LLM-supported EFL writing: AI feedback literacy, revision behaviour, and writing self-efficacy among Vietnamese undergraduates

Khanh Quoc Nguyen; Quang Nhat Vo

doi:10.18860/jetle.v8i1.44861

LLM-supported EFL writing: AI feedback literacy, revision behaviour, and writing self-efficacy among Vietnamese undergraduates

Khanh Quoc Nguyen, Quang Nhat Vo

Abstract

This cross-sectional survey examined whether AI feedback literacy and revision behaviour mediated the association between large language model (LLM) co-editing intensity and writing self-efficacy among 305 Vietnamese undergraduates with recent experience using LLM tools for English writing revision. The questionnaire measured LLM co-editing intensity, AI feedback literacy, revision behaviour, and writing self-efficacy. Reliability estimates were acceptable to good, and exploratory factor analysis supported the proposed four-factor structure. Serial mediation analysis with 5,000 bootstrap resamples showed significant indirect associations between LLM co-editing intensity and writing self-efficacy through AI feedback literacy, revision behaviour, and their sequential pathway. The serial indirect effect was 0.048, with a 95% bootstrap confidence interval of [0.024, 0.080], and the total indirect effect was 0.206, 95% CI [0.140, 0.283]. Given the cross-sectional and self-reported data, these findings are interpreted as associational rather than causal. Pedagogically, the results suggest that LLM-supported EFL writing instruction should focus not simply on increasing tool use but on helping students evaluate AI-generated feedback and translate it into purposeful revision decisions.

Keywords

AI feedback literacy; generative AI feedback; LLM-supported writing; revision behaviour; writing self-efficacy

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References

Bandura, A. (1997). Self-efficacy: The exercise of control. W. H. Freeman.

Bruning, R., Dempsey, M., Kauffman, D. F., McKim, C., & Zumbrunn, S. (2013). Examining dimensions of self-efficacy for writing. Journal of Educational Psychology, 105(1), 25–38. https://doi.org/10.1037/a0029692

Carless, D., & Boud, D. (2018). The development of student feedback literacy: Enabling uptake of feedback. Assessment & Evaluation in Higher Education, 43(8), 1315–1325. https://doi.org/10.1080/02602938.2018.1463354

Crosthwaite, P., & Sun, S. (2026). Generative AI and L2 written feedback studies: A scoping review. RELC Journal, 57(1), 207–219. https://doi.org/10.1177/00336882251386530

Fu, H., & Liu, X. (2022). EFL learner engagement in automatic written evaluation. Frontiers in Psychology, 13, Article 871707. https://doi.org/10.3389/fpsyg.2022.871707

Han, Y., & Hyland, F. (2015). Exploring learner engagement with written corrective feedback in a Chinese tertiary EFL classroom. Journal of Second Language Writing, 30, 31–44. https://doi.org/10.1016/j.jslw.2015.08.002

Hayes, A. F. (2022). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach (3rd ed.). The Guilford Press.

Karatay, Y., & Karatay, L. (2024). Automated writing evaluation use in second language classrooms: A research synthesis. System, 123, Article 103332. https://doi.org/10.1016/j.system.2024.103332

Kohnke, L., Moorhouse, B. L., & Zou, D. (2023). ChatGPT for language teaching and learning. RELC Journal, 54(2), 537–550. https://doi.org/10.1177/00336882231162868

Koltovskaia, S. (2020). Student engagement with automated written corrective feedback (AWCF) provided by Grammarly: A multiple case study. Assessing Writing, 44, Article 100450. https://doi.org/10.1016/j.asw.2020.100450

Li, J., Link, S., & Hegelheimer, V. (2015). Rethinking the role of automated writing evaluation (AWE) feedback in ESL writing instruction. Journal of Second Language Writing, 27, 1–18. https://doi.org/10.1016/j.jslw.2014.10.004

Lin, S., & Crosthwaite, P. (2024). The grass is not always greener: Teacher vs. GPT-assisted written corrective feedback. System, 127, Article 103529. https://doi.org/10.1016/j.system.2024.103529

Link, S., Mehrzad, M., & Rahimi, M. (2022). Impact of automated writing evaluation on teacher feedback, student revision, and writing improvement. Computer Assisted Language Learning, 35(4), 605–634. https://doi.org/10.1080/09588221.2020.1743323

Liu, J., Shi, Z., & Li, W. (2026). Developing students’ feedback literacy in disciplinary academic writing through generative artificial intelligence. Assessing Writing, 68, 101030. https://doi.org/10.1016/j.asw.2026.101030

Lu, Q., Yao, Y., Xiao, L., Zhu, X., & Yin, H. (2026). Exploring the impact of a GenAI-supported feedback practice on student feedback literacy in L2 writing. Computer Assisted Language Learning. Advance online publication. https://doi.org/10.1080/09588221.2025.2605541

Nguyen, T. L., & Nguyen, X. Q. (2026). Vietnamese EFL students’ perceptions and preferences for ChatGPT, peer, and teacher feedback in writing revision. Computer-Assisted Language Learning Electronic Journal, 27(2), 173–191. https://doi.org/10.54855/callej.262729

Pajares, F. (2003). Self-efficacy beliefs, motivation, and achievement in writing: A review of the literature. Reading & Writing Quarterly, 19(2), 139–158. https://doi.org/10.1080/10573560308222

Ranalli, J. (2021). L2 student engagement with automated feedback on writing: Potential for learning and issues of trust. Journal of Second Language Writing, 52, Article 100816. https://doi.org/10.1016/j.jslw.2021.100816

Rosseel, Y. (2012). lavaan: An R package for structural equation modeling. Journal of Statistical Software, 48(2), 1–36. https://doi.org/10.18637/jss.v048.i02

Teng, M. F. (2024). “ChatGPT is the companion, not enemies”: EFL learners’ perceptions and experiences in using ChatGPT for feedback in writing. Computers and Education: Artificial Intelligence, 7, Article 100270. https://doi.org/10.1016/j.caeai.2024.100270

Teng, M. F., & Wang, C. (2023). Assessing academic writing self-efficacy belief and writing performance in a foreign language context. Foreign Language Annals, 56(1), 144–169. https://doi.org/10.1111/flan.12638

Tian, L., & Zhou, Y. (2020). Learner engagement with automated feedback, peer feedback and teacher feedback in an online EFL writing context. System, 91, Article 102247. https://doi.org/10.1016/j.system.2020.102247

Tsao, J. J., Tseng, W. T., Hsiao, T. Y., Wang, C., & Gao, A. X. (2021). Toward a motivation-regulated learner engagement WCF model of L2 writing performance. SAGE Open, 11(2), Article 21582440211023172. https://doi.org/10.1177/21582440211023172

Yu, S., Zhang, E. D., & Liu, C. (2022). Assessing L2 student writing feedback literacy: A scale development and validation study. Assessing Writing, 53, Article 100643. https://doi.org/10.1016/j.asw.2022.100643

Zhang, Z. V. (2020). Engaging with automated writing evaluation (AWE) feedback on L2 writing: Student perceptions and revisions. Assessing Writing, 43, Article 100439. https://doi.org/10.1016/j.asw.2019.100439

Zhang, Z. V., & Hyland, K. (2018). Student engagement with teacher and automated feedback on L2 writing. Assessing Writing, 36, 90–102. https://doi.org/10.1016/j.asw.2018.02.004

DOI: https://doi.org/10.18860/jetle.v8i1.44861