Identifying content-related threads in MOOC discussion forums

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This study investigated the extent to which students asked and instructors answered content-related questions in MOOC discussion forums; subsequently a classification model was built to identify such questions based on extracted linguistic features. Results showed content-related threads were a minority and underaddressed by instructors. However, linguistic modeling was promising in identifying them with high reliability.

Original languageEnglish (US)
Title of host publicationL@S 2015 - 2nd ACM Conference on Learning at Scale
PublisherAssociation for Computing Machinery, Inc
Pages299-303
Number of pages5
ISBN (Electronic)9781450334112
DOIs
StatePublished - Mar 14 2015
Event2nd ACM Conference on Learning at Scale, L@S 2015 - Vancouver, Canada
Duration: Mar 14 2015Mar 18 2015

Publication series

NameL@S 2015 - 2nd ACM Conference on Learning at Scale

Other

Other2nd ACM Conference on Learning at Scale, L@S 2015
CountryCanada
CityVancouver
Period3/14/153/18/15

Keywords

  • Machine learning
  • Massive open online courses
  • Natural language processing
  • Social interaction

ASJC Scopus subject areas

  • Software
  • Education
  • Computer Science Applications
  • Computer Networks and Communications

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  • Cite this

    Cui, Y., & Wise, A. F. (2015). Identifying content-related threads in MOOC discussion forums. In L@S 2015 - 2nd ACM Conference on Learning at Scale (pp. 299-303). (L@S 2015 - 2nd ACM Conference on Learning at Scale). Association for Computing Machinery, Inc. https://doi.org/10.1145/2724660.2728679