Episodic learner modeling

被引:1
作者
Weber, G
机构
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暂无
中图分类号
B84 [心理学];
学科分类号
04 ; 0402 ;
摘要
Modeling the learner is a central aspect of intelligent tutoring systems and knowledge-based help systems that support learners in complex problem-solving domains. In this article, the episodic learner model ELM is introduced as a hybrid system that analyses novices' solutions to programming tasks based on both rule-based and case-based reasoning. ELM behaves like to a human tutor. initially, ELM is able to analyze problem solutions based only on its domain knowledge. With increasing knowledge about a particular learner captured in a dynamic episodic case bose, it adapts to the learner's individual problem-solving behavior. Two simulation studies were performed to validate the system. The first study shows that the system con learn which rules are applied successfully to diagnose code produced by programmers and that using this information reduces the computational effort of diagnoses. Using information from the episodic learner model additionally speeds up the diagnostic process. The second study shows that ELM is able to predict individual solutions. Finally, correspondences and differences to related systems are discussed.
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页码:195 / 236
页数:42
相关论文
共 65 条
[1]  
Anderson J., 1983, The architecture of cognition
[2]  
Anderson J.R., 1993, RULES MIND
[3]   COGNITIVE MODELING AND INTELLIGENT TUTORING [J].
ANDERSON, JR ;
BOYLE, CF ;
CORBETT, AT ;
LEWIS, MW .
ARTIFICIAL INTELLIGENCE, 1990, 42 (01) :7-49
[4]  
ANDERSON JR, 1985, BYTE, V10, P159
[5]   SKILL ACQUISITION - COMPILATION OF WEAK-METHOD PROBLEM SOLUTIONS [J].
ANDERSON, JR .
PSYCHOLOGICAL REVIEW, 1987, 94 (02) :192-210
[6]  
ANDERSON JR, 1989, COGNITIVE SCI, V13, P467, DOI 10.1207/s15516709cog1304_1
[7]  
ANDERSON JR, 1984, P 6 ANN C COGN SCI S
[8]  
BARLETTA R, 1988, P DARPA WORKSH CAS B
[9]  
BONAR J, 1988, ARTIFICIAL INTELLIGE
[10]  
CARR B, 1977, 406 MIT AI LAB