Identifying student online discussions with unanswered questions

Authors:
Jihie Kim;Jia Li;Taehwan Kim
Affiliations:
USC/Information Sciences Institute, Marina del Rey, CA, USA;USC/Information Sciences Institute, Marina del Rey, CA, USA;USC/Information Sciences Institute, Marina del Rey, CA, USA
Venue:
Proceedings of the fifth international conference on Knowledge capture
Year:
2009

Citing 2
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Abstract

This paper presents an approach for identifying student discussions with unresolved issues or unanswered questions. In order to handle highly incoherent data, we perform several data processing steps. We then apply a two-phase classification algorithm. First, we classify "speech acts" of individual messages to identify the roles that the messages play, such as question, issue raising, and answers. We then use the resulting speech acts as features for classifying discussion threads with unanswered questions or unresolved issues. We performed a preliminary analysis of the classifiers and the system shows an average F score of 0.76 in discussion thread classification.