Identifying unresolved issues in online student discussions: A multi-phase dialogue classification approach

Jihie Kim, Taehwan Kim, Jia Li

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

Abstract

Automatic tools for analyzing student online discussions are highly desirable for providing better assistance and encouraging participation. This paper presents an approach for automatically identifying student discussions with unresolved issues or unanswered questions. We 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, answer, issue raising, or acknowledgement. We then use the resulting speech acts as features for identifying discussion threads with unresolved issues or questions. We performed a preliminary analysis of the classifiers and achieved an average accuracy of 78%.

Original languageEnglish
Title of host publicationFrontiers in Artificial Intelligence and Applications
PublisherIOS Press
Pages704-706
Number of pages3
Edition1
ISBN (Print)9781607500285
DOIs
StatePublished - 2009

Publication series

NameFrontiers in Artificial Intelligence and Applications
Number1
Volume200
ISSN (Print)0922-6389
ISSN (Electronic)1879-8314

Keywords

  • Discussion assessment
  • On-line discussion board
  • Speech acts

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