The DOI matches its Crossref record; 43 of the 43 references it cites were found in a registry or an index.
Applying the UTAUT Model to Explain the Students’ Acceptance of Mobile Learning System in Higher Education
Open accessAbstract
Mobile learning applications have been growing in demand and popularity and have become a common phenomenon in modern educational systems, especially with the implementation of mobile learning projects. This study applies the Unified Theory of Acceptance and Use Technology (UTAUT) model to examine the effects of different factors that were identified from the literature on students' acceptance of mobile learning applications in higher education. The data was collected from a 697 university students responded to an online questionnaire. SEM method was used for data analysis. The results showed that perceived information quality, perceived compatibility, perceived trust, perceived awareness, and availability of resources, self-efficacy, and perceived security are the main motivators of students' acceptance of mobile learning system, and consequently success the implementation of mobile learning projects. Results from this study provide the necessary information as to how higher education institutions can enhance students' acceptance of mobile learning system in order to support the usage of mobile technologies in learning and teaching process. These results offer important implications for mobile learning acceptance and usage.
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1 retracted
Almaiah, M. A. (2018) · Education and Information Technologies · doi:10.1007/s10639-018-9694-6 · Cited by 108
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User Acceptance of Information Technology: Toward A Unified View1
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User Acceptance of Computer Technology: A Comparison of Two Theoretical Models
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Cited by
Almaiah, M. A., Al-Khasawneh, A., & Althunibat, A. (2020) · Education and Information Technologies · doi:10.1007/s10639-020-10219-y · Cited by 1,205
Self-citationStrzelecki, A., & ElArabawy, S. (2024) · British Journal of Educational Technology · doi:10.1111/bjet.13425 · Cited by 260
Generative artificial intelligence acceptance scale: A validity and reliability study
Yilmaz, F. G. K., Yilmaz, R., & Ceylan, M. (2024) · International Journal of Human–Computer Interaction · doi:10.1080/10447318.2023.2288730 · Cited by 244
Students’ acceptance of online learning in developing nations: scale development and validation
Rajeb, M., Wang, Y., Man, K., & Morett, L. M. (2023) · Educational technology research and development · doi:10.1007/s11423-022-10165-1 · Cited by 20
Metadata
- Authors
- Almaiah, M. A., Alamri, M. M., & Al-Rahmi, W.
- Venue
- IEEE Access
- Published
- 2019
- Volume
- 7
- Pages
- 174673-174686
- ISSN
- 2169-3536 (ISSN-L)
- OpenAlex
- W2993371666
- Cited by
- 348
- References
- 43
- FWCI
- 44.36
- Type
- journal article
- Language
- en
- Open access
- gold
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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