Fuzzy logic based modeling for building contextual student group recommendations

Abstract

Group learning plays an important role in Web based educational process. Groups of students who are to learn together should be characterized by similar features. However course needs 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 preferences. In the paper, using fuzzy logic for modeling students and groups is considered. We propose to describe student characteristics by means of fuzzy sets and to use the possibility-based representation of each group. We assume that context is represented by a vector of weights. Then recommendations for new students are determined by applying pattern matching technique including respective context vector. 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 real student data.