Research Article

‘It is not the same as a classroom teacher’: A qualitative study of foreign language teachers’ perspectives on artificial intelligence-supported tools in Kazakhstan

Akmarzhan Nogaibayeva 1 , Gaukhar Yersultanova 1 2 *
More Detail
1 SDU University, Almaty, KAZAKHSTAN2 Abai Kazakh National Pedagogical University, Almaty, KAZAKHSTAN* Corresponding Author
Contemporary Educational Technology, 17(4), October 2025, ep599, https://doi.org/10.30935/cedtech/17405
Published: 10 November 2025
OPEN ACCESS   1095 Views   676 Downloads
Download Full Text (PDF)

ABSTRACT

This study explores secondary school teachers’ perspectives on artificial intelligence (AI)-supported tools through qualitative in-depth interviews with 16 teachers of English as a foreign language in Kazakhstan. The research aimed to understand teachers’ views on pedagogy, their knowledge of AI, and their perceptions of its opportunities and limitations. Findings revealed that teachers were largely pragmatic and open to adopting new digital tools; however, concerns arose regarding scenarios where AI might diminish the teacher’s role. The practical implication of the study suggests that AI-supported tools should be framed as context-specific contributors to learning, rather than as transformative innovations. The qualitative approach was chosen to address the challenge of limited teacher familiarity with AI, enabling interviewers to clarify concepts and provide demonstrations during discussions. Kazakhstan’s bilingual and trilingual education system provided a unique context for this study. Education reform, often associated with technology, has been a focus in the post-Soviet era, though the system remains relatively centralized compared to OECD countries. Notably, better-resourced Nazarbayev Intellectual Schools serve as a model for trilingual secondary education. Teachers reported access to continuing professional development opportunities and ICT-related training, with classrooms typically equipped with projection devices, IT rooms, and sometimes tablets. Students’ use of mobile phones in schools was regulated but permitted for specific educational purposes. This research highlights the importance of positioning AI tools as augmentative technologies, emphasizing their role in supporting rather than replacing teachers in enhancing educational outcomes.
Keywords: AI, language learning, teacher perspectives, teaching and learning

CITATION (APA)

Nogaibayeva, A., & Yersultanova, G. (2025). ‘It is not the same as a classroom teacher’: A qualitative study of foreign language teachers’ perspectives on artificial intelligence-supported tools in Kazakhstan. Contemporary Educational Technology, 17(4), ep599. https://doi.org/10.30935/cedtech/17405

