Vol. 3 No. 03 (2026): INTERNATIONAL JOURNAL OF SCIENCE AND TECHNOLOGY
Articles

TEACHERS' PERCEPTIONS OF AI TOOLS IN UNIVERSITY EFL CLASSROOMS: A CROSS-FACULTY STUDY AT FERGANA STATE UNIVERSITY

PDF
  • Toshmatov Alimardon
Toshmatov Alimardon
a senior lecturer at Fergana State University

Published 17-02-2026

Keywords

  • artificial intelligence, EFL teaching, teacher perceptions, technology acceptance, higher education, Central Asia
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

TEACHERS’ PERCEPTIONS OF AI TOOLS IN UNIVERSITY EFL CLASSROOMS: A CROSS-FACULTY STUDY AT FERGANA STATE UNIVERSITY. (2026). INTERNATIONAL JOURNAL OF SCIENCE AND TECHNOLOGY, 3(03), 26-38. https://doi.org/10.70728/tech.v3.i03.006

Abstract

This mixed-methods study investigates teachers' perceptions of artificial intelligence (AI) tools in English as a Foreign Language (EFL) instruction across three faculties at Fergana State University in Uzbekistan. Drawing on the Technology Acceptance Model (TAM) and contemporary literature on AI in education, the research examines how 67 EFL teachers from the Economy, Science, and English Language and Literature faculties perceive the usefulness, challenges, and integration potential of AI tools such as ChatGPT, Grammarly, and QuillBot. Data were collected through a structured questionnaire (n=67) and semi-structured interviews (n=15). Findings reveal that while teachers across all faculties acknowledge AI tools' utility for lesson preparation and feedback generation, significant concerns persist regarding academic integrity, student dependency, and assessment validity. Notably, faculty-specific differences emerged: Economy faculty teachers view AI pragmatically as a professional communication aid, Science faculty teachers express cautious optimism about simplifying technical texts, and English Language and Literature faculty teachers demonstrate heightened concerns about preserving authorial voice and critical thinking. The study contributes to understanding AI integration in non-Western higher education contexts and offers practical recommendations for faculty-specific professional development, institutional policy frameworks, and pedagogical adaptation in AI-rich environments.

