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TIDES - Using Bayesian Networks for Student Modeling
Kerkrade, The Netherlands July 05-July 07
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICALT.2006.323Sixth IEEE International Conference o ...
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Abderrahim Danine, University of Quebec at Montreal, Canada
Bernard Lefebvre, University of Quebec at Montreal, Canada
Andre Mayers, University of Sherbrooke, Canada
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.
Citation:
Abderrahim Danine, Bernard Lefebvre, Andre Mayers, "TIDES - Using Bayesian Networks for Student Modeling," icalt, pp.1002-1007, Sixth IEEE International Conference on Advanced Learning Technologies (ICALT'06), 2006
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