Digital Learning Acceptance in Islamic Education: Validity and Reliability Testing of the Modified Technology Acceptance Model


  • Mussa Abubakari Sultan Hassanal Bolkiah Institute of Education, Universiti Brunei Darussalam
  • Gamal Abdul Nasir Zakaria Sultan Hassanal Bolkiah Institute of Education, Universiti Brunei Darussalam
  • Juraidah Musa Sultan Hassanal Bolkiah Institute of Education, Universiti Brunei Darussalam



Islamic Education, Digital Technology, Technology Acceptance, CFA, Higher Education, TAM, Digital Learning


Digital technologies (DT) have revolutionised various sectors, including education. In Islamic education, integrating DT can potentially enhance the teaching and learning processes. However, incorporating these technologies into Islamic education requires careful consideration due to the unique nature of the subject matter and cultural sensitivities. Thus, this pilot study assessed the validity and reliability of the TAMISE (Technology Acceptance Model in Islamic Education) through confirmatory factor and composite analyses. The TAMISE framework extended the Technology Acceptance Model (TAM) with perceived Islamic education compatibility to address the acceptance of digital technologies in Islamic education. The study employed a survey questionnaire administered to a sample (N = 65) of Islamic education students from Indonesia and Malaysia. The data collected were analysed using confirmatory factor analysis (CFA) and confirmatory composite analysis (CCA). The results indicated that the TAMISE model demonstrated adequate validity and reliability, thus supporting its applicability as a theoretical model for understanding digital technology adoptions in Islamic educational systems. Furthermore, the findings theoretically contribute to Islamic education and technology acceptance by providing insights into factors influencing students' adoption and use of digital technologies.


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Abubakari, M. S., & Mashoedah. (2021). Online Learning Engagement Model for International Students in Indonesia amid Covid-19 Period: A Conceptual Model Proposal. International Journal of Distance Education and E-Learning, 6(2), 15–30.

Abubakari, M. S., Nurkhamid, & Hungilo, G. (2021). Evaluating an e-Learning Platform at Graduate School Based on User Experience Evaluation Technique. Journal of Physics: Conference Series, 1737(1).

Abubakari, M. S., Nurkhamid, N., & Priyanto, P. (2022). Factors Influencing Online Learning Engagement: International Students’ Perspective and the Role of Institutional Support. Turkish Online Journal of Distance Education, 23(3), 118–136.

Abubakari, M. S., & Priyanto. (2021). Information and Communication Technology Acceptance in Madrasa Education: Religious’ Perspective in Tanzania. International Journal of Social Sciences & Educational Studies, 8(3), 129–148.

Abubakari, M. S., & Zakaria, G. A. N. (2023). Technology Acceptance Model in Islamic Education (TAMISE) for Digital Learning: Conceptual Framework Proposal. Canadian Journal of Educational and Social Studies, 3(4), 25–42.

Abubakari, M. S., Zakaria, G. A. N., Priyanto, P., & Triantini, D. T. (2023). Analysing Technology Acceptance for Digital Learning in Islamic Education: The Role of Religious Perspective on ICT. Journal of Computing Research and Innovation, 8(1), 1–16.

Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211.

Ajzen, I., & Fishbein, M. (1977). Attitude-behavior relations: A theoretical analysis and review of empirical research. Psychological Bulletin, 84(5), 888–918.

Al-Harbi, B. A. (2019). The Attitudes of Islamic Education Teachers towards the Use of Social Media in Teaching and Learning. In International Education Studies (Vol. 12, Issue 11, pp. 154–163).

Al-rahmi, W. M., Zeki, A. M., Alias, N., & Saged, A. A. (2017). Information Technology Usage in the Islamic Perspective: A Systematic Literature Review. The Anthropologist, 29(1), 27–41.

Alamri, M. M., Almaiah, M. A., & Al-Rahmi, W. M. (2020). Social media applications affecting students’ academic performance: A model developed for sustainability in higher education. Sustainability (Switzerland), 12(16), 1–14.

Alenezi, M. (2023). Digital Learning and Digital Institution in Higher Education. Education Sciences, 13(1), 88.

Ali, A. H., Idris, M. R., & Rahman, M. N. A. (2016). Technology Influence and Self-aspect on Blog Acceptance as a Teaching Medium for Islamic Education in Muslim Y Generation at IPTA. International Journal of Academic Research in Business and Social Sciences, 6(12), 197–210.

