A Descriptive Analysis of Undergraduate Students’ Continuance Intention Toward ChatGPT Use in Malaysian Higher Education
DOI:
https://doi.org/10.32890/jtom2026.21.1.3Keywords:
Continuance Intention, ChatGPT, UTAUT2, Generative Artificial Intelligence, Higher EducationAbstract
The increasing adoption of generative artificial intelligence tools such as ChatGPT has transformed learning practices in higher education, raising questions about students’ intentions to continue using these technologies beyond initial adoption. This study examines undergraduate students’ continuance intention toward the use of ChatGPT in Malaysian higher education, guided by the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2). A quantitative survey was administered to undergraduate students who had prior experience using ChatGPT for academic purposes. Data were analysed using descriptive statistics, including mean scores and standard deviations, to examine students’ perceptions of key UTAUT2 constructs. The findings indicate generally positive perceptions of ChatGPT, particularly in relation to performance expectancy, effort expectancy, and facilitating conditions, suggesting favourable conditions for continued intention to use the tool in academic contexts. However, variations were observed across constructs, highlighting differing levels of perceived usefulness, enjoyment, and habitual use among students. As the analysis is descriptive in nature, no causal relationships or predictive effects are inferred. This study contributes to the literature by providing contextual, theory-informed insights into students’ continuance intention toward generative AI tools within Malaysian higher education. The findings offer baseline evidence that can inform educators and institutions in understanding students’ perceptions of ChatGPT use, while also laying the groundwork for future studies employing inferential or longitudinal approaches to examine continuance behaviour more comprehensively.
References
Acosta-Enriquez, B. G., Ramos Farroñan, E. V., Villena Zapata, L. I., Mogollon Garcia, F. S., Rabanal-León, H. C., Angaspilco, J. E. M., & Bocanegra, J. C. S. (2024). Acceptance of artificial intelligence in university contexts: A conceptual analysis based on UTAUT2 theory. Heliyon, 10(19), e38315. https://doi.org/10.1016/j.heliyon.2024.e38315
Alghazo, R., Fatima, G., Malik, M., Abdelhamid, S. E., Jahanzaib, M., Nayab, D. e, & Raza, A. (2025). Exploring ChatGPT’s Role in Higher Education: Perspectives from Pakistani University Students on Academic Integrity and Ethical Challenges. Education Sciences, 15(2), 158. https://doi.org/10.3390/educsci15020158
Ali, Z., Bhaskar, Sb., & Sudheesh, K. (2019). Descriptive statistics: Measures of central tendency, dispersion, correlation and regression. Airway, 2(3), 120. https://doi.org/10.4103/ARWY.ARWY_37_19
Al-kfairy, M. (2024). Factors Impacting the Adoption and Acceptance of ChatGPT in Educational Settings: A Narrative Review of Empirical Studies. Applied System Innovation, 7(6), 110. https://doi.org/10.3390/asi7060110
Almarashdeh, I., & Alzaqebah, M. (2023). The Impact of Technology Identity on Student‘s Adoption of Social Media in Online Learning. International Journal of Information and Education Technology, 13(11), 1809–1819. https://doi.org/10.18178/ijiet.2023.13.11.1993
