ISSN: 2226-6348
Open access
This study explores the factors influencing higher education students' behavioral intentions to adopt mobile learning (M-learning) at UNITAR International University, Malaysia. Using a cross-sectional approach with 364 respondents, the research examines the relationship between behavioral intention (BI) and four factors: Performance Expectancy (PE), Effort Expectancy (EE), Social Influence (SI), and Facilitating Conditions (FC), based on the Unified Theory of Acceptance and Use of Technology (UTAUT) model. The results reveal significant positive relationships between all four factors and students' BI toward M-learning, suggesting that improving these factors can enhance M-learning adoption. The findings emphasize the need for educational institutions to provide user-friendly platforms, socio-cultural support, and technological resources like high-speed internet. The study contributes to the understanding of M-learning adoption, offering insights for educators, policymakers, and developers to foster a more conducive digital learning environment in higher education.
Abbad, M. M. (2021, May 15). Using the UTAUT model to understand students' usage of e-learning systems in developing countries. Education and information technologies, 26(6), 7205–7224. https://doi.org/10.1007/s10639-021-10573-5
Samad, M. R., Iksan, Z. H., & Khalid, F. (2019). Acceptance and readiness to use M-learning among primary school science teachers. Creative Education, 10(12), 3003-3011.
Aç?kgül, K., & ?ad, S. N. (2021). High school students’ acceptance and use of mobile technology in learning mathematics. Education and Information Technologies, 26(4), 4181-4201. https://doi.org/10.1007/s10639-021-10466-7
Alfalah, A. A. (2023). Factors influencing students’ adoption and use of mobile learning management systems (m-LMSs): A quantitative study of Saudi Arabia. International Journal of Information Management Data Insights, 3(1), 100143.
Almaiah, M. A., Alamri, M. M., & Al-Rahmi, W. (2019). Applying the UTAUT model to explain the students’ acceptance of mobile learning system in higher education. IEEE Access, 7, 174673-174686.
Alyoussef, I. Y. (2021). Factors Influencing Students’ Acceptance of M-Learning in Higher Education: An Application and Extension of the UTAUT Model. Electronics, 24, 3171.
Ameri, A., Khajouei, R., Ameri, A., & Jahani, Y. (2020). Acceptance of a mobile-based educational application (LabSafety) by pharmacy students: An application of the UTAUT2 model. Education and Information Technologies, 25(1), 419-435. https://doi.org/10.1007/s10639-019-09965-5
Azizi, S. M., Roozbahani, N., & Khatony, A. (2020). Factors affecting the acceptance of blended learning in medical education: application of UTAUT2 model. BMC medical education, 20, 1-9.
Balakrishnan, V., & Gan, C. L. (2016). Students’ learning styles and their effects on the use of social media technology for learning. Telematics and Informatics, 33(3), 808-821. https://doi.org/10.1016/j.tele.2015.12.004
Chao, C. M. (2019, July 16). Factors Determining the Behavioral Intention to Use Mobile Learning: An Application and Extension of the UTAUT Model. Frontiers in psychology, 10, 1652. doi:10.3389/fpsyg.2019.01652
Cheng, Y., Sharma, S., Sharma, P., & Kulathunga, K. M. M. C. B. (2020). Role of personalization in continuous use intention of Mobile news apps in India: Extending the UTAUT2 model. Information, 11(1), 33. https://doi.org/10.3390/info11010033
Faqih, K. M. (2022). Investigating The Adoption Of An Innovation Using An Extended Utaut Model: The Case Of Mobile Learning Technology. Journal of Theoretical and Applied Information Technology, 100(17), 5600-5631.
Gharrah, A. S. A., & Aljaafreh, A. (2021, October). Why students use social networks for education: Extension of UTAUT2. Journal of Technology and Science Education, 11(1), 53-66. https://doi.org/10.3926/jotse.1081
Giannakos, M. N., Mikalef, P., & Pappas, I. O. (2021). Systematic literature review of e-learning capabilities to enhance organizational learning. Information Systems Frontiers, 1-17.
Gupta, N., & Irwin, J. D. (2016). In-class distractions: The role of Facebook and the primary learning task. Computers in Human Behavior, 55, 1165-1178.
Hashemi, M., Azizinezhad, M., Najafi, V., & Nesari, A. J. (2011). Retracted: What is mobile learning? Challenges and capabilities.
Ikhsan, R. B., & Prabowo, H. A. R. T. I. W. I. (2021). Drivers of the mobile-learning management system’s actual usage: Applying the utaut model. ICIC express letters. Part B, Applications: an international journal of research and surveys, 12(11), 1067-1074.
