal whether age is a significant factor. Chess playing offers a rather unique environment in which to pursue questions of skill-age tradeoff. Older players, despite showing the memory declines anticipated for aging individuals, still maintain high levels of skill. The exact mechanisms for compensation have yet to be identified. Future research will need to focus on identifying the knowledge base that players possess. Studies will also need to test the extent to which speed constrains skilled performance. Bridge Whereas it is possible to have a chess program play in a masterful way without knowing much about chess beyond the rules of play. it is impossible to avoid embedding a great deal of knowledge in bridge-playing programs. Bridge, unlike chess, is a game of incomplete information. The problem-solver must deal with uncertainly about the exact layout of the playing cards held by the opponents and partner during the bidding phase, and is uncertain about half of the cards at the beginning of playing out a contract (whether declarer or one of the defence players). Players must deal with probabilities and constantly revise their predictions about card holdings that are unseen (count cards during play and make inferences: see Charness, 1989;Frey, Truscott & Kearse, 1976;Engle & Bukstel. 1978). Skill in playing out a contract involves knowing a great deal about specific card combinations and their proper play. Similarly, in the bidding phase, bidding systems demand that the player memorize specific card-bid combinations. Take the case of opening the bidding with "one no trump" in "Standard American" bidding. It is bid when a player has 16-18(sometimes 15-17)high card points (Ace = 4, King = 3, Queen = 2. Jack = 1) and the suit distribution (number of cards held in spade. heart, diamond, and club suits) is 43-3-3or 4-4-3-2, and occasionally 5-3-3-2where the 5-card suit is diamonds or clubs, There may be dozens of such to-be-learned bids in a typical comprehensive bidding system. Human and computer

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alike must master a great deal of detail, since search is a n impractical way to proceed. Age and Skill Effects

Early work in bridge supported the notion that sktll depended on a large knowledge base. Skill in bridge was estimated via the logarithm of accumulated master points, self-rating. and perfoxmance on a bridge quiz in Charness (1979).The problem with master points as a measure of skill is that they can be won, but never lost, so they accumulate over a player's lifetime. If you play often enough, even at a modest level of skill, you can accumulate many points. Both Charness (1979)and Engle and Bukstel (1978) showed that memory for recently played bridge hands was a good predictor of skill level. Similar to the case in chess, Charness (1979)also showed that both incidental and intentional memory for bridge hands declined with age, and increased with skill. However, two criterion measures, bidding accuracy and play planning accuracy, increased with skill and were unaected by age. The Charness (1979)sample was very small (N = 20) and was not selected to ensure that age and skill were uncorrelated. When 45 players were selected such that age and skill were uncorrelated (r = -.06: Charness, 1983. 1987).similar results were obtained. Speed of bridge bidding increased with skill, but decreased with age. Bidding accuracy, though uniformly high, increased with skill, and was unaected by age. As was the case in chess, an interaction between age and skill was observed, here, for bidding speed. The greater a player's age, the less the advantage to being more skilled. By about age 60. there was no longer any bidding speed advantage assoclated with being more skilled. Similarly, when the stage of determining the honour card point count was investigated (Charness, 1987).again accuracy was related solely to skill, whereas latency (decomposed into slope and intercept components) was positively correlated with age (for the intercept) and negatively correlated with skill (for the slope). Unlike the earlier case, however. no interaction was observed between age, skill, and point count estimation speed. The somewhat artificial bidding task did generate patterns of effects for

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age that mirror other laboratory studies. Skill was associated with manipulating already encoded information efficiently (the slope parameter), whereas age was associated with difficulties in getting information into and out of the system (strong intercept effects). It is worth stressing that in normal bridge play there is no necessity to announce a bid or make a play as quickly as possible. (In fact, too rapid a bid may be unethical in the context of the player's usual bidding latency. Such a rapid response may convey the information that the player had such poor cards that there was nothing to think about.) Bidding accuracy is the "ecologically valid" measure of bidding acumen. In bridge, there is no premium on rapid responses. One of the hallmarks of weaker players is their impulsive play and lack of planning (Charness. 1989). Bridge play possibly represents a case where compensation may not be necessary for older players. Skill in bridge may be a form of power test: Do players have the knowledge to make the correct play or bid, or are they lacking the knowledge? Still, memory constraints can play an important role in a player's ability to keep track of events and plan future bids and plays. (Recall the negative age effects observed for incidental memory for played hands: Charness, 1979). There is little evidence of searching in bridge (Charness, 1989).though the laboratory tasks have not yet done an adequate job of capturing on-line problem solving. It can be expected that errors will occur more frequently in older players if their memory system is less reliable. The short duration tasks investigated so far may not be adequate to detect such age effects. Since there is no "gold standard' for measuring bridge skill, there is less of an opportunity to trace the age of peak bridge playing. Also, since bridge is a partnership game (play is by pairs and teams of four players), it will be difficult to disentangle ageperformance relationships if partners are not the same age. Investigation of age and skill effects in bridge is still in its infancy. MOTOR SKILLS The next two domains we'll review do have the benefit of "gold standards" for measuring skill. Typing speed is often measured in net words per minute, a combined speed/accuracy measure. It is

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easily enough measured with standardized test passages that job descriptions will require specific speeds (e.g., want ads appear specifying 60 wpm). Similarly, track and field and other athletic events are often administered under highly controlled conditions. Record times are measured quite accurately. Often there are agreed upon criteria for crediting performance even in team events (e.g., who is the winning pitcher when several participate in a baseball game). Motor skills have the further benefit that they tap into human performance at what are thought to be physiological levels. At least in theory, compensation ought to be more difficult the more a task depends upon hardware limitations. Yet, surprisingly, cognitive components appear to be important contributors to skill in these domains (e.g.. Allard 8t Starkes, in preparation).

Several cross-sectional studies have reported no age-related declines in typing speed (Bosman, in preparation: Salthouse. 1984) indicating that older adults are able to perform at very high speeds. For example, a typist whose speed is 80 words per minute (wpm) Is executing a keystroke every 150 ms. A less skilled typist whose speed is 40 wpm is executing a keystroke every 300 ms. That older typists are able to maintain these speeds is quite impressive given the age-related declines that are typically found on reaction time tasks. For example, in a recent study examining age differences in simple reaction time, Wilkinson and Allison (1989) reported a n increase in reaction time from 240 ms in the twenties to 280 ms in the sixties indicating that elderly adults are 1.17 times slower than young adults. For choice reaction time tasks elderly adults are approximately 1.6 to 1.7 times slower than young adults (Cerella, 1985). A critical question becomes why is there no age-related slowing in a complex task like typing when such declines occur on much less complex reaction time tasks. Research examining age differences in typing skill has tried to answer this question in several ways. One approach involves examining age difTerences in the molecular components underlying typing sku1 (Bosman. in preparation; Salthouse, 1984). Molecular

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components can be regarded a s the constituent parts, or building blocks, of skilled performance. They represent the simpler parts that are combined to produce the more complex skill. Examples of the molecular components underlying typing are finger tapping and choice reaction time. For samples in which there is no correlation between age and skill level, identifying age-sensitive molecular components makes it possible to infer which processes are agesensitive, and suggests where in the process of combining the molecular components older adults may be required to compensate if they are to maintain performance. Another approach involves trying to identify compensatory mechanisms that may be employed by older typists through a fine grained analysis of typing performance. In addition to varying in terms of typing speed, typists of different skill levels also vary on other descriptive measures of typing skill. The objective of this line of research is to identi@ age differences on these measures. Age Differences on Molecular Components

At least three categories of processing underlie typing performance: a) input processes which are concerned with reading the text; b) translation processes which operate to convert the letters in the text into the appropriate motor programs, and c) execution processes which are responsible for executing motor programs. Evidence regarding age-related changes in the molecular components underlying typing skill suggests that when age-related declines are observed they are located in the translation and execution stages.

Input processes Normal reading speed has been used as an index of the efficiency of the input processes involved in typing. Several studies have shown that there is little relationship between age and reading speed for typists: r = -.13,Bosman (in preparation); mean r = .02. Salthouse (1984). This suggests that typists of varying ages are probably equally efficient in perceiving the to-be-typed text. In addition, it is generally thought that the limit on typing speed is not

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associated with input processes. Even for typists whose speed is in excess of 1 0 0 wpm. reading speed is at least twice as fast as typing speed. (The Gufnness Book of World Records, 1989, gives top manual typewriter rates of 170 net wpm for one minute, 176 net wpm for five minutes, and 147 net wpm for one hour of typing. The rather severe penalty of 10 words lost per error was imposed in these contests.) Several studies have demonstrated that there is no relationship between reading speed and typing skill ( r = .lo, Bosman. in preparation: r = .13.Salthouse. 1984). Taken together these findings suggest that input processes are probably not the locus of age-related declines in typing. Tt.anslation processes

The Digit Symbol subtest from the Wechsler Adult Intelligence has been used as an index of the speed of perceptualScale (WNS) motor translation processes involved in typing. Digit Symbol performance is moderately correlated with typing skill ( r = .31, Bosman. in preparation: r = .53,Salthouse. 1984)suggesting that it is not strongly related to the translation processes involved in typing. However, the moderate correlation with typing skill, coupled with the pronounced age-related declines on Digit Symbol performance suggests that translation processes are one locus of age-related declines on the molecular components underlying typing. Choice reaction time (CriT) has also been used as an index of the speed of translation processes involved in typing. The available evidence suggests that the pattern of sktll and age merences in C W among skilled typists depends upon how similar the reaction time task is to typing. In one task that was quite dissimilar to typing, either an 'L'or a n 'R could appear on a screen, and the response was to press the key associated with each letter (Salthouse. 1984).As expected. the task was related to age, (mean r = .54).but showed only a slight relationship with typing skill (mean r = -.27). The latter finding suggests that this particular CRT task may not be representative of the translation processes involved in typing. Consequently, it is not clear if the age-related decline observed in

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this task indicates a specific age-related difficulty with the translation processes involved in typing. This possibility received some support from the pattern of age and skill differences in a choice reaction time task more similar to typing (Bosman, in preparation). The task required the typist to sit with their hands in the home row position, and when a letter appeared on the screen they were to type the letter as quickly as they could. The results revealed significant effects of age (r = .51). and skill (r = -.65). Even more interestingly the results revealed a significant interaction between age and skill indicating age-related declines in reaction time for less skilled typists, but no age-related differences in reaction time for highly skilled typists. The implication is that for highly skilled older typists there is compensation at the level of molecular components.

Motor processes Speed of finger tapping has been used as an index of speed of execution processes. Tapping rates for a single finger are modestly related to typing skill (r = -.30.Bosman. in preparation; mean r = .32,Salthouse. 1984). and do not always show strong age-related declines ( r = .23,Bosman, in preparation: mean r = .68. Salthouse. 1984). However, tapping rates for alternate finger tapping be.. tapping a finger from each hand in alternation), are moderately related to skill, (mean r = -.43) and seem to show more consistent age-related declines (mean r = .46, Salthouse, 1984). This finding is consistent with studies examining novice-expert differences which have shown that expert typing speed is in part dependent upon the ability to overlap finger movements across and within hands. In contrast, the slower speed of novices is in part attributable to a n inability to effectively overlap finger movements (for reviews. see Gentner, 1983; Salthouse, 1986 ). Speed of alternate flnger tapping can be regarded as an index of the ability to overlap finger movements, and the finding of an age-related decline on this task suggests that older typists may have greater difficulty than younger typists in effectively overlapping finger movements. The research reviewed above suggests that there are no agerelated declines for input processes, but the results for translation

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and motor processes are less clear. One difficulty with research examining age and skill dmerences in the molecular components underlying typing skill is that there is no consensus regarding which tasks are most representative of the underlying component processes. For example, Digit Symbol performance, and reaction times on a C W task unrelated to typing skill suggest age-related declines on translation processes. A choice reaction time task more similar to typing reveals an interaction between age and skill suggesting compensation by older skilled typists. Additional research is required to identify the most representative tasks before the pattern of age-related changes on the molecular components of typing can be accurately specifled.

Compensatory Mechanisms An age-related difference in typing skill that seems to function as a compensatory mechanism is the increase in the size of the eyehand span with age (Bosman, in preparation: Salthouse. 1984). A typist always reads a few characters ahead of the actual letter they are typing: and the eye-hand span refers to the number of characters between the character being read, and the character being typed. Although it can be measured by monitoring eyemovements, the eye-hand span is usually measured indirectly by varying text preview, &e., varying the number of characters in the to-be-typed text that can be seen while typing). If the amount a typist can read ahead is less than their usual eye-hand span, typing speed falls off sharply. This implies that the eye-hand span represents the amount of text the typist needs to have available in order to maintain typing speed. In addition. the size of the eyehand span varies with skill, being no more than 2 or 3 keystrokes for novice typists, and as much as 6-8 keystrokes for experts. The implication is that skill acquisition is associated with a n increased reliance upon advance preparation of keystrokes. Considered in conjunction with these findings, the age-related increase in the eye-hand span suggests that dder typists maintain typing performance by beginning preparation of keystrokes sooner than younger typists.

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At present there are no definitive answers regarding how the eye-hand span enables older typists to compensate for age related declines. In part the answer depends upon the hypothesized function of the eye-hand span during typing. One suggestion is that the eye-hand span reflects the number of characters required to keep the translation and execution processes continuously supplied. That is, the eye-hand span reflects the demand for characters by the translation and execution processes (Cooper. 1983;Salthouse. 1984). Consistent with this interpretation is the finding that within a n individual typist the size of the eye-hand span varies with typing speed. As the individual's rate of typing slows their eye-hand span decreases in size, and vice versa. When typing speed slows there is a reduced demand for characters by the motor and execution processes, and consequently the eye-hand span decreases (Salthouse, 1984). Also consistent with this interpretation is the argument that the limit on typing speed is not associated with input processes, but rather with translation and motor processes. If this interpretation of the eye-hand span is accepted, it suggests that older typists require a larger buffer of characters if translation and motor processes are to be optimally supplied. Although the available evidence is not entirely consistent with this interpretation, it could be argued that older typists compensate for slower translation and motor processes by beginning preparation of keystrokes sooner, and consequently have a larger eye-hand span. Another possibility is that translation and motor processes are more variable in older typists, or more easily disrupted. To maintain continuous output older typists may require a larger buffer of characters so that they can recover quickly from any disruptions that would otherwise slow performance. The argument is that the larger eye-hand span of older typists does not function to compensate for age-related slowing, but makes it easier for older typists to compensate for an increased susceptibility to the breakdown of performance.

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Conclusions Among the skills that have been examined by research focusing upon age differences in skilled performance, typing is unique because it is the only skill for which there is direct evidence indicating that older typists may be compensating for age-related declines. The results of the CRT task employed by Bosman (in preparation) suggests that highly skilled older typists are able to maintain performance on some of the molecular components of typing skill. The age-related increase in the eye-hand span suggests that greater advance preparation is another mechanism used by older typists to maintain performance. Future research should seek to define the boundary conditions of these two compensatory mechanisms in order to better understand their nature of operation. It is likely that there are additional compensatory mechanisms that have not yet been identified, and an objective of future research should also be to identify other compensatory mechanisms employed by older typists. Athletics

As the Talland quote made clear, the sports domain is critical for examining questions about skill and age. For no other human endeavor is the emphasis on youth so great. Recently. there has been a push to ensure a place for older athletes in competitive sports with the "Masters" categories. The age at which the masters events begins varies considerably. Ericsson (in press) noted that for swimmers, the youngest "old" swimmers category is 25-29years in Germany. For runners the earliest masters age category is 40. The official categories internationally. however, are 40 for men and 35 for women. Peak Performance and Age In a recent review, Schulz and Curnow (1988)have shown that the mean age of peak performance by athletes in some sports domains has remained remarkably constant over the past century. Over the same time frame, the levels of performance have continued

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to improve, from as little as 10% to as much as 90% (the latter in shot put). They looked primarily at Olympic sports (track and field, swimming) as well as tennis, golf, and baseball. They also examined sex dltrerences. showing that the peak age of performance for females tends to occur a year to two years earlier than for males. These sex differences tend to align with physical maturation rates, which also peak one to two years earlier In females. Nonetheless, there were pronounced daerences in the peak ages depending on the sport. In events requiring explosive energy mobilization (short distance running and swimming, jumping, shot put), peak ages are in the 21-24 year range. In golf and baseball, where knowing what to do may be more important than doing something quickly. the peak ages (31 and 28 years, respectively) are later. Long distance events (running, swimming) have later peak ages (25-29 years of age) than short distance events. The one notable exception for the distance rule is female swimmers, where increasing distance of event is correlated with a younger peak age. The authors argue that biologically-related buoyancy factors may play an important role there.

