Abstract
Learning scenario determination is one of the key tasks of every Intelligent Learning Systems (ILS). This paper presents a method for learner classification in ILS based on rough classification methods proposed by Pawlak. The goal of rough learner classification is based on the selection of such a minimal set of learner profile attributes and their values that can be used for determination of optimal learning scenario. For this aim the problems of rough classification are defined and their solutions are presented.
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Nguyen, N.T., Sobecki, J. (2005). Rough Classification Used for Learning Scenario Determination in Intelligent Learning System. In: Kłopotek, M.A., Wierzchoń, S.T., Trojanowski, K. (eds) Intelligent Information Processing and Web Mining. Advances in Soft Computing, vol 31. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-32392-9_12
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DOI: https://doi.org/10.1007/3-540-32392-9_12
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25056-2
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