A Review of Research on Artificial Intelligence Writing Feedback: Mechanisms, Learner Behaviours, and Future Directions

Gufeng Wu; Rosilawati Sueb; Qingyi Deng

doi:10.62177/jetp.v2i4.961

Authors

Gufeng Wu Universiti Teknologi MARA (UiTM)
Rosilawati Sueb Universiti Teknologi MARA (UiTM)
Qingyi Deng Guangzhou Huali College

DOI:

https://doi.org/10.62177/jetp.v2i4.961

Keywords:

Artificial Intelligence Writing Feedback, Automated Writing Evaluation, Generative AI, Revision Behaviour, Feedback Satisfaction, Learner Engagement

Abstract

This study systematically reviews the evolution of Artificial Intelligence (AI) writing feedback from Automated Writing Evaluation (AWE) to generative Large Language Models. Existing evidence indicates that AI enhances writing quality. However, research regarding the mechanisms through which feedback translates into concrete revision behaviours remains insufficient. Drawing upon Feedback Intervention Theory and Writing Process Theory, this paper analyses the distinctions between local linguistic feedback and global discourse feedback. It further explores critical variables including learner cognitive assessment, revision intention, and affective responses. A comprehensive conceptual framework is constructed. This framework elucidates the mediating role of feedback satisfaction in connecting technical characteristics with revision depth. Addressing current limitations in process data collection and short-term designs, the article calls for a shift towards longitudinal empirical paradigms combined with behavioural tracking. Ultimately, the study underscores the necessity of enhancing feedback literacy and establishing ethical norms within the context of human-machine synergy to achieve sustainable development in writing education.

Downloads

Download data is not yet available.

References

Perkins, M. (2023). Academic Integrity considerations of AI Large Language Models in the post-pandemic era: ChatGPT and beyond. Journal of University Teaching and Learning Practice, 20(2). https://doi.org/10.53761/1.20.02.07

Mizumoto, A., & Eguchi, M. (2023). Exploring the Potential of Using an Ai Language Model for Automated Essay Scoring (SSRN Scholarly Paper No. 4373111). Social Science Research Network. https://doi.org/10.2139/ssrn.4373111

Wang, L., & Ren, B. (2024). Enhancing Academic Writing in a Linguistics Course with Generative AI: An Empirical Study in a Higher Education Institution in Hong Kong. Education Sciences, 14(12), 1329. https://doi.org/10.3390/educsci14121329

Fan, N., & Ma, Y. (2022). The Effects of Automated Writing Evaluation (AWE) Feedback on Students’ English Writing Quality: A Systematic Literature Review. Language Teaching Research Quarterly, 28, 53–73. https://doi.org/10.32038/ltrq.2022.28.03

Kurt, G., & Kurt, Y. (2024). Enhancing L2 Writing Skills: ChatGPT as an Automated Feedback Tool. Journal of Information Technology Education: Research, 23, 024. https://doi.org/10.28945/5370

Saeli, H., Rahmati, P., & Koltovskaia, S. (2023). Learner Engagement with Written Corrective Feedback: The Case of Automated Writing Evaluation. Journal of Response to Writing, 9(2). https://scholarsarchive.byu.edu/journalrw/vol9/iss2/1

Cotos, E. (2023). Automated Feedback on Writing. In O. Kruse, C. Rapp, C. M. Anson, K. Benetos, E. Cotos, A. Devitt, & A. Shibani (Eds), Digital Writing Technologies in Higher Education: Theory, Research, and Practice (pp. 347–364). Springer International Publishing. https://doi.org/10.1007/978-3-031-36033-6_22

Polakova, P., & Ivenz, P. (2024). The impact of ChatGPT feedback on the development of EFL students’ writing skills. Cogent Education, 11(1), 2410101. https://doi.org/10.1080/2331186X.2024.2410101

Kluger, A. N., & DeNisi, A. (1996). The effects of feedback interventions on performance: A historical review, a meta-analysis, and a preliminary feedback intervention theory. Psychological Bulletin, 119(2), 254–284. https://doi.org/10.1037/0033-2909.119.2.254

Zaheer, S., Ma, C., Zhu, Y., & Vasinda, S. (2025). GenAI in Academic Writing- Empowering Learners or Redefining Traditional Pedagogical Practices? A Systematic Review From 2019-2023. International Journal of Artificial Intelligence (AI) in Teaching and Learning (IJAITL), 1(1), 1–34. https://doi.org/10.4018/IJAITL.373582

Hattie, J., & Timperley, H. (2007). The Power of Feedback. Review of Educational Research, 77(1), 81–112. https://doi.org/10.3102/003465430298487

Yang, H., Gao, C., & Shen, H. (2024). Learner interaction with, and response to, AI-programmed automated writing evaluation feedback in EFL writing: An exploratory study. Education and Information Technologies, 29(4), 3837–3858. https://doi.org/10.1007/s10639-023-11991-3

