Artificial Intelligence in the English Language Education: A Study among University Students

The integration of Artificial Intelligence (AI) into English language education has fundamentally transformed pedagogical practices and student engagement, particularly within higher education contexts, where diverse proficiency levels and large class sizes present ongoing instructional challenges. This study systematically investigates the application, efficacy, and implications of AI technologies in supporting English learning among university students. Employing a mixed-methods research design, data were collected from 120 undergraduates across three Chinese universities through structured surveys, classroom observations, and semi-structured interviews, enabling a comprehensive exploration of both quantitative outcomes and qualitative experiences. The findings reveal that AI tools—including intelligent writing assistants, adaptive vocabulary applications, and automated feedback systems—substantially enhance learners’ writing accuracy, lexical sophistication, and overall motivation, while simultaneously promoting greater autonomy and self-regulated learning behaviors. Students reported that AI-supported activities, when integrated with traditional instruction, facilitated more active engagement and personalized learning trajectories. Nevertheless, challenges emerged, notably the potential for overreliance on technology, ethical concerns regarding data privacy, and disparities in digital literacy across learners. The study underscores that AI can serve as both a supportive and transformative agent in English language education when its deployment is guided by clear pedagogical frameworks, ethical standards, and institutional oversight. These findings contribute to ongoing discourse on technology-enhanced language learning (TELL) and provide actionable recommendations for educators and policymakers seeking to harness AI to foster sustainable, student-centered innovation in university-level English instruction.

Artificial Intelligence, English Language Education, University Students

1. Braun, V., & Clarke, V. (2019). Reflecting on reflexive thematic analysis. Qualitative Research in Sport, Exercise and Health, 11(4), 589–597. https://doi.org/10.1080/2159676X.2019.1628806 [Google Scholar] [Crossref]

2. Chapelle, C. A. (2019). The encyclopedia of applied linguistics: Computer-assisted language learning (CALL). Wiley. [Google Scholar] [Crossref]

3. Cohn, A., et al. (2019). Automation complacency in human–AI interaction: Implications for learning. Human Factors, 61(8), 1224–1236. https://doi.org/10.1177/0018720819871234 [Google Scholar] [Crossref]

4. Creswell, J. W., & Plano Clark, V. L. (2018). Designing and conducting mixed methods research (3rd ed.). SAGE. [Google Scholar] [Crossref]

5. Deci, E. L., & Ryan, R. M. (2000). The “what” and “why” of goal pursuits: Human needs and the self-determination of behavior. Psychological Inquiry, 11(4), 227–268. https://doi.org/10.1207/S15327965PLI1104_01 [Google Scholar] [Crossref]

6. Floridi, L., & Cowls, J. (2019). A unified framework of five principles for AI in society. Harvard Data Science Review, 1(1). https://doi.org/10.1162/99608f92.8cd550d1 [Google Scholar] [Crossref]

7. Godwin-Jones, R. (2022). AI applications in language learning. Language Learning & Technology, 26(1), 1–18. https://doi.org/10.1016/j.llt.2022.03.001 [Google Scholar] [Crossref]

8. Hockly, N. (2022). Ethical considerations for AI in English language teaching. ELT Journal, 76(3), 241–250. https://doi.org/10.1093/elt/ccab087 [Google Scholar] [Crossref]

9. Holmes, W., Bialik, M., & Fadel, C. (2022). Artificial intelligence in education: Promises and implications for teaching and learning. Center for Curriculum Redesign. [Google Scholar] [Crossref]

10. Jonassen, D. H. (1999). Constructivist learning environments: Case studies in instructional design. Educational Technology Publications. [Google Scholar] [Crossref]

11. Kohnke, L., & Zou, D. (2022). Learner confidence and motivation in digital language learning. Computer Assisted Language Learning, 35(5–6), 1123–1145. https://doi.org/10.1080/09588221.2021.1974567 [Google Scholar] [Crossref]

12. Kukulska-Hulme, A., & Shield, L. (2018). Enhancing language learning through mobile-assisted learning. ReCALL, 30(2), 123–141. https://doi.org/10.1017/S0958344018000030 [Google Scholar] [Crossref]

13. Lee, L. (2022). Automation in writing instruction: Benefits and risks. Language Teaching Research, 26(4), 569–588. https://doi.org/10.1177/13621688211052345 [Google Scholar] [Crossref]

14. Levy, M., & Stockwell, G. (2021). CALL dimensions: Options and issues in computer-assisted language learning (2nd ed.). Routledge. [Google Scholar] [Crossref]

15. Li, Z. (2022). AI-generated feedback and advanced learners’ writing evaluation. Journal of Second Language Writing, 56, 101–118. https://doi.org/10.1016/j.jslw.2022.101118 [Google Scholar] [Crossref]

16. Li, Z. (2023). Personalized language learning through AI: A higher education perspective. Computer Assisted Language Learning, 36(3), 556–575. https://doi.org/10.1080/09588221.2022.2109876 [Google Scholar] [Crossref]

17. Li, Z., & Hegelheimer, V. (2013). Mobile-assisted grammar exercises: Effects on language acquisition. Language Learning & Technology, 17(3), 1–17. [Google Scholar] [Crossref]

18. Nguyen, T., & Zhang, X. (2021). Learner motivation and engagement with AI tools in EFL classrooms. System, 99, 102–119. https://doi.org/10.1016/j.system.2021.102510 [Google Scholar] [Crossref]

19. Selwyn, N. (2020). Should robots replace teachers? AI and the future of education. Polity Press. [Google Scholar] [Crossref]

20. Sun, Y. (2024). Digital equity and AI integration in higher education English learning. Journal of Educational Technology & Society, 27(2), 45–60. [Google Scholar] [Crossref]

21. Sun, Y., & Xu, J. (2024). AI-driven conversational bots in university English classrooms. ReCALL, 36(1), 89–107. https://doi.org/10.1017/S0958344023000210 [Google Scholar] [Crossref]

22. Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. Harvard University Press. [Google Scholar] [Crossref]

23. Wang, X., & Chen, L. (2022). AI-based pronunciation training for EFL learners. Computer Assisted Language Learning, 35(7–8), 1504–1523. https://doi.org/10.1080/09588221.2022.2041101 [Google Scholar] [Crossref]

24. Warschauer, M. (2000). CALL for the 21st century: New tools and outcomes. Language Learning & Technology, 4(1), 7–17. [Google Scholar] [Crossref]

25. Warschauer, M. (2023). Human-centered AI in language teaching: Balancing innovation with pedagogy. Language Learning & Technology, 27(2), 1–20. https://doi.org/10.1016/j.llt.2023.102312 [Google Scholar] [Crossref]

26. Woolf, B. P. (2021). Building intelligent interactive tutors: Student-centered strategies for revolutionizing e-learning. Morgan Kaufmann. [Google Scholar] [Crossref]

27. Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on AI in higher education. International Journal of Educational Technology in Higher Education, 16(1), 39. https://doi.org/10.1186/s41239-019-0171-0 [Google Scholar] [Crossref]

28. Zhang, W. (2023). Effects of AI-assisted writing platforms on university students. Journal of Second Language Writing, 62, 102–121. https://doi.org/10.1016/j.jslw.2023.102121 [Google Scholar] [Crossref]

29. Zhang, W., & Hyland, F. (2020). Learner autonomy and AI feedback in writing. Language Learning & Technology, 24(2), 1–18. [Google Scholar] [Crossref]

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