Mobile Learning Acceptance In Higher Education: An Integrated Model And Empirical Study Based On The Perceptions Of Private Higher Vocational Colleges Students
Keywords:
mobile learning, Private Higher Vocational Institutions, TAM, UTAUTAbstract
With the rapid development of information technology, mobile learning (M-learning) has become an important part of higher vocational education and one of the most promising educational technologies developed in the educational environment. The purpose of this study is to investigate the factors that influence the use of m-learning by college students in private higher vocational colleges and universities. A comprehensive model integrating TAM and UTAUT theories was constructed to predict mobile learning acceptability. The study collected data from a total of 270 college students of Guangzhou City Construction College through questionnaires. The data were analyzed using SPSS version 26 and Smart-PLS 3.3.9. The results of the study showed that perceived usefulness, perceived ease of use, attitude, facilitating conditions, and social influence positively influenced students' intention to use m-learning.
References
Afandi,W.(2022). Saudi Higher Education Student Acceptance of Mobile Learning. International Journal of Information and Education Technology, Vol. 12, No. 6, June. https://doi.org/10.18178/ijiet.2022.12.6.1647
Al Amin, M., Razib Alam, M., & Alam, M. Z. (2023). Antecedents of students’ e-learning continuance intention during COVID-19: An empirical study. E-Learning and Digital Media, 20(3), 224-254. https://doi.org/10.1177/20427530221103915
Alhussain, T., Al-Rahmi, W.M.& Othman, M.S.(2020). Students’ Perceptions of Social Networks Platforms use in Higher Education: A Qualitative Research. International Journal of Advanced Trends in Computer Science and Engineering, 9(3).
Aliaño, Á. M., Hueros, A. M. D., Franco, M. D. G., & Aguaded, I. (2019). Mobile learning in university contexts based on the unified theory of acceptance and use of technology (UTAUT). Journal of New Approaches in Educational Research, 8(1), 7–17. https://doi.org/10.7821/naer.2019.1.317
Almaiah, M.A.(2018). Acceptance and usage of a mobile information system services in University of Jordan. Educ. Inf. Technol, 23,1873–1895.
Alowayr, A., & Al-Azawei, A. (2021). Predicting mobile learning acceptance: An integrated model and empirical study based on the perceptions of higher education students. Australasian Journal of Educational Technology, 37(3), 38–55. https://doi.org/10.14742/ajet.6154
Alowayr, A., & Al-Azawei, A. (2021). Predicting mobile learning acceptance: An integrated
model and empirical study based on the perceptions of higher education students. Australasian Journal of Educational Technology, 37(3), 38–55. https://doi.org/10.14742/ajet.615
Al-Rahmi, A. M., Ramin, A. K., Alamri, M. M., Al-Rahmi, W. M., Yahaya, N., Abualrejal, H., & AlMaatouk, Q. (2019a). Evaluating the intended use of Decision Support System (DSS) via academic staf: An applying Technology Acceptance Model (TAM). Int. J. Recent Technol. Eng. (IJRTE), 8, 268–275.
Al-Rahmi, A.M., & Al-Rahmi, W.M., & Alturki, U., & Aldraiweesh, A., & Almotairi, S., & Al-Adwan, A. (2022). Acceptance of mobile technologies and M-learning by university students: An empirical investigation in higher education. Education and Information Technologies. 27. 10.1007/s10639-022-10934-8.
Al-Rahmi, A.M., Al-Rahmi,W.M., Alturki, U., Aldraiweesh, A.,Almutairy, S., Al-Adwan,A.S.,(2021).Exploring the Factors Affecting Mobile Learning for Sustainability in Higher Education. Sustainability,13, 7893. https://doi.org/10.3390/su13147893
Al-Rahmi,A.M,Al-Rahmi,W.M,& Alturki,U.,Aldraiweesh, A., Almotairi, S., & Al-Adwan, A. (2022). Acceptance of mobile technologies and M-learning by university students: An empirical investigation in higher education. Education and Information Technologies. 27. 10.1007/s10639-022-10934-8.
Alraja, M. N. (2016). The effect of social influence and facilitating conditions on e-government acceptance from the individual employees’ perspective. Pol. J. Manag. Stud. 14, 18–27. doi: 10.17512/pjms.2016.14.2.02
Alsswey, A.& Al-Samarraie, H.(2019). M-learning adoption in the Arab gulf countries: A systematic review of factors and challenges.Educ. Inf. Technol, 24, 1–14.
Alturki, U.& Aldraiweesh, A. ( 2022).Students’ Perceptions of the Actual Use of Mobile Learning during COVID-19 Pandemic in Higher Education. Sustainability, 14, 1125. https://doi.org/10.3390/ su14031125
Alturki, U.& Aldraiweesh, A.(2022). Students’ Perceptions of the Actual Use of Mobile Learning during COVID-19 Pandemic in Higher Education. Sustainability, 14,1125. https://doi.org/10.3390/su14031125
Arain, A.A., Hussain, Z., Rizvi, W.H., Vighio, M.S. (2019). Extending UTAUT2 toward acceptance of mobile learning in the context of higher education. Univers. Access Inf. Soc, 18, 659–673.
Basurra, S. & Bamansoor ,S.(2021) .Factors Influencing Students' Intention To Use Mobile Learning:A Study at Yemen Higher Education Institutions,2021 2nd International Conference on Smart Computing and Electronic Enterprise (ICSCEE), Cameron Highlands, Malaysia, pp. 206-211, http://doi.org/ 10.1109/ICSC-EE50312.2021.9498251.
