A model of the self-explanation effect.

Several investigators have taken protocols of students learning sophisticated skills, such as physics problem solving and LISP coding, by studying examples and solving problems. These investigations uncovered the self-explanation effect: Students who explain examples to themselves learn better, make more accurate self-assessments of their understanding, and use analogies more economically while solving problems. We describe a computer model, Cascade, that accounts for these findings. Explaining an example causes Cascade to acquire both domain knowledge and derivational knowledge. Derivational knowledge is used analogically to control search during problem solving. Domain knowledge is acquired when the current domain knowledge is incomplete and causes an impasse. If the impasse can be resolved by applying an overly general rule, then a specialization of the rule becomes a new domain rule. Computational experiments indicate that Cascade's learning mechanisms are jointly sufficient to reproduce the self-expl...

[1]  K. VanLehn.  Problem solving and cognitive skill acquisition , 1989 .

[2]  Paul J. Feltovich,et al.  Categorization and Representation of Physics Problems by Experts and Novices , 1981, Cogn. Sci..

[3]  C SchankRoger,et al.  Dynamic Memory: A Theory of Reminding and Learning in Computers and People , 1983 .

[4]  P. Pirolli.  Effects of Examples and Their Explanations in a Lesson n Recursion: A Production System Analysis , 1991 .

[5]  Ann L. Brown,et al.  Reciprocal Teaching of Comprehension-Fostering and Comprehension-Monitoring Activities , 1984 .

[6]  Michael Redmond,et al.  Distributed Cases for Case-Based Reasoning: Facilitating Use of Multiple Cases , 1990, AAAI.

[7]  N. Webb.  Peer interaction and learning in small groups , 1989 .

[8]  Allen Newell,et al.  Human Problem Solving. , 1973 .

[9]  Monte Zweben,et al.  Learning Search Control for Constraint-Based Scheduling , 1990, AAAI.

[10]  Kurt VanLehn,et al.  Non-LIFO Execution of Cognitive Procedures , 1989, Cogn. Sci..

[11]  Kurt VanLehn,et al.  Explanation-Based Learning of Correctness: Towards a Model of the Self-Explanation Effect , 1990 .

[12]  Stephen K. Reed,et al.  Usefulness of analogous solutions for solving algebra word problems. , 1985 .

[13]  Michelene T. H. Chi,et al.  Self-Explanations: How Students Study and Use Examples in Learning To Solve Problems. Technical Report No. 9. , 1987 .

[14]  J. Carbonell.  Learning by Analogy: Formulating and Generalizing Plans from Past Experience , 1983 .

[15]  J. LeFevre,et al.  Do Written Instructions Need Examples , 1986 .

[16]  Jaime G. Carbonell,et al.  Derivational analogy: a theory of reconstructive problem solving and expertise acquisition , 1993 .

[17]  P. Pirolli,et al.  The role of learning from examples in the acquisition of recursive programming skills. , 1985 .

[18]  Stellan Ohlsson,et al.  Artificial Instruction. A Method for Relating Learning Theory to Instructional Design. , 1992 .

[19]  K. VanLehn.  Mind Bugs: The Origins of Procedural Misconceptions , 1990 .

[20]  S. Ohlsson.  Trace Analysis and Spatial Reasoning: An Example of Intensive Cognitive Diagnosis and Its Implications for Testing. September 1987. Technical Report. , 1987 .

[21]  Kurt Van Lehn.  Two Pseudo-Students: Applications of Machine Learning to Formative Evaluation , 1990 .

[22]  Michael G. Dyer,et al.  The Role of Prior Causal Theories in Generalization , 1986, AAAI.

[23]  John R. Anderson,et al.  Learning to Program in LISP , 1984, Cogn. Sci..

[24]  Kurt VanLehn,et al.  Rule Acquisition Events in the Discovery of Problem-Solving Strategies , 1991, Cogn. Sci..

[25]  Andrea A. diSessa,et al.  Knowledge in pieces : An evolving framework for understanding knowing and learning , 1988 .

[26]  David M. Neves.  Learning Procedures from Examples and by Doing , 1985, IJCAI.

[27]  Andrea Pohoreckyj Danyluk,et al.  Finding New Rules for Incomplete Theories: Explicit Biases for Induction with Contextual Information , 1989, ML.

[28]  John R. Anderson,et al.  The Adaptive Character of Thought , 1990 .

[29]  John H. Mayer.  Explanation-Based Knowledge Acquisition of Schemas in Practical Electronics: A Machine Learning Approach , 1990 .

[30]  Kurt VanLehn,et al.  Integration of Analogical Search Control and Explanation-Based Learning of Correctness , 1993 .

[31]  Clayton Lewis,et al.  Why and How to Learn Why: Analysis-Based Generalization of Procedures , 1988, Cogn. Sci..

