Cognitive Skills and Their Acquisition (Carnegie Mellon Symposia on Cognition Series)

First published in 1981. This book is a collection of the papers presented at the Sixteenth Annual Carnegie Symposium on Cognition, held in May 1980. Front Cover Cognitive Skills and Their Acquisition Copyright Page Contents Preface Acknowledgments 1. Mechanisms of Skill Acquisition and the Law of Practice: Allen Newell and Paul S. Rosenbloom Introduction The Ubiquitous Law of Practice Basics About Power Laws Fitting the Data To a Family of Curves Possible Explanations Conclusion 2. Knowledge Compilation: Mechanisms for the Automatization of Cognitive Skills: David M. Neves and John R. Anderson Introduction Encoding Proceduralization Composition Effects of Practice Conclusion 3. Skill in Algebra: Clayton Lewis Abstract Introduction Framework Hypotheses About Skilled Performance Subjects The Problems Procedure Length of Solutions Stategic Choices Powerful Operators The Formation of Combined Operations Combining Transposing and Collecting Experts Make Mistakes Why Do They Make Mistakes? Reflections 4. The Development of Automatism: Richard M. Shiffrin and Susan T. Dumais Introduction Automatism and Control in Search-Detection Tasks A Definition of and Test for Automatism The Development of Automatism What is Learned During Automatization? The Loss of Automatism Automatization in Skill Development 5. Skilled Memory: William G. Chase and K. Anders Ericsson Introduction The Learning Curve The Mnemonic System The Retrieval Structure On the Speedup of Encoding and Retrieval Operators Concluding Remarks 6. Acquisition of Problem-Solving Skill: John R. Anderson, James G. Greeno, Paul J. Kline and David M. Neves Introduction A Model of the Skill Underlying Proof Generation Learning from the Text Subsumption: Learning With Understanding Knowledge Compilation Knowledge Optimization Summary 7. Advice Taking and Knowledge Refinement: An Iterative View of Skill Acquisition: Fredrick Hayes-Roth, Philip Klahr, and David J. Mostow Abstract What is Learned? What is Advice? How Can a Learner Operationalize Advice? What Kinds of Events Trigger Learning? What Can Be Learned, and How is This done? Conclusions 8. The Processes Involved in Designing Software: Robin ,Jeffries, Althea A. Turner, Peter G. Polson, and Michael E. Atwood Introduction Research on Design and Planning A Theory of Problem Solving in Software Design A Comparison of Expert and Novice Design Processes Discussion 9. Mental Models of Physical Mechanisms and Their Acquisition: Johan de Kleer and John Seely Brown Introduction The Motivation for Defining Some Esthetic Principles The No-Function-In-Structure Principle The Weak Causality Principle Methodology Technical Issues A Simple Qualitative Model for the Buzzer A Time Model of the Buzzer A Causal Model for the Buzzer No-Function-In-Structure and the Locality Principles Connections and Device Topology A Mythical Time Model A Representation For Causal Attribution Causality Principles and Envisonment A Critique of the Rieger and Grinberg's Approach Deletion Principle Discontinuity The Role of Momentum in Qualitative Reasoning 10. Enriching Formal Knowledge: A Model for Learning to Solve Textbook Physics Problems: Jill H. Larkin Introduction Learning in Formal Domains A Model for Problem Solving in Physics Human Solvers The Reality of the Model Summary 11. Analogical Processes in Learning: David E. Rumelhart and Donald A. Norman Introduction Some Characteristics of the Human Knowledge Representation System New Schemata By Analogy With Old Analogical Processes in Learning a Text Editor Conclusions 12. The Central Role of Learning in Cognition: Pat Langley and Herbert A. Simon Introduction Characteristics of a Good Explanation Learning In Complex Systems Are There General Principles of Learning? Is Learning Really Invariant? A Research Strategy Author Index Subject Index