Flower, L., & Hayes, J. R. (1981). A Cognitive Process Theory of Writing. College Composition & Communication, 32(4), 365–387. https://doi.org/10.58680/ccc198115885

Li, W., & Zhang, F. (2021). Tracing the Path Toward Self-Regulated Revision: An Interplay of Instructor Feedback, Peer Feedback, and Revision Goals. Frontiers in Psychology, 11. https://doi.org/10.3389/fpsyg.2020.612088

Al-Othman, A. A.-A. M. (2024). EFL Students Develop Cognitive and Metacognitive Self-Regulated Writing Strategies Using Automated Feedback: A Case Study. Theory and Practice in Language Studies, 14(5), 1525–1536. https://doi.org/10.17507/tpls.1405.26

Suraworachet, W., Zhou, Q., & Cukurova, M. (2023). Impact of combining human and analytics feedback on students’ engagement with, and performance in, reflective writing tasks. International Journal of Educational Technology in Higher Education, 20(1), 1. https://doi.org/10.1186/s41239-022-00368-0

Teng, M. F., & Huang, J. (2025). Incorporating ChatGPT for EFL Writing and Its Effects on Writing Engagement. International Journal of Computer-Assisted Language Learning and Teaching (IJCALLT), 15(1), 1–21. https://doi.org/10.4018/IJCALLT.367874

Tsao, J.-J. (2024). Unveiling the Links Between EFL Learners’ Perceived L2 Writing Classroom Goal Structures, Engagement with Teacher Written Corrective Feedback, and Self-Reported Writing Proficiency Through Structural Equation Modeling. Sage Open, 14(4), 21582440241299161. https://doi.org/10.1177/21582440241299161

Shen, R., & Chong, S. W. (2023). Learner engagement with written corrective feedback in ESL and EFL contexts: A qualitative research synthesis using a perception-based framework. Assessment & Evaluation in Higher Education, 48(3), 276–290. https://doi.org/10.1080/02602938.2022.2072468

Pearson, W. S. (2024). Affective, behavioural, and cognitive engagement with written feedback on second language writing: A systematic methodological review. Frontiers in Education, 9. https://doi.org/10.3389/feduc.2024.1285954

Shi, Y. (2021). Exploring Learner Engagement with Multiple Sources of Feedback on L2 Writing Across Genres. Frontiers in Psychology, 12. https://doi.org/10.3389/fpsyg.2021.758867

Yu, S., & Liu, C. (2021). Improving student feedback literacy in academic writing: An evidence-based framework. Assessing Writing, 48, 100525. https://doi.org/10.1016/j.asw.2021.100525

Rad, H. S., & Mirzaei, A. (2024). Developing feedback literacy, scaffolded writing, and resilience through intervention on feedback processes for L2 writing students. Studies in Educational Evaluation, 81, 101354. https://doi.org/10.1016/j.stueduc.2024.101354

Ding, L., Zou, D., & Kohnke, L. (2025). ChatGPT as an automated writing evaluation tool: How students perceive it and how it affects their writing. Education and Information Technologies. https://doi.org/10.1007/s10639-025-13775-3

Wei, P., Wang, X., & Dong, H. (2023). The impact of automated writing evaluation on second language writing skills of Chinese EFL learners: A randomized controlled trial. Frontiers in Psychology, 14. https://doi.org/10.3389/fpsyg.2023.1249991

Mao, Z., Lee, I., & Li, S. (2024). Written corrective feedback in second language writing: A synthesis of naturalistic classroom studies. Language Teaching, 57(4), 449–477. https://doi.org/10.1017/S0261444823000393

Thi, N. K., & Nikolov, M. (2023). Effects of teacher, automated, and combined feedback on syntactic complexity in EFL students’ writing. Asian-Pacific Journal of Second and Foreign Language Education, 8(1), 6. https://doi.org/10.1186/s40862-022-00182-1

Wang, I. X., Wu, X., Coates, E., Zeng, M., Kuang, J., Liu, S., Qiu, M., & Park, J. (2024). Neural Automated Writing Evaluation with Corrective Feedback (No. arXiv:2402.17613). arXiv. https://doi.org/10.48550/arXiv.2402.17613

Chen, Q. (2025). Students’ Perceptions of AI-Powered Feedback in English Writing: Benefits and Challenges in Higher Education. International Journal of Changes in Education. https://doi.org/10.47852/bonviewIJCE52025580

Ozan, O., & Azap, S. (2025). Students’ Perceptions of ChatGPT as a Feedback Tool in EFL Writing. Open Access Journal of Education & Language Studies, 3(1). https://doi.org/10.19080/OAJELS.2025.03.555604