Theories of Age and Peak Performance Theorists about age and peak athletic performance (e.g., Ericsson, in press: Hartley & Hartley, 1984, 1986; Stones & Kmma, 1982. 1984, 1985, 1986) have attempted to link peak performance age with biological and training/practice explanations. Stones and Kozma (1986) evaluated a number of models proposed to account for age trends across various athletic events (particularly track and field events). They concluded that their "power output relative to power available" model (POrPA) provided the best fits to reaction time, strength assessment, and athletic records. Their model assumes that the typical negative age trends for record performance will be steeper when the event requires a high amount of energy relative to the available supply. There are two sources of energy supply: anaerobic and aerobic. Anaerobic power depends on the ATP-PC and lactic acid metabolic systems. Aerobic power depends on oxygen metabolism, Power output demands in

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many athletic events are related to two features: the strength required and the duration of the event. In short duration events, which rely mostly on anaerobic power sources, age-related decline will increase with strength demanded. Hurdles and high jump, events which have pronounced "explosive" strength demands, will show greater age decline than sprints. where power translation is probably smoother past the explosive start phase. In longer duration events where aerobic power becomes more important, such a s long distance running and swimming, age decline will increase with event length. Aerobic energy sources will be mobilized less effectively with increasing age. Such predictions were well-supported by the data. At first blush, such results seem paradoxical when contrasted with Schulz and Curnow's (1988)finding that peak age is later for long distance events. But peak age depends largely on training. Aerobic fitness and long-term changes in muscle fiber composition may require a longer perlod of intensive training for long distance events than for short ones. (Most sedentary young people can probably muster enough energy to run for 100 m, but many would not be able to maintain running speed for 1000 m.1 Once you are past peak age, the decline slope may still be greater for events demanding high power output relative to the power available. Underlying these predictions are assumptions about agestrength and age-oxygen utilization trends. Power depends in part on muscle mass (as well as neural enervation). Large muscles (legs, trunk) show greater age decline in strength than smaller muscles (arm, hand). Similarly. aerobic capacity shows strong linear age decline in sedentary individuals. Of course, both capacities (strength, aerobic capacity) show remarkable plasticity with respect to training effects. Nonetheless, peak capabilities may be age-sensitive, and skilled athletes may well be operating near asymptotic levels where such peaks matter. Perhaps a good analogy for age and peak performance effects is the case of a rechargeable battery: the lithium cell model. Power output is a function of the previous charging period (training), the freshness of the internal components (age), and the length of time that the battery is active (event duration).

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Trafntng Effects Ericsson (in press) focused most closely on training effects. To get around the problem of relying on Olympic performance records, since the athlete has only one opportunity every four years, Ericsson examined running went performances of the top 10 male athletes for a variety of countries in 1986. He found different age peaks in different countries (e.g., China had significantly younger peak competitors, because, Ericsson surmised. China only recently provided organized training). But, he confirmed the tendency for longer distance track events to be best performed by older runners. Ericsson also noted that there was very high variability among the oldest participants in Masters athlete programs, suggesting that training effects might be a factor. He cited a longitudinal study (13 years) by Letzelter which showed that German masters athletes in swimming showed no statistical declines in performance. Stability was attributed to frequency and intensity of training. To look at individual trends, Ericsson examined in detail three top calibre competitors (Nurmi: running, Hein: hammer throw, Jiixvinen: javelin). He found that personal best performances (27 years, 30 years, 27 years, respectively) occurred later than would be expected from Olympic records, though how much this may be due to secular trends (improvements in equipment and track conditions) is unknown. Further, it is difficult to generalize from only three cases. Strong age trends were quite evident when looking at yearly peak performances. Ericsson also considered the physiological evidence for peak athletic performance, focusing on runners for whom the most data is available. Aerobic power, ability to utilize oxygen. is a very important aspect of such sustained motor activity. Early on it was clear that features such as increased capillary supply to muscles, heart size, and percent of slow-twitch muscle fiber were important daerentiators of elite athletes and inexperienced athletes and nonathletes. Proportion of slow-twitch fiber was a strong predictor of long-distance running success for a mixed distance group of runners, though it was not a significant predictor within a group of elite long distance runners. The classification of fiber types, however, is controversial (Houston, 1978), s o statements about

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percent of slow-twitch fibers are best viewed a s heuristic. Nonetheless, such variables as fiber type, capillary supply, and heart size do tap into the anatomical underpinnings of aerobic power. It was also believed that such factors had high heritability coefficients (90%). (Athletes were born, not made.) Ericsson summarized later work which showed how intensive exercise was sufficient to promote these changes, including the change in composition of muscle fiber (fast-twitch being replaced by slow-twitch fiber). Later estimates of heritability were considerably lower. The training necessary to effect such changes was not shortterm. Evidently, reliable changes in muscle fiber composition are only observed with training periods in excess of 20 weeks. It usually takes about 10 years for runners to reach their peak. Further, only muscle groups that are exercised show changes. Ericsson cites a study by Tesch and Karlsson that shows that middle and long-distance runners have higher percentages of slowtwitch fiber in the legs than control subjects, but not in the back. Kayakers show the reverse pattern. Even in sports, however, cognitive factors can set limits. Work by Backman and Molander on miniature golf (Backman & Molander, 1986a. 1986b; Molander & BAckman. 1989) suggests that ability to handle cognitive arousal during competition diminishes for players in their fifties. When older players move from training to competition, their performance declines, whereas the opposite is true for younger players. Older players fail to show heart rate deceleration during concentration phases of putting, whereas younger players exhibit such deceleration, and it is greater during competition. Ericsson concluded that athletic performance can be maintained with minor decrements into the 60s, if there is continuous intensive training. He also notes, however, that with intensive training comes an increased risk of injury. Age may set the limits for performance, but these limits are rather generous ones for those who can avoid injury. It is in the area of athletic performance that the boundaries between hardware (architecture) and software (task knowledge) begin to blur. Practice and training significantly alter the

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hardware (muscle fiber, blood supply, heart size), though a s Ericsson noted, training cessation often leads to a reversal in muscle fiber composition. Here, as in other domains, it is only the specific task (and task-related hardware) that shows change with training (contrast kayakers and runners). The Salthouse and the Bosman studies show that typists only appear superior when the task maintains important elements of transcription typing. Although there is a hint of a generalized (genetic?) advantage for skilled performers (e.g., a slight tapping speed correlation with typing skill). it may be the by-product of training rather than the determinant of typing skill. THEORIES OF COMPENSATION If aging is associated with inefficiencies in cognitive and perceptual-motor processing, how do older adults maintain their performance? There are a number of possibilities. First, we may be making an unwarranted assumption that aging leads inevitably to inefficient functioning for every older adult. Longitudinal studies of psychometric performance suggest that little decline is noticeable in most people until the 60s and that for some, no decline is evident until the 70s or later (see Schaie. 1989). Nonetheless, lack of molar decline, as argued earlier, is not strong evidence against hardware deterioration. Given the remarkable improvements that can accrue from knowledge accumulation and task-specific practice, we have to wonder why there is no improvement in performance with increasing age. One possibility is that knowing too much could slow down retrieval. Even with parallel search, the more information that is in the system, the slower will be the retrieval process. Another explanation for the absence of a positive trend with age is forgetting. Since humans forget, it is also possible that a s people age. they forget old information at the same rate that they gain new information, leaving performance unchanged, as Salthouse ( 1989) suggested. A second possibility for maintained performance is that aging impairs some functions but selectively spares others. (Such an assumption underlies much of experimental research on cognitive

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aging, since the hope is to show interactions with age across experimental conditions. The goal is to identify age-sensitive and age-insensitive processes.) The tasks that adults perform competently may, by chance, fall into the set of spared functions. If you accept standard information processing assumptions (e.g., Card et al., 1983).basic cycle times (such as those for the perceptual, cognitive, and motor processors) are thought to drive all operations. Aside from practice-mediated improvements, if the cycle time lengthens with age, all mental operations are expected to be slowed. Such slowing can be expected to hurt efficiency of performance quite generally. The age-slowing hypothesis falls out of these assumptions, and there is reasonably compelling support for this hypothesis. Thus, a selective sparing view must posit that, for instance, the motor and cognitive processors are hurt by aging, but not the perceptual one, thus leaving tasks that depend heavily on perceptual processes intact. No simple class of activities fits well with such a selective processor-sparing viewpoint. Older adults seem to be able to perfom well in motor domains as well as cognitive ones. A variant on the latter view is that practiced tasks are insulated from age-related deterioration, but novel ones that rely on slowed processing show age-related deficits. Ftybash, Hoyer, and Roodin (1986)called the results of practice "encapsulation". There is a substantial body of evidence that practice enables older adults to improve their performance drastically, even to levels well beyond those achieved by novice young adults. Some of the studies mentioned in this chapter flt such a perspective. Nonetheless, it is not yet clear how the complex processes that support everyday activities and more critically, paid employment, fit into this framework. Practice and Skill What processes improve with practice? There is a long history of finding limited transfer of training for practiced activities. Thus far, there is only weak evidence for a general cognitive toning-up function for general mental exercise. With training "near transfer" is commonplace, but "far transfer" is quite weak (e.g.. Baltes,

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Sowarka h Kliegl. 1989). Unless you develop a great many different procedures to handle specific cases. simple practice may not improve a broad function such a s memorizing ability very much (see Ericsson, 1985,for a review of memory training). We will need a close examination of typical working environments to understand better the mbt of practiced and unpracticed activities. It may be the streaming of successive pieces of the processing chain that undergoes the greatest change with practice. Anderson ( 1982, 1987)used the terms "compilatfon" and "proceduralization" to describe these processes. Only about one third of the speed-up that Chamess and Campbell (1988)observed in a two-digit mental squaring task was due to faster execution of elementary arithmetic operations. Most of the speed-up was attributed to learning how to chain the subgoals together quickly and efficiently. T h e Fisk, McGee, and Giambra (1988)semantic categorization results indicate that older adults may have a difficult time developing automaticity. Such task organization processes (control processes) may be important mediators of age and skill differences. In short, we have a long way to go in developing adequate models of how Compensatory mechanisms operate in older adults. Even when we look at typing, the one clear-cut case where a compensatory mechanism has been isolated, intriguing questions arise. Why, for instance, don't younger typists avail themselves of the same buffering mechanism to type even faster than they already do? If buffering keystrokes is good for the skilled, and better for the old and skilled. why isn't it best for the skilled young? One argument is that perfomance would break-down if younger typists attempted to read further ahead in the text. Specifically, input processes would get too far ahead of translation and execution processes causing a break-down in performance. The assumption is that the size of the eye-hand span cannot be flexibly controlled by the typist, but as discussed previously, reflects the demand by translation and execution processes for characters. The implication is that the eye-hand span increases in size when text characteristics or skill acquisition increases the speed of execution processes thereby increasing the demand for characters. There is no reason to assume that increasing the she of the eye-hand span by reading further ahead than normal would increase the efficiency

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of execution processes, and as suggested, this may interfere with typing. We can also fall back on the argument that people usually satisfice (Simon. 1969) rather than optimize performance. After all, typists don't usually have to meet a 100 wpm typing speed criterion to be hired or even to be promoted once hired. In certain highly competitive environments. particularly in athletic endeavors, where optimization is the goal, we do see that virtually all the world record holders are young. CONCLUSIONS We want to argue that aging, at least with respect to cognitive tasks and some perceptual-motor ones, can be viewed as a process causing slowing in the rate of information processing. Such slowing leads to poorer performance on non-practiced operations, and likely slower acquisition of new skills, particularly those dependent on new knowledge structures. Countering age-related slowing in most real world tasks are the effects of practice. Practiced operations speed up for young and old alike. Practice can maintain the performance of older adults at high levels, with one proviso. The task to be accbmplished must be self-paced rather than externally paced. That Is. the input flow rate must be under the person's control, otherwise slowing in basic perceptual operations may limit performance. -ping is an example of a task that allows successful compensation, primarily because the maximal output flow rate (keystrokes) is considerably less rapid than input processing rates (reading speed). In sports domains, where output processes are slaved to unpredictable inputs (e.g.. tennis) such buffering is not possible, and age-related slowing effects cannot be overcome. Practice is not necessarily an easy cure for age-related slowing. Sometimes it takes a great deal of practice to produce the cognitive or physiological changes that support high level performance. One can draw the analogy between the "fast-twitch to slow-twitch" change in muscle fiber and the development of compiled programs (automaticity) for cognitive tasks.

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Still, with this viewpoint comes the admittedly extreme claim that virtually every skilled older person (age 65+)who performs at similar levels to younger adults is doing so via some compensatory mechanism. Further. when.it comes to peak performance in speedconstrained tasks, no old individual will outperform a comparably (Establishing trained young individual in that domain. "comparable training" is not going to be easy, though there are some interesting attempts at cataloguing practice with diaries (Ericsson, Tesch-Rlimer, & Krampe, in press.) The extreme claim of no old individual being better than the best young one derives considerable support from the field of athletics. Nonetheless, Ericsson (in press) noted that some of today's Masters athletes (using the 1979 Masters competitors' records) have achieved performances that equalled or bettered those of young athletes who won events in the 1896 Olympic games. Such record-surpassing or equalling performance only occurred for Masters athletes less than 65 years old, with the exception of the marathon. There were no cases, however, of Masters athletes equalling the 1896 World Records. Given improvement trends, even that barrier is likely to fall, if it hasn't done so already. Another potentially important factor in age decline is forgetting: a form of the "disuse" hypothesis captured in the quote "use it or lose it". Forgetting rates do not vary much with age {Charness & Campbell, 1988; Kriauciunas 1968; Salthouse & Somberg, 1982; Wickelgren. 1975). Admittedly, older adults have a longer time frame over which to forget information than their younger counterparts. particularly if they do not use the information. Some recent research by Salthouse, Babcock, Shovronek, Mitchell, and Palmon ( 1990) suggests, however, that disuse is not the explanation for the decline in spatial visualization ability experienced by skilled older architects. Concatenating these phenomena leads to some interesting predictions. First. there ought to be a great deal of plasticity in the performance of older adults, since it is unlikely that they have practiced a specific skill to asymptotic levels. Second. it will take them considerably longer to reach the same performance levels a s the young: if both practice a task, the gap will close slowly, and perhaps not at all (Fisk. McGee, & Giambra, 1988). (Neither the

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young nor the old may live long enough to hone a skill to the level of automaticity that brings them down to physiological limits of response.) Third, maximal age differences are expected in simple, poorly practiced tasks, where hardware sets limits on performance. Minimal age differences are anticipated in complex tasks demanding knowledge. when the old are more likely to possess the relevant knowledge than the young, and when they also have the time to prepare their response. Maximal differences can also be expected in complex tasks demanding the assembly of new performance programs, because of the slower learning rate of older adults. Life in the lab is difficult when it comes to aging research. We have to contend with an independent variable, age, that cannot be manipulated. We also run the risk that our tasks will not have much generalizability beyond the lab, Nonetheless, the study of expertise and aging holds some promise that when we look through the lab window, we can see behaviors that are life-like. Most of the time the environment (work or play) poses challenges that do not tax the capabilities of most aging adults too heavily. They resemble young people in their performance at the molar level. Digging a little deeper, you sometimes discover that molar equivalence is achieved in fundamentally different ways by young and old. As biology has amply demonstrated, a diverse set of mechanisms can cope successfully with the same environmental challenges. Aging research is at the early stage of establishing a taxonomy of compensatory mechanisms. It is a necessary first step if we hope to uncover the path that leads from laboratory theories to life practices. ACKNOWLEDGMENTS

This work was supported by grants from the Natural Sciences and Engineering Research Council of Canada, NSERC A0790, and BellNorthern Research. We thank Fran Allard, Tom Hess. and Tim Salthouse for helpful comments on earlier drafts.

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Grant, E. A., Storandt, M. & Botwinick. J. (1978).Incentive and practice in the psychomotor performance of the elderly. Journal ofGerontology. 33,413-415. Guinness Book of World Records (1989).New York Bantam. Hartley. A. A. & Hartley, J. T. (1984).Performance changes in champion swimmers aged 30 to 84 years. Experimental Aging Research, 10, 141-147. Hartley. A A & Hartley. J. T. (1986).Age differences and changes in sprint swimming performances of master athletes. Experimental Aging Research, 12,65-70. Herzog. A. R. & Rodgers. W. L. (1989).Age differences in memory performancc and memory ratings a s measured in a sample survey. Psychobgy and Aging, 4. 173-182. Holding, D. H. (1985). Thepsychology ofchess skffl. Hillsdale, N.J.: Erlbaum . Homer, K. L.. Murray, H. G., & Rushton. J. P. (1989). Relation between aging and rated teaching effectiveness of academic psychologists. Psychology and Aging. 4. 226-229. Homer, K. L., Rushton, J. P., & Vernon, P. A. (1986).Relation between aging and research productivity of academic psychologists. Psychology and Aging, 4 . 319-324. Houston. M. E. (1978). The use of histochemistry in muscle adaptation: A critical assessment. Canadfan Journal of Sport Sciences, 3, 109-118. Kausler. D. H. (1982).Experimental psychology and h u m aging. New York Wiley. Kliegl. R.. Smith, J. & Baltes. P. B. (1986).Testing-the-limits, expertise, and memory in adulthood and old age. In F. Klix and H. Hagendorf [Eds.) Human memory and cognitive capabilities (pp. 395-407). Amsterdam: Elsevier Science Publishers. Testing-the-limits and the Kliegl, R., Smith, J. & Baltes, P. B. (1989). study of adult age differences in cognitive plasticity of a mnemonic sktll. Developmental PsycFtologg, 25,247-256. Kriauciunas, R. (1968). The relationship of age and retentioninterval activity in short-term memory. Journal of Gerontology, 23. 169-173. Labouvie-Vief, G. (1985). Intelligence and cognition. In J. E. Birren & K. W . Schaie (Eds.) Handbook of the psychology of aging (2nd ed., pp. 500-530).New York Van Nostrand Reinhold. Lehman. H. C. (1953).Age and achievement. Princeton, N.J.: Princeton University Press. Miller. G. A. (1956).The magical number seven, plus or minus two: Some limits on our capacity for processing information. Psychological Review, 63, 81-97.

