Homogeneous group formation in collaborative learning using fuzzy C-means

One of the issues in collaborative learning is forming groups based on criteria that have been determined before such as grades, learning style, free time, and others. Computer-Supported Group Formation (CSGF) is a research field which purpose is to automate this process so group formation can be done efficiently and effectively. This paper discusses a research on CSGF to form homogeneous groups using a Fuzzy C-Means Clustering method. The parameter used is learning styles according to Felder-Silverman model. The goal of the clustering is that all students can be grouped, without orphan students, the learning styles of learners among all members in each formed cluster are as similar as possible. The proposed method has been applied in two classes of 42 and 39 undergraduate students. The results show that the clustering goals can be achieved.