REFERENCES

  1. Aghaziarati, A., Nejatifar, S., & Abedi, A. (2023). Artificial Intelligence in education: Investigating teacher attitudes. AI and Tech in Behavioral and Social Sciences, 1(1), 35–42. https://doi.org/10.61838/kman.aitech.1.1.6
  2. Alghamdy, R. Z. (2023). Pedagogical and ethical implications of artificial intelligence in EFL context: A review study. English Language Teaching, 16(10), 1–87. https://doi.org/10.5539/elt.v16n10p87
  3. Almanea, M. (2024). Instructors’ and learners’ perspectives on using ChatGPT in English as a foreign language courses and its effect on academic integrity. Computer Assisted Language Learning. https://doi.org/10.1080/09588221.2024.2410158
  4. Bahri, H., & Mahadi, T. S. T. (2016). The application of mobile devices in the translation classroom. Advances in Language and Literary Studies, 7(6), 237–242. https://doi.org/10.7575/aiac.alls.v.7n.6p.237
  5. Banaeian, H., & Gilanlioglu, I. (2021). Influence of the NAO robot as a teaching assistant on university students’ vocabulary learning and attitudes. Australasian Journal of Educational Technology, 37(3), 71–87. https://doi.org/10.14742/ajet.6130
  6. Barrett, A., & Pack, A. (2023). Not quite eye to AI: Student and teacher perspectives on the use of generative artificial intelligence in the writing process. International Journal of Educational Technology in Higher Education, 20(1), Article 59. https://doi.org/10.1186/s41239-023-00427-0
  7. Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa
  8. Bretag, T., Harper, R., Burton, M., Ellis, C., Newton, P., Rozenberg, P., Saddiqui, S., & van Haeringen, K. (2019). Contract cheating: A survey of Australian university students. Studies in Higher Education, 44(11), 1837–1856. https://doi.org/10.1080/03075079.2018.1462788
  9. Burstein, J. (2023). The Duolingo English Test Responsible AI Standards. https://go.duolingo.com/ResponsibleAI
  10. Cancino, M., & Panes, J. (2021). The impact of Google Translate on L2 writing quality measures: Evidence from Chilean EFL high school learners. System, 98, Article 102464. https://doi.org/10.1016/j.system.2021.102464
  11. Cojean, S., Brun, L., Amadieu, F., & Dessus, P. (2023). Teachers’ attitudes towards AI: What is the difference with non-AI technologies? In Proceedings of the Annual Meeting of the Cognitive Science Society.
  12. Cope, B., Kalantzis, M., & Searsmith, D. (2021). Artificial intelligence for education: Knowledge and its assessment in AI-enabled learning ecologies. Educational Philosophy and Theory, 53(12), 1229–1245. https://doi.org/10.1080/00131857.2020.1728732
  13. Cuban, L. (2023). The enduring classroom: Teaching then and now. University of Chicago Press. https://doi.org/10.7208/chicago/9780226828824.001.0001
  14. Cukurova, M., Miao, X., & Brooker, R. (2023). Adoption of artificial intelligence in schools: Unveiling factors influencing teachers’ engagement. In N. Wang, G. Rebolledo-Mendez, N. Matsuda, O. C. Santos, & V. Dimitrova (Eds.), Artificial intelligence in education. AIED 2023. Lecture notes in computer science (), vol 13916 (pp. 151–163). Springer. https://doi.org/10.1007/978-3-031-36272-9_13
  15. Dizon, G. (2023). Affordances and constraints of intelligent personal assistants for second-language learning. RELC Journal, 54(3), 848–855. https://doi.org/10.1177/00336882211020548
  16. Dizon, G., Tang, D., & Yamamoto, Y. (2022). A case study of using Alexa for out-of-class, self-directed Japanese language learning. Computers and Education: Artificial Intelligence, 3, Article 100088. https://doi.org/10.1016/j.caeai.2022.100088
  17. Fathi, J., & Rahimi, M. (2024). Utilising artificial intelligence-enhanced writing mediation to develop academic writing skills in EFL learners: A qualitative study. Computer Assisted Language Learning. https://doi.org/10.1080/09588221.2024.2374772
  18. Galindo-Domínguez, H., Delgado, N., Campo, L., & Losada, D. (2024). Relationship between teachers’ digital competence and attitudes towards artificial intelligence in education. International Journal of Educational Research, 126, Article 102381. https://doi.org/10.1016/j.ijer.2024.102381
  19. Guilherme, A. (2019). AI and education: The importance of teacher and student relations. AI & SOCIETY, 34, 47–54. https://doi.org/10.1007/s00146-017-0693-8
  20. Haristiani, N. (2019). Artificial intelligence (AI) chatbot as language learning medium: An inquiry. Journal of Physics: Conference Series, 1387(1), Article 012020. https://doi.org/10.1088/1742-6596/1387/1/012020