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Molander, B. & Backman. L. (1989).Age differences in heart rate patterns during concentration in a precision sport: Implication Journal of Gerontology: for attentional functioning. Psychological Scfences, 44, P80-87. Mumell. K. F. H. (1965).Human performance in industry. New York: Reinhold. Newell, A. (1989).Putting it all together. In D. Klahr and K. Kotovsky (Eds.) Complex information processing: The impact of Herbert A, Sfmon(pp. 399-440).Hfllsdale, N.J.:Erlbaum. Patel, V.L. & Groen. G. J. (1986). Knowledge based solution strategies in medical reasoning. Cognfffve Scfeme, 10,91 - 1 16. Hau, H. D. & Murphy, M. D. (1988).Role of verbal knowledge in chess skill. American Journal of Psychology. 101.73-86. Rybash, J. M.,Hoyer, W.J.. & Roodin, P. A. (1986).Adult cognitfon and agtng. New York Pergamon. Salthouse, T. A. (1984). Effects of age and skill in typing. Journal of Experimental Psychology: General, 13,345-371. Salthouse, T.A. (1985).A theory of cognftfue aging. Amsterdam: Elsevier Science Publishers. Salthouse, T. A (1986).Perceptual, cognitive, and motoric aspects of transcription typing. Psychologkal Bulletfn. 99, 303-319. Salthouse, T.A. (1988). Initiating the formalization of theories of cognitive aging. Psychology and Aglng, 3.3-16. Salthouse, T. A. (1989). Aging and skilled performance. In A. Colley & J. Beech (Eds.) The acqufsftion of cognitive skills (pp. 247264).Chichester. U.K.:John Wiley & Sons. Salthouse, T. A. (1990).Cognitive competence and expertise in aging. In J. E. Birren & K. W. Schaie (Eds.). Handbook of the psychology of agfng (3rd ed., pp. 310-314).New York Academic Press. Salthouse, T. A, Babcock, R. L., Skovronek, E..Mitchell, D. R D., & Palmon, R. (1990). Age and experience effects in spatial visualization. Developmental Psychology, 26, 128-136. Salthouse, T. A. & Somberg, B. L.. (1982).Skilled performance: Effects of adult age and experience on elementary processes. Journal of Experimental Psychology: General, 1 1 1. 176-207. Schaie. K. W. (1983).The Seattle longitudinal study: A 21-year exploration of psychometric intelligence in adulthood. In K. W. Schaie (Ed.) Longftudlnal studfes of adult psychological development (pp. 64-135). New York Guilford Press. Schaie. K. W. (1989).The hazards of cognitive aging. The Gerontologlst, 29, 484-493.

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Schulz. R. 81 Cumow, C. (1988).Peak performance and age among superathletes: Track and field, swimming. baseball, tennis, and golf. Journal of Gerontology: Psychological Sciences, 43, P113120. Simon, D. P. & Simon, H. A. (1978).Individual differences in solving physics problems. In R. Siegler (Ed.), Children's thinking: What dewlops? (pp. 325-348).Hillsdale. NJ: Erlbaum. Simon. H. A. (1969).The sciences ofthe a@ticial. Cambridge, M. A.: MI" Press. Simon, H. A. (1979).Information-processing models of cognition. Annual Review of PsychotOgy, 30, 363-396. Simon, H. A & Gflmartin, K. (1973). A simulation of memory for chess positions. Cognitive Psychology, 5,29-46. Simonton, D.K. (1988). Age and outstanding achievement: What do we know after a century of research? Psychological Bulletfn. 104.251-267. Stones, M. J. & Kozma, A. (1982). Cross-sectional, longitudinal, and secular age trends in athletic performances. Experimental Aging Research, 8, 185-188. Stones, M. J. & Korma, A. (1984).Longitudinal trends in track and field performances. Experimental Aging Research, 10, 107-1 10. Stones, M. J. & Kozma, A. (1985).Physical performance. In N. Chamess (Ed.) Agtng and human performance. (pp. 261-291). Chichester, U.K.:John Wiley & Sons. Age trends in maximal physical Stones, M. J. & Kozrna, A. (1986). performance: Comparison and evaluation of models. Experimental Aging Research, 12,207-215. Talland, G.A. (1965).Initiation of response, and reaction time in aging, and with brain damage. In A. T. Welford and J. E. Birren (Eds.) Behaufor, aging, and the nervous system Ipp. 526-561). Springfield, Illinois: Charles C. Thomas. Todd, M., Davis. K. E., & CaEerty, T. P. (1983).Who volunteers for adult development research?: Research findings and practical steps to reach low volunteering groups. International Journal of Aging and Human Development, 18. 177-184. Welford. A. T. (1985).Changes of performance with age: An overview. In N. Charness (Ed.) Aging and human performance (pp. 333-369).Chichester, U.K.: John Wfley & Sons. Wickelgren, W. A. (1975).Age and storage dynamics in continuous recognition memory. Developmental Psychology. 1 1 , 165-169. W i h o n . R.T..& Allison, S.(1989).Age and simple reaction time: Decade difllerences for 5,325 subjects. Journal of Gerontology: Psychological Sciences, 44(2),P29-P35.

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Aging and Cognition: Knowledge Organization and Utilization Thomas M. Hess Editor) 0 Elsevier Science Publishers B.V. North-Hollandl, 1990

CHAPTERNINE

LEVELS OF KNOWLEDGE UTILIZATION IN VISUAL INFORMATION PROCESSING William J. Hoyer Syracuse University

SUMMARY

The aim of this chapter is to consider the interactive effects of aging and experience on knowledge utilization at several levels of analysis. Age-related and knowledgerelated changes in visual information processing operate at a range of levels of encoding and access beginning with the information available to the observer in the visual array. It is suggested that there are several ways in which knowledge and the processes of aging interact to aff'ect visual information processing performance. First, there are age-related and experience-related changes in the extent to which stimulus constraints enable object recognition. Second, the possession of prior knowledge affects the extent to which particular stimulus factors trigger or prime the' semantic aspect of visual object recognition. Third, the amount and type of prior knowledge affects information selection (e.g., target/distractor filtering) and the semantic processes (e.g., object naming) associated with visual object recognition. Age-related deficits are mainly associated with the selective processing of available information and with access to the semantics- of visual object recognition. That these aspects of perceptual processing are (or seem) less impaired when older adults possess specific prior knowledge relevant to the visual domain suggests that the skilled visual information processing performance of older adults depends on the extent to

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which knowledge utilization processes have become inpenetratable to normal age losses as a function of domain-relevant experience. The aim of this chapter is to provide a description of developmental change (and regularity) in visual cognition in terms of age-related and experience-related changes in the processes that affect the speed and efficiency of knowledge utilization. Much of the research in cognitive aging has been directed at documenting agerelated changes in the speed and diciency of general encoding and retrieval processes. These findings provide a base relevant to describing age-related and experience-related changes in the processes involved in knowledge utilization. However, little attention has been given to examining the effects of what is processed on encoding and retrieval. It has long been observed that older adults can efficiently encode and retrieve some kinds of information (e.g.. in mastered domains), even under highly demanding conditions and despite deficits in what appear to be requisite processing abilities. Perhaps one of the most challenging issues in the study of cognitive aging is to explain how processing of some kinds of information is maintained against a background of age-related losses in the basic visual cognitive processes. Rabbitt ( 1977) posed the problem as follows: In view of the deterioration of memory and perceptual motor performance Wth advancing age, the right kind of question may well be not "why are old people so bad at cognitive tasks" but rather "how, in spite of growing disabilities. do old people preserve such relatively good performance?" (p. 623). It is a fact that cognition does not show an orderly pattern of change with advancing age. Within- and across-individuals, some aspects of visual cognitive performance improve, some are maintained at roughly the same level, and some decline with aging. Visual cognitive performance depends on a variety of subject characteristics (age, experience) and stimulus factors that interactively determine what and how information is processed. Visual knowledge must be functionally defined relative to the observer. The familiarity, salience, meaningfulness, affective

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value, and complexity of the information for a particular subject determine what and how such information is processed. In addition, age-related differences in the speed and efficiency of the basic processes required for the encoding, selection, and retrieval of visual information need to be considered. Central questions in the study of aging and knowledge utilization in visual perception pivot on the relations between the efficiency of pick up of visual information and the efficiency of utilization of acquired knowledge. In complex visual processing tasks. the individual's prior knowledge pertaining to the visual array and the individual's abilities to apply relevant knowledge to task demands, determine performance. A complete description of age-related and experience-related processes affecting performance involves the examination of the processes of knowledge utilization at a number of levels of analysis. Consideration should be given to the processes that are involved in: a) pick up, selection. and organization of stimulus information; and b) selective activation, access. and retrieval of prior knowledge related to the stimulus information. A complete theory of the developmental aspects of knowledge utilization will require specification of the interacting effects of the stimulus characteristics and observer characteristics that determine performance. Emphasis in this chapter is on the analysis of age-related changes in the high-level visual perceptual processes associated with knowledge utilization. Processes at this level are presumed to operate on perceptual units that correspond to objects, and the parts and features that comprise objects, However, it is important to keep in mind that age-related declines in the basic visual processes associated with acuity, contrast sensitivity. retinal eccentricity. accommodation, and adaptation probably aflect the efficiency of higher-level processes [e.g., Fozard, 1990; Kosnik, Winslow. Mine, Rasinski, & Sekuler. 1988).

LEVELS OF ANALYSIS OF KNOWLEDGE UTILIZATION Fodor and Pylyshyn (1988) have noted that the study of cognitive architectures involves the investigation of causal relationships at many diiferent levels of analysis. To quote Fodor

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and Pylyshyn (1988, p. 9): there is a scientific story to be told about quarks: and a scientific story to be told about atoms: and a scientific story to be told about molecules ... And the story that scientists tell about the causal structure that the world has at any one of these levels may be quite different from the story that they tell about its causal structure at the next level up or down." The implication of these remarks is that analyses of cognitive aging must specify the level of analysis that is at issue. The point is particularly relevant to the investigation of age and experience factors in knowledge utilization because very different kinds of methodologies and theories are involved at different levels of analysis. Types of visual knowledge range from that which is directly available in the visual array to that which gives meaning to what is perceived. Clearly, some aspects of visual processing are directly related to the quantity of information available in the visual array, and on this basis, some researchers have argued that visual processing is most usefully studied at a quantitative level that is free of higher order influences involving memory and inference (Gibson, 1966; McArthur. 1982). According to Gibson, for example, utilization of visual knowledge involves the detection and registration of invariant properties in the optical array. At this level, visual knowledge exists within the myriad of physical and photometric processes involving light and surface reflectance. Indeed, work by Marr (1982). Pinker (1984), Ullman (1984). and Zucker (1986) has shown that visual knowledge can be specifled in terms of measurable characteristics of the structure of visual arrays. It has also been shown that there are detectors and input analyzing systems at the retinotopic level that are highly specialized for responding to certain kinds of featural information (e.g., Todd & Reichel, 1989). Even these early input analyzing systems are influenced by experience across relatively brief exposures (e.g.. as in light adaptation) and by relatively long term experience (e.g., acquired recognition skills, a s in reading). Thus, there is a vast amount of visual knowledge utilization that is fast. ubiquitous, and derived directly from input; and this level of visual knowledge utilization operates prior to the activation of the processes of conscious recognition and object naming. At later levels of knowledge utilization, visual processing entails activation 'I...

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of codes and networks of knowledge representations that are associated with recognizing, identifying, categorizing. and otherwise giving meaning to information in the visual array. Recently, Schacter (in press) and Tulving and Schacter (1990) have discussed some the factors that are related to activation of distinct types of codes. Higher-order knowledge utilization processes begin with or draw on the information that is available in the visual array. It is generally assumed that observers bring their prior knowledge to bear on the interpretation of objects and other aspects of the visual world. Consistent with a constructivist view of visual perception, higher-order knowledge serves to enable the individual to go beyond the information given (e.g.. via inferential and constructive processes). According to Neisser (1967). the observer acts a s a "paleontologist who carefully extracts a few fragments of what might have been bones from a mass of irrelevant details and 'reconstructs' the dinosaur" (p. 94). In addition to the service of filling-in and going-beyond. higher order knowledge utilization serves to constrain the selection of what is processed. Zucker (1986) pointed out that there may be an infinite variety of visual signals that could give rise to the same visual knowledge. but that problems of recognition are solved or at least simplified by exploiting constraints in the form of high level semantic knowledge about objects and scenes derived from past experience. As already mentioned, it seems useful to distinguish between visual knowledge that is part of information pick up and various kinds of declarative, representational, and semantic knowledge that provide the conscious experiences of visual perception. Beck (1966) asked young adult subjects to rate the perceptual similarity of an upright and a tilted T and of an upright T and a backward L. The upright T and tilted T were rated as more similar by the subjects, perhaps because readers are experienced at seeing letters in varying orientations. However, analyses of texture grouping revealed that the upright T and the tilted T were more differentiated by the visual system than were the upright T and the backward L. Thus,what appears similar at one level of analysis may be distinct at another level.

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AGE-RELATED LIMITATIONS IN KNOWLEDGE UTILIZATION Although researchers can seldom pinpoint the specific mechanisms responsible for gains and losses in visual cognitive performance, it is possible to provide a rough summary of the kinds of processes that are most age-sensitive and the conditions under which age-related declines are most likely to be found. It is relatively well-established that rate and efficiency of a variety of higher-order encoding and retrieval processes account for a substantial amount of the interindividual variability in visual cognitive performance (e.g., Cerella. 1985. 1990;Salthouse. 1985). Age-related declines are frequently reported when performance involves visual search, localization. and selectivity (e.g.. Madden, 1986;Plude & Hoyer, 1981, 1985. 1986;Sekuler & Ball, 1986). mental rotation and spatial visualization (e.g., Berg, Hertzog. & Hunt, 1982;Salthouse, Babcock, Skovronek, Mitchell, & Palmon, 1990),memory search and retrieval (e.g., Salthouse & Somberg. 1982;Wickens, Braune. & Stokes, 1987).and stimulus selection under conditions of uncertainty (e.g., Hoyer & Familant. 1987; Nissen & Corkin. 1984;Rabbitt. 1982). Craik (1983)suggested that adult age dmerences in memory can be. explained in terms of the extent t o which self-initiated constructive operations are required. Craik pointed out that agereductions in memory performance are most evident in retrieval situations that require substantial self-initiated effort. By extension, some knowledge utilization tasks provide minimal environmental or contextual support and require a high degree of self-inititated activity, whereas other tasks are substantially context-bound and do not seem to involve effortful retrieval. Studies of semantic priming and aging typically show negligible age differences in the extent to which words activate networks of related words and meanings (Chiarello, Church, & Hoyer, 1985; Howard, McAndrews. & Lasaga, 1981). However, there are agerelated declines in the efficiency of retrieval of contextual information (e.g., Moscovitch, Winocur, & McLachlan, 1986).and in the extent to which certain information is accessible or available through priming (e.g.. Clancy & Hoyer. 1990).Recently, Tulving and Schacter (1990)provided evidence to suggest that memory involves

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the operation of functionally independent (or dissociated) processing systems. Some findings in the area of memory aging have been interpreted along these lines (Light & Singh, 1987; Mitchell, 1989;but see Chiarello & Hoyer, 1988).

HOW DOES KNOWLEDGE UTILIZATION ENHANCE VISUAL COGNITIVE PERFORMANCE?

