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International Educational Data Mining Society, Paper presented at the International Conference on Educational Data Mining (EDM) (8th, Madrid, Spain, Jun 26-29, 2015)

While MOOCs undoubtedly provide valuable learning resources for students, little research in the MOOC context has sought to evaluate students' learning gains in the environment. It has been long acknowledged that conversation is a significant way for students to construct knowledge and learn. However, rather than studying learning in MOOC discussion forums, the thrust of current research in that context has been to identify factors that predict dropout. Thus, cognitively relevant student behavior in the forums has not been evaluated for its impact on cognitive processes and learning. In this paper, we adopt a content analysis approach to analyze students' cognitively relevant behaviors in a MOOC discussion forum and further explore the relationship between the quantity and quality of that participation with their learning gains. As an integral part of our approach, we built a computational model to automate the analysis so that it is possible to extend the content analysis to all communication that occurred in the MOOC. We identified significant associations between discourse behavior and learning. Theoretical and practical implications are discussed. [For complete proceedings, see ED560503.]

Descriptors: Online Courses, Discussion Groups, Student Behavior, Cognitive Processes, Achievement Gains, Learning, Content Analysis, Student Participation, Automation, Computation, Pretesting

International Educational Data Mining Society. e-mail: admin[at]; Web site:

Autor: Wang, Xu; Yang, Diyi; Wen, Miaomiao; Koedinger, Kenneth; Rosé, Carolyn P.


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