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Homogeneous group formation in collaborative learning using fuzzy C-means

机译:使用模糊C-Means的协同学习中均相组形成

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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.
机译:协作学习中的一个问题是基于以前确定的标准形成群体,例如等级,学习风格,空闲时间和其他人。计算机支持的组形成(CSGF)是一个研究领域,目的是自动化该过程,因此可以有效且有效地完成组形成。本文讨论了CSGF使用模糊C型聚类方法形成均匀组的研究。使用的参数是根据Felder-Silverman模型的学习方式。聚类的目标是所有学生都可以分组,没有孤立学生,每个形成的群集中的所有成员之间的学习者的学习方式就像尽可能相似。该拟议的方法已应用于两类42和39名本科生。结果表明,可以实现聚类目标。

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