Iranian EFL Instructors’ Perspectives on Integrating Artificial Intelligence Applications into English Language Teaching and Learning
Article Sidebar
EFL Instructors’ Perception,
Language Teaching and Learning,
Iran
Main Article Content
Hossein Isaee
Abstract
Background: AI tools are increasingly recognized for their potential to enhance language acquisition, personalize instruction, and improve classroom efficiency.
Aims: This study investigates the perceptions of English as a Foreign Language (EFL) instructors in Iran regarding the integration of artificial intelligence (AI) applications into teaching and learning.
Methods: A quantitative research design was employed, collecting data via a structured survey from 50 EFL instructors across public and private universities in Iran.
Result: Findings indicate that most instructors viewed AI applications positively, particularly for their ability to deliver tailored feedback, foster engagement, and adapt learning to students’ individual needs. AI-assisted tools, such as Duolingo and ELSA Speak, were noted as effective for improving pronunciation, grammar, and vocabulary. However, challenges such as limited technological infrastructure, potential cultural mismatches in content, and high implementation costs were also highlighted. Statistical analysis revealed significant differences in perceptions of AI benefits based on teaching experience, but no significant differences in perceived challenges.
Conclusion: The study concludes by recommending increased teacher training, investment in localized AI resources, and strategies to ensure cultural relevance in AI-driven language learning.
Article Details
Copyright (c) 2025 Hossein Isaee
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
References
Abalkheel, A. (2021). Amalgamating Bloom’s Taxonomy and Artificial Intelligence to Face the Challenges of Online EFL Learning amid Post-COVID-19 in Saudi Arabia. International Journal of English Language and Literature Studies, 11(1), 16–30. https://ideas.repec.org/a/asi/ijells/v11y2022i1p16-30id4409.html
Akyuz, Y. (2020). Effects of Intelligent Tutoring Systems (ITS) on Personalized Learning (PL). Creative Education, 11(6), 953–978. https://doi.org/10.4236/ce.2020.116069
Barjesteh, H., & Isaee, H. (2024). Is technology an asset? Enhancing EFL learners’ vocabulary knowledge and listening comprehension through CALL. International Journal of Research in English Education, 9(1), 50–69. https://ijreeonline.com/browse.php?a_id=848andsid=1andslc_lang=fa
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 319–340.
Deng, X., & Yu, Z. (2022). A systematic review of machine-translation-assisted language learning for sustainable education. Sustainability, 14(13), 7598. https://doi.org/10.3390/su14137598
Dong, S., Wang, P., & Abbas, K. (2021). A survey on deep learning and its applications. Computer Science Review, 40, 100379. https://doi.org/10.1016/j.cosrev.2021.100379
García, I., & Pena, M. (2010). Can Machine Translation Help the Language Learner? ICT for Language Learning Conference Proceedings, 4–7. https://conference.pixel-online.net/conferences/ICT4LL2010/common/download/Proceedings_pdf/TRAD02-Garcia.pdf
Hazaymeh, W. A., Bouzenoun, A., & Remache, A. (2024). EFL instructors’ perspective on using AI applications in English as a foreign language teaching and learning. Emerging Science Journal, 8(5), 73–87. https://law.aau.ac.ae/uploads/2024/06/202406031023482.pdf
Holstein, K., McLaren, B. M., & Aleven, V. (2017). Spacle: Investigating learning across virtual and physical spaces using spatial replays. ACM International Conference Proceeding Series, 358–367. https://doi.org/10.1145/3027385.3027450
Hooda, M., Rana, C., Dahiya, O., Rizwan, A., & Hossain, M. S. (2022). Artificial Intelligence for Assessment and Feedback to Enhance Student Success in Higher Education. Mathematical Problems in Engineering, 2022, 5215722. https://doi.org/10.1155/2022/5215722
Hoseini Moghadam, M. (2023). Artificial Intelligence and the Future of University Education in Iran. Quarterly Journal of Research and Planning in Higher Education, 29(1), 1–25. https://doi.org/10.61838/irphe.29.1.1
Isaee, H., & Barjesteh, H. (2023). EFL teachers’ professional development needs: A comparative phenomenological analysis for face-to-face and online instruction. Journal of Studies in Learning and Teaching English, 12(2), 45–56. https://www.researchgate.net/publication/373757956
Isaee, H., & Barjesteh, H. (2025). Screening EFL Teachers’ and Learners’ Perceptions of Emergency Remote Teaching During COVID-19 Pandemic: A Comparative Analysis. Human Arenas, 8(2), 568–599. https://doi.org/10.1007/s42087-023-00353-7
Isaee, H., & Barjesteh, H. (2026). Exploring teachers’ and learners’ perceptions of AI-supported pedagogical tools in English language teaching. Discover Artificial Intelligence. https://doi.org/10.1007/s44163-026-00933-w
Isaee, H., Barjesteh, H., & Rad, N. F. (2024). Research Paper Integrating Brain-Based Learning Activities into Online TESOL Courses : Exploring Different Learning Styles. December.