Almogren, A. S., Al-Rahmi, W. M., & Dahri, N. A. (2024). Exploring factors influencing the acceptance of ChatGPT in higher education: A smart education perspective. Heliyon, 10(11), e31887. https://doi.org/10.1016/j.heliyon.2024.e31887
Arbulú Ballesteros, M. A., Acosta Enríquez, B. G., Ramos Farroñán, E. V., García Juárez, H. D., Cruz Salinas, L. E., Blas Sánchez, J. E., Arbulú Castillo, J. C., Licapa-Redolfo, G. S., & Farfán Chilicaus, G. C. (2024). The Sustainable Integration of AI in Higher Education: Analyzing ChatGPT Acceptance Factors Through an Extended UTAUT2 Framework in Peruvian Universities. Sustainability, 16(23), 10707. https://doi.org/10.3390/su162310707
Ciampa, K., Wolfe, Z. M., & Bronstein, B. (2023). ChatGPT in education: Transforming digital literacy practices. Journal of Adolescent & Adult Literacy, 67(3), 186–195. https://doi.org/10.1002/jaal.1310
Deng, P., Chen, B., & Wang, L. (2023). Predicting students’ continued intention to use E-learning platform for college English study: the mediating effect of E-satisfaction and habit. Frontiers in Psychology, 14. https://doi.org/10.3389/fpsyg.2023.1182980
Etikan, I., Musa, S. A., & Alkassim, R. S. (2016). Comparison of Convenience Sampling and Purposive Sampling. American Journal of Theoretical and Applied Statistics, 5(1), 1. https://doi.org/10.11648/j.ajtas.20160501.11
Grassini, S., Aasen, M. L., & Møgelvang, A. (2024). Understanding University Students’ Acceptance of ChatGPT: Insights from the UTAUT2 Model. Applied Artificial Intelligence, 38(1). https://doi.org/10.1080/08839514.2024.2371168
Heung, Y. M. E., & Chiu, T. K. F. (2025). How ChatGPT impacts student engagement from a systematic review and meta-analysis study. Computers and Education: Artificial Intelligence, 8, 100361. https://doi.org/10.1016/j.caeai.2025.100361
Huang, L. (2023). Ethics of Artificial Intelligence in Education: Student Privacy and Data Protection. Science Insights Education Frontiers, 16(2), 2577–2587. https://doi.org/10.15354/sief.23.re202
Jeilani, A., & Abubakar, S. (2025). Perceived institutional support and its effects on student perceptions of AI learning in higher education: the role of mediating perceived learning outcomes and moderating technology self-efficacy. Frontiers in Education, 10. https://doi.org/10.3389/feduc.2025.1548900
Karkoulian, S., Sayegh, N., & Sayegh, N. (2024). ChatGPT Unveiled: Understanding Perceptions of Academic Integrity in Higher Education - A Qualitative Approach. Journal of Academic Ethics. https://doi.org/10.1007/s10805-024-09543-6
Kotronoulas, G., Miguel, S., Dowling, M., Fernández-Ortega, P., Colomer-Lahiguera, S., Bağçivan, G., Pape, E., Drury, A., Semple, C., Dieperink, K. B., & Papadopoulou, C. (2023). An Overview of the Fundamentals of Data Management, Analysis, and Interpretation in Quantitative Research. Seminars in Oncology Nursing, 39(2), 151398. https://doi.org/10.1016/j.soncn.2023.151398
Labadze, L., Grigolia, M., & Machaidze, L. (2023). Role of AI chatbots in education: systematic literature review. International Journal of Educational Technology in Higher Education, 20(1), 56. https://doi.org/10.1186/s41239-023-00426-1
Lawaju, P., Adhikari, S. U., & Devkota, J. (2024). Impact of AI in Education: An Evidence from Use of ChatGPT in Management Education in Nepal. ISSN Quest Journal of Management and Social Sciences, 6(3), 621–642. https://doi.org/10.3126/qjmss
Loeb, S., Dynarski, S., Mcfarland, D., Morris, P., Reardon, S., & Reber, S. (2017). Descriptive Analysis in Education: A Guide for Researchers. http://ies.ed.gov/ncee/.