PDF

References

  1. Airey, J. (2016). EAP, EMI or CLIL? In K. Hyland & P. Shaw (Eds.), The Routledge handbook of English for academic purposes (pp. 71-83). Routledge.
  2. Aripova, M., & Khamidov, O. (2020). Higher education reforms in Uzbekistan: Toward a new quality assurance system. Higher Education in Russia and Beyond, 2(24), 12-14.
  3. Basturkmen, H. (2019). ESP teacher education needs. Language Teaching, 52(3), 318-330. https://doi.org/10.1017/S0261444817000398
  4. Bin-Hady, W. R. A., Al-Kadi, A., Hazaea, A., & Ali, J. K. M. (2023). Exploring the dimensions of ChatGPT in English language learning: A global perspective. Library Hi Tech. Advance online publication. https://doi.org/10.1108/LHT-05-2023-0200
  5. Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77-101. https://doi.org/10.1191/1478088706qp063oa
  6. Cotton, D. R. E., Cotton, P. A., & Shipway, J. R. (2023). Chatting and cheating: Ensuring academic integrity in the era of ChatGPT. Innovations in Education and Teaching International, 61(2), 228-239. https://doi.org/10.1080/14703297.2023.2190148
  7. Creswell, J. W., & Plano Clark, V. L. (2018). Designing and conducting mixed methods research (3rd ed.). SAGE Publications.
  8. Crompton, H., & Burke, D. (2023). Artificial intelligence in higher education: The state of the field. International Journal of Educational Technology in Higher Education, 20, Article 22. https://doi.org/10.1186/s41239-023-00392-8
  9. 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
  10. Fitria, T. N. (2021). QuillBot as an online tool: Students' alternative in paraphrasing and re-writing of English writing. Englisia: Journal of Language, Education, and Humanities, 9(1), 183-196. https://doi.org/10.22373/ej.v9i1.10233
  11. Fitria, T. N. (2023). Artificial intelligence (AI) in education: Using AI tools for teaching and learning process. Prosiding Seminar Nasional & Call for Paper STIE AAS, 6(1), 134-147.
  12. Gao, X., Wang, Y., & Peng, J. (2023). Understanding language teachers' adoption of generative AI in education: Perspectives from China. System, 119, Article 103176. https://doi.org/10.1016/j.system.2023.103176
  13. Grassini, S. (2023). Shaping the future of education: Exploring the potential and consequences of AI and ChatGPT in educational settings. Education Sciences, 13(7), Article 692. https://doi.org/10.3390/educsci13070692
  14. Huang, J., Saleh, S., & Liu, Y. (2023). A review on artificial intelligence in education. Academic Journal of Interdisciplinary Studies, 12(4), 259-270. https://doi.org/10.36941/ajis-2023-0101
  15. Hyland, K. (2018). Metadiscourse: Exploring interaction in writing (2nd ed.). Bloomsbury Academic.
  16. Ilyosov, A., & Rahimov, S. (2021). Challenges and opportunities in higher education in Uzbekistan: A case study analysis. Central Asian Journal of Education, 6(2), 45-62.
  17. Kasneci, E., Seßler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., Krusche, S., Kutyniok, G., Michaeli, T., Nerdel, C., Pfeffer, J., Poquet, O., Sailer, M., Schmidt, A., Seidel, T., ... Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103, Article 102274. https://doi.org/10.1016/j.lindif.2023.102274
  18. Khlaif, Z. N., Sanmugam, M., Joma, A. I., Odeh, A., & Barham, K. (2023). Factors influencing teacher's technostress experienced in using emerging technology: A qualitative study. Technology, Knowledge and Learning, 28(2), 865-899. https://doi.org/10.1007/s10758-022-09607-9
  19. Li, Z., Huang, J., & Lim, L. (2022). The effects of Grammarly on L2 writing: Improvement and dependence. Journal of Educational Technology & Society, 25(3), 151-163.
  20. Moorhouse, B. L., Yeo, M. A., & Wan, Y. (2023). Generative AI tools and assessment: Guidelines of the world's top-ranking universities. Computers and Education Open, 5, Article 100151. https://doi.org/10.1016/j.caeo.2023.100151
  21. Nikolic, S., Daniel, S., Haque, R., Belkina, M., Hassan, G. M., Grundy, S., Lyden, S., Neal, P., & Sandison, C. (2023). ChatGPT versus engineering education assessment: A multidisciplinary and multi-institutional benchmarking and analysis of this generative artificial intelligence tool to investigate assessment integrity. European Journal of Engineering Education, 48(4), 559-614. https://doi.org/10.1080/03043797.2023.2213169
  22. O'Neill, R., & Russell, A. M. T. (2019). Stop! Grammar time: University students' perceptions of the automated feedback program Grammarly. Australasian Journal of Educational Technology, 35(1), 42-56. https://doi.org/10.14742/ajet.3795
  23. Perkins, M., Roe, J., Postma, D., McGaughran, J., & Hickerson, D. (2023). Detection of GPT-4 generated text in higher education: Combining academic judgement and software to identify generative AI tool misuse. Journal of Academic Ethics. Advance online publication. https://doi.org/10.1007/s10805-023-09492-6
  24. Ranalli, J. (2021). Beyond the interface: How automated writing evaluation programs affect learning. Computers and Composition, 60, Article 102640. https://doi.org/10.1016/j.compcom.2021.102640
  25. 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
  26. Sullivan, M., Kelly, A., & McLaughlan, P. (2023). ChatGPT in higher education: Considerations for academic integrity and student learning. Journal of Applied Learning & Teaching, 6(1), 1-10. https://doi.org/10.37074/jalt.2023.6.1.17
  27. Teo, T., Zhou, M., Fan, A. C. W., & Huang, F. (2019). Factors that influence university students' intention to use Moodle: A study in Macau. Educational Technology Research and Development, 67(3), 749-766. https://doi.org/10.1007/s11423-019-09650-x
  28. Tondeur, J., van Braak, J., Ertmer, P. A., & Ottenbreit-Leftwich, A. (2017). Understanding the relationship between teachers' pedagogical beliefs and technology use in education: A systematic review of qualitative evidence. Educational Technology Research and Development, 65(3), 555-575. https://doi.org/10.1007/s11423-016-9481-2
  29. Yan, D. (2023). Impact of ChatGPT on learners in a L2 writing practicum: An exploratory investigation. Education and Information Technologies. Advance online publication. https://doi.org/10.1007/s10639-023-12137-8