  21. Holmes, W. (2023). Asian & European teachers’ perspectives on AI and education. Asia-Europe Foundation. https://asef.org/publications/asian-and-european-teachers-perspectives-on-ai-and-education/
  22. Holmes, W., & Miao, F. (2023). Guidance for generative AI in education and research. Unesco Publishing.
  23. Hopcan, S., Türkmen, G., & Polat, E. (2023). Exploring the artificial intelligence anxiety and machine learning attitudes of teacher candidates. Education and Information Technologies, 29, 7281–7301. https://doi.org/10.1007/s10639-023-12086-9
  24. Huang, H.-W., Li, Z., & Taylor, L. (2020). The effectiveness of using Grammarly to improve students’ writing skills. In Proceedings of the 5th International Conference on Distance Education and Learning (pp. 122–127). https://doi.org/10.1145/3402569.3402594
  25. Jiang, R. (2022). How does artificial intelligence empower EFL teaching and learning nowadays? A review on artificial intelligence in the EFL context. Frontiers in Psychology, 13. https://doi.org/10.3389/fpsyg.2022.1049401
  26. Karabassova, L. (2020). Understanding trilingual education reform in Kazakhstan: Why is it stalled? In D. Egea (Ed.), Education in Central Asia: A kaleidoscope of challenges and opportunities (pp. 37–51). https://doi.org/10.1007/978-3-030-50127-3_3
  27. Kim, N. J., & Kim, M. K. (2022). Teacher’s perceptions of using an artificial intelligence-based educational tool for scientific writing. Frontiers in Education, 7. https://doi.org/10.3389/feduc.2022.755914
  28. Kimmons, R., & Veletsianos, G. (2018). Public internet data mining methods in instructional design, educational technology, and online learning research. TechTrends, 62(5), 492–500. https://doi.org/10.1007/s11528-018-0307-4
  29. Kirkpatrick, A. W. (2022). Communicating proximity: The effects of technology media on information sharing about artificial intelligence. Washington State University.
  30. Kohnke, L., Moorhouse, B. L., & Zou, D. (2023). Exploring generative artificial intelligence preparedness among university language instructors: A case study. Computers and Education: Artificial Intelligence, 5, Article 100156. https://doi.org/10.1016/j.caeai.2023.100156
  31. Koltovskaia, S., Rahmati, P., & Saeli, H. (2024). Graduate students’ use of ChatGPT for academic text revision: Behavioral, cognitive, and affective engagement. Journal of Second Language Writing, 65, Article 101130. https://doi.org/10.1016/j.jslw.2024.101130
  32. Korstjens, I., & Moser, A. (2017). Series: Practical guidance to qualitative research. Part 4: Trustworthiness and publishing. European Journal of General Practice, 24(1), 120–124. https://doi.org/10.1080/13814788.2017.1375092
  33. Kostka, I., & Toncelli, R. (2023). Exploring applications of ChatGPT to English language teaching: Opportunities, challenges, and recommendations. TESL-EJ, 27(3). https://doi.org/10.55593/ej.27107int
  34. Lee, S.-M. (2020). The impact of using machine translation on EFL students’ writing. Computer Assisted Language Learning, 33(3), 157–175. https://doi.org/10.1080/09588221.2018.1553186
  35. Liang, J.-C., Hwang, G.-J., Chen, M.-R. A., & Darmawansah, D. (2023). Roles and research foci of artificial intelligence in language education: An integrated bibliographic analysis and systematic review approach. Interactive Learning Environments, 31(7), 4270–4296. https://doi.org/10.1080/10494820.2021.1958348
  36. Lindner, A., Romeike, R., Jasute, E., & Pozdniakov, S. (2019). Teachers’ perspectives on artificial intelligence [Paper presentation]. The 12th International Conference on Informatics in Schools.
  37. Lo, S. (2023). Neural machine translation in EFL classrooms: Learners’ vocabulary improvement, immediate vocabulary retention and delayed vocabulary retention. Computer Assisted Language Learning, 38(3), 592–611. https://doi.org/10.1080/09588221.2023.2207603
  38. Luckin, R., & Holmes, W. (2016). Intelligence unleashed: An argument for AI in education. Pearson.
  39. Miao, F., Holmes, W., Huang, R., & Zhang, H. (2021). AI and education: A guidance for policymakers. UNESCO.
  40. Nazaretsky, T., Cukurova, M., Ariely, M., & Alexandron, G. (2021). Confirmation bias and trust: Human factors that influence teachers’ attitudes towards AI-based educational technology. In Proceedings of the 16th European Conference on Technology Enhanced Learning. AI for Blended-Learning: Empowering Teachers in Real Classrooms Workshop. Springer. https://doi.org/10.35542/osf.io/dzqju
