Effects of sentiment discreteness on Moocs’ disconfirmation
Text analytics in online reviews
Bibliographic Data
| ID | 21631426 |
|---|---|
| Authors | Wei Wang (0000-0001-5806-2368, Huaqiao University), Haiwang Liu (0000-0002-2205-7054, Huaqiao University), Y J Wu (0000-0001-5479-2873, Graduate Institute of Global Business and Strategy, National Taiwan Normal University Taipei, Taiwan, corresponding author) |
| Year | 2025 |
| Volume | 33 |
| Issue | 3 |
| Pages | 2099-2116 |
| Publication date | 2025-03-16 |
| Open Access | No |
| Type | ARTICLE |
| Venue | Interactive Learning Environments (JOURNAL) |
| Journal identifiers | ISSN: 1049-4820 • E-ISSN: 1744-5191 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/10494820.2024.2391050 |
| OpenAlex | W4401718960 |
| Language | EN |
| Citations received | 1 |
| References cited | 33 |
In Massive Open Online Courses (MOOCs), online reviews serve as a basis for teachers to improve their courses. The disconfirmation effect of online reviews, i.e. the inconsistency between the level of attention paid to a course factor and the actual weight of that factor’s influence on learner satisfaction, leads to erroneous judgments by teachers. Based on the two-factor theory of emotion, 4,070 courses and 165,705 online reviews are adopted as a corpus to identify the effect of learner sentiment on the disconfirmation effect. The empirical results show that there is a significant disconfirmation effect for negative reviews, but not for positive ones. A fine-grained analysis on negative sentiment finds that reviews containing more sadness and anger sentiments have a stronger disconfirmation effect. A comparison of course types reveals that the disconfirmation effect is stronger for instrument-based courses than that for knowledge-based and practice-based ones. In addition, negative word-of-mouth weakens the disconfirmation effect of sadness and anger reviews and enhances the disconfirmation effect of positive reviews. Further, learner’s reputation weakens the disconfirmation effect of sadness reviews and enhances the disconfirmation effect of positive and anger reviews
Analytics · Cognitive psychology · Data science · Learning analytics · Multimedia · Online learning · Sentiment analysis · Advanced Text Analysis Techniques · Computer Science · Online Learning and Analytics · Psychology · Sentiment Analysis and Opinion Mining · Artificial Intelligence
Teacher enthusiasm and students’ social-behavioral learning engagement
Negativity Bias, Negativity Dominance, and Contagion
Cognitive, social, and physiological determinants of emotional state.
Does University Ranking Matter? Choosing a University in the Digital Era
Foreign language learning through collaborative writing in knowledge building forums
Mooc student dropout prediction model based on learning behavior features and parameter optimization
The effect of interaction between knowledge map and collaborative learning strategies on teachers’ learning performance and self-efficacy of group learning
Self-regulation of learning and Mooc retention
Automated detection of emotional and cognitive engagement in Mooc discussions to predict learning achievement
Key factors in Mooc pedagogy based on NLP sentiment analysis of learner reviews
What predicts student satisfaction with Moocs
Investigating sense of place of the Las Vegas Strip using online reviews and machine learning approaches
On the Reluctance to Communicate Undesirable Messages (The MUM Effect)
Engagement and desertion in Moocs
| Citations per year | 1 |
|---|---|
| Citation span | 2026 - 2026 (1) |
| Highly cited | No |