Unified Mooc utilization model (Umum) for exploring computer-supported learning with educational technology in terms of Mooc utilization in higher education
Bibliographic Data
| ID | 21631478 |
|---|---|
| Authors | Maimoona Salam (0000-0001-7102-274X, University of Engineering and Technology), Muhammad Shoaib Farooq (0000-0003-3263-2646, University of Engineering and Technology, corresponding author), Mohsin Shahzad (0000-0002-2101-8619, Liaoning Normal University), Azhar Ali (0000-0002-5750-6761, Dalian University of Technology), Saif ur Rehman (0000-0001-8371-4911, University of Management and Technology) |
| Year | 2026 |
| Volume | 34 |
| Issue | 3 |
| Pages | 1802-1838 |
| Publication date | 2026-03-16 |
| Peer Reviewed | Yes |
| 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 | 10.1080/10494820.2025.2530631 |
| OpenAlex | W4412878191 |
| Language | EN |
| Citations received | 1 |
| References cited | 67 |
By integrating the two theoretical strands of DeLone & McLean’s IS success model and fit-related constructs of task technology fit model this study puts forward the unified MOOC utilization model (UMUM). The proposed UMUM model also comprises quality and fit variables to explain the students’ intention to re-use MOOCs. Further, UMUM model proposed that the intention to re-use MOOCs ultimately maximizes MOOC’s overall utilization. The UMUM research model was empirically validated by employing the PLS-SEM approach, using data collected from 370 students registered in a MOOC based study program. Findings confirmed that the proposed quality-related factors of the UMUM model (i.e. system, information, service, and ELIQ) and task characteristics positively influence fit factors. Likewise, the association between users’ self-reported satisfaction with MOOC and their intention to re-use it is also positive and significant. Finally, intention to re-use, task-technology fit (i.e. fulfilling the technical expectations of users for their learning tasks), and task-service fit in the UMUM model positively influence and predict overall MOOC utilization. Future studies concerning MOOCs and educational technology can employ the UMUM model for the assessment of MOOC utilization and students’ intention to re-use MOOCs
Educational technology · Higher education · Mathematics education · Multimedia · Political science · Computer Science · Online and Blended Learning · Online Learning and Analytics · Psychology · Technology-Enhanced Education Studies
Modern factor analysis
Lower bounds on sample size in structural equation modeling
Task-Technology Fit and Individual Performance
Minimum sample size estimation in PLS‐SEM
Continuance intention to use Moocs
Information Systems Success
Gain more insight from your PLS-SEM results
Progress in partial least squares structural equation modeling use in marketing research in the last decade
Common Method Bias
Common methods variance detection in business research
Common method biases in behavioral research
Evaluating Structural Equation Models with Unobservable Variables and Measurement Error
Sources of Method Bias in Social Science Research and Recommendations on How to Control It
Common Method Bias in PLS-SEM
The measurement and characteristic analysis of learner interaction levels in cMoocs based on path analysis
The effects of the expectation confirmation model (ECM) and the technology acceptance model (TAM) on learning management systems (LMS) in sub-saharan Africa
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Assessment of digital skills of university Mooc instructors
The evolution of language Moocs in Mainland China
How do learners’ content network characteristics evolve in cMooc from the perspective of clustering and comparing learners
How do learners participate in interaction in different types of discussion topics and learning tools of cMoocs
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Assessing the factors affecting users’ behavioural intention to use Moocs
Enhancing student engagement and higher-order thinking in human-centred design projects
Early prediction of Mooc dropout in self-paced students using deep learning
Effects of sentiment discreteness on Moocs’ disconfirmation
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Service learning in higher education
Travel web-site design
| Unique citing works | 1 |
|---|---|
| Citations per year | 1 |
| Citation span | 2026 - 2026 (1) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 1 |