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We present an ontological approach to the design of the student model for a tutorial agent system (TAS). Our model emphasizes the classification and detection of error types. If the student has any systematic and predictable misconceptions, the system attempts to determine the underlying reasons for such errors. We adopt the "identification, simulation, interaction, and mapping" (ISIM) strategy to achieve this goal. The tutorial agent system first identifies which problem solving method a student is using. It then simulates the procedure in a step-by-step fashion. If there is any ambiguity in the diagnosis of error types during the simulation, the system will interact with the student to resolve it. Finally, the interaction will lead to appropriate error types. The related knowledge is constructed in an ontological framework, InfoMap. In this paper, we focus on how to construct the knowledge and how the simulation works.
Tu et al. (Thu,) studied this question.
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