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Feb 13, 2026
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Mar 13, 2026
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Abstract

The growth of Technological Pedagogical Content Knowledge (TPACK) among EFL student teachers during their teaching practicum is examined in this study in relation to self-regulated learning (SRL) and technology acceptance (TA).  Three student teachers' semi-structured interviews, reflective journals, and lesson plans were all examined using a qualitative case study design.  According to thematic analysis (Braun & Clarke, 2006), it is revealed that their lesson preparation, decision-making, and reflective practices were influenced by SRL processes like planning, monitoring, and reflection.  Simultaneously, TA beliefs, which emphasize usefulness and ease of use, increased self-assurance, motivation, and digital tool experimentation.  The findings show that both SRL and TA contributed to the development of TPACK by providing the necessary metacognitive support and motivation, respectively. Therefore, to support technology-enhanced pedagogy, teacher education programs ought to promote reflective SRL practices and constructive TA beliefs

Keywords

Self-Regulated Learning, Technology Acceptance, TPACK, EFL Student Teachers, Teaching Practicum

Article Details

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How to Cite
Dewi, N. S. N., & Supriyono, Y. (2026). Exploring the Role of Self-Regulated Learning and Technology Acceptance in Shaping EFL Student Teachers’ TPACK during Teaching Practicum. ELITE JOURNAL, 8(1), 85-96. Retrieved from https://elitejournal.org/index.php/ELITE/article/view/310

References

  1. Brenner, R. (2022). Supporting self-regulated learning in teacher education: A motivational perspective. Smart Learning Environments, 9(1), 1–16. https://doi.org/10.1186/s40561-021-00184-5
  2. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008
  3. Galimova, E., Chernyavskaya, O., Tareva, E., Zadorozhnaya, O., & Sabitova, R. (2024). Technology acceptance in teacher education: A systematic review and bibliometric analysis. Frontiers in Education, 9, 1436724. https://doi.org/10.3389/feduc.2024.1436724
  4. Granić, A. (2023). Examining determinants of technology acceptance in education: A meta-analysis. In L. Uden, D. Liberona, & Y. H. Tao (Eds.), Learning technology for education challenges (pp. 153–167). Springer. https://doi.org/10.1007/978-981-19-2080-6_11
  5. Hsu, P.-S. (2016). Examining current beliefs, practices and barriers about technology integration: A case study. TechTrends, 60(1), 30–40. https://doi.org/10.1007/s11528-015-0014-3
  6. Mishra, P., & Koehler, M. J. (2006). Technological pedagogical content knowledge: A framework for teacher knowledge. Teachers College Record, 108(6), 1017–1054. https://doi.org/10.1111/j.1467-9620.2006.00684.x
  7. Mouza, C., Yang, H., Pan, Y. C., Ozden, S. Y., & Pollock, L. (2017). Resetting educational technology coursework for pre-service teachers: A computational thinking approach to the development of technological pedagogical content knowledge (TPACK). Australasian Journal of Educational Technology, 33(3), 61–76. https://doi.org/10.14742/ajet.3521
  8. Rodríguez-Gómez, D., Muñoz-Moreno, J. L., & Ion, G. (2024). Empowering teachers: Self-regulated learning strategies for sustainable professional development. Sustainability, 16(7), 3021. https://doi.org/10.3390/su16073021
  9. 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, 13–35. https://doi.org/10.1016/j.compedu.2018.09.009
  10. Stephenson, J., Taylor, M., Butterfield, N., & Smith, L. (2024). Supporting preservice teachers’ self-regulated learning: The impact of short-term professional learning on self-regulated learning strategies. Frontiers in Education, 9, 1451314. https://doi.org/10.3389/feduc.2024.1451314
  11. Teng, F., & Zhang, L. J. (2016). A questionnaire-based validation of multidimensional models of self-regulated learning strategies. The Modern Language Journal, 100(3), 674–701. https://doi.org/10.1111/modl.12327
  12. Teo, T. (2011). Factors influencing teachers’ intention to use technology: Model development and test. Computers & Education, 57(4), 2432–2440. https://doi.org/10.1016/j.compedu.2011.06.008
  13. Teo, T., & Yunus, M. M. (2023). Exploring teachers’ technology acceptance during the COVID-19 pandemic: A systematic review (2020–2022). Education and Information Technologies, 28(8), 8931–8956. https://doi.org/10.1007/s10639-023-11866-7
  14. Valtonen, T., Sointu, E., Kukkonen, J., Kontkanen, S., Lambert, M. C., & Makitalo-Siegl, K. (2017). TPACK updated to measure pre-service teachers’ twenty-first century skills. Australasian Journal of Educational Technology, 33(3), 15–31. https://doi.org/10.14742/ajet.3518
  15. Wang, M., Chen, Z., Xu, Y., Maheshi, B., & Gašević, D. (2025). Intelligent teaching analytics for collaborative reflection: Investigating pre-service teachers’ perceptions, experiences and shared regulation processes. International Journal of Educational Technology in Higher Education, 22(45). 1-25. https://doi.org/10.1186/s41239-025-00538-w
  16. Zimmerman, B. J. (2002). Becoming a self-regulated learner: An overview. Theory Into Practice, 41(2), 64–70. https://doi.org/10.1207/s15430421tip4102_2