The benefits of knowledge utilization involve making emcient use of the information available in the visual array. Earlier. it was suggested that prior knowledge and experience have their effects at several levels of analysis. At an early level, information in familiar scenes is probably in a form that can be readily picked up without appealing to representative or inferential processes. Early detection is relatively automatic: the subject has little volitional control over what is selected, even though aspects of detection are influenced by prior knowledge. There seem to be few if any agerelated limitations at the level of parsing common or familiar visual arrays; efficiency of early detection is age-invariant and asymptotic. given sufficient perceptual experience. At this level, processing is merely a matter of detecting contextual constraints, a relatively resource-free, age-invariant process. At higher levels, processing involves access to prior knowledge in the form of schemas, and there is some evidence to suggest no decline in the contextualization of input and retrieval processes with aging (Azmitia & Perlmutter. 1988: Hess & Slaughter, in press). Object recognition is strongly contextually-based, object recognition is improved when the object is presented as part of coherent scene (e.g.. Biederman, 1981:Biederman. Blickle, Teitelbaum, & Klatsky, 1988;Boyce, Pallatsek & Rayner. 1989:Friedman. 1979).and the meaning of pictorial displays is picked-up in a glance, within 150 milliseconds (Boyce et al., 1989;Loftus, Nelson, & Kallman. 1983). At intermediate levels. where processing involves activation of memory and inference processes that give meaning and interpretation to visual scenes, there are age-related declines. However, the efficiency of these processes remains unaffected (or less affected) by age-related insult within highly practiced domains. I suggest that prior knowledge does not affect the pick up of

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information from the visual array; rather, it affects the higherorder, resource-limited aspects of processing, which would ordinarily be slower with aging and without the benefit of prior knowledge. The benefits of knowledge utilization in some kinds of visual tasks may be associated with the attentional factors of preparation and selectivity. Suppose you are trying to find a contact lens that dropped onto a multi-colored carpet. If you know some of the characteristics of a contact lens, such prior knowledge will serve to simplify the task of finding the object. The benefits of prior knowledge in visual selective attention can be inferred from studies showing improvements in performance under conditions in which the opportunity to expect particular stimulus information is increased (e.g.. Hoyer & Familant. 1987;Posner. 1980).The time needed to access or use preparatory information is age-related and practice-related. Also. preparatory information (e.g., primes) can trigger access to different semantic codes at different rates as a function of age (Mitchell, 1989)and experience (Clancy & Hoyer, 1990).Along these lines, Posner and his colleagues (e.g., Posner, Inhoff, Friedrich. & Cohen, 1987)have provided some evidence that different aspects of attentional selectivity are controlled by different neural mechanisms. However, it should be noted that examination of the effects of age-related and knowledge-related differences in the time-course of selectivity and preparation involves consideration of a range of factors at a number of levels of knowledge utilization. First. the factors affecting preparation and selectivity (i.e., longer SOAS, more practice trials, consistent mapping) may yield improvements in some aspects of performance (e.g.. automatic access to targets in memory), but other aspects of performance (e.g., alertness) may show deterioration (i.e., altertness decrement) a s a function of the same factors depending on the task and individual differences in the time course of these effects. Second, the relation between performance benefits and costs and the readiness to select particular targets depends on the individual's level of skill at the task. Third, performance may be relatively domain-specific because the processes of attentional selectivity and preparation become dedicated to expected stimulus-response mappings. Fourth,

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performance may vary as a function of age and skill differences in strategy if, for example, there are reliable age-related and skillrelated individual differences in response criteria, stimulus sensitivity, or speed-accuracy trade-offs. All of these issues involve the extent to which preparation and selectivity affect different component processes at different levels of knowledge utilization. depending on a variety of age-related and experience-related individual difference variables. One of the best studies of the effects of age and skill was conducted by Salthouse (1984). He found that typing speed was uncorrelated with age for skilled typists, despite the expected negative correlations between age and psychomotor speed. On the typing task, it seemed that older skilled typists compensated for general psychomotor slowing by using a strategy of looking farther ahead within the window of available text; apparently, looking further ahead gave more time to plan the execution of keystrokes. Salthouse's findings bear on the domain-specific nature of skilled performance, since skilled typists did not effectively employ the "look ahead" strategy on other domain-general tasks. In another study, Clancy and Hoyer (1988)examined the effects of age and skill on the capacity demands of visual recognition performance. Although previous investigators had examined dflerences between novices and experts in the visual analysis of radiographic displays (e.g., Lesgold, Rubinson. Feltovich. Glaser, Klopfer & Wang. 1988; Myles-Worsley. Johnston, 8t Simons, 19881, Clancy and Hoyer selected the domain of medical laboratory diagnostics because there was a relatively wide age range of equivalently skilled individuals in this professional field. The experimental task involved visual detection of microbiological materials, and expert subjects were medical laboratory technologists with a substantial amount of knowledge and experience in microbiological analysis (Le., 5-20 years). It was expected that younger and middle-aged control subjects would be slower and less accurate under dual-task conditions when skilled visual recognition was the primary task compared with agematched experts. As predicted, skilled obsewers showed a typical pattern of age-related decline in domain-general visual processing. but only minimal age-related reductions in domain-specific visual

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detection. Although these results suggest the importance of knowledge in accounting for maintenance of domain-specific performance in older adults, the findings r a s e questions about how to explain the benefits of knowledge. In this study, the beneficial effects of prior knowledge on visual recognition can be interpreted in several ways, First, it can be suggested that if skilled observers know what to see or look for in famillar displays, then compared to less skilled observers, less processing time (and/or capacity) is required for handling nonsalient infonnation. That is. compared with novices, it seems that skilled observers use different (or fewer) processing components to perform the same complex task. The typically observed deficits in the computational aspects of recognition, identification, search, selection, and localization are somehow made more efficient. these systems are either circumvented or replaced. or these systems have sufficient lead time to "run" without noticeable deficit. Further, there may be reduced susceptibility to distractor information in skilled domains. Skilled older observers may be able to effectively "see through" the noise available in familiar displays, even though older adults are generally more prone to noise distractors when searching unfamiliar displays (e.g.. Cremer & Zeef. 1987). It may be that the disadvantageous effects of noise are at minimum for experts, because of the benefits of attentional selectivity and preparation, which attenuate the typical pattern of age-related differences found when familiarity or preparation effects are not available. It is also reasonable to suggest that visual recognition performance in skilled domains involves a criterion adjustment at the encoding or identification stages of visual representation. Familiar context may affect the observer's criteria for reporting object identification on the basis of partial stimulus information. Particular features of the display may operate as primes to facilitate the encoding and stimulus identification processes through network activation. Thus, skilled performance in this domain may involve increased use of contextual cues and constraints available in the display, especially for the older experts.

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KNOWLEDGE AT THE LEVEL OF OBJECT FEATURES

Emphasis can be given to the importance of both feature-driven and object-driven processes in accounting for age-related and knowledge-related differences in visual cognitive performance. There is compelling evidence to suggest that visual objects are processed in terms of their parts or features. Purely feature-driven theories of visual cognition suggest that the observer first encodes structural features and then somehow organizes these features into patterns or objects (e.g., Biedeman. 1987: Julesz. 1984; Marr. 1982; Pinker, 1984). This data-driven view focuses on the ability of the visual processing system to "pick-up" and analyze the essential features or parts of objects, referred to as "primitives", and the ability of higher-order processing systems to represent and construct objects in the world in terms of such features. Presumably, a collection of primitives combine to give rise to phenomenologically real (or identifiable) objects. Anne Treisman's research on early feature analysis is exemplary of some of the work in this area. Treisman and Gormfcan (1988), for example, used visual search asymmetry data as evidence to suggest that the visual system automatically codes such elementary features a s color, contrast, brightness, texture, line ends, blobness. tilt, and curvature. Treisman and Gormican also suggested that there are temporary recognition networks (stored descriptions of objects), and that these relatively transient, knowledge-based networks serve to handle variations in a wide range of stimulus factors (illumination, blur, noise, object quality). Another line of research bearing on the role of structural features in object recognition gives emphasis to line arrangement principles and simple grouping features that serve to define the basic units le.g.. blocks, cylinders, cones) that comprise everyday objects (e.g.. Biederman, 1987; Lowe, 1985; Marr, 1982; Ullman. 1984). From this perspective, the computational requirements of visual perception involve the composition of features into parts and shapes. and the exploitation of knowledge-based uniformities at first approximation to recognition. According to Hoffman and Richards (1984). the visual system first parses object boundaries and extracts critical stimulus features. Second, parts of the object

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are arranged hierarchically and organized on the basis of certain rules and regularities. Third, inferences are made based on featural configurations such that specific featural arrangements trigger memory search and activate specific memory representations. Based on research findings already discussed, the observer's relevant knowledge or experience affects object recognition by improving (or simplifying) the computational efficiency of these steps at the feature processing level. Biederman's ( 1987)recognition-by-components (RBC)theory is representative of the view that everyday objects are composed of basic geometric units. He proposed that the edges of any twodimensional image are segmented at regions of concavity into simple volumetric components (geons)such as cylinders, cones, and cubes. Although Biederman stressed the importance of information at the vertices, at areas of cotermination, and at the regions of convexity and curvature, as sources of first-order information about the organization of the features of objects, he argued that objects containing the same features are distfnguished on the basis of specific relations among the geons of an object. It is the organization of geon components that is matched to representations in memory. Thus, FU3C theory predicts the conditions under which specific types of contour deletions prevent object recognition. If essential features of the object are unavailable (i.e., by the removal or omission of the nonaccidental properties of collinearity or curvilinearity, RBC theory predicts impaired object recognition. In support of this hypothesis, Biederman and Blickle (cited in Biederman, 1987)reported that if edge-based deletions of contour were made at regions of concavity in such a way that collinearity or curvilinearity would not fill-in gaps, then the object was unrecognizable (nonrecoverable). Figure 1 illustrates the differences between recoverable and non-recoverable deletions at three levels of fragmentation as used in Biederman and Blickle's study. They found that when deletions were made at midsegment. and the visual properties were not constrained, the missing information was readily filled-in and the object was identifiable. When deletions corresponded to the removal or omission of the nonaccidental properties of collinearity or curvilinearity, object recognition was prevented, even at very long exposure durations (5

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NONRECOVERABLE

mure 1. Examples of Biederman's (1987)recoverable and nonrecoverable objects

seconds) and even under several conditions of familiarity. Biederman concluded that the most critical information was provided by the primitives of the object. and when these components were removed, object recognition was virtually impossible. A recent study by Frazier and Hoyer ( 1990)examined adult age differences in the type and amount of information necessary for object recognition using Blederman's (1987) RBC theory as a framework. The purpose of this study was to determine if there were age-related differences in the use of invariant features and contextual features in the recognition of incomplete objects. Consistent with Biederman and Blickle's findings. the type of features removed from the objects was a significant factor for younger adults. However, older adults were substantially slower

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and less accurate at recognizing objects under fragmented conditions, regardless of the type of fragmentation. Results of two studies by Salthouse (i.e.. Danziger & Salthouse, 1978:Salthouse & Prill, 1988)also suggest that there is a variety of factors affecting adult age differences in object recognition. Salthouse and Prill (1988)investigated the extent to which age differences in the perception of incomplete objects is related to differences in the effectiveness of deriving implications, testing implications, and evaluating hypotheses regarding perceptual information. Deriving implications from partial information in a display required that subjects locate useful regions of the stimulus. Subjects were asked to locate the most informative regions of figures. Two measures of informativeness were investigated, absolute location and location relative to a fixed position within the display. Participants were asked to compare a display of a specific complete part of an object with an incomplete version of an object, and judge whether the part could have belonged to the figure. In another condition, subjects were shown two displays containing incomplete parts of a n object, and were to decide if both parts came from the same original object. This condition was designed to examine age differences in testing and evaluating hypotheses. Although it was not possible to attribute age differences in perceptual closure to a particular component, Salthouse and Prill (1988)suggested that each component was age-sensitive and contributed to the age deficit in object processing (see also Danzinger & Salthouse. 1978). KNOWLEDGE AT A REPRESENTATIONAL LEVEL

Although sometimes it seems that researchers are just now discovering the influence of knowledge in perceptual analysis, some of the first scientific work in the area of visual perception emphasized the relationship between knowledge and perception. In 1867,for example, Helmholtz took the position that we perceive the objects or events that most likely fit the sensory pattern that we are trying to interpret (Hochberg, 1968). In recent years, there has been a large amount of research demonstrating the effects of top-down knowledge on the selection of features and on the semantics of

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object recognition (e.g.. Hoyer & Plude. 1982: ltrersky & Schiano, 1989; Ullman, 1984). The current view is that top-down visual routines subserve the analysis and selection of particular information (e.g., specific shape properties, figure boundaries, and feature locations) that enable recognition (e.g., Ullman, 1984). Intuitively, given the veridicality of object recognition, one is practically forced to accept the position that visual cognition is highly inferential and dependent on prior knowledge. contextual factors, expectations, and so on. At one level, recognition of objects involves matching descriptions of what one sees with representational knowledge of what one has already seen. It seems likely that the processes involved in selecting, encoding, and integrating featural information about objects, and the processes involved in accessing object-specific knowledge or representations, are the main loci of age-related and experience-related differences in visual cognition. Practically, the computational processes at the detection level of visual object recognition must be largely automatic. Imagine the computational demands of recognition if every time one looked at an object one had to construct it from its features and parts, as well as its orientation, size, color, angle of view, luminance, and degree of occlusion. Such constraints suggest the principles that involve the use of knowledge in object recognition. First, it is necessary to assume that object recognition does not depend solely on the efficiency of processing featural details. Object recognition does not require processing of evey feature of an object prior to recognition. Knowledge probably serves the function of filling-in when featural information is incomplete or when there is missing information. The observer's knowledge and expectancies serve to simplify the demands of object processing. Second, top-down knowledge allows for constancies in object recognition despite featural variations associated with orientation, size, color, degree of occlusion, luminance, and so on. Given these principles, older observers may come to rely more on knowledge-based expectancies and constancies in familiar situations, as feature-integration processes become less eflicient and more time-demanding. More broadly, age-related gains and losses in various aspects of cognition have been characterized in terms of increased domain-

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specificity and reduced plasticity of knowledge access (Baltes. 1987; Hoyer, 1987;Hoyer, Rybash, & Roodin, 1989;Rybash, Hoyer, & Roodin, 1986).Despite the well-known age-related declines in some of the components of infobnation processing, performance seems relatively unaffected by aging in skilled domains. Skilled performance can be maintained or extended more easily in some domains than in others. For example, performance in fast-paced types of work or sport eventually declines with age, even for experts (e.g.. Backman & Molander, 1986).yet skilled performance in cognitive domains that allow more time for planning, knowledge utilization. and retrieval is more likely to be maintained with age. Performance in skilled domains is associated with the efficiency of access to domain-specific knowledge and/or to the utilization of contextual cues or constraints available in familiar tasks. Specialized knowledge can facilitate the encoding and/or retrieval of complex visual patterns in a variety of ways. In studies of game domains, for example, Chase and Simon (1973)and DeGroot (1966)reported that chess masters could recall the positions of approximately 25 pieces from a game after having seen the display for 5 seconds, while a novice player could remember the locations of only about one-quarter as many pieces after the same exposure. However, even though experts were able to recall large amounts of domain-specific information, experts were no better than novices on domain-general measures of memory. The flnding that experienced individuals can recall at a glance far more specialized information than novices has also been reported in other domains such as the analysis of radiographic displays (e.g.. Myles-Worsley. Johnston, & Simons, 1988). CONCLUSIONS

It has been suggested that age-related and experience-related changes interact at several levels to determine task performance. Although most cognitive aging researchers would probably agree with this position, some of the problems associated with vedying (and unverifying) this approach should be mentioned. First, it is often difficult to isolate and independently measure age-related and experience-related variables. Clancy and Hoyer ( 1988) and

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Salthouse (1984) were able to independently sample the subject variables of years of experience and age: however, experience is usually cumulative and age-correlated, and there can be substantial practical dFfficulties in obtaining representative samples of these variables (see Salthouse. 1990). Despite such practical dimculties, it is still surprising that so little research effort has been directed to the examination of the characteristics (e.g., experience, knowledge) that individuals bring to cognitive tasks, given the amount of experience-related interindividual variability typically obsenred in cognitive aging studies. Another problem is that observed, age-related declines in the speed or efficiency of visual encoding and access are generally attributed to age-reductions in the capacity, rate, or allocation of resources, but such claims must be considered unsubstantiated and unverified, without an independent measure of capacity, rate, or resource. However, careful analysis of the structure and organization of the visual array can provide a valid measure of the m o u n t and salience of visual knowledge that can be extracted from the array. Finally, it is suggested that researchers should take into account what is known about age-related changes in brain and sensory function when generating hypotheses about age-related changes in visual information processing. For example, Plude and Hoyer (1985, 1986) and others (e.g., Sekuler & Ball, 1986) have demonstrated that there are substantial age-related deficits in visual search performance, and relatively minor age dmerences in visual filtering 0.e.. object recognition and identification without search or localization requirements). These findings are consistent with recent work in the neurophysiology of vision suggesting that information about "what" and "where" is processed separately in the visual system (see Cowey, 1985). It has been shown that the neurons that represent an object's shape have relatively large receptive fields, and these neurons respond when the stimulus falls anywhere within a wide range of positions. Recently, Mishkin (e.g., Mishkin, Ungerleider, & Macko, 1983) has reported that different visual systems are responsible for locating objects and identifying objects within displays. One system is involved in the recognition of objects and features thereof, and enables application of

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previously acquired knowledge to the task of object recognition. Once one has recognized an object, one h o w s its function and some of its attributes. A second (and presumably independent) processing subsystem enables the location of objects within the visual field. In this case, the task is not to encode features or objects in order to access relevant semantic knowledge, but the task is to locate "where" things are. The reported age-related deficits in localization, in contrast to no age differences in identification processes, may be interpreted a s suggesting differential aging of particular neurophysiological subsystems that subserve visual processing. ACKNOWLEDGMENTS Preparation of this chapter was supported by NIA grant AGO604 1 to WJH. REFERENCES Azmitia, M., & Perlmutter, M. (1988).Age differences in adults' scene memory: Knowledge and strategy interactions. Comprehensive Gerontology, 2, 75-84. Bi.ichan, L.,& Molander. B. (1986).Effects of adult age and level of skill on the ability to cope with high-stress conditions in a precision sport. Psychology and Aging, 1,334-336. Baltes. P. B. (1987).Theoretical propositions of life-span developmental psychology: On the dynamics between growth and decline. Developmental Psychology, 23, 61 1-626. Beck, J. (1966).Effect of orientation and of shape similarity on perceptual grouping. Perception and Psychophysfcs, 1, 300-302. Berg, C., Hertzog, C. K.. & Hunt, E. (1982). Age Werences in the speed of mental rotation. Developmental Psychology. 18.95-107. Biederman, I. (1981).Do background depth gradients facilitate object identification? Perceptton, 10, 573-578. Biederman, I. ( 1987). Recognition-by-components:A theory of human image understanding. Psychological Review. 94, 1 15147. Biedeman, I., Blickle. T. W., Teitelbaum, R. C., & Klatsky. G. J. (1988).Object search in nonsense displays. Journal of Experimental Psychology: Learning, Memory, and Cognition, 14,456-467.

