An analysis of cognitive learning context in MOOC forum messages

Jian Syuan Wong, Bart Pursel, Anna Divinsky, Bernard Jansen

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

3 Citations (Scopus)

Abstract

In this research, we analyze a large number of discussions of forum messages from three MOOC courses using a keyword taxonomy approach to identify learning processes occurring among the students. We conduct analysis on more than 100,000 forum messages from 14,647 forum threads from three MOOCs, with a combined 200,000+ enrollment. We map messages to six levels of Bloom's Taxonomy for cognitive learning. The results of this research indicate that learning processes of particular cognitive learning levels could be observed within discussions on MOOC forums. Results imply that different types of forum communications have features associated to particular learning levels, and the volume of higher levels of cognitive learning domains increase as the course progresses.

Original languageEnglish
Title of host publicationCHI EA 2016: #chi4good - Extended Abstracts, 34th Annual CHI Conference on Human Factors in Computing Systems
PublisherAssociation for Computing Machinery
Pages1315-1321
Number of pages7
Volume07-12-May-2016
ISBN (Electronic)9781450340823
DOIs
Publication statusPublished - 7 May 2016
Event34th Annual CHI Conference on Human Factors in Computing Systems, CHI EA 2016 - San Jose, United States
Duration: 7 May 201612 May 2016

Other

Other34th Annual CHI Conference on Human Factors in Computing Systems, CHI EA 2016
CountryUnited States
CitySan Jose
Period7/5/1612/5/16

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Keywords

  • Cognitive learning
  • E-learning
  • MOOC

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Graphics and Computer-Aided Design
  • Software

Cite this

Wong, J. S., Pursel, B., Divinsky, A., & Jansen, B. (2016). An analysis of cognitive learning context in MOOC forum messages. In CHI EA 2016: #chi4good - Extended Abstracts, 34th Annual CHI Conference on Human Factors in Computing Systems (Vol. 07-12-May-2016, pp. 1315-1321). Association for Computing Machinery. https://doi.org/10.1145/2851581.2892324