  41. Nogaibayeva, A., Yersultanova, G., Tas, M., Ozkan, A., & Yildiztas, A. (2024). The ecological framework of ICT used in teaching and learning: A case study in Kazakhstan. Forum for Linguistic Studies, 6(6), 863–875. https://doi.org/10.30564/fls.v6i6.7234
  42. Nunan, D. (2003). The impact of English as a global language on educational policies and practices in the Asia‐Pacific Region. TESOL Quarterly, 37(4), 589–613. https://doi.org/10.2307/3588214
  43. OECD. (2019). Country note: Results from Talis 2018. OECD. https://www.oecd.org/countries/kazakhstan/TALIS2018_CN_KAZ.pdf
  44. Perrotta, C., & Selwyn, N. (2020). Deep learning goes to school: Toward a relational understanding of AI in education. Learning, Media and Technology, 45(3), 251–269. https://doi.org/10.1080/17439884.2020.1686017
  45. Rudolph, J., Tan, S., & Tan, S. (2023). ChatGPT: Bullshit spewer or the end of traditional assessments in higher education? Journal of Applied Learning and Teaching, 6(1). https://doi.org/10.37074/jalt.2023.6.1.9
  46. Rus, D., Pusnei, I., & Stefanovici, S. (2024). Navigating the digital frontier: Teacher attitudes towards AI in language education. In Proceedings of the Interdisciplinarity in Engineering Conference (pp. 449–458). Springer. https://doi.org/10.1007/978-3-031-54671-6_33
  47. Sarrafzadeh, B., Jauhar, S. K., Gamon, M., Lank, E., & White, R. W. (2021). Characterizing stage-aware writing assistance for collaborative document authoring. Proceedings of the ACM on Human-Computer Interaction, 4(CSCW3), 1–29. https://doi.org/10.1145/3434180
  48. Sudina, E., & Plonsky, L. (2024). The effects of frequency, duration, and intensity on L2 learning through Duolingo: A natural experiment. Journal of Second Language Studies, 7(1), 1–43. https://doi.org/10.1075/jsls.00021.plo
  49. Sütçü, S. S., & Sütçü, E. (2023). English teachers’ attitudes and opinions towards artificial intelligence. International Journal of Research in Teacher Education, 14(3), 183–193.
  50. Turing, A. (1950). Computing machinery and intelligence. Mind, 59, 433–460. https://doi.org/10.1093/mind/LIX.236.433
  51. Ulla, M. B., Perales, W. F., & Busbus, S. O. (2023). ‘To generate or stop generating response’: Exploring EFL teachers’ perspectives on ChatGPT in English language teaching in Thailand. Learning: Research and Practice, 9(2), 168–182. https://doi.org/10.1080/23735082.2023.2257252
  52. Urlaub, P., & Dessein, E. (2022). Machine translation and foreign language education. Frontiers in Artificial Intelligence, 5. https://doi.org/10.3389/frai.2022.936111
  53. VanLehn, K. (2011). The relative effectiveness of human tutoring, intelligent tutoring systems, and other tutoring systems. Educational Psychologist, 46(4), 197–221. https://doi.org/10.1080/00461520.2011.611369
  54. Velander, J., Taiye, M. A., Otero, N., & Milrad, M. (2023). Artificial intelligence in K-12 Education: Eliciting and reflecting on Swedish teachers’ understanding of AI and its implications for teaching & learning. Education and Information Technologies, 29, 4085–4105. https://doi.org/10.1007/s10639-023-11990-4
  55. Williamson, B., & Piattoeva, N. (2018). Objectivity as standardization in data-scientific education policy, technology and governance. Learning, Media and Technology, 44(1), 64–76. https://doi.org/10.1080/17439884.2018.1556215
  56. Wilson, A., Watson, C., Thompson, T. L., Drew, V., & Doyle, S. (2017). Learning analytics: Challenges and limitations. Teaching in Higher Education, 22(8), 991–1007. https://doi.org/10.1080/13562517.2017.1332026
  57. Yakavets, N. (2014). Educational reform in Kazakhstan: The first decade of independence. Cambridge University Press.
  58. Yue, M., Jong, M. S. Y. & Ng, D. T. K. (2024). Understanding K-12 teachers’ technological pedagogical content knowledge readiness and attitudes toward artificial intelligence education. Education and Information Technologies, 29, 19505–19536. https://doi.org/10.1007/s10639-024-12621-2
  59. Yueh, H.-P., & Chiang, F.-K. (2020). AI and robotics in reshaping the dynamics of learning. British Journal of Educational Technology, 51(5), 1804–1807. https://doi.org/10.1111/bjet.13017
  60. Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education – where are the educators? International Journal of Educational Technology in Higher Education, 16, Article 39. https://doi.org/10.1186/s41239-019-0171-0
  61. Zhu, X. (2020). Machine translation in foreign language learning classroom-learners’ indiscriminate use or instructors’ discriminate stance. English Linguistics Research, 9(4), 1−5. https://doi.org/10.5430/elr.v9n4p1