TIDES - Using Bayesian Networks for Student Modeling

Authors:
Abderrahim Danine;Bernard Lefebvre;Andre Mayers
Affiliations:
University of Quebec at Montreal, Canada;University of Quebec at Montreal, Canada;University of Sherbrooke, Canada
Venue:
ICALT '06 Proceedings of the Sixth IEEE International Conference on Advanced Learning Technologies
Year:
2006

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Abstract

We present in this paper an intelligent tutoring system using a Bayesian network. This tutor is dedicated to the analysis and diagnosis of student's errors. The elaboration of such a system necessitates nearly always taking into consideration information that is potentially incomplete or uncertain. Indeed, in a learning situation, we can neither know exactly the student's plan nor his goal. In addition, we cannot observe what the student knows or does not know, but we can only make imperfect estimations through his actions. In order to model the student in this situation, we designed and implemented an intelligent system that uses Bayesian networh.