Abstract
In this paper we present an integrated theoretical approach for student modelling based on an Adaptive Bayesian Network. A mathematical formalization of the Adaptive Bayesian Network is provided, and new question selection criteria presented. Using this theoretical framework, a tool to assist in the diagnosis process has been implemented. This tool allows the definition of Bayesian Adaptive Tests in an easy way: the only specifications required are a curriculum-based structured domain (together with a set of weights) and a set of questions about the domain (the item pool), which will be internally converted into a Bayesian Network. In this way, we intend to make available this theoretically sound technology to educators, minimizing the knowledge engineering effort required.
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Millán, E., Pérez-de-la-Cruz, J.L., Suárez, E. (2000). Adaptive Bayesian Networks for Multilevel Student Modelling. In: Gauthier, G., Frasson, C., VanLehn, K. (eds) Intelligent Tutoring Systems. ITS 2000. Lecture Notes in Computer Science, vol 1839. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45108-0_57
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DOI: https://doi.org/10.1007/3-540-45108-0_57
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