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Boyce, S. J.,Pollatsek. A..& -per. K. (1989).Effect of background information on object identiflcation. Journal of Experimental Psychokgy: Human Perception and Perfxmmce, 15, 556-566. Cerella, J. (1985).Information processing rates in the elderly. Psychologfcd Bulletin. 98,67-83. Cerella, J. (1990).Aging and infomation processing rate. In J. E. Birren & K. W. Schaie (Eds.), Handbook of the psychology of ugmg (3rd ed. , pp. 201-221).New York: Academic Press. Chase, W.G.. & Simon, H. k (1973).Perception in chess. Cognitive Psychology. 4. 55-81. Chiarello, C., Church, K., & Hoyer. W. J. (1985).Automatic and controlled semantic priming: Accuracy. response bias, and aging. Journal of Gerontology,40, 593-600. Chiarello, C., & Hoyer. W.J. (1988).Adult age dlfferences in implicit and explicit memory. Psychofogy and Aging, 3,358-366. Clancy, S . M..& Hoyer, W. J. (1988).Effects of age and skill on domain-specific search. In V. L. Pate1 & G. J. Groen (Eds.), Proceedings of the tenth conference of the Cognitive Science Socfety (pp. 398-404).Hillsdale, NJ: Erlbaum. Clancy, S. M.. & Hoyer. W. J. (1990,April). Age and skU in prfmfng. Paper presented at the Cognitive Aging Conference. Atlanta, GA. Cowey, A. (1985).Aspects of cortical organization related to selective attention and selective impairments of visual perception: A tutorial review. In M. I. Posner & 0. S. M. M a r i n (Eds.), Attention and performance XI (pp. 41-62).Hillsdale. NJ: Erlbaum. Craik. F. I. M. (1983).On the transfer of information from temporary to permanent memory. Philosophical Damactions of the Royal Society of London, B302, 341-359. Cremer, R., & Zeef, E.J.(1987).What kind of noise increases with age? Journal of Gerontology, 42. 515-518. Danziger, W. L., & Salthouse, T. A. (1978). Age and the perception of incomplete figures. Experimental Aging Research, 4,67-80. DeGroot, A. (1965). Thought and choice in chess. The Hague: Mouton. Fodor, J. A., & Qlyshyn, 2. W. (1988).Connectionism and cognitive architecture. Cognitton, 22, 3-71. Fozard, J. L. (1990). Vision and hearing in aging. In J. E. Birren & K. W. Schaie (Eds.),Handbook of the psychology of aging (3rd ed. pp. 150-171). New York Academic Press. Frazier, L. D., & Hoyer, W. J. (1990). Components of object recognition: Adult age dffferences. Unpublished manuscript, Syracuse University.

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Friedman. A. (1979).Framing pictures: The role of knowledge in automatized encoding and memory for gist. Journal of Experimental Psychology: General, Z 08. 3 16-355. Gibson, J. J. (1966).The senses considered as perceptual systems. Boston: Houghton-Mifflin. Helmholtz, H. von. (1962).neatbe on physiofogfcal optics: Vol3. New York Dover (original work published in 1867). Hess, T. M.,& Slaughter, S . J. (in press). Schematic knowledge influences on memory for scene information. Developmental Psychology. Hochberg, J. (1968). Perception. Englewood Cliffs, NJ: Prentice Hall. Hoffman, D. D., & Richards, W. (1985).Parts of recognition. Cognition, 18,65-96. Howard, D. V., McAndrews, M. P., & Lasaga, M. I. (1981).Semantic priming of lexical decisions in young and old adults. Journal of Gerontology, 36, 707-714. Hoyer, W. J. (1987).Acquisition of knowledge and decentralization of g in adult intellectual development. In C. Schooler & K. W. Schaie (Eds.), Cognitfuefunctiontng and soctal structures ouer the lfe course (pp. 120-141).Norwood, NJ: Ablex. Hoyer, W. J.. & Familant, M. E. (19871.Adult age dHerences in the rate of processing expectancy information. C o g n ftiue Development, 2, 57-70. Hoyer, W. J., & Plude, D. J. (1982).Aging and the allocation of attentional resources in visual information processing. In R. Sekuler, D. Kline, & K. Dismukes (Eds.). Aging and human ulsualfunction (pp. 245-2631,New York Alan R. Liss. Hoyer, W. J., Rybash. J. M., & Roodin. P. A. (1989). Age-related cognitive change as a function of knowledge access. In M. L. Commons, J. D. Sinnott, F. A. Richards. & C. Armon (Eds.), Adult development: Vol. 1 . Comparisons and applications of developmental models (pp. 293-305). New York Praeger. Julesz. B. (1984).Toward an axiomatic theory of preattentive vision. In G. M. Edelman. W. E. Gall, W. M. Cowan (Eds.), Dynamfc aspects of neocorticat function (pp. 585-612).New York Neurosciences Research Foundation. Kosnik. W.. Winslow, L.,Kline, D. W.. & RasinsM. K., & Sekuler, R (1988).Visual changes in daily life throughout adulthood. Journal of Gerontology: Psychological Sciences, 43, P63-P70.

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Lesgold. A.. Rubinson, H..Feltovitch. P.. Glaser. R, Klopfer, D., & Wang. Y. (1989).Expertise in a complex skUk Diagnosing X-ray pictures. In M. T. H. Chi. R Glaser. & M. J. Farr (Eds.). The nature of expertfse (pp. 31 1-342).Hillsdale, NJ: Lawrence Erlbaum Associates. Light, L. L.. & Singh, A. (1987).Implicit and explicit memory in young and older adults. Journal of Experimental Psychology: Learning, Memory, and Cognftfon.13, 531-541. Loftus. G. R., Nelson, W. W.. & Kallman. H. J. (1983).Differential acquisition rates for different types of information from pictures. Quarterly Journal of Experimental Psychology, 35. 187-198. Lowe, D.G.(1985).Perceptual organlzation and ukual recognition. Boston: Kluwer. Madden, D. J. (1986).Adult age differences in the attentional capacity demands of visual search. CognftfueDeuelopment, 1. 335-363. Marr. D. (1982). Vision. San Francisco. CA: Freeman. Computer vision and perceptual psychology. McArthur. D. J. (1982). PsychologfcalBulletin, 92. 283-309. Mishkin, M., Ungerleider, L. G., & Macko, K. A. (1983).Object vision Trends fn and spatial vision: T w o cortical pathways. neurosciences, 6,414-417. Mitchell, D. B. (1989). How many memory systems? Evidence from aging. Journal of Experimental Psychology: Learning, Memory, and Cognition, 15,31-49. Moscovitch. M., Winocur, G., & McLachlan. D. (1986).Memory a s assessed by recognition and reading time in normal and memory-impaired people with Alzheimer's Disease and other neurological disorders. Journal of Experimental Psychology: General, 115, 331-347. Myles-Worsley, M., Johnston, W. A.. & Simons. M. A. (1988).The influence of expertise on X-ray image processing. Journal of

Experimental Psychology: Learnfng, Memory. and Cognitfon. 14,553-557. Neisser. U. (1967). Cognitive psychology. New York Appletion Century Crofts, Nissen. M. J., & Corkin, S. (1984). Effectiveness of attentional cueing in older and younger adults. Journal of Gerontology, 40. 185-191. Pinker, S . (1984). Visual cognition: An introduction. Cognition 18, 1-63.

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Plude. D. J.. & Hoyer. W. J. (1981).Adult age differences in visual search as a function of stimulus mapping and processing load. Journal Of Gm~ntology,36, 598-604. Plude, D.J., & Hoyer, W.J. (1985).Attention and performance: Identifying and localizing age deficits. In N. Charness (Ed.), Aging and human performance (pp. 47-99). London: Wiley. Aging and the selectivity of visual Plude, D. J., & Hoyer, W. J. (1986). information processing. Psychology and Aging, 1. 1-9. Posner, M. I. (1980).Orienting of attention. Quarterly Journal of Experimental Psychology, 32, 3-25. Posner. M. I.. Inhoff. A. W., & Friedrich. F. J. (1987).Isolating attentional systems: A cognitive anatomical analysis. PSyChoblology, 15, 107-121. Rabbitt, P. M. A. (1977).Changes in problem solving ability in old age. In J. E. Birren & K. W. Schaie (Eds.), Handbook of the psychology of aging (2nd ed., pp. 606-625).New York: Van Nostrand Reinhold. Rabbitt. P. M. A, (1982).Breakdown of control processes in old age. In T. M. Field. A Huston, H. C. Quay, L. Troll. & G. Finley (Eds.). Review of human deuelopment (pp. 540-550).New York Wiley. Rybash, J. M., Hoyer, W. J.. & Roodin. P. A. (1986). Adult cognition and aging: Developmental changes in processing, knowing, and thfnking. Elmsford. New York Pergamon Press. Salthouse, T. A. (1984). Effects of age and skill in typing. Journal of Experimental Psychology: General. 1 13, 345-371. Salthouse, T. A. (1985).Speed of behavior and its implications for cognition. In J. E. Birren & K. W. Schaie (Eds.), Handbook ofthe psychology of aging (2nd ed.. pp. 400-426).New York: Van Nostrand Reinhold. Salthouse, T. A. (1990).Cognitive competence and expertise in aging. In J. E. Birren & K. W. Schaie (Eds.). Handbook of the psychology of aging (3rd ed., pp. 310-319):New York: Academic Press. Salthouse, T. A., Babcock, R. L., Skovronek, E., Mitchell, D. R. D., & Palmon, R. (1990).Age and experience effects in spatial visualization. Developmental Psychology, 26, 128-136. Salthouse, T.A., & Prill. K.A. (1987).Effects of aging on perceptual closure. American Journal of Psychology. 101. 217-238. Salthouse, T.A.. & Somberg, B. L. (1982). Skilled performance: The effects of adult age and experience on elementary processes. Journal of Experimental Psychology: General, 1 1 1 , 176-207.

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Schacter, D. L. (in press).Perceptual representation systems and implicit memory: Toward a resolution of the multiple memory systems debate. In A. Diamond (Ed.), Development and neural bases of higher cognitiue functions. New York Annals of the New York Academy of Sciences. Sekuler, R., & Ball, K. (1986).Visual localization: Age and practice. Journal of the Optical Society of America. 3, 864-867. Todd, J. T.,& Reichel. F. D. (1989).Ordinal structure in the visual perception and cognition of smoothly curved surfaces. Psychological Review. 96,643-657. Treisman, A.. & Gormican, S. (1988).Feature analysis in early vision: Evidence from search asymmetries. Psychological Reulew, 95.15-48. Tulving, E.. & Schacter. D. L. (1990).Priming and human memory systems. Sctence, 247.301-306. Tversky, B., & Schiano, D. J. (1989).Perceptual and conceptual factors in distortions in memory for graphs and maps. Journal of Experimental Psychology: General. 1 1 8 . 387-398. Ullman, S.(1984). Visual routines. Cognition. 18, 97-159. Wickens, C. D.. Braune, R, & Stokes, A (1987). Age merences in the speed and capacity of information processing: 1. A dual-task approach. Psychology and Aging, 2.605-614. Zucker, S . W. (1986).The diversity of perceptual grouping. In M. &bib 8t A. Hanson (Eds.), Vision, brain, and cooperative computatton (pp. 1-29). Cambridge: MIT Press.

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Aging and Cognition: Knowledge Organization and Utilization Thomas M. Hess (Editor) 0 Elsevier Science Publishers B.V. (North-Holland), 1990

CHAPTER TEN

AGING AND EVERYDAY COGNITNE ABILITIES Steven W.Cornelius Cornell University

SUMMARY

In this chapter, recent work on everyday cognitive abilities in adults and the elderly is reviewed. Despite substantial theory and data that have been generated in the study of intellectual aging, there has been a recurrent concern that traditional paradigms for assessing intellectual abilities are insensitive to cognitive skills adults use in adapting to the demands of everyday life. In the first section, we examine how this concern has been paralleled by recent studies of people's implicit theories of intelligence. Implicit theories refer to people's ideas and beliefs about intelligence and how it changes across the life span. Findings show that people have distinct concepts of everyday and academic intelligence, and they believe that facets of everyday intelligence become increasingly salient, especially in middle age and late adulthood. In the second section, research on adults' selfconceptions of intelligence and conceptions of ability tests is discussed. The findings underscore the multidimensional nature of everyday intelligence and highlight the distinct importance of practical and social cognitive abilities in conceptions of everyday intelligence. In the third section, two tasks recently developed to assess adults' strategic knowledge about solutions to problems in everyday and stressful situations are described. Results show differences and similarities between performance on everyday and traditional ability

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tests and suggest the potential for growth in everyday cognitive abilities during adulthood. Research on intelligence has been a focal point of scientific inquiry in the psychology of aging for more than 70 years (e.g., Dixon, Kramer, & Baltes, 1985:Woodruff, 1983). Initially, much of the research focused on age-related declines in functioning. However, more work has appeared during recent decades which qualifies conclusions about general and universal decline. Indeed, it now appears that whether intelligence declines, remains stable, or increases with age depends on which aspect of intelligence is examined. Findings that have emerged from research on intellectual aging suggest that intelligence is a multidimensional construct, and cognitive changes during adulthood involve a n interplay between decline. stability, and growth (e.g.. Denney. 1982; Labouvie-Vief, 1985;Staudinger. Cornelius, & Baltes, 1989). A number of researchers have argued that the characteristics of tests differ for measures that do and do not show age-related decrement (e.g., Cornelius, 1984). One common observation is that ability tests that show increments or are stable with age involve more familiar content or skills than ability tests that exhibit age decrements with increasing age. For example, Anastasi (1968) suggested that 'Whether intelligence test scores rise or decline with increasing age in adulthood depends largely on what experiences the individual undergoes during those years and on the relationships between these experiences and the functions covered by these tests" (p. 294). Likewise, Botwinick (1977)argued that verbal ability tests apparently measure "the manipulation of familiar material in familiar ways" whereas nonverbal or performance ability tests measure "the manipulation of unfamiliar materials, perhaps in unfamiliar ways" (p. 588). More recently, Denney (1982)proposed that abilities that are relevant to adults' experiences and "optimally exercised" may remain relatively constant in adulthood, whereas "unexercised abilities" may decline as a function of disuse and lack of practice. These perspectives raise fundamental questions about the nature of intelligence in adulthood and its assessment. More than thirty years ago, Demming and Pressey (1957)issued a critique of

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traditional methods of ability assessment in research on intellectual aging. They argued that tests commonly used in research were inappropriate for the assessment of intellectual functioning in adulthood because many tests were adapted to a large extent from instruments designed for children and youth to predict academic performance. They suggested that adult ability assessment should focus on the skills and knowledge that adults use to function in everyday living. Since their critique, other gerontologists (e.g., Schaie. 1978; Scheidt, 1981: Willis & Baltes, 1980) have reiterated concern about traditional measures with special attention devoted to issues of external and ecological validity. During the recent decade, there has been growing interest in everyday cognitive abilities a s evidenced by an increasing number of investigations examining everyday or practical problem solving, practical intelligence, a s well as cognitive skills in particular domains of everyday functioning (e.g., Cavanaugh, Kramer, Sinnott, Camp, & Markley, 1985: Frederiksen. 1986; Kuhn. Pennington, & Leadbeater. 1983; Poon, Rubin, & Wilson. in press; Sinnott, 1989a: Sternberg & Wagner, 1986). Much of the recent work h a s originated from contextual models of intellectual development (e.g., Berg & Sternberg. 1985: Ceci. 1990: Dixon & Baltes, 1986; Labouvie-Vief. 1985). Although there is some diversity in how contextual theorists define intelligence, contextual models seem to concur in viewing intelligence a s consisting of the mental activities that enable individuals to adapt successfully to their environment (e.g.. Berg, 1989; Labouvie-Vief. 1985: Staudinger et al.. 1989; Sternberg, 1985a). The purpose of the present chapter is to review some recent work in the study of everyday intelligence and cognition in adulthood and old age. As is the case for other domains of psychological inquiry, researchers have adopted both implicit and explicit approaches in the study of everyday intelligence. In the first section, we address the question of what intelligence is by examining people’s implicit theories or mental representations of the concept of intelligence. In doing so, our aim is to elucidate the attributes that people believe characterize intelligent functioning with special attention to such functioning in everyday contexts.

