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AIED
2007
Springer

Profiling Student Interactions in Threaded Discussions with Speech Act Classifiers

8 years 11 months ago
Profiling Student Interactions in Threaded Discussions with Speech Act Classifiers
On-line discussion is a popular form of web-based computer-mediated communication and is an important medium for distance education. Automatic tools for analyzing online discussions are highly desirable for better information management and assistance. This paper presents an approach for automatically profiling student interactions in on-line discussions. Using N-gram features and linear SVM, we developed “speech act” classifiers that identify the roles that individual messages play. The classifiers were used in finding messages that contain questions or answers. We then applied a set of thread analysis rules for identifying threads that may have unanswered questions and need instructor attention. We evaluated the results with three human annotators, and 70-75% of the predictions from the system were consistent with human answers.
Sujith Ravi, Jihie Kim
Added 07 Jun 2010
Updated 07 Jun 2010
Type Conference
Year 2007
Where AIED
Authors Sujith Ravi, Jihie Kim
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