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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
CAI Shu-yi, YU Wei-tao
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DOI:10.17265/2159-5836/2025.07.002
School of Foreign Languages, Wuhan University of Technology, Wuhan, China
The advancement of generative AI has reshaped EFL education, particularly in EFL writing. This qualitative case study investigates the perceptions of Chinese college students and EFL teachers towards the integration of Gen AI in EFL writing. The research involved semi-structured interviews with 13 students and 10 EFL teachers. Thematic analysis, guided by the Technology Acceptance Model (TAM), was employed to analyze the qualitative data. The findings reveal the perceptions of students and teachers regarding the role of generative AI in EFL writing. Regarding usefulness, students appreciate Gen AI for reducing writing difficulty and enhancing efficiency, though some note that it may produce logical flaws and misinformation. Teachers share similar perceptions, but stress effectiveness depends on students’ language level. Some teachers also advocate traditional writing initially to build foundational skills. On the ease of use, most students find it easy interacting with Gen AI but mention dialogical understanding challenges. Both students and teachers stress clear prompts are crucial, indicating “AI interaction literacy” should be part of teaching. Moreover, teachers worry that Gen AI’s ease of use may lead to over-reliance. These results reveal contradicting goals of using Gen AI: students value efficiency, while teachers focus on ability cultivation. These insights guide more effective integration of Gen AI in EFL writing education.
Generative AI, EFL writing, Technology Acceptance Model (TAM), AI integration in education, Perception
Journal of Literature and Art Studies, July 2025, Vol. 15, No. 7, 526-539
Abdaljaleel, M., Barakat, M., Alsanafi, M., et al. (2024). A multinational study on the factors influencing university students’ attitudes and usage of ChatGPT. Sci Rep, 14, 1983. https://doi.org/10.1038/s41598-024-52549-8.
Albayati, H. (2024). Investigating undergraduate students’ perceptions and awareness of using ChatGPT as a regular assistance tool: A user acceptance perspective study. Computers and Education: Artificial Intelligence, 6, 100203. https://doi.org/10.1016/j.caeai.2024.100203.
Atlas, S. (2023). ChatGPT for higher education and professional development: A guide to conversational AI. https://digitalcommons.uri.edu/cba_facpubs/548.
Barrett, A., & Pack, A. (2023). Not quite eye to A.I.: Student and teacher perspectives on the use of generative artificial intelligence in the writing process. International Journal of Educational Technology in Higher Education, 20(1). https://doi.org/10.1186/s41239-023-00427-0.
Barrot, J. S. (2023). Using ChatGPT for second language writing: Pitfalls and potentials. Assessing Writing, 57, 100745, https://doi.org/10.1016/j.asw.2023.100745.
Chan, C. K. Y., & Hu, W. (2023). Students’ voices on generative AI: Perceptions, benefits, and challenges in higher education. International Journal of Educational Technology in Higher Education, 20(1). https://doi.org/10.1186/s41239-023-00411-8.
Creely, E., & Janssen, K. (2025). Onto-epistemological understandings of generative Artificial Intelligence in education. International Journal of Changes in Education. DOI: 10.47852/bonviewIJCE52024380.
Darvishi, A., Khosravi, H., Sadiq, S., Gašević, D., & Siemens, G. (2024). Impact of AI assistance on student agency. Computers and Education, 210, 104967. https://doi.org/10.1016/j.compedu.2023.104967.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319. https://doi.org/10.2307/249008.
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982-1003. https://doi.org/10.1287/mnsc.35.8.982.
Dong, W., Pan, D., & Kim, S. (2024). Exploring the integration of IoT and Generative AI in English language education: Smart tools for personalized learning experiences. Journal of Computational Science, 46, 102019. https://doi.org/10.1016/j.jocs.2024.102397.
Elsayed, A. M., Kholikov, A., Abdullayeva, I., Al-Farouni, M., & Wodajo, M. R. (2024) Teacher support in AI-assisted exams: An experimental study to inspect the effects on demotivation, anxiety management in exams, L2 learning experience, and academic success. Lang Test Asia, 14(1), 53. https://doi.org/10.1186/s40468-024-00328-7.
Farrokhnia, M., Banihashem, S. K., Noroozi, O., & Wals, A. (2023). A SWOT analysis of ChatGPT: Implications for educational practice and research. Innovations in Education and Teaching International, 61(3), 460-474. https://doi.org/10.1080/14703297.2023.2195846.
Guan, L., Lee, J. C.-K., Zhang, Y., & Gu, M. M. (2025). Investigating the tripartite interaction among teachers, students, and generative AI in EFL education: A mixed-methods study. Computers and Education: Artificial Intelligence, 8, 100384, https://doi.org/10.1016/j.caeai.2025.100384.
Hussein, M. A., Hassan, H., & Nassef, M. (2019). Automated language essay scoring systems: a literature review. PeerJ. Computer Science, 5, e208. https://doi.org/10.7717/peerj-cs.208.
Jacob, S., Tate, T., & Warschauer, M. (2023). Emergent AI-assisted discourse: Case study of a second language writer authoring with ChatGPT. arXiv.org. https://arxiv.org/abs/2310.10903.
King, M. R., & chatGPT. (2023). A conversation on artificial intelligence, chatbots, and plagiarism in higher education. Cellular and Molecular Bioengineering, 16(1), 1-2. https://doi.org/10.1007/s12195-022-00754-8.
