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Arab World English Journal (AWEJ) Volume 16. Number 1, March 2025 Pp.384-402
The English Unit, College of Applied Studies, Northern Border University, Arar, Saudi Arabia.
Department of Languages and Translation, Northern Border University, Arar, Saudi Arabia.
Department of Languages and Translation, Northern Border University, Arar, Saudi Arabia
Department of Languages and Translation, Faculty of Arts and Science- Rafha, Northern Border University, Arar, Saudi Arabia
Department of Languages and Translation, Faculty of Arts and Science- Rafha, Northern Border University, Arar, Saudi Arabia
Department of Languages and Translation, Faculty of Arts and Science- Rafha, Northern Border University, Arar, Saudi Arabia
Department of English, Applied College Rafha, Faculty of Education and Arts, Northern Border University, Arar, Saudi Arabia.
Department of Languages and Translation, Faculty of Arts and Science- Rafha, Northern Border University, Arar, Saudi Arabia
This study investigates how AI-driven Automated Written Corrective Feedback can facilitate EFL writing, teaching, and evaluation in Arab schools and universities. The study addresses a significant research gap in the Computer-Assisted Language Learning literature by examining the impact of Automated Essay Scoring systems’ feedback on EFL University students’ writing. AI-powered AWCF tools have the potential to enhance writing accuracy, provide individualized feedback, and reduce teachers’ workload by offering automated yet effective corrective feedback. By analyzing EFL learners’ and instructors’ perceptions, this study contributes to developing user-centered AWE systems that align with the pedagogical needs of L2 writing instruction. The findings will inform educators, software developers, and policymakers on optimizing AI-driven feedback for EFL learners. The Main Research Question is: How does AI-driven Automated Written Corrective Feedback influence EFL university students’ writing proficiency and feedback preferences? A mixed-methods approach was used to conduct a longitudinal controlled experiment at Northern Border University in Saudi Arabia. The study involved questionnaires with 120 students and interviews with 27 students and 4 teachers. An exploratory factor analysis was employed to analyze perceptions of AWCF. The data analyzed the impact of ease of use, clarity, usefulness, EFL learners’ perceptions, and feedback explicitness on AWCF use. The findings proved that EFL students and teachers found AWE systems easy to use and useful for corrective feedback. Furthermore, students preferred using specific AWCF strategies over generic feedback. Developers should consider diverse factors influencing EFL learners’ preferences and views of AWCF to create useful, clear, and desirable tools.
Elmotri, B., Harizi, R., Boujlida,A., Elyasa, Y.M., Garrouri, S., Amri, F., Malik, F. H., & Al-humari, M.A. (2025). The Impact of AI-Generated Feedback Explicitness. Arab World English Journal, 16(1):384-402
Alenazi, M, S., Elmotri, B., Khamis, J., & Darem, A. (2025). Assessing the efficacy of ChatGPT’s automated corrective feedback in enhancing students’ writing proficiency. International Journal of Advanced And Applied Sciences, 12(2), 90-100.
Al-Zubaidi, K., Jaafari, M., & Touzani, F. Z. (2024). Impact of ChatGPT on Academic Writing at Moroccan Universities. Arab World English Journal (AWEJ) Special Issue on ChatGPT, April 2024:4-25. DOI: https://dx.doi.org/10.24093/awej/ChatGPT.1
Bitchener, J. (2008). Evidence in support of written corrective feedback. Journal of Second Language Writing, 17(2), 102-118.
Bitchener, J., & Knoch, U. (2008). The value of written corrective feedback for migrant and international students. Language teaching research, 12(3), 409-431.
Bitchener, J., & Ferris, D. R. (2012). Written corrective feedback in second language acquisition and writing: Routledge.
Burstein, J., Chodorow, M., & Leacock, C. (2004). Automated essay evaluation: The Criterion online writing service. AI Magazine, 25(3), 27-27. doi:https://doi.org/10.1609/aimag.v25i3.1774
Burstein, J. et al. (2018). Writing mentor: Writing progress using self-regulated writing support. Journal of Writing Analytics, 2, 285-313.
Cavaleri, M. R., & Dianati, S. (2016). You want me to check your grammar again? The usefulness of an online grammar checker as perceived by students. Journal of Academic Language Learning, 10(1), A223-A236. Retrieved from https://journal.aall.org.au/index.php/jall/article/view/393
Conference on College Composition and Communication. (2014). Writing Assessment: A Position Statement. Retrieved from https://ncte.org/statement/writingassessment/
Chapelle, C., & Erik, V. (2016). 20 years of technology and language assessment in language learning & technology. Language Learning Technology, 20(2), 116-128. http://llt.msu.edu/issues/june2016/chapellevoss.pdf
Chen, C.-F. E., & Cheng, W.-Y. E. C. (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.
Desoky, M., Elmotri, B. (2024). Effectiveness of LMSs in assessing students’ actual level from a distance during the COVID-19 pandemic. International Journal of Advanced and Applied Sciences. https://www.science-gate.com/IJAAS/Articles/2024/2024-11-06/1021833ijaas202406013.pdf.
Ellis, R. (2009). Corrective feedback and teacher development. L2 Journal: An electronic refereed journal for foreign and second language educators, 1(1).
