Production systems, learning, and tutoring
Production system models of learning and development
Artificial intelligence and tutoring systems: computational and cognitive approaches to the communication of knowledge
Explanation-Based Generalization: A Unifying View
Machine Learning
Explanation-Based Learning: An Alternative View
Machine Learning
EACL '89 Proceedings of the fourth conference on European chapter of the Association for Computational Linguistics
Preprogramming knowledge: a major source of misconceptions in novice programmers
Human-Computer Interaction
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An original methodology, called backward model tracing to model student performance which features a profitable integration of the bug collection and bug construction techniques is presented. This methodology has been used for building the modelling module of a new version of ET (English Tutor), an ITS aimed at supporting the learning of the English verb system. Backward model tracing is based on the idea of analyzing the reasoning process of the student by reconstructing, step by step and in reverse order, the chain of reasoning (s)he has followed in giving his/her answer. In order to do this, both correct domain specific knowledge and a catalogue of stereotyped errors (malrules) are utilized. When the system is unable to explain the student behavior by exploiting its previous knowledge, new malrules are generated dynamically, by utilizing explanation-based learning techniques. The overall process is based on a deep modelling of the student problem solving and the discrimination among possible explicative hypotheses about the reasons underlying the student behavior is carried on nonmonotonically through a truth maintenance system. The proposed approach has been fully implemented in a student modelling module developed in PROLOG.