Modelling Thai EFL students' acceptance of an LMS for prosody instruction: A UTAUT2-based mixed-methods study
DOI:
https://doi.org/10.62819/jel.2026.2169Keywords:
blended learning, LMS, prosody instruction, Thai EFL, UTAUT2Abstract
English prosody remains underemphasised in Thai EFL curricula despite its role in communicative competence. This study examines Thai university EFL students’ behavioural intention towards a prosody‑focused blended learning module incorporating a learning management system (LMS). Using the UTAUT2 framework, quantitative survey data from 157 participants were analysed with PLS‑SEM, and semi‑structured interviews with 20 purposefully selected students were examined through thematic analysis. Performance Expectancy (β = .28, p < .001) and Hedonic Motivation (β = .25, p < .001) emerged as the strongest predictors of Behavioural Intention, accounting for 58% of variance. Effort Expectancy and Social Influence showed smaller but significant effects. Behavioural Intention (β = .45, p < .001) and Facilitating Conditions (β = .31, p < .001) predicted actual use behaviour. Interview data contextualised these findings: participants reported heightened prosodic awareness and reduced speaking anxiety through private, asynchronous practice, with technical frustrations non‑disruptive to overall acceptance. These findings contribute to our understanding of LMS acceptance in Thai EFL by demonstrating that when platforms are designed around specific language learning objectives such as prosody practice, students’ perceived usefulness and enjoyment of the LMS drive behavioural intention and subsequent use.
References
Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211.
Al-Nuaimi, M. N., & Al-Emran, M. (2021). Learning management systems and technology acceptance models: A systematic review. Education and Information Technologies, 26(5), 5499–5533.
Bandura, A. (1997). Self-efficacy: The exercise of control. W. H. Freeman.
Baptista, G., & Oliveira, T. (2015). Understanding mobile banking: The unified theory of acceptance and use of technology combined with cultural moderators. Computers in Human Behavior, 50, 418–430. https://doi.org/10.1016/j.chb.2015.04.024
Beaton, D. E., Bombardier, C., Guillemin, F., & Ferraz, M. B. (2000). Guidelines for the process of cross-cultural adaptation of self-report measures. Spine, 25(24), 3186–3191. https://doi.org/10.1097/00007632-200012150-00014
Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa
Brown, S., Murphy, L., & Hammond, K. (2021). Learning management system adoption by academics: A perspective following the forced lockdown of NZ universities due to COVID-19. Journal of Open, Flexible and Distance Learning, 25(2), 55–65.
Celce-Murcia, M., Brinton, D. M., Goodwin, J. M., & Griner, B. (2010). Teaching pronunciation: A course book and reference guide (2nd ed.). Cambridge University Press.
Clark, R. C., & Mayer, R. E. (2024). e-Learning and the science of instruction: Proven guidelines for consumers and designers of multimedia learning (5th ed.). Wiley.
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Lawrence Erlbaum Associates.
Creswell, J. W., & Plano Clark, V. L. (2018). Designing and conducting mixed methods research (3rd ed.). Sage.
Derwing, T. M., & Munro, M. J. (2005). Second language accent and pronunciation teaching: A research-based approach. TESOL Quarterly, 39(3), 379–397. https://doi.org/10.2307/3588486
El-Masri, M., & Tarhini, A. (2017). Factors affecting the adoption of e-learning systems in Qatar and USA: Extending the unified theory of acceptance and use of technology 2 (UTAUT2). Educational Technology Research and Development, 65(3), 743–763. https://doi.org/10.1007/s11423-016-9508-8
Elyakim, N. (2025). Bridging expectations and reality: Addressing the price–value paradox in teachers’ AI integration. Education and Information Technologies, 30(12), 16929–16968. https://doi.org/10.1007/s10639-025-13466-z
Flick, U. (2022). Revitalising triangulation for designing multi-perspective qualitative research. In U. Flick (Ed.), The SAGE handbook of qualitative research design (pp. 652–664). Sage.
