Identifying student online discussions with unanswered questions

Jihie Kim, Jia Li, Taehwan Kim

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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.

Original languageEnglish
Title of host publicationK-CAP'09 - Proceedings of the 5th International Conference on Knowledge Capture
Pages195-196
Number of pages2
DOIs
StatePublished - 2009
Event5th International Conference on Knowledge Capture, K-CAP'09 - Redondo Beach, CA, United States
Duration: 1 Sep 20094 Sep 2009

Publication series

NameK-CAP'09 - Proceedings of the 5th International Conference on Knowledge Capture

Conference

Conference5th International Conference on Knowledge Capture, K-CAP'09
Country/TerritoryUnited States
CityRedondo Beach, CA
Period1/09/094/09/09

Keywords

  • Algorithms
  • H.3.1 content analysis and indexing
  • H.4 information systems applications I.2.7: natural language processing
  • Human factors
  • Languages

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