The Influence of AI-Powered Feedback on English Language Learners' Writing Development
DOI:
https://doi.org/10.57033/1fjw2a25Keywords:
AI-powered feedback, automated writing evaluation, ChatGPT, L2 writing, written corrective feedback, learner engagement, feedback literacyAbstract
Feedback is one of the most influential factors in second language (L2) writing development, yet providing timely and individualised feedback remains a major challenge for teachers of large classes. The emergence of automated writing evaluation (AWE) systems and, more recently, generative artificial intelligence (AI) tools such as ChatGPT has transformed the ways in which English language learners receive feedback on their texts. This article reviews theoretical foundations and empirical research on AI-powered feedback in order to examine its influence on learners' writing development. The analysis shows that AI feedback has a moderate positive effect on writing performance, especially on lexical and surface-level accuracy, and can increase revision activity and learner engagement. At the same time, its effectiveness depends on the accuracy of the feedback, learners' feedback literacy and the mediating role of the teacher. The article proposes an integrated human-AI feedback model for English writing instruction.
References
1. Hattie, J. & Timperley, H. (2007). The power of feedback. Review of Educational Research, 77(1), 81–112. https://doi.org/10.3102/003465430298487
2. Hyland, K. & Hyland, F. (2006). Feedback on second language students’ writing. Language Teaching, 39(2), 83–101. https://doi.org/10.1017/S0261444806003399
3. Truscott, J. (1996). The case against grammar correction in L2 writing classes. Language Learning, 46(2), 327–369. https://doi.org/10.1111/j.1467-1770.1996.tb01238.x4. Ferris, D. (1999). The case for grammar correction in L2 writing classes:a response to Truscott (1996). Journal of Second Language Writing, 8(1), 1–11. https://doi.org/10.1016/S1060-3743(99)80110-6
4. Bitchener, J. & Ferris, D. R. (2012). Written Corrective Feedback in Second Language Acquisition and Writing. New York:Routledge.
5. 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
6. Schmidt, R. W. (1990). The role of consciousness in second language learning. Applied Linguistics, 11(2), 129–158. https://doi.org/10.1093/applin/11.2.129
7. Swain, M. (1995). Three functions of output in second language learning. In:G. Cook & B. Seidlhofer (eds.), Principle and Practice in Applied Linguistics:Studies in Honour of H. G. Widdowson, pp. 125–144. Oxford:Oxford University Press.
8. Flower, L. & Hayes, J. R. (1981). A cognitive process theory of writing. College Composition and Communication, 32(4), 365–387. https://doi.org/10.2307/356600 9.
10. Vygotsky, L. S. (1978). Mind in Society:The Development of Higher Psychological Processes. Cambridge, MA:Harvard University Press.
10. Ellis, R. (2009). A typology of written corrective feedback types. ELT Journal, 63(2), 97–107. https://doi.org/10.1093/elt/ccn023
11. 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/10.1 080/02602938.2018.1463354
12. Warschauer, M. & Grimes, D. (2008). Automated writing assessment in the classroom. Pedagogies:An International Journal, 3(1), 22–36.
13. Chen, C.-F. E. & Cheng, W.-Y. E. (2008). Beyond the design of automated writing evaluation:pedagogical practices and perceived learning effectiveness in EFL writing classes. Language Learning & Technology, 12(2), 94–112.
14. Stevenson, M. & Phakiti, A. (2014). The effects of computer-generated feedback on the quality of writing. Assessing Writing, 19, 51–65.
15. Dikli, S. & Bleyle, S. (2014). Automated essay scoring feedback for second language writers:how does it compare to instructor feedback? Assessing Writing, 22, 1–17.
16. Ranalli, J. (2018). Automated written corrective feedback:how well can students make use of it? Computer Assisted Language Learning, 31(7), 653–674.
17. Su, Y., Lin, Y. & Lai, C. (2023). Collaborating with ChatGPT in argumentative writing classrooms. Assessing Writing, 57, 100752. https://doi.org/10.1016/j.asw.2023.100752
18. Guo, K. & Wang, D. (2024). To resist it or to embrace it? Examining ChatGPT’s potential to support teacher feedback in EFL writing. Education and Information Technologies, 29(7), 8435–8463. https://doi.org/10.1007/s10639-023-12146-0
19. Steiss, J., Tate, T., Graham, S., Cruz, J., Hebert, M., Wang, J. et al. (2024). Comparing the quality of human and ChatGPT feedback of students’ writing. Learning and Instruction, 91, 101894. https:// doi.org/10.1016/j.learninstruc.2024.101894
20. Fleckenstein, J., Liebenow, L. W. & Meyer, J. (2023). Automated feedback and writing:a multi-level meta-analysis of effects on students’ performance. Frontiers in Artificial Intelligence, 6, 1162454.
21. Ngo, T. T.-N., Chen, H. H.-J. & Lai, K. K.-W. (2024). The effectiveness of automated writing evaluation in EFL/ESL writing:a three-level meta-analysis. Interactive Learning Environments, 32(2), 727–744. https://doi.org/10.1080/10494820.2022.2096642
22. 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.
23. Wilson, J. & Czik, A. (2016). Automated essay evaluation software in English Language Arts classrooms:effects on teacher feedback, student motivation, and writing quality. Computers & Education, 100, 94–109.
24. 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.
25. Zhang, Z. V. & Hyland, K. (2018). Student engagement with teacher and automated feedback on L2 writing. Assessing Writing, 36, 90–102.
26. Koltovskaia, S. (2020). Student engagement with automated written corrective feedback (AWCF) provided by Grammarly:a multiple case study. Assessing Writing, 44, 100450. https://doi. org/10.1016/j.asw.2020.100450
27. Nicol, D. J. & Macfarlane-Dick, D. (2006). Formative assessment and self-regulated learning:a model and seven principles of good feedback practice. Studies in Higher Education, 31(2), 199–218. https://doi.org/10.1080/03075070600572090
28. Escalante, J., Pack, A. & Barrett, A. (2023). AI-generated feedback on writing:insights into efficacy and ENL student preference. International Journal of Educational Technology in Higher Education, 20, Article 57.
29. Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F. et al. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103, 102274. https://doi.org/10.1016/j.lindif.2023.102274
30. Yan, D. (2023). Impact of ChatGPT on learners in a L2 writing practicum:an exploratory investigation. Education and Information Technologies, 28(11), 13943–13967.
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Ibodat Obidkhujayeva (Author)
This work is licensed under a Creative Commons Attribution 4.0 International License.
All contributions published in the SGELC proceedings are licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) licence. Authors retain copyright and grant the conference the right of first publication. Readers are free to share and adapt the material for any purpose, provided that appropriate credit is given to the authors and the original publication.