Granić, A., & Marangunić, N. (2023). Technology acceptance models in education: A systematic review. British Journal of Educational Technology, 54(3). https://doi.org/10.1111/bjet.13205
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. https://doi.org/10.1108/EBR-11-2018-0203
Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. https://doi.org/10.1007/s11747-014-0403-8
Horwitz, E. K. (2001). Language anxiety and achievement. Annual Review of Applied Linguistics, 21, 112–126. https://doi.org/10.1017/S0267190501000071
Jaroonruk, C., & Boonmoh, A. (2020). English pronunciation instruction in Thai EFL contexts. LEARN Journal, 13(2), 1–24.
Keane, T., Linden, T., Hernandez-Martinez, P., Molnar, A., & Blicblau, A. (2023). Digital technologies: Students’ expectations and experiences during transition from high school to university. Education and Information Technologies, 28(1), 857–877. https://doi.org/10.1007/s10639-022-11184-4
Kock, N. (2015). Common method bias in PLS-SEM: A full collinearity assessment approach. International Journal of e-Collaboration, 11(4), 1–10. https://doi.org/10.4018/ijec.2015100101
Lekwilai, P. (2021). “Read it like you mean it”: Developing prosodic reading using reader’s theater. rEFLections, 28(1), 1–18.
Levis, J. M. (2018). Intelligibility, oral communication, and the teaching of pronunciation. Cambridge University Press.
Lewin, C., Smith, A., Morris, S., & Craig, E. (2019). Using digital technology to improve learning: Evidence review. Education Endowment Foundation.
Nowell, L. S., Norris, J. M., White, D. E., & Moules, N. J. (2017). Thematic analysis: Striving to meet the trustworthiness criteria. International Journal of Qualitative Methods, 16(1), 1–13. https://doi.org/10.1177/1609406917733847
O’Brien, M. G., Derwing, T. M., Cucchiarini, C., Hardison, D. M., Mixdorff, H., Thomson, R. I., Strik, H., Levis, J. M., Munro, M. J., Foote, J. A., & Levis, G. M. (2018). Directions for the future of technology in pronunciation research and teaching. Journal of Second Language Pronunciation, 4(2), 182–207. https://doi.org/10.1075/jslp.17001.obr
Palinkas, L. A., Horwitz, S. M., Green, C. A., Wisdom, J. P., Duan, N., & Hoagwood, K. (2015). Purposeful sampling for qualitative data collection and analysis in mixed method implementation research. Administration and Policy in Mental Health, 42(5), 533–544. https://doi.org/10.1007/s10488-013-0528-y
Peerachachayanee, S. (2022). Towards the phonology of Thai English. Academic Journal of Humanities and Social Sciences, 30(3), 64–92.
Pibooltaew, P. W. P., & Chantarakamol, P. (2025). Factors influencing academic self-regulation of primary school children: Insights from Thai socio-cultural perspectives. Acta Psychologica, 261, Article 105940. https://doi.org/10.1016/j.actpsy.2025.105940
Raza, S. A., Qazi, W., Khan, K. A., & Salam, J. (2021). Social isolation and acceptance of the learning management system in the time of COVID-19: An expansion of the UTAUT model. Journal of Educational Computing Research, 59(2), 183–208. https://doi.org/10.1177/0735633120960421
Teimouri, Y., Goetze, J., & Plonsky, L. (2019). Second language anxiety and achievement: A meta-analysis. Studies in Second Language Acquisition, 41(2), 363–387. https://doi.org/10.1017/S0272263118000311
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540
Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157–178. https://doi.org/10.2307/41410412
Wang, Q., Amini, M., & Fu, Z. (2025). AI acceptance and Chinese EFL learners’ behavioral engagement with mediating effects of motivation. Scientific Reports, 15, Article 33310. https://doi.org/10.1038/s41598-025-11305-2
Zheng, H., Han, F., Huang, Y., Wu, Y., & Wu, X. (2025). Factors influencing behavioral intention to use e-learning in higher education during COVID-19: A meta-analytic review based on UTAUT2. Education and Information Technologies, 30, 12015–12053. https://doi.org/10.1007/s10639-024-13299-2
Downloads
Published
How to Cite
Issue
Section
