Influencing factors in MOOCs adoption in higher education: a meta-analytic path analysis
(1) Background: Due to the rapid growth of Massive Online Open Courses (MOOCs), higher educational institutions across the world are investing heavily in MOOCs to support their traditional teaching, their students’ learning experience, and their performance. However, the success of MOOCs highly depe...
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| Формат: | Статья |
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Multidisciplinary Digital Publishing Institute
2022
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| _version_ | 1825938612675411968 |
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| author | Zaremohzzabieh, Zeinab Roslan, Samsilah Mohamad, Zulkifli Ismail, Ismi Arif Ab Jalil, Habibah Ahrari, Seyedali |
| author_facet | Zaremohzzabieh, Zeinab Roslan, Samsilah Mohamad, Zulkifli Ismail, Ismi Arif Ab Jalil, Habibah Ahrari, Seyedali |
| author_sort | Zaremohzzabieh, Zeinab |
| collection | UPM |
| description | (1) Background: Due to the rapid growth of Massive Online Open Courses (MOOCs), higher educational institutions across the world are investing heavily in MOOCs to support their traditional teaching, their students’ learning experience, and their performance. However, the success of MOOCs highly depends on several factors that influence their success in higher education. Prior studies have attempted to investigate and predict user acceptance of MOOCs in higher education by using a variety of theoretical viewpoints. Nonetheless, these studies have yielded conflicting findings and are inconclusive. (2) Purpose: This study aims to develop a model that integrates the Theory of Planned Behavior (TPB), the Unified Theory of Acceptance and Use of Technology (UTAUT), as well as the Task-Technology Fit (TTF) to explore the factors that influence the acceptance and use of MOOCs in higher education institutions, while synthesizing previous empirical findings in the field. (3) Methods: The model was tested using Meta-analytic Structural Equation Modelling (MASEM) based on the data gathered from 43 studies (k = 45 samples, n = 16,774). (4) Results: Effort expectancy (EE), attitude (ATT), performance expectancy (PE), and TTF—determined by several task and technology characteristics—were identified as the direct predictors of behavioral intention (BI) to continue using MOOCs. (5) Conclusions: This model provides a cohesive view of MOOCs’ acceptance in higher educational institutions, and it helps to identify potential research opportunities in this area. (6) Implications: Results from MASEM offer managerial guidance for the effective implementation of MOOCs and provide directions for further research, to augment current knowledge of MOOCs’ adoption, by higher education institutions. |
| first_indexed | 2024-03-06T11:16:12Z |
| format | Article |
| id | upm.eprints-101915 |
| institution | Universiti Putra Malaysia |
| last_indexed | 2024-03-06T11:16:12Z |
| publishDate | 2022 |
| publisher | Multidisciplinary Digital Publishing Institute |
| record_format | dspace |
| spelling | upm.eprints-1019152023-06-16T20:25:38Z http://psasir.upm.edu.my/id/eprint/101915/ Influencing factors in MOOCs adoption in higher education: a meta-analytic path analysis Zaremohzzabieh, Zeinab Roslan, Samsilah Mohamad, Zulkifli Ismail, Ismi Arif Ab Jalil, Habibah Ahrari, Seyedali (1) Background: Due to the rapid growth of Massive Online Open Courses (MOOCs), higher educational institutions across the world are investing heavily in MOOCs to support their traditional teaching, their students’ learning experience, and their performance. However, the success of MOOCs highly depends on several factors that influence their success in higher education. Prior studies have attempted to investigate and predict user acceptance of MOOCs in higher education by using a variety of theoretical viewpoints. Nonetheless, these studies have yielded conflicting findings and are inconclusive. (2) Purpose: This study aims to develop a model that integrates the Theory of Planned Behavior (TPB), the Unified Theory of Acceptance and Use of Technology (UTAUT), as well as the Task-Technology Fit (TTF) to explore the factors that influence the acceptance and use of MOOCs in higher education institutions, while synthesizing previous empirical findings in the field. (3) Methods: The model was tested using Meta-analytic Structural Equation Modelling (MASEM) based on the data gathered from 43 studies (k = 45 samples, n = 16,774). (4) Results: Effort expectancy (EE), attitude (ATT), performance expectancy (PE), and TTF—determined by several task and technology characteristics—were identified as the direct predictors of behavioral intention (BI) to continue using MOOCs. (5) Conclusions: This model provides a cohesive view of MOOCs’ acceptance in higher educational institutions, and it helps to identify potential research opportunities in this area. (6) Implications: Results from MASEM offer managerial guidance for the effective implementation of MOOCs and provide directions for further research, to augment current knowledge of MOOCs’ adoption, by higher education institutions. Multidisciplinary Digital Publishing Institute 2022-07-06 Article PeerReviewed Zaremohzzabieh, Zeinab and Roslan, Samsilah and Mohamad, Zulkifli and Ismail, Ismi Arif and Ab Jalil, Habibah and Ahrari, Seyedali (2022) Influencing factors in MOOCs adoption in higher education: a meta-analytic path analysis. Sustainability, 14 (14). art. no. 8268. pp. 1-21. ISSN 2071-1050 https://www.mdpi.com/2071-1050/14/14/8268 10.3390/su14148268 |
| spellingShingle | Zaremohzzabieh, Zeinab Roslan, Samsilah Mohamad, Zulkifli Ismail, Ismi Arif Ab Jalil, Habibah Ahrari, Seyedali Influencing factors in MOOCs adoption in higher education: a meta-analytic path analysis |
| title | Influencing factors in MOOCs adoption in higher education: a meta-analytic path analysis |
| title_full | Influencing factors in MOOCs adoption in higher education: a meta-analytic path analysis |
| title_fullStr | Influencing factors in MOOCs adoption in higher education: a meta-analytic path analysis |
| title_full_unstemmed | Influencing factors in MOOCs adoption in higher education: a meta-analytic path analysis |
| title_short | Influencing factors in MOOCs adoption in higher education: a meta-analytic path analysis |
| title_sort | influencing factors in moocs adoption in higher education a meta analytic path analysis |
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