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Moreover, implicit theories of adult intellectual development highlight the central role of everyday intellectual competence in defining intelligence during the latter part of the life span. In the second section, research conducted in our laboratory examining everyday cognitive abilities in adulthood and old age from an implicit approach is reviewed. This research has focused on adults' self-conceptions of everyday intelligence and its relation to objective test performance, and the correspondence between people's ideas about the characteristics associated with exceptional performance on ability tests and their relation to psychologists' conception of everyday intelligence. In the third section. an explicit approach to the assessment of everyday cognitive abilities is described. Results from two experiments we have performed to examine everyday problem solving and adults' knowledge about adaptive responses to stressful situations are discussed as illustrative of two key facets of everyday intelligence. The findings demonstrate differences and similarities between everyday cognitive abilities and traditional measures of verbal and problem-solving abilities and emphasize the potential for growth in everyday cognitive abilities during adulthood. IMPLICIT THEORIES OF INTELLIGENCE

Implicit theories are concerned with people's ideas and beliefs about psychological functioning, and such theories reflect how people construct and mentally represent psychological concepts. Explicit theories, on the other hand. involve scientists' constructions of concepts to describe or explain psychological phenomena. Implicit and explicit theories differ in the type of data one views as the basis for examining psychological functioning. In implicit theories, the data of interest focus on people's communications about their beliefs regarding the psychological construct of interest. By contrast, explicit theories are based on people's performance on tasks or tests that are presumed to measure psychological functioning. Implicit theories are important for understanding psychological constructs because explicit theories frequently are derived from implicit theories of a construct. Particularly at

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initial points in inquiry, implicit theories provide a framework for the development of explicit theories because they aid in articulating some basic conceptual dimensions for investigation (e.g., Sternberg, 1985a). For example, in the domain of personality, people’s implicit theories have been useful in developing a taxonomy of dimensions (e.g.. McCrae & Costa, 1985). From a contextual perspective, implicit theories are significant because they help clarify how people in a given sociocultural context define a particular psychological construct. Prototypic Conceptions of Everyday and Academic Intelligence The concept of intelligence is frequently used in social discourse to describe a major component of human personality and functioning (e.g., McCrae & Costa, 1985). Natural language provides a means for communication about intellectual characteristics with descriptors available for describing desirable (e.g., logical, knowledgeable. wise) and undesirable (e.g., confused, absentminded, forgetful) aspects of cognitive functioning (e.g., Heckhausen, Dixon, & Baltes. 1989). People’s judgments about intelligence can reflect different foci depending on whether a person evaluates one’s own or another person’s abilities (e.g.. Kihlstrom & Cantor, 1984). In either case, the judgment one reaches about how intelligent an individual is may depend on the extent to which an individual’s behavior resembles an ideal or prototypic concept of an intelligent person (e.g.. Neisser. 1979). From this perspective, different individuals might be viewed to be of comparable intelligence but could resemble an ideal prototype along different dimensions. Despite the importance of the concept of intelligence in self and interpersonal evaluations, relatively little systematic research has been conducted on the content or structure of people’s prototypic conceptions of intelligence. Recently, Stemberg and his colleagues (Sternberg, 1985b: Sternberg & Berg, 1987; Sternberg, Conway. Ketron. & Bernstein. 1981) reported a series of investigations exploring people’s implicit theories of intelligence. In their initial work (Stemberg et al. 1981).people were surveyed about behaviors they thought were indicative of intelligence. Afterwards, experts

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(i.e, psychologists conducting research on intelligence) and laypersons (Lealadults without formal training in psychology) rated the extent to which .each of these behaviors characterized their ideal concepts of "everyday intelligence" and "academic intelligence". Sternberg et al. (1981) found some important differences between these concepts of intelligence that appear to reflect a sensitivity or awareness to the context-specific nature of intelligent functioning, Experts and laypersons endorsed similar ideas about the behaviors characterizing these concepts, but both groups attributed different characteristics to everyday and academic intelligence. For example, when the profiles of attributes characterizing each of these concepts were examined. experts' and laypersons' judgments were quite similar about behaviors that were most and least characteristic of everyday intelligence (r = .81) as well as academic intelligence (r = .89).They also made a meaningful distinction between conceptions of intelligence in everyday and academic settings. The profiles for everyday and academic intelligence showed only a moderate degree of similarity within each group (for experts, r = .43: for laypersons, r = .45). Thus, the behaviors that people believe are most characteristic of a n intelligent person in everyday settings dif€er from those they think characterize exceptional intelligence in an academic context. Differences in the content of people's mental representations of everyday and academic intelligence were clarified by factor analyses of the ratings for these concepts. Analyses of experts' ratings for everyday intelligence revealed three dimensions involving Practical Problem-Solving Ability (e.g., "seeks explanations and causes", "sees individual elements in their overall context", "perceives implied assumptions and conclusions"), Practical Adaptive Behavior (e.g., "able to cope with crises", "acts in a practical manner", "sizes up situations well"), and Social Competence (e.g., "displays common sense". "able to cope with everyday environment", "has good intuitions"). By comparison, analyses of experts' ratings for academic intelligence indicated dimensions of Problem-Solving Ability (e.g., "solves problems well". "makes good decisions". "gets to the heart of problems"). Verbal Ability (e.g., "is verbally fluent", "reads widely".

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"communicates ideas well"), and Motivation (e.g., "displays dedication and motivation in chosen pursuits". "displays persistence", "studies hard'). These results suggest that the ability to solve problems is an important dimension that underlies concepts of both everyday and academic intelligence. The relative salience of other types of behaviors differs for these two concepts. In particular, experts believe that being able to adapt successfully to crises and to engage in competent interpersonal functioning are more characteristic of an ideally intelligent person in an everyday context, whereas verbal abilities and heightened motivation to acquire knowledge are more salient for intelligent functioning in academic settings. Implicit Theories of Adult Intellectual Development Because there is a shift in the contexts that adults encounter a s they complete their formal education in youth and then experience transitions in work and family roles, people's ideas about the nature and meaning of intelligence might be expected to change in ways that reflect such transitions. Thus, an important question is whether people believe that intelligence is manifest differently as individuals move through the life course. In the present section, three types of evidence are reviewed: (a) adults' beliefs about changes in psychological functioning during adulthood, (b) prototypic conceptions of intelligence across adulthood, and (c) adults' perceptions of changes in their own cognitive abilities. In general, findings from this research show that people believe that abilities reflective of everyday intelligence assume increasing importance, particularly in middle age and later life. Results emerging from research on people's conceptions of psychological change in adulthood indicate that adults perceive adult development to involve multidirectional changes in which both gains and losses in functioning coexist (e.g., Heckhausen & Baltes. 1989; Heckhausen et al.. 1989). Heckhausen et al. (1989) asked young, middle-aged, and older adults to rate an extensive set of psychological attributes on three dimensions: (a) the extent to which an attribute increased with age, (b) the desirability of the

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attribute, and (c)the ages at which change was expected to begin and end. The dominant finding was that people perceived an increasing number of losses (i.e.. increases in undesirable attributes) and a decreasing number of gains (Lee,an increase with age in desirable attributes) for most domains of psychological functioning across adulthood. For example. there was a strong negative correlation (r = -.68)between the perceived desirability of attributes and the expected age of onset. Thus. increasing mean ages for the beginning of developmental change were associated with fewer and less desirable changes and more and more undesirable changes. Moreover, results of this study showed substantial consensus among adults from different age groups especially about their expectations of the desirability and timing of change. Focusing only on the results for the intellectual characteristics examined in this study, the dominant flnding indicated that people believe that increases in undesirable attributes (e.g., forgetful, slow, overcautious) begin in later adulthood, whereas increases in desirable attributes (e.g., intelligent, logical, knowledgeable) begin in early adulthood. There were some clear exceptions to this general trend, however. Heckhausen et al. (1989)also found that people believe that some desirable intellectual attributes--for example, being experienced, knowledgeable about human nature, or wise--increase with age in adulthood. In addition, people expected increases on such attributes to be most likely to begin in middle age and to continue until some time in old age. Evidence from the investigation of implicit theories of adult intellectual development also shows that people think everyday intellectual abilities become more salient in adulthood. Sternberg and Berg (1987)examined people's prototypic concepts of intelligence for early adulthood, middle age, and late adulthood. In their study, adults. who ranged in age from 26 to 85. rated how likely it would be for individuals of average and exceptional intelligence at ages 30. 50, and 70 to display behavioral characteristics that had been nominated as indicative of adult intelligence. Data were factor analyzed for each target age. Results revealed three factors for each target age. The factors for target age 30 were: (a) Novelty in Problem Solving, (b) Crystallized

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Intelligence, and (c) Everyday Competence. The factors for target age 50 were: (a) Novelty in Problem Solving, (b) Everyday Competence, and (cl Social Competence. The factors for target age 70 were: (a) Composite Fluid and Crystallized Intelligence, (b) Everyday Competence, and (c) Cognitive Investment. The findings suggest that the behavioral attributes people use to characterize exceptional intelligence for middle-aged or older adults differ to some extent from those characterizing intellectual functioning for younger adults. In particular, Everyday Competence was a significant dimension underlying people's prototypic concepts for each target age, but the variance accounted for by this factor was greater for older than younger prototypes. Substantively, the dimension of Everyday Competence was identified by behaviors involving adapting well to the environment, being perceptive about people and things, and adjusting to difficult life situations (Sternberg & Berg. 1987). Everyday competence may assume increasing importance in people's ideas about intellectual functioning for older ages because of the overlap between people's concepts of intelligence and wisdom (e.g., Sternberg, 1985b). In particular, intelligent functioning in middle or late adulthood may be manifest by a person who has acquired from experience an elaborate system of knowledge about life. Such knowledge may be reflected in an appreciation of uncertainties that occur in life course development and a sensitivity to contextual influences that moderate and shape pathways during adult life Ie.g., Baltes & Smith, in press). If this knowledge is implemented, it may be reflected in sound, effective. or practical judgments about the conduct of life particularly during transitions involving normative or non-normative developmental tasks (e.g., Smith, Dixon. & Baltes. in press). In addition to ideal conceptions of adult intellectual development, research examining older adults' retrospective evaluations of changes in their own intellectual functioning suggests that people perceive an improvement in everyday cognitive abilities. Williams. Denney. and Schadler (1983)interviewed older adults and asked them whether they had experienced changes in their memory and problem-solving abilities. They found that the majority of adults believed that their memory abilities had

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declined with age. By contrast, they also found that most older adults believed that their abilities to think, reason, and solve problems had improved with age. The perceptions expressed by older adults contrast shaiply with much research on problem solving that has consistently indicated age-related declines in performance on a number of problem-solving tasks (e.g., Denney, 1982; Reese & Rodeheaver, 1985). Further probing, however, revealed that the majority of older adults referred to their ability to solve everyday and financial problems rather than to the types of problems used by researchers in traditional problem-solving tasks. Similar evidence was obtained by Birren (1969) in an interview study of adults about decision making. He found that adults perceived changes in the strategies they used in making decisions in their work lives (also see Streufert & Streufert, 1978). The interviews indicated that changes in solving everyday problems might occur because people defined their problems dLfferently resulting from the additional experience they had accumulated from early to middle adulthood. For example, many respondents noted that problems had become easier to deal with because the intensity of their emotional reactions to situations had diminshed. In addition, the internews revealed that people perceived that their goals had changed and might continue to change in the future. Furthermore, adults expressed the belief that their strategies in making decisions were influenced by efforts to compensate for psychological changes accompanying aging. In combination, research on people's implicit theories of intelligence reveals four key findings. First. adults with and without formal training in psychology hold similar ideas about the meaning of intelligence. Although there are some daerences in the content and structure of these concepts among various groups, there is also a rather striking degree of agreement about the attributes people believe are indicative of exceptional intellectual functioning. Second, people's conceptions of intelligence are multifaceted and reflect multiple dimensions of intellectual functioning. Problem-solving and verbal abilities emerge a s salient dimensions in experts' concept of academic intelligence, and these dimensions seem to correspond well to abilities that have been identified in several explicit psychological theories, such as

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dmerential theories of intelligence (e.g., Cattell, 1971; Horn. 1982; Thurstone, 1935). Third, people's conceptions of intelligence also appear to be richer in scope than the domains of abilities represented in most explicit theories of intelligence (however. see Gardner, 1983; Sternberg. 1985a). In particular, adults accord greater recognition to practical and social cognitive abilities especially in their beliefs about everyday intelligence. Practical intelligence is marked by a n interest and awareness in the immediate environment and world at large, the ability to appraise situations well, and skill in devising means to attain one's goals. Social competence is associated with effective interpersonal behavior, acknowledgment of one's errors, engaging in socially appropriate behavior. and displaying concern about social issues. Finally, practical and social cognitive abilities appear to be central to people's ideas about changes in adult intellectual competence, especially changes in functioning during middle age and later adulthood. These ideas are reflected in the expectation that there is a potential for growth extending into old age in everyday intellectual abilities, and older adults' perception of improvements in their ability to solve practical problems and make decisions. EVERYDAY COGNITIVE ABILITIES: AN IMPLICIT APPROACH Implicit theories of intelligence. especially findings concerning people's prototypic conceptions (Sternberg et al.. 1981).influenced our initial efforts to examine everyday cognitive abilities. This research was directed toward two major issues. One issue has focused on the possible growth of everyday cognitive abilities in adulthood suggested by people's implicit theories a s well a s theoretical models of adult cognitive development (e.g., Dixon & Baltes. 1986: Labouvie-Vief, 1982; Schaie. 1977/ 1978). The second issue centered on the question of similarities and dflerences between everyday cognitive abilities and traditional abilities. In the following sections, we describe the results of two experiments investigating everyday intelligence from an implicit approach. In the first study, we examined adults' self-conceptions of intelligence

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and their relation to performance on standard ability tests. In the second experiment, an investigation of the kinds of ability tests people believe are indicative of everyday intelligence is reported. Experiment 1: Self-conceptions of Intelligence Neisser (1979) argued that a person may be considered intelligent to the degree that his or her behavior corresponds to attributes that characterize a prototypic or ideal concept of intelligence. Following this orientation, Sternberg et al. (198 1) examined the relation between adults' self-conception of behavior and experts' prototypes of everyday and academic intelligence. They found that people's self-conceptions resembled both prototypes. but they were more similar to experts' characterization of everyday than academic intelligence. In addition, performance on a verbal measure of intelligence was more highly related to people's self-conception of academic intelligence (r = .56) than to their self-conception of everyday intelligence ( r = .45). The prototype resemblance paradigm was adopted in our work (Cornelius et al., 1989) to explore adults' self-conceptions of intelligence. The experiment had two major objectives. The first was to determine whether the correspondence between adults' beliefs about their abilities and prototypic concepts of academic and everyday intelligence were related to age and education-two factors that have shown considerable importance in the analysis of objective test performance. The second objective was to investigate relations between performance on standard ability tests and adults' self-conceptions of their intellectual functioning. Based on arguments (e.g., Willis & Baltes. 1980)that traditional tests are less representative of everyday than academic kinds of cognitive abilities. it was expected that objectively measured performance would be less related to adults' self-conception of everyday intelligence. In the study, young, middle-aged, and elderly adults between the ages of 20 and 89 were administered an abridged version of the questionnaire compiled by Sternberg et al. (1981). Participants rated how characteristic each behavior was of themselves on a seven-point scale (1 = highly uncharacteristic, 7 = highly

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characteristic). Self-concept measures of everyday and academic intelligence were then obtained by computing correlations between each individual's response pattern and experts' profile of ratings for prototypes of everyday and academic intelligence. The possible range of scores was from - 1.OO to + 1.OO with higher positive scores indicating closer resemblance between an individual's self-concept and the pattern of qualities characterizing an ideal prototype. In general, participants' self-conceptions were more similar to experts' concept of everyday intelligence (M= .31.SD = .2 1) than academic intelligence (M= .18, SD = .21). Individual differences in self-conceptions of intelligence were quite large. however: For everyday intelligence, scores ranged from -.21 to .71.and for academic intelligence, scores ranged from -.22 to .62.

Relations between self-conceptionsof intelligence, age, and education. To address the first objective of the experiment. analyses were conducted to examine the relation between age, education, and the self-concept measures of everyday and academic intelligence. The findings are depicted in Figure 1. Mean scares on the prototype similarity measures of everyday and academic intelligence are shown for three age groups (Young adults, M age = 25.6 years; Middle-aged adults, M age = 49.4 years: Old adults, M age = 70.7 years) and for adults with lower (High school diploma or less education) vs. higher (More than a high school diploma) levels of education. The findings shown in Figure 1 emphasize that the extent to which age and education are related to self-conceptions of intelligence differs for self-concept measures of everyday and academic intelligence. In particular, age was not related to selfconceptions of everyday intelligence, whereas self-conceptions of academic intelligence declined with increasing age. In addition, self-conceptions of everyday intelligence were somewhat higher for adults with higher levels of education, but self-conceptions of academic intelligence were much higher for adults with higher levels of education.

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0.4,

IYOUNG MIDDLGAGEI)

HOLD

EVERYDAY ACADEMIC SELF- CONCEPTION OF INTELLIGENCE

1 LOW EDUCATION 1 HIGH EDUCATION

EVERYDAY ACADEMIC SELF- CONCEPTION OF INTELLIGENCE

Figure 1. Self-conceptions of everyday and academic intelligence by age and educational background.