Jiang, R. (2022). How does artificial intelligence empower EFL teaching and learning nowadays? Frontiers in Psychology, 13. https://www.frontiersin.org/articles/10.3389/fpsyg.2022.1049401
Kuning, D. S. (2019). Technology in teaching speaking skills. Journal of English Education, Literature and Linguistics, 2(1), 50–59. https://mail.ojs.stkippgri-lubuklinggau.ac.id
Lee, D., Kim, H. H., & Sung, S. H. (2023). Development research on an AI English learning support system to facilitate learner-generated context-based learning. Educational Technology Research and Development, 71(2), 629–666. https://link.springer.com/article/10.1007/s11423-022-10172-2
Manoocherzadeh, M., Isaee, H., & Barjesteh, H. (2025). Artificial intelligence in project-based learning: A systematic review. Indonesian Journal of Pedagogy and Teacher Education, 3(3), 81–91. https://ejournal.gomit.id/index.php/ijopate/article/view/502
Marandi, S. S., & Hosseini, S. (2024). AI-Driven Assessment in Iranian High School English Classes. 11th International and the 17th National Conference on E-Learning and E-Teaching, ICeLeT 2024, 1–3. https://doi.org/10.1109/ICeLeT62507.2024.10493060
Mohammadi, S. E., Ghasemi, S. A., & Abbasi Nami, H. (2025). The application of artificial intelligence in school management (education). Sociology of Education, 10(3), 249–260. https://www.iase-jrn.ir/article_719989_86ea3bcd4630099ce8ee830716292607.pdf
Niño, A. (2020). Exploring the use of online machine translation for independent language learning. Research in Learning Technology, 28, 1–32.
Olyaee, S., Montazer, G. A., & Hosseini Moghaddam, M. (2024). Policy recommendations for the realization of intelligent higher education in Iran. Journal of Science and Technology Policy, 17(2), 69–88.
Opyr, M., Dobrovolska, S., & Panchyshyn, S. (2022). Artificial intelligence for learning English.
Risdianto, E., Shirzadi, S., Rad, N. F., Barjesteh, H., & Isaee, H. (2025). Advancing English Language Education through Artificial Intelligence: A Review of Benefits and Challenges. Journal of New Trends in English Language Learning, 4. https://doi.org/10.57647/JNTELL.2025.si-01
Rogers, E. M. (2003). Diffusion of Innovations (5th ed.). Free Press.
Schmidt, T., & Strassner, T. (2022). Artificial intelligence in foreign language learning and teaching. Anglistik, 33(1), 165–184. https://doi.org/10.33675/angl/2022/1/14
Sumakul, D. T. Y. G., Hamied, F. A., & Sukyadi, D. (2022). Artificial Intelligence in EFL Classrooms: Friend or Foe? LEARN Journal: Language Education and Acquisition Research Network, 15(1), 232–256.
Vorobiev, N. S., Gornostaev, P. B., Lozovoi, V. I., Smirnov, A. V, Shashkov, E. V, & Schelev, M. Y. (2016). A PS-1/S1 picosecond streak camera in experimental physics. Instruments and Experimental Techniques, 59(4), 551–556. https://doi.org/10.1134/S0020441216030246
Wang, X., Liu, Q., Pang, H., Tan, S. C., Lei, J., Wallace, M. P., & Li, L. (2023). What matters in AI-supported learning. Computers & Education, 194, 104703. https://doi.org/10.1016/j.compedu.2022.104703