Ranau Primary School Teachers’ Perceptions of Artificial Intelligence Integration in English as a Second Language Classroom

Authors

Jester Daniel Jayes

Faculty of Education, National University Malaysia, Sekolah Kebangsaan St. Benedict, Ranau (Malaysia)

Melor Mohd Yunus

Faculty of Education, National University (Malaysia)

Harwati Hashim

Faculty of Education, National University (Malaysia)

Article Information

DOI: 10.47772/IJRISS.2026.10100525

Subject Category: Education

Volume/Issue: 10/1 | Page No: 6796-6806

Publication Timeline

Submitted: 2026-01-21

Accepted: 2026-01-29

Published: 2026-02-16

Abstract

In ESL education, practitioners now recognizing Artificial Intelligence (AI) as a tool to improve student engagement and provide personalized learning experiences while also increasing the efficiency of instruction. On the other hand, for AI to be effectively integrated into classrooms, it is essential that teachers accept the technology, particularly in lower-resourced, rural environments. Therefore, this study seeks to investigate the perceptions of primary ESL school teachers in Ranau, Sabah regarding the incorporation of AI into their classrooms through an examination of attitudes surrounding perceived usefulness (PU) and perceived ease of use (PEOU) guided by Technology Acceptance Model (TAM). The research implemented a quantitative exploratory approach that utilizes surveys with 12 ESL Teachers from 4 primary schools located within the rural areas. The results analysed teachers' responses to the survey to determine any trends based on teachers' perceptions of using AI in the classroom. The results of this study indicate that teachers perceive AI as supportive teaching and learning tool. Respondents’ confidence level of their ability to learn using AI tools was considered moderate. In addition, comments arose regarding the integration of AI in the classroom, long-term skill development, and a need for sufficient cognitive effort when utilising AI.

Keywords

Artificial intelligence in education, English as a Second Language (ESL), Technology Acceptance Model (TAM), Teachers’ perceptions

Downloads

References

1. Adeshola, I., & Adepoju, A. P. (2023). The impact of artificial intelligence-based applications on student engagement and learning outcomes. Education and Information Technologies, 28(3), 3291–3310. [Google Scholar] [Crossref]

2. Al-Smadi, M. K., Qawasmeh, O. A., & Altarawneh, H. (2024). Artificial intelligence in education: Teachers’ perspectives and instructional implications. Journal of Educational Technology Systems, 52(1), 3–21. [Google Scholar] [Crossref]

3. Amdan, N. A., Ismail, I., & Abdullah, M. Y. (2024). Technology integration challenges in rural Malaysian schools. Malaysian Journal of Learning and Instruction, 21(1), 45–63. [Google Scholar] [Crossref]

4. Bressane, A., Marques, B. P., & Pimentel, M. (2023). Factors influencing teachers’ ease of use of educational technologies. Computers & Education, 190, 104600. [Google Scholar] [Crossref]

5. Chan, C. K. Y., & Tsi, M. K. (2023). Professional development and teachers’ confidence in educational technology adoption. Teaching and Teacher Education, 118, 103827. [Google Scholar] [Crossref]

6. Chen, J., Liu, L., & Cheng, Y. (2020). Technology acceptance in lesson planning: An empirical study. Educational Technology Research and Development, 68(4), 1881–1902. [Google Scholar] [Crossref]

7. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. [Google Scholar] [Crossref]

8. Enríquez, M. A., Gómez, R. L., & Rueda, M. M. (2024). Teachers’ perceptions of AI-supported instruction in language education. System, 120, 103127. [Google Scholar] [Crossref]

9. Filiz, S., Yildiz, E. P., & Yilmaz, R. (2025). Ethical concerns and teacher attitudes toward artificial intelligence in education. Educational Technology & Society, 28(1), 1–14. [Google Scholar] [Crossref]

10. Gentile, M., La Marca, A., & Longo, L. (2023). Teachers’ perceptions of AI as a time-saving tool in education. Education Sciences, 13(6), 573. [Google Scholar] [Crossref]

11. Gustilo, L. E., Lapitan, L. D., & De Vera, P. V. (2024). Teachers’ attitudes toward artificial intelligence in language classrooms. Asian EFL Journal, 28(2), 34–52. [Google Scholar] [Crossref]

12. Harry, M., & Sayudin, N. (2023). Digital literacy and technology resistance among teachers. Journal of Language and Education, 9(4), 45–58. [Google Scholar] [Crossref]

13. Holden, R. J., & Rada, R. (2011). Understanding the influence of perceived usability and usefulness. International Journal of Human–Computer Interaction, 27(4), 365–386. [Google Scholar] [Crossref]

14. Huertas-Abril, C. A., & Palacios-Hidalgo, F. J. (2023). Artificial intelligence in EFL writing: Opportunities and risks. Language Learning & Technology, 27(2), 1–15. [Google Scholar] [Crossref]