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Regression analyses performed with age and education as predictors of self-conceptions of intelligence clarified these findings. Results showed that these variables accounted for less variance in self-conceptions of everyday intelligence (R2=.12) than academic intelligence (R2= .34).For everyday intelligence, age was not a signlficant predictor [D = .02) but education was significant [D = .34,p < .01). For academic intelligence, both age CD = -.30.p < .01) and education (D = .54,p < .01) were significant predictors. In addition to the prototypic resemblance measures, a factor analysis was conducted to examine dimensions underlying people's self-conceptions of intelligence. Four factors were extracted with eigenvalues greater than 1. The first factor was indicative of problem-soluing ability. It included high loadings on items associated with objectivity, quality of problem solving, and task persistence. The second factor was associated with uerbal intelligence and knowledge. It was loaded highly by behaviors indicative of communicative competence, verbal facility, and curiosity. The third factor comprised behavioral qualities associated with practical intelligence and social competence. It was loaded highly by variables indicative of common sense, acceptance of social conventions, ethical judgment, and interpersonal competence. The fourth factor represented facets of motivation It was loaded highly by variables such as self-appraisal. goalorientation, and achievement. The relationship between age and self-conceptions of intellectual functioning differed depending on the dimension examined. Figure 2 displays the main results. There was an increase with age in self-assessments of practical intelligence ( r = .32). By contrast, participants' age displayed negative but insignificant relationships with self-concept measures of problem solving (r = -.08), verbal intelligence (r = -.04), and motivation ( r = .02). Self-assessments on these dimensions also showed differential relationships with participants' educational background. Education was positively correlated with self-assessed problem solving (r = .25) and verbal intelligence (r = .32).but it was not related to self-assessed practical intelligence (r = -.04)or motivation ( r = .06).

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.2 4

w

.

0 .I. U

c n .

cr:o

0

i - . -.14

L

4

w

L

.

-.2.

SOLVING

. -.34

INTELLIGENCE YObG

-

MIDDLE-AGED A G E

PRACIlCAL INTELLIGENCE

8 MOTIVATlON

&

G R O U P

FYgure 2. Assessments of problem solving, verbal intelligence, practical

intelligence, and motivation by age.

These findings are partially consistent with previous literature suggesting that people perceive an increase in everyday cognitive abilities during adulthood. Self-assessments on the dimension of practical intelligence showed an increase with age. However, age was not related to the prototype similarity measure of everyday intelligence. These findings may occur because prototypes of intelligence are multifaceted and reflect several dimensions. Correlations between prototypic measures and self-ratings (i.e., factor scores) on specific dimensions showed that self-conceptions of everyday intelligence were positively correlated not only with self-ratings of practical intelligence and social competence ( r = .60) but also self-ratings of problem solving ability ( r = .54). verbal intelligence and knowledge ( r = .50),and motivation ( r = .38).By comparison, self-conceptions of academic intelligence were unrelated to self-ratings of practical intelligence (r = -.lo), but positively related to ratings on the dimensions of problem solving ( r = .64). verbal intelligence ( r = .61)and motivation (r = -21).

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Relations between self-conceptionsof tntellfgence and ability test performance In order to examine the relation between self-concept measures of intelligence and objective test performance, seven ability tests were administered to participants. Nonverbal tests included measures of inductive reasoning (Letter Series. Blieszner et al., 1981; and Letter Sets. Blieszner et al., 1981) and logical classification (Figural Relations Matrices, Plemons, Willis & Baltes. 1978). Verbal measures of analogical reasoning (Verbal Analogies: Guilford, 19691, vocabulary [Verbal Meaning: Thurstone, 1962). practical judgment (Comprehension subtest of the WAIS, Wechsler, 1955). and social judgment (Social Situations test, Horn & Cattell. 1966)were also administered. Table 1 lists correlations between objective test performance and self-concept measures of intelligence. The first two columns show that objectively measured abilities are significantly related to self-concept measures of everyday and academic intelligence, but the correlations are consistently higher with academic intelligence, The only exception to this general pattern occurs for the Social Situations test which shows a higher correlation with self-conceptions of everyday intelligence than it does with academic intelligence. The correlations between objective performance and self-conceptions are comparable with those reported in other research (e.g.. Cornelius & Caspi. 1986: McCrae & Costa, 1985; Sternberg. 1985b; Sternberg et al., 1981; Willis & Schaie, 1986). In the third through sixth columns of Table 1, correlations between ability performance and self-ratings on specific ability dimensions are listed. As expected, self-rated problem-solving ability was positively related to performance on each test. Likewise, self-rated verbal intelligence was significantly related to performance on five of the seven ability tests. Objectively measured performance, however, was not related to self-ratings of practical intelligence or motivation. Many of the ability tests included in this study were not designed to assess practical abilities or social competence. It was surprising, however, that self-assessments of practical intelligence

Table 1 Correlations Between Self-conceptions of intelligence and Ability Performance Ability Test performance

Self-Concept Variable Everyday Academic Problem Verbal Practical intelligence intelligence solving intelligence intelligence motivation

Letter Series

.28**

.46**

.22*

-18

-.16

-.12

Letter Sets

.w*

,42**

.26**

.22*

-.08

-.03

Matrices

.42**

.52**

.37**

.27**

- .07

Verbal Analogies

.37**

-55.'

.37**

.30**

-.15

-.0f3

Verbal Meaning

.41**

.49**

.39*

.36**

.o1

-.10

Comprehension

.36**

.a**

.37**

.30**

.05

-.01

Social Situations

.29**

.18

.19*

.06

-01

-.04

**

pc.01

* pc.05

-08

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429

were unrelated to performance on either the Comprehension or Social Situations test. In the Comprehension test, an examinee is required to respond to a question (e.g.. Why are child labor laws needed?), including in the response all information that is needed to answer it adequately. Wechsler (1958) suggested that the Comprehension test assesses practical judgment, common sense, and the ability to evaluate past experience. In the Social Situations test, an examinee is presented with an interpersonal dilemma and chooses from among four alternative responses the one that provides the best solution. The Social Situations test has been described a s an indicator of the ability "experiential evaluation". which is characterized by maktng good judgments and using social conventions in making decisions (e.g.. Horn & Donaldson. 1980). If these interpretations of the tests are correct, the negligible relations between performance and self-rated practical intelligence could result because adults do not accurately assess their practical intelligence. Perhaps the feedback a person receives about performance in everyday situations is too ambiguous for a n individual to form accurate estimates of their practical abilities. It is also possible, however, that these tests tap only some attributes identified with adults' self-conceptions of their practical intelligence. Therefore, we conducted an experiment to examine people's conceptions of the qualities assessed by ability tests and their relation to implicit theories of intelligence. Experiment 2: Implicit Theories of Intelligence and Ability Tests Neisser (1979)proposed that omnibus scales of intelligence (e.g.. Stanford-Binet, WAIS) may be relatively successful in the assessment of intelligence because different tests included in the battery capture different facets of intelligence. Any ability test, by itself, is unlikely to be a n adequate indicator of intelligence. Intelligence is a multidimensional construct, and a single ability test is likely to assess only some of the qualities associated with the construct. For example, the prototypic conception of academic intelligence emphasizes both verbal and problem-solving abilities. Performance on tests of both kinds of abilities may provide a reasonable approximation to academic intelligence. Indeed, in

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research on adult intelligence (Schde. 1979).a composite index of educational aptitude has been formed from performance on verbal comprehension (i.e.. Verbal Meaning) and inductive reasoning tests (Lea,Letter Series). The purpose of Experiment 2 was to investigate people's beliefs about the qualities characterizing exceptional performance on ability tests designed from an explicit approach and their relation to experts' prototypic conceptions of everyday and academic intelligence. Based on findings from research examining the relations between objective test performance and self-conceptions of intelligence, it was expected that people's characterizations of most ability tests would display greater correspondence to a prototypic conception of academic intelligence, because most ability tests emphasize problem-solving or verbal abilities rather than practical intelligence or social competence. Therefore, in addition to traditional tests of fluid (i.e.. problem solving) and crystallized abilities, tests we have developed to assess everyday cognitive abilities were also included a s stimuli in the study. Tests of fluid abilities included Letter Series (Blieszner et al.. 1981).Letter Sets (Blieszner et al., 1981) and Figural Relations Matrices tests (Plemons et al.. 1978). Two tests involved verbal reasoning (Verbal Analogies: Guilford. 1969) and verbal comprehension (Verbal Meaning; Thurstone. 1962). Finally, four tests included content relevant to practical intellectual abilities: the Everyday Problem Solving Inventory (Cornelius & Caspi. 1987), Stressful Situations Questionnaire (Cornelius & Rose. 1987).Social Situations test (Horn & Cattell. 1966),and Comprehension subtest of the WAIS (Wechsler. 1955). The format of these tests is described in more detail elsewhere (Cornelius et al., 1989). A sample of college students was randomly assigned to rate one of the nine ability tests. They were told to read the instructions for a test and were allowed t o examine practice and test problems included in it. Identifying information about the test (e.g.. the title) was removed. After inspecting the test, participants were instructed to characterize the qualities they believed would be displayed by a person performing extremely well on the test using items from an abridged version of the questionnaire developed by Sternberg et al. (1981)on people's conceptions of intelligence. Subjects rated

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431

exceptional performance for a test on these items using a sevenpoint scale (1 = Very Uncharacteristic. 7 = Very Characteristic). Three major findings emerged from analyses of these data. First, contrary to our expectations, ratings for most of the ability tests displayed greater similarity to the prototype of everyday than academic intelligence. Prototypicality measures were computed to assess the degree of similarity between ratings of the ability tests and prototypes of everyday and academic intelligence. Prototypicality measures were obtained by correlating each participant's ratings of a test with the pattern of ratings characterizing experts' concepts of these two types of intelligence. Figure 3 displays mean scores on the prototype similarity measure for each test. The prototype of everyday intelligence showed its largest correspondence with two tests developed in our work to assess practical and social abilities (i.e., Everyday Problem Solving Inventory, Stressful Situations), followed by traditional measures of practical and social judgement (Le.. Social Situations, Comprehension) and fluid ability tests (Letter Series, Letter Sets, Matrices), and least correspondence with verbal ability tests (e.g., Verbal Analogies. Verbal Meaning). By contrast, attributes associated with academic intelligence showed the greatest resemblance to ratings of tests of verbal ability, followed by ratings of fluid ability tests, and the least resemblance to ratings of tests involving practical abilities. A second key finding was that different characteristics of intellectual functioning were attributed to exceptional performance on different ability tests. The data were first factor analyzed to identify a parsimonious set of dimensions underlying judges' evaluations of exceptional performance on the test stimuli. Four factors were extracted with eigenvalues greater than 1. The factor solution that we obtained was similar to results of factor analyses of people's prototypic conceptions of intelligence (Sternberg et al., 1981) and people's self-conceptions of intelligence described in the previous section. The first factor was associated with attributes indicative of practtcal problem-solufng ability. It included high loadings on items associated with decision making, reasoning, and quality of

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EVERYDAY INTELLIGENCE

0 ACADEKIC INTELLIGENCE

-.1 EPSI

STRS SOCS COW LSER LSET MAT VANL VMNG T E S T

S T I M U L U S

F'fgure3. Resemblance between prototypes of intelligence and test rating profiles. Test titles are abbreviated EPSI (Everyday Problem Solving Intentory), STRS (Stressful Situations), SOCS (Social Situations), COMP WAIS Comprehension), LSER (Letter Series), LSET (Letter Sets), MAT (Matrices),VANL (Verbal Analogies), and VMNG ('Verbal Meaning).

The second factor was indicative of verbal intelligence and knowledge. It was loaded highly by behaviors involving reading, verbal facility, and achievement. The third factor comprised behavioral qualities associated with social Competence and practical Intelligence. It was loaded highly by variables indicative of interpersonal competence, ethical judgment, and giving advice. The fourth factor represented several indicators of cognitfue style. It was loaded positively by variables such as curiosity, thoughtfulness, and style of problem solving. Comparisons between tests rated on these four dimensions revealed three major patterns (see Figure 4). Tests of practical abilities (Lee, Everyday Problem Solving Inventory. Stressful Situations, Social Situations, Comprehension) were evaluated highly on behaviors indicative of practical problem solving a s well a s social competence. Fluid ability tests (i.e.. Letter Series, Letter Sets, Matrices) were judged most highly on characteristics associated with practical problem solving ability. Finally, verbal ability tests (Verbal Analogies, Verbal Meaning) were rated highly problem solving.

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6.0.

i ii f f

5.5.

5.0.

4.5.

4.0.

L

1.o

PRACIICAI, PROBLEM SOLVING A VERBAL INTELLIGENCE I

EPSI

eCOGNITIVE STYLE

I

I

STRS

SOCIAL COMPETENCE

SOCS COMP LSER LSET T E S T

1

MAT

I

VANL VMNG

S T I M U L U S

Flgure 4. Ratings of test stimuli on dimensions of intelligence (after Cornelius et d.,1989). Test titles are abbreviated: EPSI (Everyday Problem Solving Inventory). STRS (Stressful Situations), SOCS (Social Situations), COMP ( WAIS Comprehension), LSER (Letter Series), LSET (Letter Sets), MAT (Matrices),VANL (Verbal Analogies),and VMNG (Verbal Meaning).

on facets of verbal intelligence and knowledge. Overall. the pattern of ratings appears to coincide with researchers' interpretations of the tests and suggest that different tests may tap different features of intellectual functioning. Finally, a third major finding was that a combination of tests yielded a better prediction of experts' prototypic concepts of intelligence than any single test. A profile was computed for each test by averaging judges' ratings on each item in the questionnaire. Intraclass correlation coefficients were computed to obtain a n index of the reliability of these profiles. There was a high degree of interjudge similarity in ratings (M intraclass coefficient = .85) with intraclass correlations ranging from .79 to .92 for the different tests. Regression analyses were then performed using the profiles of ratings for the ability tests as predictor variables. Criterion

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variables in these analyses were the proffles of ratings for experts' conceptions of everyday and academic intelligence. Results showed that the pattern of characteristics associated with everyday intelligence was best predicted by the rating proffles of four tests: Everyday Problem Solving Inventory 1p = .37). Stressful Situations 1p = .25). Letter Series Cp = .28), and Verbal Meaning [D = .24, all p's c .Ol). Ratings on these four tests accounted for 73 percent of the variance (R = .85. p < .001). Academic intelligence was predicted best by ratings of the Verbal Meaning ID = .67) and Letter Series tests (J.3 = .25. p's c .001). and together these tests accounted for 61 percent of the variance (R = -78.p c .OOl). In summary, the findings of this experiment highlight similarities and differences between concepts of everyday and academic intelligence and their relation to people's perceptions of ability tests. These conceptions of intelligence are distinguishable because different facets of intellectual behavior are weighted differently in people's ideas about these concepts. Experts emphasize both verbal and problem-solving abilities in their concept of academic intelligence. and people's conceptions of tests of these abilities provide good predictors of this prototype. These abilities are also significant in the prediction of experts' concept of everyday intelligence. However, independent of these, tests of everyday problem solving and coping with stressful situations also contribute to the prediction of the prototype of everyday intelligence. In line with Neisser's (1979) argument, the results suggest that a combination of ability tests may be required to assess adequately the multifaceted attributes that people believe are characteristic of intelligence. Similar to our findings examining self-conceptions of intelligence and ability test performance, these results suggest that verbal and problem-solving abilities are important aspects of both everyday and academic intelligence. These abilities provide only a partial account of everyday intelligence, however, and need to be supplemented by measures that specifically tap features of social competence and practical intelligence (cf. Willis & Schaie. 19861. The lack of attention to these dimensions in explicit approaches to the study of intelligence may have resulted from the focus on

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academic performance as the primary criterion for evaluating the validity of ability tests. EVERYDAY COGNITIVE ABILITIES: AN EXPLICIT APPROACH In this section, two experiments that were conducted to examine performance on measures of everyday cognitive abilities are discussed. Based on findings concerning experts' prototypic conceptions of everyday intelligence (Sternberg et al., 1981).these measures were designed to assess two major facets of practical and social cognitive abilities-everyday problem solving and knowledge about adaptive behavior.

Experiment 3: Everyday Problem Solving in Adulthood and Old Age

Phase 1 The first phase of our research was devoted to the development of an instrument to assess everyday problem solving. The Everyday Problem Solving Inventory (Cornelius & Caspi. 1987) was constructed using a behavior-analytic model for assessing competence (Goldfried & D'Zurilla, 1969;also see, D'Zurilla & Nezu. 1982). The basic elements consisted of specifying problematic situations, enumerating possible responses to them, and evaluating the perceived efficacy of the responses. The Everyday Problem Solving Inventory consists of 48 hypothetical problem situations sampling six content domains- problems an adult might experience as an economic consumer, in deaIing with complex or technical informatfon. in managing a home, in resolving interpersonal conflicts with one's family members, in resolving conflicts with friends, or in conflict resolution with coworkers. The majority of situations in the Everyday Problem Solving Inventory are similar to ones included in situational taxonomies (Scheidt & Schaie, 1978).inventories of unpleasant events (Lewinsohn & Talkington, 19791,and hassles in everyday living (Kanner. Coyne, Schaefer, & Lazarus, 1981). A

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sample problem from the information domain and alternative responses to it follow.

was returned because you misinterpreted the instructions on how tofill it out. A. Obtain more information on how to complete the form correctly. B. Try to figure out on your own what was wrong. C. Ask someone to fill out the form for you. D. Blame the company for not making the instructions more clear.

