Unpacking the Rejection of L2 Students Toward ChatGPT-Generated Feedback: An Explanatory Research
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Purpose Drawing on the Unified Theory of Acceptance and Use of Technology (UTAUT), this sequential mixed-method study explored L2 learners’ challenges in seeking corrective feedback in an AI-assisted educational environment. Design/Approach/Methods The data was collected from 45 university students in a Computer Science program who were encouraged to seek corrective feedback from ChatGPT for their argumentative writing report. Self-reflection data were qualitatively and quantitatively analyzed. Findings Findings suggested that 45.9% of the AI-generated feedback was rejected by students, with a higher rejection rate observed for content-focused feedback (58.7%) compared to form-focused feedback (41.3%). AI-generated content-focused feedback was rejected due to misalignments between expected and received feedback, anticipated high workload to respond, mismatch between feedback from AI and external references, and impeding conditions for students to engage with the feedback. Meanwhile, the rejection of form-focused feedback was largely associated with the high level of expected effort. Originality/Value This study is one of the few existing studies on the L2 learners’ challenges in seeking corrective feedback from generative AI systems. Notably, the study differentiates between form-focused and content-focused feedback and identifies the distinct challenges and learning opportunities that impact students’ rejection of AI feedback.
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Systematic reviews show that most gains occur when AI is embedded in pedagogy that promotes critical engagement with feedback and human-AI negotiation, rather than passive acceptance.
“Systematic reviews show that most gains occur when AI is embedded in pedagogy that promotes critical engagement with feedback and human-AI negotiation, rather than passive acceptance (Li et al., 2025; Chen, 2025).”
From A New Era with Artificial Intelligence Powered Learner Corpora for Teaching and Learning of English as a Second Language in Primary School Education (2025) · cites this paper as Chen, 2025
Similar patterns of ambivalence and partial rejection have been reported in recent studies of AI feedback in higher education.
“Similar patterns of ambivalence and partial rejection have been reported in recent studies of AI feedback in higher education (Chen et al., 2025).”
From A New Era with Artificial Intelligence Powered Learner Corpora for Teaching and Learning of English as a Second Language in Primary School Education (2025) · cites this paper as Chen et al., 2025
Cites
Chatting and cheating: Ensuring academic integrity in the era of ChatGPT
Cotton, D. R. E., Cotton, P. A., & Shipway, J. R. (2024) · Innovations in Education and Teaching International · doi:10.1080/14703297.2023.2190148 · Cited by 3,087 · see citing works
Chatting and Cheating. Ensuring academic integrity in the era of ChatGPT
Cotton, D., Cotton, P., & Shipway, J. R. (2023) · doi:10.35542/osf.io/mrz8h · Cited by 3,079 · see citing works
The development of student feedback literacy: Enabling uptake of feedback
Carless, D., & Boud, D. (2018) · Assessment & Evaluation in Higher Education · doi:10.1080/02602938.2018.1463354 · Cited by 2,428 · see citing works
Interacting with educational chatbots: A systematic review
Kuhail, M. A., Alturki, N., Alramlawi, S., & Alhejori, K. (2023) · Education and Information Technologies · doi:10.1007/s10639-022-11177-3 · Cited by 841 · see citing works
AI-generated feedback on writing: insights into efficacy and ENL student preference
Escalante, J., Pack, A., & Barrett, A. (2023) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-023-00425-2 · Cited by 589 · see citing works
Using digital story writing as a pedagogy to develop AI literacy among primary students
Ng, D. T. K., Luo, W., Chan, H. M. Y., & Chu, S. K. W. (2022) · Computers and Education Artificial Intelligence · doi:10.1016/j.caeai.2022.100054 · Cited by 266 · cited 1× · see citing works
“To address the signi fi cant effort required to process feedback, we suggest establishing courses on computational thinking and designing materials to enhance critical evaluation skills (Ng et al., 2022).”
Hew, K. F., Huang, W., Du, J., & Jia, C. (2023) · Journal of Computing in Higher Education · doi:10.1007/s12528-022-09338-x · Cited by 245 · see citing works
Grammarly as AI-powered English Writing Assistant: Students' Alternative for Writing English
Fitria, T. N. (2021) · Metathesis: Journal of English Language, Literature, and Teaching · doi:10.31002/metathesis.v5i1.3519 · Cited by 221 · see citing works
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Generative AI and L2 Written Feedback Studies: A Scoping Review
Crosthwaite, P., & Sun, S. (2026) · RELC Journal · doi:10.1177/00336882251386530 · Cited by 50 · see citing works
Wong, W. L., & Fong, S. (2025) · Applied Language Sciences · doi:10.65553/als.250105 · Cited by 2 · see citing works
- Authors
- Chen (陈子淇), Z., Wei (韦卫), W., Zhu (祝新华), X., & Yao (姚远), Y.
- Affiliations
- Macao Polytechnic University
- The Hong Kong Polytechnic University
- Venue
- ECNU Review of Education
- Publisher
- SAGE Publications
- Published
- 2025-01-07
- Volume
- 9
- Issue
- 1
- ISSN
- 2096-5311 (ISSN-L)
- 2632-1742
- OpenAlex
- W4406126518
- Cited by
- 16
- References
- 8
- Citations by year
- 2026: 6 · 2025: 10
- FWCI
- 57.63
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- Locations
- ECNU Review of Education (publishedVersion, cc-by-nc)
- PolyU Institutional Research Archive (Hong Kong Polytechnic University) (publishedVersion, cc-by-nc)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Macao Polytechnic University Research Grant (RP/FCA-08-2023)
- Topics
- Social Sciences › Arts and Humanities › Language and Linguistics › EFL/ESL Teaching and Learning
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Social Sciences › Education › Student Assessment and Feedback
- Keywords
- ChatGPT, AI-generated feedback, corrective feedback, second language writing, argumentative writing, UTAUT, generative AI in education, student effort, computer science students
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