[32]  Heinz Mandl,et al.  Computer-Based Learning Environments and Problem Solving , 1992 .

[33]  Davida Charney,et al.  Goal Setting and Procedure Selection in Acquiring Computer Skills: A Comparison of Tutorials, Problem Solving, and Learner Exploration , 1990 .

[34]  Paul S. Rosenbloom,et al.  Knowledge Level and Inductive Uses of Chunking (EBL) , 1990, AAAI.

[35]  A. Newell.  Unified Theories of Cognition , 1990 .

[36]  Roger C. Schank,et al.  Explanation Patterns: Understanding Mechanically and Creatively , 1986 .

[37]  Kurt VanLehn,et al.  Learning one Subprocedure per Lesson , 1987, Artif. Intell..

[38]  Gerhard Widmer,et al.  A tight integration of deductive and inductive learning , 1989, ICML 1989.

[39]  Robert C. Berwick,et al.  The acquisition of syntactic knowledge , 1985 .

[40]  W. D. Gray,et al.  Transfer of Cognitive Skills , 1987 .

[41]  John R. Anderson,et al.  Use of analogy in a production system architecture , 1989 .

[42]  Harry E. Pople,et al.  Session 6 Theorem Proving and Logic: I I ON THE MECHANIZATION OF ABDUCTIVE LOGIC , 2006 .

[43]  Matthew W. Lewis,et al.  Self-Explonations: How Students Study and Use Examples in Learning to Solve Problems , 1989, Cogn. Sci..

[44]  Alan Bundy,et al.  Solving mechanics problems using meta-level inference , 1979, IJCAI 1979.

[45]  M. Ferguson-Hessler,et al.  Studying Physics Texts: Differences in Study Processes Between Good and Poor Performers , 1990 .

[46]  William W. Cohen.  Learning from Textbook Knowledge: A Case Study , 1990, AAAI.

[47]  Tom Michael Mitchell,et al.  Explanation-based generalization: A unifying view , 1986 .

[48]  Gordon S. Novak,et al.  Research on Expert Problem Solving in Physics , 1980, AAAI.

[49]  David C. Wilkins,et al.  Knowledge Base Refinement Using Apprenticeship Learning Techniques , 1988, AAAI.

[50]  J. Sweller,et al.  The Use of Worked Examples as a Substitute for Problem Solving in Learning Algebra , 1985 .

[51]  Michael J. Pazzani.  A reply to Cohen's book review of Creating a Memory of Causal Relationships , 1993, Machine Learning.

[52]  John H. Holland,et al.  Induction: Processes of Inference, Learning, and Discovery , 1987, IEEE Expert.

[53]  M. Chi,et al.  The Content of Physics Self-Explanations , 1991 .

[54]  J. Sweller,et al.  Structuring Effective Worked Examples , 1990 .

[55]  Robert J. Hall.  Learning by failing to explain: Using partial explanations to learn in incomplete or intractable domains , 1988, Machine Learning.

[56]  W. Kintsch.  Learning From Text , 1986, Knowing, Learning, and Instruction.

[57]  Kurt VanLehn.  Arithmetic Procedures are Induced from Examples. , 1985 .

[58]  Pat Langley,et al.  A model of retrieval in problem-solving , 1989 .

[59]  Francesco Bergadano,et al.  Deduction in Top-Down Inductive Learning , 1989, ML.

[60]  Stellan Ohlsson,et al.  An Information Processing Analysis of the Function of Conceptual Understanding in the Learning of Arithmetic Procedures. , 1988 .

[61]  N. Goodman.  Fact, Fiction, and Forecast , 1955 .

[62]  Renée Elio,et al.  Modeling Novice-to-Expert Shifts in Problem-Solving Strategy and Knowledge Organization , 1990, Cogn. Sci..

[63]  S. Carey.  Conceptual Change in Childhood , 1985 .

[64]  Stuart J. Russell,et al.  A Logical Approach to Reasoning by Analogy , 1987, IJCAI.

[65]  Peter Pirolli,et al.  A Model of Self-Explanation Strategies of Instructional Text and Examples in the Acquisition of Programming Skills. , 1990 .

[66]  Ashwin Ram,et al.  Incremental Learning of Explanation Patterns and Their Indices , 1990, ML.

[67]  Kamal M. Ali,et al.  Augmenting Domain Theory for Explanation-Based Generalization , 1989, ML.

[68]  Tom Fawcett.  Learning from Plausible Explanations , 1989, ML.

[69]  Kurt VanLehn,et al.  Competitive Argumentation in Computational Theories of Cognition. , 1982 .

[70]  John R. Anderson,et al.  Induction of Augmented Transition Networks , 1977, Cogn. Sci..

[71]  John R. Anderson,et al.  The Transfer of Cognitive Skill , 1989 .

[72]  John R. Anderson.  Acquisition of cognitive skill. , 1982 .