Using Clustering Technique for Students' Grouping in Intelligent E-Learning Systems

In the paper, application of cluster analysis for students' grouping in intelligent e-learning systems is considered. It is proposed the system architecture, in which teaching paths as well as proper layouts are adjusted to groups of students according to their learning styles and usability preferences. Considered student models are built on the basis of Felder and Silverman model, together with student color choices. It is considered usage of two versions of two-phase hierarchical clustering algorithm for students' grouping. Experimental results for both of the approaches are compared and discussed.

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