Weibelzahl, S., & Weber, G. (2003). Evaluating the Inference Mechanism of Adaptive Learning Systems. In Brusilovsky, P., Corbett, A. & de Rosis, F. (Eds.), User Modeling: Proceedings of the Ninth International Conference, Lecture Notes in Artificial Intelligence LNAI 2702 (© Springer-Verlag) (pp. 154-168). Berlin: Springer.

DOI: 10.1007/3-540-44963-9_21

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.

author = {Stephan Weibelzahl and Gerhard Weber},
title = {Evaluating the Inference Mechanism of Adaptive Learning Systems},
booktitle = {User {M}odeling. {P}roceedings of the {N}inth {I}nternational {C}onference, {UM2003}},
publisher = {Springer},
editor = {Peter Brusilovsky and Albert Corbett and Fiorella {de Rosis}},
address = {Berlin},
pages = {154--168},
year = {2003},
doi = {10.1007/3-540-44963-9\_21}