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Homogeneous group formation in collaborative learning using fuzzy C-means

机译:使用模糊C均值的协作学习中的同质组形成

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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:协作学习中的问题之一是根据之前确定的标准(例如成绩,学习方式,空闲时间等)组成小组。计算机支持的组形成(CSGF)是一个研究领域,其目的是使此过程自动化,以便可以高效地完成组形成。本文讨论了使用模糊C均值聚类方法对CSGF形成齐次基团的研究。使用的参数是根据Felder-Silverman模型的学习风格。聚类的目的是可以对所有学生进行分组,而没有孤儿,在每个形成的聚类中,所有成员之间的学习者学习风格应尽可能相似。所提出的方法已应用于42名和39名本科生的两个班级。结果表明,可以实现聚类目标。

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