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

Sari, E., & Han, T. (2024). The impact of automated writing evaluation on English as a foreign language learners’ writing self-efficacy, self-regulation, anxiety, and performance. Journal of Computer Assisted Learning, 40(5), 2065–2080. https://doi.org/10.1111/jcal.13004

Cheng, X., & Zhang, L. J. (2024). Examining Second Language (L2) Learners’ Engagement with AWE-Teacher Integrated Feedback in a Technology-Empowered Context. The Asia-Pacific Education Researcher, 33(4), 1023–1035. https://doi.org/10.1007/s40299-024-00877-8

Yan, D., & Zhang, S. (2024). L2 writer engagement with automated written corrective feedback provided by ChatGPT: A mixed-method multiple case study. Humanities and Social Sciences Communications, 11(1), 1086. https://doi.org/10.1057/s41599-024-03543-y

Tang, X. (2025). L2 Writing with AI: Perceptions and Engagement of EFL Learners in China. English Language Teaching, 18(2), p68. https://doi.org/10.5539/elt.v18n2p68

Ekizoğlu, M., & Demir, A. N. (2025). The role of AI assisted writing feedback in developing secondary students writing skills. Discover Education, 4(1), 454. https://doi.org/10.1007/s44217-025-00919-3

Schiller, R., Fleckenstein, J., Höft, L., Horbach, A., & Meyer, J. (2025). On the role of engagement in automated feedback effectiveness: Insights from keystroke logging. Computers & Education, 238, 105386. https://doi.org/10.1016/j.compedu.2025.105386

Fu, H., & Liu, X. (2022). EFL Learner Engagement in Automatic Written Evaluation. Frontiers in Psychology, 13, 871707. https://doi.org/10.3389/fpsyg.2022.871707

Crosthwaite, P., & Sun, S. (2025). Generative AI and L2 Written Feedback Studies: A Scoping Review. RELC Journal, 00336882251386530. https://doi.org/10.1177/00336882251386530

Rahman, N. A. A., Zulkornain, L. H., & Hamzah, N. H. (2022). Exploring Artificial Intelligence using Automated Writing Evaluation for Writing Skills. Environment-Behaviour Proceedings Journal, 7(SI9), 547–553. https://doi.org/10.21834/ebpj.v7iSI9.4304

Xiaosa, L., & Ping, K. (2025). How L2 student writers engage with automated feedback: A longitudinal perspective. Assessing Writing, 64, 100919. https://doi.org/10.1016/j.asw.2025.100919

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

Cengiz, B. C., Bilki, Z., Ataş, A. H., & Celik, B. (2025). Exploring second language writers’ engagement with ChatGPT feedback: Revision behaviors and perceptions. System, 134, 103837. https://doi.org/10.1016/j.system.2025.103837

Ajabshir, Z. F., & Ebadi, S. (2023). The effects of automatic writing evaluation and teacher-focused feedback on CALF measures and overall quality of L2 writing across different genres. Asian-Pacific Journal of Second and Foreign Language Education, 8(1), 26. https://doi.org/10.1186/s40862-023-00201-9

Youn, C. H., & Salam, A. R. (2025). A Systematic Review on the Use of Artificial Intelligence in Providing Feedback in Teaching Writing. LSP International Journal, 12(2), 133–142. https://doi.org/10.11113/lspi.v12.26003

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, 100270. https://doi.org/10.1016/j.caeai.2024.100270

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. https://doi.org/10.3389/frai.2023.1162454

Liu, Z., Litman, D., Wang, E., Li, T., Gobat, M., Matsumura, L. C., & Correnti, R. (2025). eRevise+RF: A Writing Evaluation System for Assessing Student Essay Revisions and Providing Formative Feedback (No. arXiv:2501.00715). arXiv. https://doi.org/10.48550/arXiv.2501.00715

Wilson, J., Huang, Y., Palermo, C., Beard, G., & MacArthur, C. A. (2021). Automated Feedback and Automated Scoring in the Elementary Grades: Usage, Attitudes, and Associations with Writing Outcomes in a Districtwide Implementation of MI Write. International Journal of Artificial Intelligence in Education, 31(2), 234–276. https://doi.org/10.1007/s40593-020-00236-w

Aladini, A., Ismail, S. M., Ahmad Saleem Khasawneh, M., & Shakibaei, G. (2025). Self-directed writing development across computer/AI-based tasks: Unraveling the traces on L2 writing outcomes, growth mindfulness, and grammatical knowledge. Computers in Human Behavior Reports, 17, 100566. https://doi.org/10.1016/j.chbr.2024.100566

Almusharraf, A., Bailey, D., Almusharraf, N., & Alotaibi, T. (2025). Students’ perceptions of generative AI in EFL writing: Strategies, self-efficacy, satisfaction and behavioural intention. Australasian Journal of Educational Technology. https://doi.org/10.14742/ajet.10045