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Erschienen in:
2015 | OriginalPaper | Buchkapitel
Learning Bayesian Networks for Student Modeling
verfasst von : Eva Millán, Guiomar Jiménez, María-Victoria Belmonte, José-Luis Pérez-de-la-Cruz
Erschienen in: Artificial Intelligence in Education
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In the last decade, there has been a growing interest in using Bayesian Networks (BN) in the student modelling problem. In order to develop a Bayesian Student Model (BSM), it is necessary to define the structure (nodes and links) and the parameters. Usually the structure can be elicited with the help of human experts (teachers), but the difficulty of the problem of parameter specification is widely recognized in this and other domains. In the work presented here we have performed a set of experiments to compare the performance of two Bayesian Student Models, whose parameters have been specified by experts and learnt from data respectively. Results show that both models are able to provide reasonable estimations for knowledge variables in the student model.