Revolutionizing EFL Classrooms in Iran: Harnessing AI Tools for Personalized Language Learning
Subject Areas : Second Language Education
fatemeh Sadat alamdar
1
*
,
abdolhamid mohammadi
2
,
Shahram Afraz
3
,
Fazlolah Samimi
4
1 - Department of Education, Ministry of Education, Hormozgan Province, Iran
2 - Faculty Member, Bandar Abbas University of Medical Sciences, Hormozgan Province, Iran
3 - Assistant Professor of TEFL, Department of English Language, Qeshm Branch, Islamic Azad University, Qeshm, Iran
4 - Department of English, Bandar-Abbas Branch, Islamic Azad University, Bandar-Abbas, Iran
Keywords: Artificial Intelligence, Educational Technology, Personalized Learning, EFL, learning,
Abstract :
ChatGPT and other AI technologies employed in Iranian EFL classrooms can enhance individualized learning but are constrained by technical, cultural, and organizational limitations. The current study examines their effects on students' engagement and individualized feedback in terms of a mixed-methods design comprising interviews, classroom observations, and Technology Acceptance Model-based questionnaires administered among 100 instructors and 100 students. Evidence indicates that ChatGPT increases student engagement through instant feedback and student-focused spaces. Teachers were rated lower in its usefulness by students since they highlighted its individualized learning potential. However, limited internet penetration, inadequate teacher training, and organizational reluctance are among the most significant issues hindering adoption. Successful adoption will require specialized training of teachers, infrastructural planning, and regional AI solutions. Overcoming the challenges will derive maximum benefits from the advantages of AI in EFL learning. This study contributes to debates on AI in education in the Iranian context of EFL with both opportunities and limitations.
Akgun, S., & Greenhow, C. (2022). Artificial intelligence in education: Addressing ethical challenges in K-12 settings. AI and ethics, 2(3), 431–440. https://doi.org/10.1007/s43681-021-00096-7
AlTwijri, L., & Alghizzi, T. M. (2024). Investigating the integration of artificial intelligence in English as foreign language classes for enhancing learners' affective factors: A systematic review. Heliyon, 10(10), e31053. https://doi.org/10.1016/j.heliyon.2024.e31053
Arango-Ibanez, J. P., Posso-Nuñez, J. A., Díaz-Solórzano, J. P., & Cruz-Suárez, G. (2024). Evidence-Based Learning Strategies in Medicine Using AI. JMIR medical education, 10, e54507. https://doi.org/10.2196/54507
Arantes J. A. (2023). Personalization in Australian K-12 classrooms: how might digital teaching and learning tools produce intangible consequences for teachers' workplace conditions?. Australian educational researcher, 50(3), 863–880. https://doi.org/10.1007/s13384-022-00530-7
Arfaie, S., Sadegh Mashayekhi, M., Mofatteh, M., Ma, C., Ruan, R., MacLean, M. A., Far, R., Saini, J., Harmsen, I. E., Duda, T., Gomez, A., Rebchuk, A. D., Pingbei Wang, A., Rasiah, N., Guo, E., Fazlollahi, A. M., Rose Swan, E., Amin, P., Mohammed, S., Atkinson, J. D., … Das, S. (2024). ChatGPT and neurosurgical education: A crossroads of innovation and opportunity. Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia, 129, 110815. https://doi.org/10.1016/j.jocn.2024.110815
Atchley, P., Pannell, H., Wofford, K., Hopkins, M., & Atchley, R. A. (2024). Human and AI collaboration in the higher education environment: opportunities and concerns. Cognitive research: principles and implications, 9(1), 20. https://doi.org/10.1186/s41235-024-00547-9
Ateş, H., & Gündüzalp, C. (2025). The convergence of GETAMEL and protection motivation theory: A study on augmented reality-based gamification adoption among science teachers. Education and Information Technologies, 1-43. https://doi.org/10.1007/s10639-025-13480-1
Baharloo, A., & Miyan Baghi, A. (2024). The Impact of AI-Assisted Learning on EFL Speaking Skills: A Mixed-Methods Study in the Iranian Context. Technology Assisted Language Education, 2(4), 69-96. DOI:10.22126/tale.2025.11299.1070
Bumbach M. D. (2024). The Use of AI Powered ChatGPT for Nursing Education. The Journal of nursing education, 63(8), 564–567. https://doi.org/10.3928/01484834-20240318-04
Castonguay, A., Farthing, P., Davies, S., Vogelsang, L., Kleib, M., Risling, T., & Green, N. (2023). Revolutionizing nursing education through Ai integration: A reflection on the disruptive impact of ChatGPT. Nurse education today, 129, 105916. https://doi.org/10.1016/j.nedt.2023.105916
Chen S. L. (2024). Hu li za zhi The journal of nursing, 71(5), 4–6. https://doi.org/10.6224/JN.202410_71(5).01
Creswell, J. W., & Creswell, J. D. (2023). Research design: Qualitative, quantitative, and mixed methods approaches (6th ed.). Sage Publications.
