1
Department of Languages and Translation, The Applied College, Northern Border University, KSA
(mrs.aseel@gmail.com)
2
Faculty of Engineering and IT, The British University in Dubai, Dubai, UAE
(.........)
3
Faculty of Business and Law, The British University in Dubai, UAE
(21002516@student.buid.ac.ae)
4
Department of Languages and Translation, The Applied College, Northern Border University, KSA
( sakurarose31@gmail.com)
5
Faculty of Art, Computing and Creative Industries, Universiti Pendidikan Sultan Idris, Malaysia
(raghad.alfaisal81@gmail.com; dodo.44844@gmail.com)
6
Faculty of Arts, Department of English Language and Literature, Yarmouk University, Irbid, Jordan
(dodo.44844@gmail.com)
Abstract :
Studies on the acceptance of social media apps are being conducted at an increasing rate. The factors influencing its popularity for learning reasons are still not well understood, though. The goal of this study is to create a conceptual model that extends the Technology Adoption Model (TAM) to account for perceived playfulness to gauge students' acceptance of social media in learning. A total of 623 authenticated questionnaire surveys were obtained from students enrolled at a reputed university in the United Arab Emirates (UAE). Tools such as partial least squares-structural equation modeling (PLS-SEM) and machine learning approaches were obtained to examine the collected data. According to the research findings, significant parameters of students' intention to use social media networks for education include perceived playfulness, perceived usefulness, and perceived ease of use.
Keywords :
Social media networks; Acceptance; Technology Acceptance Model; PLS-SEM.
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| Style | # |
|---|---|
| MLA | Aseel M. Alfaisal, Aisha Zare, Afrah Alshaafi, Rose Aljanada, Raghad M. Alfaisal, Ghadeer W. Abukhalil. "Predicting the actual use of social media sites among university communicators: using PLS-SEM and ML approaches." International Journal of Advances in Applied Computational Intelligence, Vol. 1, No. 1, 2022 ,PP. 23-33 (Doi : https://doi.org/10.54216/IJAACI.010102) |
| APA | Aseel M. Alfaisal, Aisha Zare, Afrah Alshaafi, Rose Aljanada, Raghad M. Alfaisal, Ghadeer W. Abukhalil. (2022). Predicting the actual use of social media sites among university communicators: using PLS-SEM and ML approaches. Journal of International Journal of Advances in Applied Computational Intelligence, 1 ( 1 ), 23-33 (Doi : https://doi.org/10.54216/IJAACI.010102) |
| Chicago | Aseel M. Alfaisal, Aisha Zare, Afrah Alshaafi, Rose Aljanada, Raghad M. Alfaisal, Ghadeer W. Abukhalil. "Predicting the actual use of social media sites among university communicators: using PLS-SEM and ML approaches." Journal of International Journal of Advances in Applied Computational Intelligence, 1 no. 1 (2022): 23-33 (Doi : https://doi.org/10.54216/IJAACI.010102) |
| Harvard | Aseel M. Alfaisal, Aisha Zare, Afrah Alshaafi, Rose Aljanada, Raghad M. Alfaisal, Ghadeer W. Abukhalil. (2022). Predicting the actual use of social media sites among university communicators: using PLS-SEM and ML approaches. Journal of International Journal of Advances in Applied Computational Intelligence, 1 ( 1 ), 23-33 (Doi : https://doi.org/10.54216/IJAACI.010102) |
| Vancouver | Aseel M. Alfaisal, Aisha Zare, Afrah Alshaafi, Rose Aljanada, Raghad M. Alfaisal, Ghadeer W. Abukhalil. Predicting the actual use of social media sites among university communicators: using PLS-SEM and ML approaches. Journal of International Journal of Advances in Applied Computational Intelligence, (2022); 1 ( 1 ): 23-33 (Doi : https://doi.org/10.54216/IJAACI.010102) |
| IEEE | Aseel M. Alfaisal, Aisha Zare, Afrah Alshaafi, Rose Aljanada, Raghad M. Alfaisal, Ghadeer W. Abukhalil, Predicting the actual use of social media sites among university communicators: using PLS-SEM and ML approaches, Journal of International Journal of Advances in Applied Computational Intelligence, Vol. 1 , No. 1 , (2022) : 23-33 (Doi : https://doi.org/10.54216/IJAACI.010102) |