Cognitive Skills and Their Acquisition

392 Pages·1981·8.011 MB·English

by  John R. Anderson

229x152 HB
COGNITIVE SKILLS
AND THEIR
ACQUISITION
Edited by
JOHN R. ANDERSON
CARNEGIE-MELLON UNIVERSITY
~ ~~~!~~n~~~up
NEWYORK ANDLONDON
FirstPublishedby
LawrenceErlbaum Associates, Inc., Publishers
365 Broadway
Hillsdale, NewJersey 07642
Thiseditionpublished2011byRoutledge
711ThirdAvenue,NewYork,NY10017
2ParkSquare,MiltonPark,Abingdon,Oxon,OX144RN
Copyright © 1981 by LawrenceErlbaumAssociates, Inc.
Allrightsreserved. No partofthis bookmay bereproduced in
any fonn, byphotostat, microfonn, retrieval system, orany other
means, withouttheprior written pennission ofthepublisher
Library ofCongress Cataloging in Publication Data
SymposiumonCognition, 16th,Carnegie-Mellon Uni
versity, 1980.
Cognitive skills and theiracquisitions.
Bibliography: p.
Includesindex.
1. Cognition-Congresses. 2. Learning, Psychology
of-Congresses. I. Anderson, John Robert, 1947-
II. Title. [DNLM: 1. Cognition-Congresses. 2. Learning
-Congresses. W3 C126B 16th 1980c/ BF311 C6785 1980]
BF311.S83 1980 153.4 80-28702
ISBN0-89859-093-0
Publisher'sNote
Thepublisherhasgonetogreatlengthstoensurethequalityofthisreprint
butpointsoutthatsomeimperfectionsintheoriginalmaybeapparent.
TO THE MEMORY OF OUR COLLEAGUE
LEE W. GREGG
WHO, AS MEMBER AND HEAD OF THE PSYCHOLOGY DEPARTMENT
AT CARNEGIE-MELLON UNIVERSITY, FOR A QUARTER CENTURY
GAVE HIS ENERGIES AND TALENTS UNSELFISHLYTO OUR
EXPLORATION OF THE NEW DOMAINS IN COGNITIVE PSYCHOLOGY.
Contents
Preface xi
1. Mechanismsof Skill Acquisition and
the Law of Practice
Allen Newell and Paul S. Rosenbloom 1
Introduction 1
The Ubiquitous Law of Practice 3
Basics About Power Laws 17
Fitting the Data To a Family of Curves 23
Possible Explanations 34
Conclusion 51
2. Knowledge Compilation: Mechanisms for the
Automatization of Cognitive Skills
David M. Neves andJohn R. Anderson 57
Introduction 57
Encoding 60
Proceduralization 65
Composition 67
Effects of Practice 72
Conclusion 82
vii
viii CONTENTS
3. Skill In Algebra
Clayton Lewis 85
Abstract 85
Introduction 85
Framework 86
Hypotheses About Skilled Performance 87
Subjects 89
The Problems 90
Procedure 90
Length of Solutions 91
Stategic Choices 91
Powerful Operators 96
The Formation ofCombined Operations 98
Combining Transposing and Collecting 104
Experts Make Mistakes 106
Why Do They Make Mistakes? 107
Reflections 107
4. The Development of Automatism
Richard M. Shiffrin and Susan T. Dumais 111
Introduction 111
Automatism and Control in Search-Detection Tasks 112
A Definition of and Test for Automatism 115
The Development of Automatism 125
What is Learned During Automatization? 131
The Loss of Automatism 138
Automatization in Skill Development 138
5. Skilled Memory
William G. Chase and K. Anders Ericsson. ..................... 141
Introduction 141
The Learning Curve 143
The Mnemonic System 146
The Retrieval Structure 168
On the Speedup of Encoding and Retrieval Operators 180
Concluding Remarks 186
6. Acquisition of Problem-Solving Skill
John R. Anderson, James G. Greeno, PaulJ. Kline
and David M. Neves ......................................... 191
Introduction 191
A Model ofthe Skill Underlying Proof Generation 192
Learning from the Text 200
Subsumption: Learning With Understanding 205
CONTENTS ix
Knowledge Compilation 214
Knowledge Optimization 221
Summary 227
7. Advice Taking and Knowledge Refinement:
An Iterative View of Skill Acquisition
Fredrick Hayes-Roth, Philip Klahr, and David J. Mostow ......... 231
Abstract 231
What is Learned? 231
What is Advice? 235
How Can a Learner Operationalize Advice? 237
What Kinds of Events Trigger Learning? 243
What Can Be Learned, and How is This done? 244