Kung, T. H., Cheatham, M., Medenilla, A., Sillos, C., De Leon, L., Elepaño C., Madriaga, M., Aggabao, R., Diaz-Candido, G., & Maningo, J. (2023). Performance of ChatGPT on USMLE: Potential for AI-assisted medical education using large language models. PLOS Digital Health, 2(2), e0000198. https://doi.org/10.1371/journal.pdig.0000198.
Lee, Y. H., Hsieh, Y. C., & Hsu, C. N. (2011). Adding innovation diffusion theory to the technology acceptance model: Supporting employees’ intentions to use e-learning systems. Journal of Educational Technology & Society, 14(4), 124-137.
Ma, S., & Lei, L. (2024). The factors influencing teacher education students’ willingness to adopt artificial intelligence technology for information-based teaching. Asia Pacific Journal of Education, 44(1), 94-111. https://doi.org/10.1080/02188791.2024.2305155.
Min, S., So, K. K. F., & Jeong, M. (2021). Consumer adoption of the Uber mobile application: Insights from diffusion of innovation theory and technology acceptance model. In Future of tourism marketing (pp. 2-15). London: Routledge.
Mizumoto, A., & Eguchi, M. (2023). Exploring the potential of using an AI language model for automated essay scoring. https://doi.org/10.2139/ssrn.4373111.
Ngo, T. T. A. (2023). The perception by university students of the use of ChatGPT in education. International Journal of Emerging Technologies in Learning (iJET), 18(17), 4-19. https://doi.org/10.3991/ijet.v18i17.39019.
Sallam, M., Salim, N. A., Barakat, M., Al-Mahzoum, K., Al-Tammemi, A. B., Malaeb, D., Hallit, R., & Hallit, S. (2023). Assessing health students’ attitudes and usage of ChatGPT in Jordan: Validation study. JMIR Medical Education, 9, e48254. https://doi.org/10.2196/48254.
Shanto, S. S., Ahmed, Z., & Jony, A. I. (2024). Enriching the learning process with generative AI: A proposed framework to cultivate critical thinking in higher education using ChatGPT. Tuijin Jishu/Journal of Propulsion Technology, 45(1), 3019-3029. doi:10.52783/tjjpt.v45.i01.4680.
Shen, Y., & Guo, H. (2024). “I feel AI is neither too good nor too bad”: Unveiling Chinese EFL teachers’ perceived emotions in generative AI-Mediated L2 classes. Computers in Human Behavior, 161, 108429. https://doi.org/10.1016/j.chb.2024.108429.
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. doi: 10.3389/fpsyg.2023.1260843.
Stojanov, A., Liu, Q., & Koh, J. H. L. (2024). University students’ self-reported reliance on ChatGPT for learning: A latent profile analysis. Computers and Education: Artificial Intelligence, 6, 100243. https://doi.org/10.1016/j.caeai.2024.100243.
Tatum, H. E. (2022). Honor codes and academic integrity: Three decades of research. Journal of College and Character, 23(1), 32-47. https://doi.org/10.1080/2194587X.2021.2017977.
Tseng, W., & Warschauer, M. (2023). AI-writing tools in education: if you can’t beat them, join them. Journal of China Computer-Assisted Language Learning, 3(2), 258-262. https://doi.org/10.1515/jccall-2023-0008.
Utami, S. P. T., & Winarni, R. (2023). Utilization of artificial intelligence technology in an academic writing class: How do Indonesian students perceive? Contemp. Educ. Technol, 15, ep450. doi: 10.30935/cedtech/13419.
Van Niekerk, J., Delport, P. M., & Sutherland, I. (2025) Addressing the use of generative AI in academic writing. Computers and Education: Artificial Intelligence, 8, 100342. https://doi.org/10.1016/j.caeai.2024.100342.
Warschauer, M., Tseng, W., Yim, S., Webster, T., Jacob, S., Du, Q., & Tate, T. (2023). The affordances and contradictions of AI-generated text for writers of English as a second or foreign language. Journal of Second Language Writing, 62, 101071. https:// doi.org/10.1016/j.jslw.2023.101071.
Xi, J., Wang, J., & Zhang H. (2022). A comparative analysis of mobile language teaching and learning behaviors between college teachers and students. Foreign Languages Bimonthly, 45(05), 94-102.
Xiao, Y., & Zhi, Y. (2023). An exploratory study of EFL learners’ use of ChatGPT for language learning tasks: Experience and perceptions. Languages, 8(3), 212. https://doi.org/10.3390/languages8030212.
Xu, J., & Deng, Q. (2024). Chinese EFL learners’ acceptance of live video-streamed teaching platforms: A study based on the Technology Acceptance Model. Foreign Language Teaching and Research, 56(02), 262-273+320-321. doi:10.19923/j.cnki.fltr.2024.02.009.
Yan, D. (2023). Impact of ChatGPT on learners in a L2 writing practicum: An exploratory investigation. Education and Information Technologies, 28(11), 13943-13967. https://doi.org/10.1007/s10639-023-11742-4.
Yusuf, A., Bello, S., Pervin, N., & Tukur, A. K. (2024). Implementing a proposed framework for enhancing critical thinking skills in synthesizing AI-generated texts. Thinking Skills and Creativity, 53, 101619. https://doi.org/10.1016/j.tsc.2024.101619.
Zhang, L., & Xu, J. (2025). The paradox of self-efficacy and technological dependence: Unraveling generative AI’s impact on university students’ task completion. The Internet and Higher Education, 65, 100978. https://doi.org/10.1016/j.iheduc.2024.100978.