Abstract
Groups of learners of similar features are often created in order to diversify the environment accordingly. However student preferences may differ depending on the context of the system usage. Each new student, who intends to join the community, should obtain context-aware recommendation of the group of colleagues matching his needs. In the paper, using fuzzy logic for modeling student groups is considered. We propose to build the possibility-based representation of each group. We assume that context can be modeled by a vector of weights. Then recommendations for new students are determined taking into account a degree of possibility of matching together with the respective context parameters. We examine the presented approach by taking into account learning style dimensions as attributes which characterize student preferences. The method is evaluated on the basis of experimental results obtained for data of different groups of real students.
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Myszkorowski, K., Zakrzewska, D. (2014). Building Contextual Student Group Recommendations with Fuzzy Logic. In: Cornelis, C., Kryszkiewicz, M., Ślȩzak, D., Ruiz, E.M., Bello, R., Shang, L. (eds) Rough Sets and Current Trends in Computing. RSCTC 2014. Lecture Notes in Computer Science(), vol 8536. Springer, Cham. https://doi.org/10.1007/978-3-319-08644-6_37
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DOI: https://doi.org/10.1007/978-3-319-08644-6_37
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