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Mapping the MOOC research landscape: insights from empirical studies

Costello, Eamon orcid logoORCID: 0000-0002-2775-6006, Soverino, Tiziana and Bolger, Richard (2022) Mapping the MOOC research landscape: insights from empirical studies. International Journal of Emerging Technologies in Learning, 17 (14). pp. 4-19. ISSN 1868-8799

—Several reviews have been conducted of empirical studies of MOOC learners and teachers. The scope and foci of such reviews has varied, as has the reporting of the details of how they were conducted. This study analysed 1,435 published articles, determining 922 to be empirical studies. We analysed the full text of 826 of these articles to which the research team had access using the scientometric tool SciVal, manual researcher evaluation and topic modelling to determine: the impact as measured by citations; geographic and institutional publishing patterns; and the themes and types of MOOC research. We found that MOOC research is mostly clustered in the discipline of computer science. Learner persistence and self-regulated learning continue to be a focus of study and most impactful finding respectively as studies of previous periods have found. Research is carried out worldwide, with the most influential studies and researchers clustered in particular institutions and countries. Implications of this study are that MOOC research is clustered in certain ways which may give rise to particular biases, that researchers should consider more interdisciplinary approaches in their research and greater awareness and use of open science principles and practices in their work
Item Type:Article (Published)
Uncontrolled Keywords:MOOCs; Self-regulated learning; topic modeling; scienometrics; online learning; trends
Subjects:Social Sciences > Distance education
DCU Faculties and Centres:DCU Faculties and Schools > NIDL (National Institute for Digital Learning)
Publisher:Kassel University Press/
Official URL:https://dx.doi.org/10.3991/ijet.v17i14.28721
Copyright Information:© 2021 The Authors.
Funders:The Open Education Unit of the National Institute for Digital Learning for funding for open access.
ID Code:27394
Deposited On:26 Jul 2022 12:33 by Thomas Murtagh . Last Modified 14 Mar 2023 15:05

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