| Summary: | 碩士 === 國立暨南國際大學 === 資訊工程學系 === 100 === With the development of Web 2.0 technology, people can easily share information and gain knowledge by collaborating with others using Web 2.0 tools. Social constructivism argues that people construct their knowledge in a social environment, based on which many studies designed web-based learning tools and showed its efficiency for students. However, few studies had devoted to mining students’ behaviors on such collaborative learning system. Therefore, in this research, we designed a cooperative learning system and proposed algorithms of learning behavior mining based on social network analysis, by which teachers or pedagogical researchers can understand more about how learners distribute and acquire knowledge, including the knowledge distribution path and types of a group, and knowledge distribution roles and knowledge construction methods of students. Based on the analysis results, a student evaluation approach was also derived to provide teachers good suggestions for evaluating students’ performances on a collaborative learning platform. Besides, we also proposed a learning recommendation mechanism to achieve more adaptive learning. Experiments were conducted on two college courses. The experiment results, including behavior analysis and user study, showed the feasibility of the proposed methodology of knowledge distribution analysis.
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