A complicated form you completed

For each situation, four possible response modes were devised based on previous studies of practical problem solving and coping with real-life stressors (e.g.. Billings & Moos, 1981; Denney & Palmer, 1981; Lazarus & Folkman. 1984). h-oblem-focused action (Response A to the sample problem) involves self-initiated overt behaviors to deal directly with a problem and its effects. Cognitive problem analysis (Response B) refers to intrapsychic or cognitive efforts to manage one's subjective appraisal of a situation, to understand it better, to solve the problem through logical analysis, or to reinterpret the situation from a dmerent perspective. Passfvedependent behavior (Response C) includes attempts to avoid or withdraw from a situation, the absence of self-initiated behavior to alter a situation. or actions involving dependence on another person to solve the problem. Finally, auoldant thinking and denial (Response D) includes attempts to control the meaning of a situation through cognitive avoidance, denial of the situation or of one's personal responsibility in it, selective attention to things other than the situation itself, or attempts to manage one's affective reaction through the suppression of one's emotions. Because contextual models of competence (e.g., Goldfried & D'Zurilla, 1969; Scheidt & Schaie. 1978: Sternberg. 1985a) suggest that particular modes of response are likely to be more effective in some situations than in others, we wanted to examine people's judgments about the quality of the responses for each of the problems in the inventory, Thus, in the initial phase of research, a sample of judges rated how effective they believed responses would

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be as solutions to the problems described in the Everyday Problem Solving Inventory. In making their judgments, judges were instructed to consider factors such a s the likelihood that the response would solve the problem, that it would prevent or minimize future problems, and that it would enhance the person's self-esteem (see Fisher-Beckfield & McFall, 1982). Judges were given the inventory and rated each response on a 5-point scale ( 1 = Extremely ineffective or poor solution, 5 = Extremely effective or good solution). Analyses were performed examining the effects of situation and modes of response on judgments of response efficacy. In general, problem-focused action and cognitive problem analysis were judged to be more effective than either passive-dependent behavior or avoidant thinking and denial. These analyses, however, also revealed significant interactions between situation and mode of response for each domain of problems. In fact, the pattern of ratings among the four response modes diaered depending on the situation examined. For example, in one consumer problem in which a person did not have enough money to buy a gift for a friend's birthday, problem-focused action (M= 4.6) was rated as most effective, followed by passive-dependent behavior (M = 2.6) and cognitive probIem analysis (M = 2.4), and avoidant thinkfng and denial (M = 1.1) was rated as least effective. In another consumer problem describing a person who did not have sufficient time to purchase items prior to a vacation trip, however, cognitive problem analysis (M = 4.6) was fudged to be the most effective response, followed by avoidant thinking and denial (M= 3.9)and passive-dependent behavior (M= 3.7).and problem-focused action (M= 2.6)was rated as least effective. In line with contextual models of competence, these findings suggest that an important skill in solving everyday problems may be an individual's sensitivity to situational differences and flexibility in responding to situational nuances. A heuristic strategy for solving everyday problems that involves reliance on a general response mode (e.g., problem-focused action) may prove optimal in many situations, but it may be maladaptive in particular situations. Given the heterogeneity of problems that occur in any domain of everyday life, it seems unlikely that a

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particular response mode would be uniformly effective across diverse situations (cf. Baltes & Smith,in press: Berg, 1989;Feifel & Strack, 1989;Mischel, 1984). Phase 2

In the second phase of the research, the Everyday Problem Solving Inventory was administered to young, middle-aged, and older adults. The second phase was conducted to examine age differences in everyday problem solving performance and relationships between performance o n the inventory and traditional tests of verbal and problem-solving abilities. In administering the inventory, participants were instructed to imagine themselves in the situations described and to rate the likelihood that they would act in each of the four response modes listed after each situation. Ratings were made on a 5-point scale (1 = Definitely would not do, 5 = Definitely would do). It is important to emphasize that in this format, participants did not simply select one response to describe how they would respond. Rather. because solutions to everyday problems often involve multiple actions, participants rated each possible response. Thus,for each problem domain, participants made four ratings for each of eight situations, yielding a total of 32 responses. Scores on the inventory were then derived by computing a correlation between each participant's ratings and judges' average ratings of response efficacy obtained in the first phase of the research. Separate correlations were obtained for each domain of problems, and an overall problem-solving score was computed across all problem domains. In addition, participants were given tests of verbal comprehension (i.e., Verbal Meaning; Thurstone. 1962)and inductive reasoning (i.e.. Letter Series; Blieszner et al., 1981). Table 2 shows correlations between performance on traditional verbal and problem-solving tests and the Everyday Problem Solving Inventory. Several aspects of these data are notable. First, the overall score on the Everyday Problem Solving Inventory was signiflcantly correlated with performance on Verbal Meaning and Letter Series tests. These correlations are similar to each other and

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Table 2

Correlations Among Verbal Meaning. Letter Series, and Everyday Problem Solving Performance ~~

Test variable

1

2

3

4

5

6

7

8

9

1. Verbal Meaning ---.37 ---2. Letter Series 3. Everday Problem Solving .27 .29 ---Total Score .30 .34 .86 ---4. I d o r m at io n .30 .26 .80 .57 --5. Family .24 .22 .86 -70 .62 ---6. Work .18 .30 .87 .68 .65 .72 ---7. Friend .16 .12 .82 .63 .64 .67 .68 ---8. Consumer 9 ~. . Home .12 .18 .81 .64 .63 .66 .6!5 .59 ---Note: Correlations are significant with a value of .18 (p < .05)and .23 (p < .01).

to the correlation between scores on the Verbal Meaning and Letter Series tests. Second, performance on the Verbal Meaning and Letter Series tests show similar patterns of correlations with scores for each problem domain. The highest correlation is with performance on problems involving information, and the lowest correlations are with consumer or home management problems. Third, correlations among scores from different problem domains are moderate to large. These correlations indicate that individual differences in performance are fairly consistent across the different domains of problems examined. Moreover. correlations among scores for the diMerent domains of everyday problem solving are much larger in magnitude than are their correlations with traditional ability tests. Similar to the results we obtained for people's conceptions of exceptional performance on ability tests, these findings suggest that the Everyday Problem Solving Inventory may assess facets of intellectual functioning

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that are somewhat independent from traditional measures of verbal and problem-solving abilities. Regression analyses with age, education, and sex as predictors of performance on these measures provided further support for a differentiation among them. The findings showed that these demographic characteristics were less highly related to performance on the Everyday Problem Solving Inventory ( R = .24) than on the Verbal Meaning (R = .55) or Letter Series tests ( R = 50). For the Everyday Problem Solving Inventory, only the linear component of age was a significant predictor U3 = .19. p < .05). For the Verbal Meaning test, significant predictors included the linear component of age @ = .16, p c .05) and education @ = .53, p c .001). For the Letter Series test, the linear @ = -.31) and quadratic components of age 10 = -.32) and education U3 = .30,all p's c .001) were significant predictors. The regression lines displayed in Figure 5 show the predicted values of performance on the Everyday Problem Solving Inventory, Verbal Meaning, and Letter Series tests as a function of age. Scores on the three dependent variables were transformed to T scores to facilitate a graphic display of the results. The regression lines show similar developmental functions for the Everyday Problem Solving Inventory and Verbal Meaning test. Both functions show a modest increase with age. By contrast, the function for the Letter Series test shows an increase from ages 20 to 30.relative stability from ages 30 to 50, and then a decrease from ages 50 to 70. One explanation for multidirectional age differences in cognitive abilities has centered on the differential familiarity of different ability dimensions (e.g.. Cornelius. 1984). A similar hypothesis has been proposed to account for age differences on different measures of practical abilities. For example, Cardner and Monge (1977) found that maximal performance on a test of knowledge of modes of transportation was achieved by 30 year olds. whereas peak performance on a test involving knowledge about death and disease was achieved by 60 year olds. Changes in everyday cognitive abilities may be dependent on a person's present or prior experience with similar problems or on a person's degree of interest in a particular domain of everyday life (e.g.. Camp,

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EVERYDAY PROBLEM SOLVINGINVENTORY VEREALMEANJNGTEST

1 LElTER SERIES TEST

42 40

20

30

40

50

CHRONOLOGICAL

60

70

A G E

Flgure 5. Developmental functions for different ability tests (after Cornelius & Caspt, 1987). (Regression lines display predicted levels of performance as a function of chronological age. Predicted performance is measured in standardized Tscores.)

Doherty. Moody-Thomas. & Denney, 1989; Denney. in press: Gardner & Monge, 1977). In a separate Everyday Situations Questionnaire, participants rated how frequently they experienced the situations described in the Everyday FYoblem Solving Inventory using a 5-point scale (1 = Never, 5 = Frequently). Separate problem familiarity ratings were computed for each domain, and a total score was obtained across all problems. Analyses of age differences in problem familiarity showed that young adults (M = 2.82)reported experiencing the problems a s frequently as middle-aged adults (M= 2.76). but older adults (M= 2.59) reported less familiarity with them than younger age groups. Thus, although there was a n increase with age In performance on the Everyday Problem Solving Inventory, selfreported familiarity with the problems decreased with increasing age. Likewise, analyses examining age differences in problem familiarity and problem-solving performance for each of the six domains showed little convergence. Moreover, correlations between familiarity ratings and problem-solving scores for the

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separate domains displayed little correspondence ( f s ranged from -.22 to .08). These results and those of other studies (e.g., Berg, 1989;Camp et al., 1989) indicate that familiarity with everyday problems is unrelated to people's skill or preference in solving them. There may be several explanations for these findings including the possibility that the indices of problem familiarity that have been examined may be insensitive to the characteristics of people's experiences that are most influential in everyday problem solving (see Cornelius & Caspi. 1987). Further research that distinguishes between different aspects of experience (i.e.. recent familiarity. vicarious experience, cumulative experience) will be required to clarify the role that each of them may play in accounting for changes in everyday problem solving abilities during adulthood. Experiment 4: Conceptions of Coping Although research on everyday problem solving is an important step in gerontological research on everyday intelligence, the problems investigated have typically sampled "hassles" adults experience in everyday life rather than problematic situations that seriously tax a person's adaptive capabilities. However, research on prototypic conceptions of intelligence suggests that a n ability to "cope with crises" (Sternberg et al., 1981) or "disastrous situations" (Sternberg & Berg, 1987)is an important characteristic associated with everyday intellectual competence in adulthood (cf. Flavell, 1970). Likewise, recent work emphasizes the importance of examining everyday cognitive abilities in situations involving a n integration of emotion and cognition (e.g.. Baltes & Smith, in press: Blanchard-Fields, 1986: Kramer. 1989: Labouvie-Vief, HakimLarson, & Hobart, 1987;Staudinger, 1988).Thus,we initiated work (Cornelius & Rose, 1987) on the development of a Stressful Situations Questionnaire to investigate the facet of practical adaptive behavior. The specific objective in this experiment was to examlne people's knowledge about strategies they thought would be adaptive in resolving stressful situations. Research relevant to this inquiry h a s emphasized both normative and individual difference perspectives in people's

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knowledge about adaptive behavior. On the one hand, several studies suggest that there is a normative concept of adaptation. This is reflected in a rather high degree of consensual agreement among people about strategies that would be more or less effective in solving problem situations. For example, Sternberg and Soriano (1984) presented subjects with stories describing conflict situations arising in three domains: interpersonal. interorganizational. and international relations. Subjects rated how effective seven different strategies would be in resolving each conflict situation. Their findings showed consistent profiles of efficacy ratings for these strategies both within and across the domains examined. Likewise, McCrae and Costa (1986) investigated the perceived effectiveness of 27 coping mechanisms for stressful situations involving losses, threats, or challenges. Subjects rated whether the mechanisms had been effective for solving the problem or for reducing distress. Their results showed similar patterns of ratings for both of these criteria as well as consistent patterns across different categories of stressors. On the other hand, evidence also shows that there are systematic individual differences among people in their knowledge about effective strategies. Sternberg and Soriano (1984) reported that individual differences in personality and intellectual characteristics were predictive of differences among people's judgments about conflict resolution strategies. For instance, need for deference and inductive reasoning were negatively related to judgments about the efficacy of using physical coercion or economic pressure to resolve conflicts, but these variables were positively related to judgments about the efficacy of responses involving waiting to see whether the situation would improve or accepting and making the best of a situation. Likewise, McCrae and Costa (1986)examined the relation between personality and adults' use of coping mechanisms that were judged to be more or less effective. They found that neuroticism was correlated with the use of less effective coping strategies, whereas extraversion was correlated with the use of more effective strategies. The initial phase of our research with the Stressful Situations Questionnaire was conducted to examine whether adults' conceptions of effective coping may differ across adulthood and the

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possible role of cognitive and personality variables in accounting for individual variability in their prototypical judgments about effective responding to stressful situations. Young (Mage = 30.5 years), middle-aged (Mage = 49.1 years), and older (M age = 68.9 years) adults were administered the Stressful Situations Questionnaire. and traditional tests of intellectual abilities and personality. The Stressful Situations Questionnaire includes 16 hypothetical situations involving losses, threats, and challenges. For each situation, responses modelled after strategies in the Ways of Coping checklist (Lazarus h Folkman, 1984) were listed as possible ways the character in the situation might respond to it. Subjects judged the effectiveness of each coping response as a solution to the problem using a five-point rating scale (1 = Very ineffective, 5 = Very effective). An example of a problem from the Stressful Situations Questionnaire and its associated response items follow.

Helen ONeUl went to the Department of Motor Vehicles to renew her driver's license. Much to her dismay, she failed the required eye examination even when wearing her corrective lenses. Helen became very upset at not being allowed to drive anymore. S h e was afiaid that she would lose a lot of the independence she was accustomed to due to the necessity of having to rely on other people for transportation to andfiorn places.

A. B. C. D.

Helen could feel badly that nothing can be done to improve her vision. Helen could wish that she could get over her fear of becoming dependent on others for transportation. Helen could phone her sister, Phyllis. and talk to her about her concerns about losing independence. Helen could try to accept her fear of becoming dependent but not let it prevent her from keeping up with her daily activities.

If adults' knowledge about coping is organized around a dominant conceptual prototype, profiles of ratings between

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different judges should be highly similar. When we compared profiles of ratings averaged across various subgroups of judges in the sample, the findings showed a high degree of congruence. Simple correlations were computed between the patterns of ratings by subgroups to explore consistency in judgments a s a function of the age, educational background, and sex of judges. Comparisons between the pattern of ratings by young and middle-aged judges (r = .97), young and old judges (r = .93), and middle-aged and old judges (r =.95) revealed high consistency. Likewise. there was high correspondence between ratings by judges who had a high school diploma or less education and judges who had received more education beyond a high school diploma ( r = .97). Moreover, comparison of ratings by male and female judges displayed high similarity (r = .97). Finally, an alpha coefficient was computed to obtain an estimate of the reliability of judges' ratings across all possible split halves of judges. This coefficient was also extremely high (a = .99) suggesting that the profiles of ratings were quite similar even for arbitrarily formed subgroups of judges. Even though various subgroups in the sample displayed high consistency in their prototypicality judgments about coping. judgments of individuals did not uniformly correspond to the prototype of the group as a whole. A prototype similarity score was obtained by computing a correlation between each individual's profile of ratings and the profile of ratings averaged across all other judges in the sample. These scores could range between -1.00 and + 1 .OO with larger positive values indicating greater similarity between an individual's judgments and those of the rest of the group. The average prototypicality score was relatively high (M= .69). but there was also a wide range of individual daerences (SO = ,171. Analyses were performed to determine whether individual differences in adults' knowledge about coping were systematically related to intellectual and personality variables. Participants were administered standard tests of social intelligence (George Washington Social Intelligence Test: Moss, Hunt, Omwake, & Woodward, 19491, inductive reasoning (Letter Series: Blieszner et al., 1981).and verbal comprehension (Verbal Meaning; Thurstone. 1962). a s well as measures of Extraversion and Neuroticism

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(Eysenck Personality Inventory; Eysenck & Eysenck. 1968). Relations between prototypicality judgments, intellectual performance, and personality are shown in Table 3. Simple correlations presented in the first column of Table 3 indicate that prototypicality judgments were positively correlated with performance on intellectual ability tests. As expected, the largest correlation occurred with the measure! of social intelligence, and judgments were associated to a lesser extent with performance on traditional tests of problem-solving and verbal abilities. In addition, prototypicality judgments about coping were negatively correlated with personality dimensions, in particular neuroticism. Because one might suspect that judgments about effective coping simply reflect a tendency toward socially desirable responding, the correlation between prototypicality judgments and responses to the Lie Scale of the Eysenck Personality Inventory was also examined. The correlation was negative but not significant. A regression analysis was performed with scores on the intellectual and personality measures as predictor variables, and the prototype similarity score a s the criterion variable. In combination, the intellectual and personality variables accounted for 46% of the variance in prototypicality judgments about coping ( R = .68, p c .OOl). Standardized regression coefficients from this analysis are listed in the second column of Table 3. Significant predictors included performance on the social intelligence and inductive reasoning tests and self-reported neuroticism and extraversion. Thus, individuals whose judgments about effective coping resembled the judgments of the group as a whole tended to display better performance on measures of social intelligence and problem solving and reported themselves to be more emotionally stable and introverted. These findings are compatible with both normative and individual difference approaches to the study of people's knowledge (i.e., beliefs and ideas) about adaptive behavior. Adults' judgments about effective solutions in resolving stressful situations appear to reflect a system of strategic or procedural knowledge that is quite similar across various social groups. In accord with other research (e.g., McCrae & Costa. 1986; Sternberg & Soriano, 1984). these findings suggest that people's conceptions of effective coping are

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Table 3

Relations between Prototypicality Judgments and Intellectual and Personality Tests Test Variable

Social Intelligence Letter Series Verbal Meaning Neuroticism Extraversion Lie Scale

n

*

Simple correlation (r)

Standardized regression coefficient (p)

.59***

.47***

.35***

.18* .09 16*

a***

-.27**

-.12 -.14

-.

-.17* -.11

p