Marquardson, J. (2024). Embracing Artificial Intelligence to Improve Self-Directed Learning: A Cybersecurity Classroom Study. Information Systems Education Journal, 22(1), 4–13. https://doi.org/10.62273/wzby3952
Mohd Arifin, S. R. (2018). Ethical Considerations in Qualitative Study. INTERNATIONAL JOURNAL OF CARE SCHOLARS, 1(2), 30–33. https://doi.org/10.31436/ijcs.v1i2.82
Mohd A’seri, M. S., Mahmud, M. M., Yaacob, Y., Ahmad, R., Nagasundram, U., & Mustamam, N. I. (2024). Beyond the Textbook: A Study of ChatGPT Patterns of Use Perceptions and Experiences Among Students in Higher Education. Proceedings of the 2024 16th International Conference on Education Technology and Computers, 110–116. https://doi.org/10.1145/3702163.3702179
Nawaz, S.S., Sanjeetha, M.B.F., Al-Murshidi, G, Mohamed-Riyath M.I., Yamin, F.M., Mohamed, R (2024), Acceptance of ChatGPT by undergraduates in Sri Lanka: a hybrid approach of SEM-ANN. Interactive Technology and Smart Education, 21(4), 546–570, doi: https://doi.org/10.1108/ITSE-11-2023-0227
Rabiev, H., Sadidan, I., & Nurhidayah, N. A. S. (2025). Exploring the Use of ChatGPT in Academic Assignments: Frequency, Benefits, and Perceptions among University Students. IC-ITECHS, 5(1), 465–469. https://doi.org/10.32664/ic-itechs.v5i1.1669
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. https://doi.org/10.1108/AAOUJ-08-2021-0084
Selvanathan, B., & Narayanan, S. (2024). Chatgpt in Higher Education Malaysia: An Opportunity or Threat to The Education System? International Journal of Academic Research in Progressive Education and Development, 13(3). https://doi.org/10.6007/IJARPED/v13-i3/21455
Sergeeva, O. V., Zheltukhina, M. R., Shoustikova, T., Tukhvatullina, L. R., Dobrokhotov, D. A., & Kondrashev, S. V. (2025). Understanding higher education students’ adoption of generative AI technologies: An empirical investigation using UTAUT2. Contemporary Educational Technology, 17(2), ep571. https://doi.org/10.30935/cedtech/16039
Sova, R., Tudor, C., Tartavulea, C. V., & Dieaconescu, R. I. (2024). Artificial Intelligence Tool Adoption in Higher Education: A Structural Equation Modeling Approach to Understanding Impact Factors among Economics Students. Electronics, 13(18), 3632. https://doi.org/10.3390/electronics13183632
Strzelecki, A. (2024). Students’ Acceptance of ChatGPT in Higher Education: An Extended Unified Theory of Acceptance and Use of Technology. Innovative Higher Education, 49(2), 223–245. https://doi.org/10.1007/s10755-023-09686-1
Venkatesh, V., Walton, S. M., Thong, J. Y. L., & Xu, X. (2012). CONSUMER ACCEPTANCE AND USE OF INFORMATION TECHNOLOGY: EXTENDING THE UNIFIED THEORY OF ACCEPTANCE AND USE OF TECHNOLOGY. In MIS Quarterly (Vol. 36, Issue 1). http://ssrn.com/abstract=2002388
Wang, Y.-T., & Lin, K.-Y. (2021). Understanding Continuance Usage of Mobile Learning Applications: The Moderating Role of Habit. Frontiers in Psychology, 12, 736051. https://doi.org/10.3389/fpsyg.2021.736051
Yamin, F.M., & Ishak, W.H.W. (2015). Continuous use of online storage system for document sharing. Journal Teknologi, 77(5), 23–27. https://doi.org/10.11113/jt.v77.6109
Xu, S., Chen, P., & Zhang, G. (2024). Exploring Chinese University Educators’ Acceptance and Intention to Use AI Tools: An Application of the UTAUT2 Model. Sage Open, 14(4). https://doi.org/10.1177/21582440241290013
Zou, M., & Huang, L. (2023). To use or not to use? Understanding doctoral students’ acceptance of ChatGPT in writing through technology acceptance model. Frontiers in Psychology, 14. https://doi.org/10.3389/fpsyg.2023.1259531
Published
Issue
Section
License
Copyright (c) 2026 Journal of Technology and Operations Management
This work is licensed under a Creative Commons Attribution 4.0 International License.
Disclaimer
The Journal of Technology and Operation Management (JTOM) has taken all reasonable measures to ensure that material contained in this website is the original work of the author(s). However, the Journal gives no warranty and accepts no responsibility for the accuracy or the completeness of the material; no reliance should be made by any user on the material. The user should check with the authors for confirmation. Articles published in the Journal of Technology and Operation Management (JTOM) do not represent the views held by the editors and members of the editorial board. Authors are responsible for all aspects of their articles except the editorial screen design.
