THE ROLE OF ARTIFICIAL INTELLIGENCE IN TEACHING ENGLISH AS A FOREIGN LANGUAGE TO UNIVERSITY STUDENTS: OPPORTUNITIES, CHALLENGES, AND FUTURE DIRECTIONS
DOI:
https://doi.org/10.5281/zenodo.19415350Keywords:
Artificial Intelligence (AI), English as a Foreign Language (EFL), Higher Education, Personalized Learning, Natural Language Processing (NLP), Learner Autonomy, Computer-Assisted Language Learning (CALL), Educational Technology.Abstract
This thesis explores the transformative role of Artificial Intelligence (AI) technologies in teaching English as a
Foreign Language (EFL) within the higher education sector. The rapid development of Large Language Models (LLMs),
Natural Language Processing (NLP), and personalized learning algorithms has contributed to the evolution of EFL
pedagogy from standardized approaches toward more flexible, student-centered methodologies.
The study examines how AI-driven tools—such as automated writing evaluation (AWE) systems, intelligent tutoring
systems (ITS), and virtual conversational agents—support the development of linguistic competence, learner autonomy,
and student engagement in university settings. These technologies provide valuable opportunities for personalized
instruction, adaptive learning pathways, and timely feedback, thereby enhancing the overall effectiveness of the
educational process.
At the same time, the integration of AI into education requires careful and responsible implementation. Important
considerations include ensuring fairness in algorithmic processes, protecting data privacy, maintaining academic
integrity, and redefining pedagogical roles in a constructive manner. This research emphasizes that AI should function as
a supportive and complementary tool that enhances, rather than replaces, the role of the teacher.
The study advocates for a balanced “human-in-the-loop” approach, highlighting the importance of developing digital
literacy among both students and educators, as well as establishing a strong ethical framework for the effective and
responsible use of AI technologies in higher education.
References
Ahmad, M., & Siddiqui, M. (2023). The role of artificial intelligence in English language teaching and learning: A review.
International Journal of Emerging Technologies in Learning (iJET), 18(2), 112–128.
Bennett, L., & Lockyer, L. (2020). A review of the literature on teacher digital competency and professional development.
Teachers and Teaching, 26(1), 1–17.
Hockly, N. (2023). Artificial intelligence in English language teaching. In G. Dudeney & N. Hockly (Eds.), The Routledge
handbook of teaching English with technology (pp. 34–48). Routledge.
Kohnke, L. (2023). Using ChatGPT to improve English writing skills. RELC Journal, 00336882231168923.
Li, Z., & Chen, J. (2023). Impacts of automated writing evaluation (AWE) on EFL learners’ writing quality and selfregulation.
Computer Assisted Language Learning, 36(5), 1102–1126.
O’Neill, T., & Russell, M. (2019). The automated assessment of speaking and writing. In M. Russell & T. O’Neill (Eds.),
The Routledge handbook of language testing (pp. 312–327). Routledge.
Pashler, H., McDaniel, M., Rohrer, D., & Bjork, R. (2008). Learning styles: Concepts and evidence. Psychological
Science in the Public Interest, 9(3), 105–119.
Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. Harvard University Press.
Wang, Y., & Chen, J. (2022). Automatic speech recognition (ASR) for pronunciation training: A systematic review.
Journal of Educational Computing Research, 60(3), 633–659.
Zou, D., Xie, H., Wang, F. L., & Wong, G. K. W. (2022). Artificial intelligence in education: A review of literature and
research trends. International Journal of Distance Education Technologies (IJDET), 20(1), 1–19.
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