Abstract
The evaluation of user modeling systems is an important though often neglected area. Evaluating the inference of user properties can help to identify failures in the user model. In this paper we propose two methods to assess the accuracy of the user model. The assumptions about the user might either be compared to an external test, or might be used to predict the users’ behavior. Two studies with five adaptive learning courses demonstrate the usefulness of the approach.
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Weibelzahl, S., Weber, G. (2003). Evaluating the Inference Mechanism of Adaptive Learning Systems. In: Brusilovsky, P., Corbett, A., de Rosis, F. (eds) User Modeling 2003. UM 2003. Lecture Notes in Computer Science(), vol 2702. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44963-9_21
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DOI: https://doi.org/10.1007/3-540-44963-9_21
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