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
Derakhshan, A., Kruk, M., Mehdizadeh, M., & Pawlak, M. (2021). Boredom in online classes in the Iranian EFL context: Sources and solutions. System, 101, 102556.
Dong, Y., Yu, X., Alharbi, A., & Ahmad, S. (2022). AI-based production and application of English multimode online reading using multi-criteria decision support system. Soft computing, 26(20), 10927–10937. https://doi.org/10.1007/s00500-022-07209-2
Dörnyei, Z. (2022). Research methods in applied linguistics: Quantitative, qualitative, and mixed methodologies. Oxford University Press.
Fan, J., & Zhang, Q. (2024). From literacy to learning: The sequential mediation of attitudes and enjoyment in AI-assisted EFL education. Heliyon, 10(17), e37158. https://doi.org/10.1016/j.heliyon.2024.e37158
Hemmati, M. R., & Aziz Malayeri, F. (2022). Iranian EFL teachers’ perceptions of obstacles to implementing student-centered learning: a mixed-methods study. International Journal of Foreign Language Teaching and Research, 10(40), 133-152.
Holmes, W., & Tuomi, I. (2022). State of the art and practice in AI in education. European Journal of Education, 57(4), 542–558. https://doi.org/10.1111/ejed.12533
Holmes, W., Bialik, M., & Fadel, C. (2022). Artificial intelligence in education: Promises and implications for teaching and learning. Center for Curriculum Redesign.
Huang H. (2023). Performance of ChatGPT on Registered Nurse License Exam in Taiwan: A Descriptive Study. Healthcare (Basel, Switzerland), 11(21), 2855. https://doi.org/10.3390/healthcare11212855
Huang, H. (2023). Performance of ChatGPT on registered nurse license exam in Taiwan: A descriptive study. Healthcare (Basel, Switzerland), 11(21), 2855. https://doi.org/10.3390/healthcare11212855
Jamshed, M., Manjur Ahmed, A. S. M., Sarfaraj, M., & Warda, W. U. (2024). The Impact of ChatGPT on English Language Learners' Writing Skills: An Assessment of AI Feedback on Mobile. International Journal of Interactive Mobile Technologies, 18(19). DOI:10.3991/ijim.v18i19.50361
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, 1049401. https://doi.org/10.3389/fpsyg.2022.1049401
Kamali, J., Paknejad, A., & Poorghorban, A. (2024). Exploring the challenges and affordances of integrating CHATGPT into language classrooms from teachers’ points of view: An ecological perspective. Journal of Applied Learning and Teaching, 7(2). DOI: https://doi.org/10.37074/jalt.2024.7.2.8
Kusuma, I. P. I. (2023). The Role of Gender in Student Teachers' Technology Integration in Teaching English Speaking Skills during the COVID-19 Pandemic. Knowledge Management & E-Learning, 15(3), 487-505. http://www.kmel-journal.org/ojs/index.php/online-publication
Lee H. (2024). The rise of ChatGPT: Exploring its potential in medical education. Anatomical sciences education, 17(5), 926–931. https://doi.org/10.1002/ase.2270
Leng L. (2024). Challenge, integration, and change: ChatGPT and future anatomical education. Medical education online, 29(1), 2304973. https://doi.org/10.1080/10872981.2024.2304973
Mohamed, A. M. (2024). Exploring the potential of an AI-based Chatbot (ChatGPT) in enhancing English as a Foreign Language (EFL) teaching: perceptions of EFL Faculty Members. Education and Information Technologies, 29(3), 3195-3217. https://doi.org/10.1007/s10639-023-11917-z
Naamati-Schneider L. (2024). Enhancing AI competence in health management: students' experiences with ChatGPT as a learning Tool. BMC medical education, 24(1), 598. https://doi.org/10.1186/s12909-024-05595-9
Naderi, N. (2010). The obstacles of managing change in the educational system of Iran: A study of the High Schools in Kermanshah (Doctoral dissertation). http://dx.doi.org/10.17169/refubium-5478
Namaziandost, E., & Rezai, A. (2024). The interplay of academic emotion regulation, academic mindfulness, L2 learning experience, academic motivation, and learner autonomy in intelligent computer-assisted language learning: A study of EFL learners. System, 125, 103419. https://doi.org/10.1016/j.system.2024.103419
Ng, D. T. K., Leung, J. K. L., Su, J., Ng, R. C. W., & Chu, S. K. W. (2023). Teachers' AI digital competencies and twenty-first century skills in the post-pandemic world. Educational Technology Research and Development, 71(1), 137–161. https://doi.org/10.1007/s11423-023-10203-6
Nwoko, J. C., Emeto, T. I., Malau-Aduli, A. E. O., & Malau-Aduli, B. S. (2023). A Systematic Review of the Factors That Influence Teachers' Occupational Wellbeing. International journal of environmental research and public health, 20(12), 6070. https://doi.org/10.3390/ijerph20126070
Pedro, F., Subosa, M., Rivas, A., & Valverde, P. (2019). Artificial intelligence in education: Challenges and opportunities for sustainable development. https://hdl.handle.net/20.500.12799/6533
Qiao, H., & Zhao, A. (2023). Artificial intelligence-based language learning: Illuminating the impact on speaking skills and self-regulation in Chinese EFL context. Frontiers in Psychology, 14, 1255594. https://doi.org/10.3389/fpsyg.2023.1255594
Qu, X., Yang, J., Chen, T., & Zhang, W. (2023). Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition, 54(5), 937–940. https://doi.org/10.12182/20231360302
Sadeghi, S., Aliakbari, M., & Yasini, A. (2022). A model of EFL teachers' pedagogical content knowledge: A data-driven approach. Teaching English as a Second Language Quarterly (Formerly Journal of Teaching Language Skills), 41(2), 205-243.