Alshammari, M. T., & Qtaish, A. (2019). Effective Adaptive E-Learning Systems According to Learning Style and Knowledge Level. Journal of Information Technology Education: Research, 18, 529–547.

Alsharbi, B. M., Mubin, O., & Novoa, M. (2021). Quranic Education and Technology: Reinforcement learning System for Non-Native Arabic Children. Procedia Computer Science, 184(2019), 306–313.

Arjmand, R. (2018). Introduction to Part I: Islamic Education: Historical Perspective, Origin, and Foundation. In Handbook of Islamic Education (pp. 3–31).

Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review, 84(2), 191–215.

Bandura, A. (2001). Social Cognitive Theory: An Agentic Perspective. Annual Review of Psychology, 52(1), 1–26.

Bygstad, B., Øvrelid, E., Ludvigsen, S., & Dæhlen, M. (2022). From dual digitalization to digital learning space: Exploring the digital transformation of higher education. Computers & Education, 182(August 2021), 104463.

Compeau, D., & Higgins, C. A. (1995). Computer self-efficacy: Development of a measure and initial test. MIS Quarterly: Management Information Systems, 19(2), 189–210.

Daniela, L. (2019). Smart Pedagogy for Technology-Enhanced Learning. In Didactics of Smart Pedagogy (pp. 3–21). Springer International Publishing.

Daun, H., & Arjmand, R. (2021). Globalisation and Islamic Education. In J. Zajda (Ed.), Third International Handbook of Globalisation, Education and Policy Research (pp. 451–463). Springer International Publishing.

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 Technology: A Comparison of Two Theoretical Models. Management Science, 35(8), 982–1003.

Dishaw, M. T., & Strong, D. M. (1999). Extending the technology acceptance model with task–technology fit constructs. Information & Management, 36(1), 9–21.

Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior : an introduction to theory and research. Addison-Wesley Pub. Co.

Fishbein, M., & Ajzen, I. (2015). Predicting and changing behavior : the reasoned action approach.

Forero, C. G., Maydeu-Olivares, A., & Gallardo-Pujol, D. (2009). Factor Analysis with Ordinal Indicators: A Monte Carlo Study Comparing DWLS and ULS Estimation. Structural Equation Modeling: A Multidisciplinary Journal, 16(4), 625–641.

Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., Black, W. C., & Anderson, R. E. (2019). Multivariate Data Analysis. Cengage Learning EMEA.

Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24.

Hair Jr, J., Hult, G. T., Ringle, C., & Sarstedt, M. (2017). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). SAGE Publications Inc.

Haleem, A., Javaid, M., Qadri, M. A., & Suman, R. (2022). Understanding the role of digital technologies in education: A review. Sustainable Operations and Computers, 3(May), 275–285.

Haris, A., Asnawi, N., & Fanani, M. A. (2022). Expanding the Technology Acceptance Model ( TAM ) to investigate e-learning usage behavior during the COVID-19 pandemic : Islamic Higher Education Institution ( IHEI ) context. Baltic Journal of Law & Politics, 15(1), 1885–1903.

Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55.

International Telecommunication Union [ITU], UNESCO, & UNICEF. (2020). The Digital Transformation of Education: Connecting Schools, Empowering Learners. International Telecommunication Union [ITU], United Nations Educational, Scientific and Cultural Organization [UNESCO], United Nations Children’s Fund (UNICEF).

Islam, A. Y. M. A., Mok, M. M. C., Gu, X., Spector, J., & Hai-Leng, C. (2019). ICT in Higher Education: An Exploration of Practices in Malaysian Universities. IEEE Access, 7(c), 16892–16908.

Jamaluddin, D., Ramdhani, M. A., Priatna, T., & Darmalaksana, W. (2019). Techno University to increase the quality of islamic higher education in Indonesia. International Journal of Civil Engineering and Technology, 10(1), 1264–1273.

JASP Team. (2023). JASP (Version 0.17.2) [Computer software] (0.17.2). JASP Team.

Kline, R. B. (2016). Principles and Practice of Structural Equation Modeling. In The Guilford Press (Fourth Edi). A Division of Guilford Publications, Inc.

Kock, N. (2022). Model-Driven Data Analytics: Applications with WarpPLS. In ScriptWarp Systems. ScriptWarp Systems.

Kuo, Y. C., Walker, A. E., Schroder, K. E. E., & Belland, B. R. (2014). Interaction, Internet self-efficacy, and self-regulated learning as predictors of student satisfaction in online education courses. Internet and Higher Education, 20, 35–50.

