Abstract
In this paper, we present an approach to hierarchical knowledge representation for the student’s evaluation in propositional logic. The hierarchical evaluation consists in assessing the student’s state of knowledge at several levels of granularity. The relevance of the method is justified by the need for a precise and flexible diagnosis of the learner’s skills in a given domain. For that purpose, we shall model the propagation of the evaluation from a specific level of knowledge content to more general levels, using Bayesian inferences and neural networks classifications.
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Tchétagni, J.M.P., Nkambou, R. (2002). Hierarchical Representation and Evaluation of the Student in an Intelligent Tutoring System. In: Cerri, S.A., Gouardères, G., Paraguaçu, F. (eds) Intelligent Tutoring Systems. ITS 2002. Lecture Notes in Computer Science, vol 2363. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-47987-2_71
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DOI: https://doi.org/10.1007/3-540-47987-2_71
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