Does Social Presence Play a Role in Learners’ Positions in MOOC Learner Network? A Machine Learning Approach to Analyze Social Presence in Discussion Forums

Wenting Zou, Zilong Pan, Chenglu Li, Min Liu

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

5 Scopus citations

Abstract

Low engagement has been a longstanding problem in MOOCs. How- ever, engagement is crucial in social learning contexts. To further understand learners’ engagement in MOOC discussion forum, this study focuses on the perspective of social presence, an important factor that mediates learners’ positions within a learning network. To tackle the challenge of analyzing large amounts of text data, we built and tested a machine learning model to automatically classify the student-generated posts into different categories of social presence. We then measured learners’ position in the learner network using social networking analysis (SNA) parameters (namely in-degree, closeness and betweenness centrality). Correlation tests showed that certain types of social presence have strong positive correlations with learners’ network parameters. We also divided learners into groups based on their network positions to examine the differences of social presence demonstrated across different groups. The findings will inform MOOC learners to strategically present themselves in the discussion forum in order to increase the possibilities of peer interaction and cognitive engagement.

Original languageEnglish (US)
Title of host publicationAdvances in Quantitative Ethnography - Second International Conference, ICQE 2020, Proceedings
EditorsAndrew R. Ruis, Seung B. Lee
PublisherSpringer Science and Business Media Deutschland GmbH
Pages248-264
Number of pages17
ISBN (Print)9783030677879
DOIs
StatePublished - 2021
Event2nd International Conference on Quantitative Ethnography, ICQE 2020 - Malibu, United States
Duration: Feb 1 2021Feb 3 2021

Publication series

NameCommunications in Computer and Information Science
Volume1312
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937

Conference

Conference2nd International Conference on Quantitative Ethnography, ICQE 2020
Country/TerritoryUnited States
CityMalibu
Period2/1/212/3/21

All Science Journal Classification (ASJC) codes

  • General Computer Science
  • General Mathematics

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