Moore, G. C., & Benbasat, I. (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information Systems Research, 2(3), 192–222.

Ngabiyanto, Nurkhin, A., Widiyanto, Saputro, I. H., & Kholid, A. M. (2021). Teacher’s intention to use online learning; an extended technology acceptance model (TAM) investigation. Journal of Physics: Conference Series, 1783(1), 012123.

Nuryanna, N., Halim, A., Mahzum, E., & Hamid, A. (2021). Acceptance of Technology by Islamic Boarding School Students Based on the TAM Model. Jurnal Penelitian Pendidikan IPA, 7(Special Issue), 194–198.

Peiffer, H., Schmidt, I., Ellwart, T., & Ulfert, A.-S. (2020). Digital competences in the workplace: Theory, terminology, and training. In Vocational education and training in the age of digitization: Challenges and opportunities (pp. 157–181). Verlag Barbara Budrich.

Rahman, A. H. A., Samad, N. S. A., Abdullah, A., Yasoa’, M. R., Muhamad, S. F., Bahari, N., & Mohamad, S. R. (2022). E-Learning and Sustainability of Pondok Schools: A Case Study on Post-COVID-19 E-Learning Implementation among Students of Pondok Sungai Durian, Kelantan, Malaysia. Sustainability, 14(18), 11385.

Ringle, C. M., Wende, S., & Becker, J.-M. (2022). SmartPLS 4 ( SmartPLS GmbH.

Rogers, E. M. (1995). Diffusion of Innovations: Modifications of a Model for Telecommunications. In Die Diffusion von Innovationen in der Telekommunikation (pp. 25–38). Springer Berlin Heidelberg.

Rogers, E. M. (2003). Diffusion of Innovations, 5th Edition.

Scherer, R., Siddiq, F., & Tondeur, J. (2019). The technology acceptance model (TAM): A meta-analytic structural equation modeling approach to explaining teachers’ adoption of digital technology in education. Computers & Education, 128(0317), 13–35.

Scherer, R., & Teo, T. (2019). Unpacking teachers’ intentions to integrate technology: A meta-analysis. Educational Research Review, 27(0317), 90–109.

Serin, H. (2022). Challenges and Opportunities of E-Learning in Secondary School in Iraq. International Journal of Social Sciences & Educational Studies, 9(3), 305–318.

Shan-a-alahi, A., & Huda, M. N. (2017). Role of Information Technology on Preaching Islam (Da’wah). American International Journal of Research in Humanities, Arts and Social Sciences (AIJRHASS), 17(1), 1–5.

Subiyakto, A., Sekarningtyas, R., Aini, Q., Hakiem, N., Muslimin, J. M., Subchi, I., & Ahlan, A. R. (2022). The Impacts of Perceived Trust and Perceived Validity on the Religious Electronic Resource Acceptance. ICIC Express Letters, 16(9), 1019–1028.

Teo, T., & van Schaik, P. (2012). Understanding the Intention to Use Technology by Preservice Teachers: An Empirical Test of Competing Theoretical Models. International Journal of Human-Computer Interaction, 28(3), 178–188.

Ulfert, A.-S., Antoni, C. H., & Ellwart, T. (2022). The role of agent autonomy in using decision support systems at work. Computers in Human Behavior, 126, 106987.

United Nations Educational Scientific and Cultural Organization [UNESCO]. (2021). Information and Communication Technology Use in Education. United Nations Educational, Scientific and Cultural Organization (UNESCO).

Waghid, Y. (2014). Islamic Education and Cosmopolitanism: A Philosophical Interlude. Studies in Philosophy and Education, 33(3), 329–342.

Wheeler, S. (2012). e-Learning and Digital Learning. In Encyclopedia of the Sciences of Learning (pp. 1109–1111). Springer US.

Xie, T., Zheng, L., Liu, G., & Liu, L. (2022). Exploring structural relations among computer self-efficacy, perceived immersion, and intention to use virtual reality training systems. Virtual Reality, 26(4), 1725–1744.

Yi, M. Y., Fiedler, K. D., & Park, J. S. (2006). Understanding the Role of Individual Innovativeness in the Acceptance of IT-Based Innovations: Comparative Analyses of Models and Measures. Decision Sciences, 37(3), 393–426.




How to Cite

Abubakari, M., Zakaria, G. A. N., & Musa, J. (2023). Digital Learning Acceptance in Islamic Education: Validity and Reliability Testing of the Modified Technology Acceptance Model. Canadian Journal of Educational and Social Studies, 3(6), 27–42.