Jabatan Pendidikan Tinggi Kementerian Pendidikan Tinggi MEIPTA. (n.d.). Dasar e-Pembelajaran Negara 2.0. https://cade.upm.edu.my/dokumen/PTPA1_DePAN_v2.pdf
Jeon, J. E. (2021). The Effects of User Experience-Based Design Innovativeness on User? Metaverse Platform Channel Relationships in South Korea. ??????, 19(11), 81-90.
Kemp, S. (2022). Digital 2022 October Global Statshot Report. Datareportal. https://datareportal.com/reports/digital-2022-october-global-statshot.
Kolinski, H. (2022, January 13). What Is Mobile Learning and How to Use It?. iSpring. https://www.ispringsolutions.com/blog/what-is-mobile-learning.
Meet, R. K., Kala, D., & Al-Adwan, A. S. (2022). Exploring factors affecting the adoption of MOOC in Generation Z using extended UTAUT2 model. Education and Information Technologies, 27(7), 10261-10283.
Moorthy, K., Yee, T. T., T'ing, L. C., & Kumaran, V. V. (2019). Habit and hedonic motivation are the strongest influences in mobile learning behaviours among higher education students in Malaysia. Australasian Journal of Educational Technology, 35(4).
Prasetyo, Y. T., Roque, R. A. C., Chuenyindee, T., Young, M. N., Diaz, J. F. T., Persada, S. F., ... & Perwira Redi, A. A. N. (2021, June). Determining factors affecting the acceptance of medical education elearning platforms during the covid-19 pandemic in the philippines: Utaut2 approach. In Healthcare (Vol. 9, No. 7, p. 780). MDPI.
Kumar, G., & Vasimalairaja, M. (2019). Awareness of Educational Video Games among Middle School Students. PARIPEX-Indian Journal of Research, 8(1), 477-479.
Rudhumbu, N. (2022). Applying the UTAUT2 to predict the acceptance of blended learning by university students. Asian Association of Open Universities Journal, 17(1), 15-36.
Sharples, M., Taylor, J., & Vavoula, G. (2007). A Theory of Learning for the Mobile Age. In R. Andrews, & C. Haythornthwaite (Eds.), The SAGE Handbook of E-Learning Research (pp. 221-247). Thousand oaks, California: SAGE.
Sukendro, S., Habibi, A., Khaeruddin, K., Indrayana, B., Syahruddin, S., Makadada, F. A., & Hakim, H. (2020). Using an extended Technology Acceptance Model to understand students’ use of e-learning during Covid-19: Indonesian sport science education context. Heliyon, 6(11).
Tseng, T. H., Lin, S., Wang, Y. S., & Liu, H. X. (2022). Investigating teachers’ adoption of MOOCs: the perspective of UTAUT2. Interactive Learning Environments, 30(4), 635-650.
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS quarterly, 425-478. https://doi.org/10.2307/30036540
Venkatesh, V., Thong, J. Y., & Xu, X. (2012). Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS quarterly, 157-178.
Welch, R., Alade, T., & Nichol, L. (2020). Using the unified theory of acceptance and use of technology (UTAUT) model to determine factors affecting mobile learning adoption in the workplace: a study of the science museum group. IADIS International Journal on Computer Science and Information Systems, 15(1), 85-98.
Xu, W., Shen, Z. Y., Lin, S. J., & Chen, J. C. (2022). Improving the Behavioral Intention of Continuous Online Learning Among Learners in Higher Education During COVID-19. Frontiers in Psychology, 13, 857709.
Yip, M. H., Kee, C. Y., Lee, J. W., Lee, Y. J., & Soh, Y. Y. (2018). Determinants of continuance intention of mobile learning among academicians in Malaysian private universities (Doctoral dissertation, UTAR).
Zacharis, G., & Nikolopoulou, K. (2022). Factors predicting University students’ behavioral intention to use eLearning platforms in the post-pandemic normal: an UTAUT2 approach with ‘Learning Value’. Education and Information.
Zwain, A. A. (2019, June 19). Technological innovativeness and information quality as neoteric predictors of users’ acceptance of learning management system: An 81 expansion of UTAUT2. Interactive Technology and Smart Education, 16(3), 239-254. Retrieved from https://doi.org/10.1108/ITSE-09-2018-0065
Wee, S. Y., Taha, N. M., & Azman, N. A. A. (2024). Behavioral Intentions of Higher Education Students toward Using Gadgets for Mobile Learning. International Journal of Academic Research in Progressive Education and Development, 13(4), 384–397.
Copyright: © 2024 The Author(s)
Published by HRMARS (www.hrmars.com)
This article is published under the Creative Commons Attribution (CC BY 4.0) license. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this license may be seen at: http://creativecommons.org/licences/by/4.0/legalcode