Shaikh, S., Yayilgan, S. Y., Klimova, B., & Pikhart, M. (2023). Assessing the Usability of ChatGPT for Formal English Language Learning. European journal of investigation in health, psychology and education, 13(9), 1937–1960. https://doi.org/10.3390/ejihpe13090140
Shamshiri, F., Esfahani, F. R., & Hosseini, S. E. (2023). Models of assessment in the classroom: a comparative research of CALL-based vs. traditional assessment on vocabulary learning among Iranian EFL learners. Language Testing in Asia, 13(1), 43.
Song, C., & Song, Y. (2023). Enhancing academic writing skills and motivation: assessing the efficacy of ChatGPT in AI-assisted language learning for EFL students. Frontiers in psychology, 14, 1260843. https://doi.org/10.3389/fpsyg.2023.1260843
Srinivasan, M., Venugopal, A., Venkatesan, L., & Kumar, R. (2024). Navigating the Pedagogical Landscape: Exploring the Implications of AI and Chatbots in Nursing Education. JMIR nursing, 7, e52105. https://doi.org/10.2196/52105
Stracqualursi, L., & Agati, P. (2024). Twitter users perceptions of AI-based e-learning technologies. Scientific reports, 14(1), 5927. https://doi.org/10.1038/s41598-024-56284-y
Tajik, A. (2025). Exploring the role of AI-driven dynamic writing platforms in improving EFL learners' writing skills and fostering their motivation. https://doi.org/10.21203/rs.3.rs-5788599/v1
Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision Sciences, 39(2), 273–315. https://doi.org/10.1111/j.1540-5915.2008.00192.x
Veras, M., Dyer, J. O., Rooney, M., Barros Silva, P. G., Rutherford, D., & Kairy, D. (2023). Usability and Efficacy of Artificial Intelligence Chatbots (ChatGPT) for Health Sciences Students: Protocol for a Crossover Randomized Controlled Trial. JMIR research protocols, 12, e51873. https://doi.org/10.2196/51873
Wei L. (2023). Artificial intelligence in language instruction: impact on English learning achievement, L2 motivation, and self-regulated learning. Frontiers in psychology, 14, 1261955. https://doi.org/10.3389/fpsyg.2023.1261955
Wei, P., Wang, X., & Dong, H. (2023). The impact of automated writing evaluation on second language writing skills of Chinese EFL learners: a randomized controlled trial. Frontiers in psychology, 14, 1249991. https://doi.org/10.3389/fpsyg.2023.1249991
Worthing, K. A., Roberts, M., & Šlapeta, J. (2024). Surveyed veterinary students in Australia find ChatGPT practical and relevant while expressing no concern about artificial intelligence replacing veterinarians. Veterinary record open, 11(1), e280. https://doi.org/10.1002/vro2.80
Xu, X., Chen, Y., & Miao, J. (2024). Opportunities, challenges, and future directions of large language models, including ChatGPT in medical education: A systematic scoping review. Journal of Educational Evaluation for Health Professions, 21, 6. https://doi.org/10.3352/jeehp.2024.21.6
Yu H. (2024). The application and challenges of ChatGPT in educational transformation: New demands for teachers' roles. Heliyon, 10(2), e24289. https://doi.org/10.1016/j.heliyon.2024.e24289
Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2022). Systematic review of research on artificial intelligence applications in higher education. International Journal of Educational Technology in Higher Education, 19(1), 1-27.
Zhai, X., Zhao, R., Jiang, Y., & Wu, H. (2024). Unpacking the Dynamics of AI-Based Language Learning: Flow, Grit, and Resilience in Chinese EFL Contexts. Behavioral sciences (Basel, Switzerland), 14(9), 838. https://doi.org/10.3390/bs14090838
Zheng, L., Liu, T., Islam, A. A., & Gu, X. (2023). Interpreting institute culture dynamics of technology adoption: a downscaling dynamic model. Educational technology research and development, 71(3), 919-947. https://doi.org/10.1007/s11423-023-10219-y
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