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Analyzing Learning Sentiments on a MOOC Discussion Forum through Epistemic Network Analysis

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Title: Analyzing Learning Sentiments on a MOOC Discussion Forum through Epistemic Network Analysis
Language: English
Authors: Jianhui Yu
Source: International Review of Research in Open and Distributed Learning. 2025 26(1):197-215.
Availability: Athabasca University Press. 1200, 10011-109 Street, Edmonton, AB T5J 3S8, Canada. Tel: 780-497-3412; Fax: 780-421-3298; e-mail: irrodl@athabascau.ca; Web site: http://www.irrodl.org
Peer Reviewed: Y
Page Count: 19
Publication Date: 2025
Document Type: Journal Articles
Reports - Research
Descriptors: MOOCs, Student Attitudes, Group Discussion, Computer Mediated Communication, Correlation, Instructional Effectiveness, Network Analysis, Academic Achievement, Learner Engagement, Psychological Patterns, Student Experience, Intervention, Teaching Methods, Comparative Analysis, Cognitive Mapping
ISSN: 1492-3831
Abstract: Sentiments expressed on massive open online course (MOOC) discussion forums significantly influence learning effectiveness and academic performance. The evolution of learning sentiments on MOOC discussion forums is a dynamic process; however, a gap exists in the current understanding of the interplay between evolving sentiments and their impact on MOOC efficacy. Consequently, to enhance MOOC effectiveness further empirical research is needed to uncover the underlying patterns and temporal dynamics of learning sentiments. This study collected online discussions from 158 MOOC participants and examined the discussions using epistemic network analysis to identify how learning sentiment patterns differed according to performance level and learning topics. The results showed that learning sentiment patterns were affected by both performance level and learning topics, with participants in the high-score group exhibiting stronger associations between engagement-neutral and neutral-frustration, and fewer connections between frustration-delight and frustration-boredom when compared to those in the low-score group. In addition, this study found that engagement was strongly linked to all learning topics in the high-score group, whereas for the low-score group, only engagement and experience showed strong connections. Based on these findings, we discuss the implications for learners and instructors in paving the way for the development of targeted interventions and instructional strategies tailored to optimize MOOC effectiveness.
Abstractor: As Provided
Entry Date: 2025
Accession Number: EJ1463804
Database: ERIC
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  Data: Analyzing Learning Sentiments on a MOOC Discussion Forum through Epistemic Network Analysis
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  Data: Athabasca University Press. 1200, 10011-109 Street, Edmonton, AB T5J 3S8, Canada. Tel: 780-497-3412; Fax: 780-421-3298; e-mail: irrodl@athabascau.ca; Web site: http://www.irrodl.org
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  Data: Sentiments expressed on massive open online course (MOOC) discussion forums significantly influence learning effectiveness and academic performance. The evolution of learning sentiments on MOOC discussion forums is a dynamic process; however, a gap exists in the current understanding of the interplay between evolving sentiments and their impact on MOOC efficacy. Consequently, to enhance MOOC effectiveness further empirical research is needed to uncover the underlying patterns and temporal dynamics of learning sentiments. This study collected online discussions from 158 MOOC participants and examined the discussions using epistemic network analysis to identify how learning sentiment patterns differed according to performance level and learning topics. The results showed that learning sentiment patterns were affected by both performance level and learning topics, with participants in the high-score group exhibiting stronger associations between engagement-neutral and neutral-frustration, and fewer connections between frustration-delight and frustration-boredom when compared to those in the low-score group. In addition, this study found that engagement was strongly linked to all learning topics in the high-score group, whereas for the low-score group, only engagement and experience showed strong connections. Based on these findings, we discuss the implications for learners and instructors in paving the way for the development of targeted interventions and instructional strategies tailored to optimize MOOC effectiveness.
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      – Text: English
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      Pagination:
        PageCount: 19
        StartPage: 197
    Subjects:
      – SubjectFull: MOOCs
        Type: general
      – SubjectFull: Student Attitudes
        Type: general
      – SubjectFull: Group Discussion
        Type: general
      – SubjectFull: Computer Mediated Communication
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      – SubjectFull: Correlation
        Type: general
      – SubjectFull: Instructional Effectiveness
        Type: general
      – SubjectFull: Network Analysis
        Type: general
      – SubjectFull: Academic Achievement
        Type: general
      – SubjectFull: Learner Engagement
        Type: general
      – SubjectFull: Psychological Patterns
        Type: general
      – SubjectFull: Student Experience
        Type: general
      – SubjectFull: Intervention
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      – SubjectFull: Teaching Methods
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      – SubjectFull: Comparative Analysis
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      – SubjectFull: Cognitive Mapping
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              Y: 2025
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