Mathieu Hibou

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Bayesian networks have been successfully used for student modeling in many systems. In this paper, we address the problem of Bayesian network structure construction and more particularly that of arc orientation. We think that, in the case of cognitive task modeling, the traditional causal interpretation of arc orientation is not adequate. Instead, we use(More)
The modeling of the student cognitive state requires to take into account uncertainty, and during the past decade the use of Bayesian networks has grown as a method for dealing with such a problem. Many different ad-hoc models have been built in user modeling as well as in student modeling, using either expert knowledge elicitation or machine learning(More)
Bayesian Network (BN) are often used for student modelling but some problems remain, particularly the question of the structure of the BN. The key idea of this paper is that the structure of a BN-based Student Model (BNb-SM) depends on the level of expertise of the student. Therefore, a model should be constituted with several concurrent BNs (same nodes,(More)
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