A social network analysis of online engagement for college students traditionally underrepresented in STEM

Destiny Williams-Dobosz, Renato Ferreira Leitão Azevedo, Amos Jeng, Vyom Thakkar, Suma Bhat, Nigel Bosch, Michelle Perry

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

Abstract

Little is known about the online learning behaviors of students traditionally underrepresented in STEM fields (i.e., UR-STEM students), as well as how those behaviors impact important learning outcomes. The present study examined the relationship between online discussion forum engagement and success for UR-STEM and non-UR-STEM students, using the Community of Inquiry (CoI) model as our theoretical framework. Social network analysis and nested regression models were used to explore how three different measures of forum engagement - 1) total number of posts written, 2) number of help-seeking posts written and replied to, and 3) level of connectivity - were related to improvement (i.e., relative performance gains) for 70 undergraduate students enrolled in an online introductory STEM course. We found a significant positive relationship between help-seeking and improvement and nonsignificant effects of general posting and connectivity; these results held for UR-STEM and non-UR-STEM students alike. Our findings suggest that online help-seeking has benefits for course improvement beyond what can be predicted by posting alone and that one need not be well connected in a class network to achieve positive learning outcomes. Finally, UR-STEM students demonstrated greater grade improvement than their non-UR-STEM counterparts, which suggests that the online environment has the potential to combat barriers to success that disproportionately affect underrepresented students.

Original languageEnglish (US)
Title of host publicationLAK 2021 Conference Proceedings - The Impact we Make
Subtitle of host publicationThe Contributions of Learning Analytics to Learning, 11th International Conference on Learning Analytics and Knowledge
PublisherAssociation for Computing Machinery
Pages207-215
Number of pages9
ISBN (Electronic)9781450389358
DOIs
StatePublished - Apr 12 2021
Event11th International Conference on Learning Analytics and Knowledge: The Impact we Make: The Contributions of Learning Analytics to Learning, LAK 2021 - Virtual, Online, United States
Duration: Apr 12 2021Apr 16 2021

Publication series

NameACM International Conference Proceeding Series

Conference

Conference11th International Conference on Learning Analytics and Knowledge: The Impact we Make: The Contributions of Learning Analytics to Learning, LAK 2021
Country/TerritoryUnited States
CityVirtual, Online
Period4/12/214/16/21

Keywords

  • Help-seeking
  • Online discussion forums
  • Social network connectivity
  • Underrepresentation in STEM

ASJC Scopus subject areas

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

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