Honing in on social learning networks in MOOC forums: Examining critical network definition decisions

Alyssa Friend Wise, Yi Cui, Wan Qi Jin

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

Abstract

This study examines the impact of content-based network partitioning and tie definition on social network structures and interpretation for MOOC discussion forums. Using dynamic interrelated post and thread categorization [5] based on a previously developed natural language model [27], 817 threads containing 3124 discussion posts from 567 learners in a MOOC on the use of statistics in medicine were characterized as either related to the learning of course content or not. Content-related, non-content, and unpartitioned interaction networks were constructed based on five different tie definitions: Direct Reply, Star, Direct Reply+Star, Limited Copresence, and Total Copresence. Results showed content-related and non-content networks to have distinct characteristics at the network, community, and individual node levels, validating the usefulness of the content/non-content distinction as an analytic tool. Network properties were less sensitive to differences in tie definition with the exception of Total Copresence, which showed distinct characteristics presenting dangers for general use, but usefulness for detecting inflated social status due to "superthread" initiation. Canada.

Original languageEnglish (US)
Title of host publicationLAK 2017 Conference Proceedings - 7th International Learning Analytics and Knowledge Conference
Subtitle of host publicationUnderstanding, Informing and Improving Learning with Data
PublisherAssociation for Computing Machinery
Pages383-392
Number of pages10
ISBN (Electronic)9781450348706
DOIs
StatePublished - Mar 13 2017
Event7th International Conference on Learning Analytics and Knowledge, LAK 2017 - Vancouver, Canada
Duration: Mar 13 2017Mar 17 2017

Publication series

NameACM International Conference Proceeding Series

Other

Other7th International Conference on Learning Analytics and Knowledge, LAK 2017
CountryCanada
CityVancouver
Period3/13/173/17/17

Keywords

  • Discussion forum
  • Massive open online courses
  • Network partitioning
  • Social network analysis
  • Tie extraction

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

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