Becker, J. M., Ringle, C. M., Sarstedt, M., & Völckner, F. (2015). How collinearity affects mixture regression results. Marketing Letters, 26(4), 643–659. https://doi.org/10.1007/s11002-014-9299-9
Camilleri, M.A. & Camilleri, A.C. (2022). Learning from anywhere, anytime: Utilitarian
motivations and facilitating conditions to use mobile learning applications. Technology, Knowledge and Learning, https://doi.org/10.1007/s10758-022-09608-8
Chiu, M.-S. (2020). Exploring models for increasing the effects of school information and communication technology use on learning outcomes through outside-school use and socioeconomic status mediation: The ecological techno-process. Educational Technology Research and Development, 68(1), 413–436. https://doi.org/10.1007/s11423-019-09707-x
Dahal, N., Manandhar, N. K., Luitel, L., Luitel, B. C., Pant, B. P., & Shrestha, I. M. (2022). ICT tools for remote teaching and learning mathematics: A proposal for autonomy and engagements. Advances in Mobile Learning Educational Research, 2(1), 289-296.https://doi.org/10.25082/AMLER.2022.01.013
Davis, F. D. (1986). A technology acceptance model for empirically testing new end-user information systems: Theory and results [Doctoral thesis, Massachussetts Institute of Technology]. DSpace@MIT. http://dspace.mit.edu/handle/1721.1/15192
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340.
Davis, F.D.; Bagozzi, R.P.; Warshaw, P.R.(1989). User Acceptance of Computer echnology: A Comparison of Two Theoretical Models. Manag. Sci. 1989, 35, 982–1003.
Fornell,C.&Larcker,D.F.(1981).Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. J. Mark.Res. 1981, 18, 39–50.
Hair, J.F.; Risher, J.J.; Sarstedt, M.& Ringle, C.M. (2019). When to Use and How to Report the Results of PLS-SEM. Eur. Bus. Rev. 2019.
Henseler J., Ringle CM. & Sarstedt M (2015). A new criterion for assessing discriminant validity in variancebased structural equation modeling. Journal of the Academy of Marketing Scienc,e 43: 115–135. https://doi.org/10.1007/s11747-014-0403-8
Kaliisa, R.; Palmer, E.& Miller, J.(2019). Mobile learning in higher education: A comparative analysis of developed and developing country contexts. Br. J. Educ. Technol, 50, 546–561.
Kumar Basak, S., Wotto, M., & Bélanger, P. (2018). E-learning, M-learning and D-learning: Conceptual definition and comparative analysis. E-Learning and Digital Media, 15(4), 191–216. https://doi.org/10.1177/2042753018785180
Lavidas, K., Petropoulou, A., Papadakis, S., Apostolou, Z., Komis, V., Jimoyiannis, A., & Gialamas, V. (2022). Factors affecting response rates of the Web survey with teachers. Computers, 11(9), 127.https://doi.org/10.3390/computers11090127
Lutfi, A. (2022). Factors Influencing the Continuance Intention to Use Accounting Information System in Jordanian SMEs from the Perspectives of UTAUT: Top Management Support and Self-Efficacy as Predictor Factors. Economies, 10, 75.
Lutfi, A.,Saad, M.,Almaiah,M.A.,Alsaad, A., Al-Khasawneh, A.,Alrawad, M., Alsyouf, A.,Al-Khasawneh, A.L.(2022). Actual Use of Mobile Learning Technologies during Social Distancing Circumstances: Case Study of King Faisal University Students. Sustainability, 14, 7323.https://doi.org/10.3390/su14127323
Mubuke, F., Ogenmungu, C., Masaba, A.K. & Andrew, W. (2017). The predictability of perceived enjoyment and its impact on the intention to use Mobile learning systems. Asian J. Comput. Sci. Inf. Technol, 1, 7.
Pramana, E. (2018). “Determinants of the adoption of mobile learning systems among university students in Indonesia,” J. Inf. Technol. Educ. Res., vol. 17, pp. 365–398, https://doi.org/10.28945/4119
Sabri, S. ,Gani, A. ,Yadegaridehkordi,E. ,Othman,S., Miserom,F., & Shuib, L.(2022). A Framework for Mobile Learning Acceptance Amongst Formal Part-Time Learners: From the Andragogy Perspective. inIEEE, vol. 10, pp. 61213-61227,https://doi: 10.1109/ACCESS.2022.3178718
Sandri, O. (2020). What do we mean by ‘pedagogy’ in sustainability education? Teaching in Higher Education, 1–16. https://doi.org/10.1080/13562517.2019.1699528
Saroia, A.I.& Gao, S.(2019). Investigating university students’ intention to use mobile learning management systems in Sweden. Innov. Educ. Teach. Int. 2019, 56, 569–580.
Su C-Y & Chao C-M. (2022). Investigating Factors Influencing Nurses’ Behavioral Intention to Use Mobile Learning: Using a Modified Unified Theory of Acceptance and Use of Technology Model. Front. Psychol. 13:673350. http://doi.org/10.3389/fpsyg.2022.673350
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): e05410. DOI: 10.1016/j.heliyon.2020.e05410
Venkatesh, V ., Morris, M. G., Gordon, B.& Davis, F. D. (2003).User acceptance of information technology: Toward a unified view. MIS Quart., vol. 27, no. 3, pp. 425–478, Sep. 2003, doi: 10.2307/30036540.
Voicu, M.C., & Muntean, M.(2023)Factors That Influence Mobile Learning among University Students in Romania.Electronics,12, 938.https://doi.org/10.3390/elect-ronics12040938
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 Hao Cai, PC Lai

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Published by University Tun Abdul Razak (UNIRAZAK)
