ChatGPT as a Feedback Provider: Arab Students' Perceptions of AI-Based Writing Evaluation in Academic English

Abdullah Alshayban

Abstract


The research has four constructs, including perceived usefulness, trust and accuracy, motivation, and behavior intention, which indicate the perceptions of EFL students regarding ChatGPT as a feedback tool in English writing. The mixed-methods design was used to collect data (N = 254) on surveys and open-ended responses. Quantitative methods (descriptive statistics, reliability, regression, and mediation) indicated that ChatGPT was the most useful tool in general in enhancing the grammar, organization, and clarity of readers. Its performance was impressive, but it was also inconsistent with its accuracy, as it had gaps in contexts that arose occasionally. The regression proved that perceived usefulness, trust, and motivation were all helpful predictors of behavioral intention and that motivation mediated usability. This was supported by the qualitative results, which focused on the immediacy and supportiveness of ChatGPT. To conclude, ChatGPT is a useful and supplementary type of feedback compared to the one provided by a teacher because it helps to foster self-confidence and self-reliance in a student when editing the drafts.

Keywords


ChatGPT; Feedback; Human; AI; EFL Students; Motivation; Perceived Usefulness; Trust And Accuracy; Behavioral Intention

References


Alnemrat, A., Aldamen, H., Almashour, M., Al-Deaibes, M., & AlSharefeen, R. (2025) AI vs. teacher feedback on EFL argumentative writing: a quantitative study. Frontiers in Education, 10, 1614673. https://doi.org/10.3389/feduc.2025.1614673

Alwasidi, M. A., & Al-Khalifah, K. S. (2025). Assessing the impact of ChatGPT on EFL students’ writing productivity and proficiency. Journal of Language Teaching and Research, 16(3), 986–995. https://doi.org/10.17507/jltr.1603.18

BERA (2018). Ethical guidelines for educational research. Retrieved January 10, 2026, from https://study.sagepub.com/sites/default/files/bera_ethical_guidelines_2018_4th_ed.pdf

Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008

Dörnyei, Z. (2007). Research methods in applied linguistics: Quantitative, qualitative, and mixed methodologies. Oxford University Press.

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(1), 57. https://doi.org/10.1186/s41239-023-00425-2

Fetters, M. D., Curry, L. A., & Creswell, J. W. (2013). Achieving integration in mixed methods designs—Principles and practices. Health Services Research, 48(6 Pt 2), 2134–2156. https://doi.org/10.1111/1475-6773.12117

Hayes, A. F. (2017). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. Guilford Publications.

Kurt, G., & Kurt, Y. (2024). Enhancing L2 writing skills: ChatGPT as an automated feedback tool. Journal of Information Technology Education: Research, 23, 1–17. https://doi.org/10.28945/5370

Mekheimer, M. (2025). Generative AI-assisted feedback and EFL writing: A study on proficiency, revision frequency and writing quality. Discover Education, 4(1), 170. https://doi.org/10.1007/s44217-025-00602-7

Mizumoto, A., Shintani, N., Sasaki, M., & Teng, M. F. (2024). Testing the viability of ChatGPT as a companion in L2 writing accuracy assessment. Research Methods in Applied Linguistics, 3(2), 100116. https://doi.org/10.1016/j.rmal.2024.100116

Nelson, A. S., Santamaría, P. V., Javens, J. S., & Ricaurte, M. (2025). Students’ perceptions of generative artificial intelligence (GenAI) use in academic writing in English as a foreign language. Education Sciences, 15(5), 611. https://doi.org/10.3390/educsci15050611

Pallant, J. (2020). SPSS survival manual: A step-by-step guide to data analysis using IBM SPSS. Routledge. https://doi.org/10.4324/9781003117452

Plano Clark, V. L. (2017). Mixed methods research. The Journal of Positive Psychology, 12(3), 305–306. https://doi.org/10.1080/17439760.2016.1262612

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

Ryan, R. M., & Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist, 55(1), 68–78. https://doi.org/10.1037/0003-066X.55.1.68

Shahat, H. A., Badawy, M. E., Elballah, K. A., & Ibrahim-Shook, A. (2025). Self-efficacy as a mediator between ChatGPT usage and research motivation among postgraduate students. International Journal of Innovative Research and Scientific Studies, 8(4), 987–996. https://doi.org/10.53894/ijirss.v8i4.7982

Shao, S. (2025). The role of AI tools on EFL students’ motivation, self-efficacy, and anxiety: Through the lens of control-value theory. Learning and Motivation, 91, 102154. https://doi.org/10.1016/j.lmot.2025.102154

Şimşek, A. S., Cengiz, G. Ş. T., & Bal, M. (2025). Extending the TAM framework: Exploring learning motivation and agility in educational adoption of generative AI. Education and Information Technologies, in press. https://doi.org/10.1007/s10639-025-13591-9

Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540

Wang, J., & Fan, W. (2025). The effect of ChatGPT on students’ learning performance, learning perception, and higher-order thinking: Insights from a meta-analysis. Humanities and Social Sciences Communications, 12(1), 1–21. https://doi.org/10.1057/s41599-025-04787-y

Werdiningsih, I., Marzuki, & Rusdin, D. (2024). Balancing AI and authenticity: EFL students’ experiences with ChatGPT in academic writing. Cogent Arts & Humanities, 11(1), 2392388. https://doi.org/10.1080/23311983.2024.2392388

Yıldız, T. A. (2023). The impact of ChatGPT on language learners’ motivation. Journal of Teacher Education and Lifelong Learning, 5(2), 582–597.

Youn, C. H., Salam, A. R., & Rahman, A. A. (2025). AI-driven tools in providing feedback on students’ writing. International Journal of Research and Innovation in Social Science, 9(3s), 58–67.

Zhai, X., Zhao, R., Jiang, Y., & Wu, H. (2024). Unpacking the dynamics of AI-based language learning: Flow, grit, and resilience in Chinese EFL contexts. Behavioral Sciences, 14(9), 838. https://doi.org/10.3390/bs14090838

Zhang, A., Gao, Y., Suraworachet, W., Nazaretsky, T., & Cukurova, M. (2025). Evaluating trust in AI, human, and co-produced feedback among undergraduate students. arXiv preprint, arXiv:2504.10961. https://doi.org/10.48550/arXiv.2504.10961




DOI: https://doi.org/10.18860/ijazarabi.v9i3.42134

Refbacks

  • There are currently no refbacks.


Copyright (c) 2026 Abdullah Alshayban

License URL: https://creativecommons.org/licenses/by-sa/4.0/