15. Jose, J., & Jose, R. (2024). Digital tools and learner motivation in Malaysian ESL classrooms. Malaysian Journal of ELT Research, 21(1), 67–84. [Google Scholar] [Crossref]

16. Khandaker, M. S. A., & Aktaruzzaman, M. (2025). Revisiting TAM in AI-based educational systems. Interactive Learning Environments, 33(1), 112–128. [Google Scholar] [Crossref]

17. Klímová, B., Pikhart, M., & Cierniak-Emerych, A. (2023). Artificial intelligence tools in language education: Teacher workload and pedagogical implications. Education and Information Technologies, 28(5), 5871–5890. [Google Scholar] [Crossref]

18. Kohnke, L., Zou, D., & Zhang, R. (2023). Teachers’ readiness for artificial intelligence in language education. Computer Assisted Language Learning, 36(5–6), 1097–1120. [Google Scholar] [Crossref]

19. Ma, Q., Gao, X., & Teng, M. F. (2024). Teachers’ acceptance of AI in language teaching: A TAM-based study. System, 118, 102974. [Google Scholar] [Crossref]

20. Maghsudi, M., Lan, A. S., Xu, J., & Brunskill, E. (2021). Personalized learning with artificial intelligence. Educational Data Mining, 13(1), 20–38. [Google Scholar] [Crossref]

21. Maola, J., Mphahlele, R., & Kheswa, J. (2024). Teachers’ perceptions of usability in educational technologies. Journal of Educational Computing Research, 62(1), 89–108. [Google Scholar] [Crossref]

22. Niemi, H., Pehkonen, E., & Pyhältö, K. (2022). Digital pedagogy and feedback in language learning. Teaching and Teacher Education, 109, 103548. [Google Scholar] [Crossref]

23. Park, S. Y. (2009). An analysis of the technology acceptance model in online learning environments. Educational Technology & Society, 12(3), 150–162. [Google Scholar] [Crossref]

24. Phan, T. T. T. (2023). Artificial intelligence and learner autonomy in EFL contexts. TESOL Quarterly, 57(2), 623–641. [Google Scholar] [Crossref]

25. Phua, P. K., Lim, S. W., & Tan, C. K. (2025). Ethical governance of artificial intelligence in education. AI & Society, 40(1), 77–90. [Google Scholar] [Crossref]

26. Rukiati, E., Andayani, A., & Nurkamto, J. (2023). AI-assisted learning and ESL development. Journal of Language Teaching and Research, 14(2), 356–365. [Google Scholar] [Crossref]

27. Rusmiyanto, R., Fauzi, I., & Sari, D. P. (2023). Gamified AI applications in ESL classrooms. International Journal of Instruction, 16(4), 451–468. [Google Scholar] [Crossref]

28. Sánchez-Prieto, J. C., Olmos-Migueláñez, S., & García-Peñalvo, F. J. (2020). Technology acceptance among teachers. Computers in Human Behavior, 108, 106309. [Google Scholar] [Crossref]

29. Teo, T. (2011). Factors influencing teachers’ intention to use technology. Computers & Education, 57(4), 2432–2440. [Google Scholar] [Crossref]

30. Tiwari, S. (2024). Artificial intelligence in second language education: Trends and implications. ELT Journal, 78(1), 54–63. [Google Scholar] [Crossref]

31. Uwosomah, J. C., & Dooly, M. (2025). Teachers’ perspectives on AI-mediated language learning. ReCALL, 37(1), 1–18. [Google Scholar] [Crossref]

32. Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and a research agenda. Decision Sciences, 39(2), 273–315. [Google Scholar] [Crossref]

33. Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model. Management Science, 46(2), 186–204. [Google Scholar] [Crossref]

34. Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology. MIS Quarterly, 27(3), 425–478. [Google Scholar] [Crossref]

35. Wafa, A., & Hussain, A. (2021). Artificial intelligence concepts and applications in education. Journal of Educational Computing Research, 59(5), 841–859. [Google Scholar] [Crossref]

36. Wang, Y., Li, H., & Chen, X. (2024). Institutional support and AI adoption in schools. Educational Technology Research and Development, 72(1), 89–107. [Google Scholar] [Crossref]

37. Wijayati, P. H., Bharati, D. A. L., & Rukmini, D. (2022). Artificial intelligence in English language teaching. English Education Journal, 12(3), 321–333. [Google Scholar] [Crossref]

38. Yang, X., Li, J., & Sun, Y. (2025). Teacher professional development for AI integration. Teaching and Teacher Education, 127, 104064. [Google Scholar] [Crossref]

39. Zhang, R., & Aslan, A. B. (2021). AI-supported content generation in language teaching. Computer Assisted Language Learning, 34(5–6), 769–795. [Google Scholar] [Crossref]

40. Zhou, M., Xu, Y., & Zhai, X. (2024). Artificial intelligence and feedback in language learning. Language Learning & Technology, 28(1), 85–102. [Google Scholar] [Crossref]

Metrics

Views & Downloads

Similar Articles