An empirical study of Chinese EFL student writers’ use of GenAI feedback during revision
Perceptions, engagement and motivational impact
Bibliographic Data
| ID | 19379224 |
|---|---|
| Authors | Xiaosa Li (0000-0003-0411-1122, College of Art, Nanjing University of Information Science & Technology, corresponding author), Wenyu Wang (0009-0005-5624-0657, Nanjing University), Lili Gu (0009-0001-7116-6062, Nanjing Tech University) |
| Year | 2025 |
| Pages | 1-16 |
| Publication date | 2025-11-20 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | Assessment & Evaluation in Higher Education (JOURNAL) |
| Journal identifiers | ISSN: 0260-2938 • E-ISSN: 1469-297X |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/02602938.2025.2587925 |
| OpenAlex | W4416437225 |
| Language | EN |
| Citations received | 1 |
| References cited | 26 |
This mixed-methods study aimed to investigate how English as a foreign language (EFL) student writers perceive and engage with GenAI feedback during revision. The participants were a class of 36 English majors enrolled in an advanced English class where a combined approach of GenAI, peer and teacher feedback was implemented in writing. Six students of different proficiency were chosen as the focal participants. Multiple sources of data (questionnaire, GenAI logs, writing drafts, semi-structured interviews) were collected after a semester-long treatment. The results indicate that while GenAI feedback was generally perceived to demonstrate impressive capacity in providing corrective feedback, its motivational impact on EFL writing was dubious because of computer-sourced feedback’s fundamental inability for recognition, coupled with the social, communicative nature of writing. The inability of GenAI to be involved in genuinely recognitive relations poses both opportunities and challenges in higher education feedback practices. Educators are advised to preserve the unique value of human aspects in pedagogical relationships when trying to integrate GenAI into traditional feedback mechanisms
Empirical research · Higher education · Likert scale · Qualitative research · Statistical analysis · Student engagement · Teaching method · EFL/ESL Teaching and Learning · Student Assessment and Feedback · Writing and Handwriting Education
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| Unique citing works | 1 |
|---|---|
| Citations per year | 1 |
| Citation span | 2026 - 2026 (1) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 1 |