Conclusions 249
8. The Processes Involved in Designing Software
Robin ,Jeffries, Althea A. Turner, Peter G. Polson,
and MichaelE. Atwood 255
Introduction 255
Research on Design and Planning 256
ATheory of Problem Solving in Software Design 261
AComparison of Expert and Novice Design Processes 268
Discussion 279
9. Mental Models of Physical Mechanisms and Their Acquisition
Johan de KleerandJohn Seely Brown 285
Introduction 285
The Motivation for Defining Some Esthetic Principles 287
The No-Function-In-Structure Principle 287
The Weak Causality Principle 288
Methodology 288
Technical Issues 289
A Simple Qualitative Model for the Buzzer 291
A Time Model ofthe Buzzer 292
A Causal Model for the Buzzer 294
No-Function-In-Structure and the Locality Principles 296
Connections and Device Topology 297
A Mythical Time Model 301
A Representation For Causal Attribution 302
Causality Principles and Envisonment 305
A Critique of the Rieger and Grinberg's Approach 306
Deletion Principle 307
Discontinuity 308
The Role of Momentum in Qualitative Reasoning 308
x CONTENTS
10. Enriching Formal Knowledge: A Model for Learning to
Solve Textbook Physics Problems
Jill H. Larkin 311
Introduction 311
Learning in Formal Domains 312
A Model for Problem Solving in Physics 318
Human Solvers 323
The Reality of the Model 332
Summary 333
11. Analogical Processes in Learning
David E. Rumelhartand Donald A. Norman 335
Introduction 335
Some Characteristics of the
Human Knowledge Representation System 336
New Schemata By Analogy With Old 343
Analogical Processes in Learning aText Editor 350
Conclusions 357
12. The Central Role of Learning in Cognition
Pat Langleyand HerbertA. Simon 361
Introduction 361
Characteristics of a Good Explanation 364
Learning In Complex Systems 367
Are There General Principles of Learning? 373
Is Learning Really Invariant? 375
A Research Strategy 378
Author Index 381
Subject Index 385
Preface
This book is a collection of the papers presented at the Sixteenth Annual Car
negie Symposiumon Cognition, heldinMay 1980. Acouple ofyearsearlierPat
LangleyandBobNechespersuadedthepsychologydepartmentabouttheneedto
have a symposium on the topic oflearning, and I was recruited to organize the
Symposium. Itoowaspersuadedthatthetimewasripeforanewattackonissues
of learning. In separating itself from behaviorism, cognitive psychology had
abandonedinterestinlearning andfor20years hadfocused onunderstandingthe
performance ofestablishedcognitive skills. As aconsequence wehave acquired
afairknowledge ofcognitivemechanisms, butthis knowledge ofperformanceis
both disjointed and hard to use in educational applications. Learning theory
offers both the potential of achieving a new degree of generality in our under
standing ofhuman cognition and the possibility ofopening the way for applica
tions. Given our much more sophisticated understanding of cognition, we can
hope that learning mechanisms can be developed that avoid the weaknesses of
pastlearningtheories. The needforanewlearningtheoryandpotentialofsucha
learning theory is discussed at length in the Langley and Simon chapter.
Inthepastfew years therehasdeveloped anumberofexcitingnewendeavors
at understanding learning. I invited what I thought were among the best prac
titionersofthis newapproachtolearning, andthey allaccepted. Thesymposium
promised to be exciting and it was. It turned out that our ideas about learning
weremoresimilarthanIhadexpected,givenwhatabroaddomainofphenomena
mightfit underthetopic. Inparticular, wewereinterestedincognitive skillsand
howtheydevelopincomplexenvironments overlongperiodsofpractice. More
over, we found we were using similar manipulations, choosing similartypes of
xi