Elmotri, B. et.al. (2024). Do LMOOCs support second language acquisition: Understanding the digital factor associated with improving EFL students’ English language skills—An empirical study. The Seybold Report Journal. https://seyboldreport.org/article_overview?id=MTAyMDI0MDMxNzI1MzE4NTYy.
Elmotri, B. et .al. (2024). Potentials within ChatGPT to Enhance ESP Writing Skills (Autonomous Language Learning): The Case of EFL Saudi Learners. TheSeyboldReportJournal. https://seyboldreport.org/article_overview?id=MTAyMDI0MDMxNzQ5NTM3NDI1.
Elmotri, B. et.al. (2025). The Use of Authentic Materials in English-medium Instructed Business Classes in Higher Education and Academic Efficacy. Ianna Journal Of Interdisciplinary Studies.
Elmotri, B.. et. al. (2024). Unlocking Language Proficiency: A Comprehensive Comparison of Duolingo and Oxford English Coach Effectiveness in Language Learning. (2025). Mediterranean Journal of Social Sciences, 16(1), 23. https://doi.org/10.36941/mjss-2025-0003
Elmotri, B., & Smaoui, C. (2024). Evaluating the effectiveness of using automated written corrective feedback on EFL university students’ writing. International Journal of Information Technology and Language Studies (IJITLS).8,(1) pp. 13-33 https://journals.sfu.ca/ijitls/index.php/ijitls/article/view/353.
Ferris DR. SECOND LANGUAGE WRITING RESEARCH AND WRITTEN CORRECTIVE FEEDBACK IN SLA: Intersections and Practical Applications. Studies in Second Language Acquisition. 2010;32(2):181-201. doi:10.1017/S0272263109990490
Ferris, Liu, H., Sinha , A., & Senna , M. (2013). Written corrective feedback for individual L2 writers. Journal of second language writing, 22(3), 307-329. doi:https://doi.org/10.1016/j.jslw.2012.09.009
Ferris, & Roberts, B. (2001). Error feedback in L2 writing classes: How explicit does it need to be? Journal of Second Language Writing, 10(3), 161-184. doi:https://doi.org/10.1016/S1060-3743(01)00039-X
Ferris, D. (2006). Does error feedback help student writers? New evidence on the short-and long-term effects of written error correction. Feedback in second language writing: Contexts and issues, 81104.
Fu, Q.-K., Zou, D., Xie, H. & Cheng, G. (2022) A review of AWE feedback: Types, learning outcomes, and implications. Computer Assisted Language Learning. Advance online publication. https://doi.org/10.1080/09588221.2022.2033787
Gass, S., & Selinker, L. (1983). Language Transfer in Language Learning. Issues in Second Language Research: ERIC.
Goins, M. (2015). Written corrective feedback: strategies for l2 writing instructors. SLW News: The Newsletter of the Second Language Writing Interest Section, TESOL.org . http://newsmanager.commpartners.com/tesolslwis/issues/2015-10-07/3.html.
Graham, S. et al. (2016). Retrieved from the NCEE website: http://whatworks. ed. gov. Teaching secondary students to write effectively (NCEE 2017-4002). Washington, DC: National Center for Education Evaluation Regional Assistance, Institute of Education Sciences, US Department of Education. Retrieved from the NCEE website: http://whatworks. ed. gov.
Hartshorn, K. J. et al. (2010). Effects of dynamic corrective feedback on ESL writing accuracy. TESOL Quarterly, 44(1), 84-109.
Hyland, K., & Hyland, F. (2006). Feedback on second language students’ writing. Language teaching, 39(2), 83–101.
Kasneci, E., et al. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences.
Ranalli, J. (2018). Automated written corrective feedback: How well can students make use of it? Computer Assisted Language Learning, 31(7), 653–674. doi:10.1080/09588221.2018.1428994
Ranalli, J. (2021). L2 student engagement with automated feedback on writing: Potential for learning and issues of trust. Journal of Second Language Writing, 52, 100816.
Ranalli, J., Link, S., & Chukharev-Hudilainen, E. (2017). Automated writing evaluation for formative assessment of second language writing: investigating the accuracy and usefulness of feedback as part of argument-based validation. Educational Psychology, 37(1), 8-25. 10.1080/01443410.2015.1136407.
Schmidt, R. (1990). The Role of Consciousness in Second Language Learning1. Applied Linguistics, 11(2), 129–158. doi:10.1093/applin/11.2.129 %J Applied Linguistics
Schmidt, R. (1992). Psychological mechanisms underlying second language fluency. Studies in Second Language Acquisition, 357–385.
Truscott, J. (1996). The case against grammar correction in L2 writing classes. Language Learning, 46(2), 327–369.
Truscott, J. (1999). The case for “The case against grammar correction in L2 writing classes”: A response to Ferris. Journal of Second Language Writing, 8(2), 111–122.
Truscott, J. (2007). The effect of error correction on learners’ ability to write accurately. Journal of Second Language Writing, 16(4), 255–272.
Tseng, W., & Warschauer, M. (2023). AI-writing tools in education: If you can’t beat them, join them. Journal of China Computer-Assisted Language Learning, 3(2), 258–262. https://doi.org/10.1515/ jccall-2023-0008
Warschauer, M., & Grimes, D. (2008). Automated writing assessment in the classroom. Pedagogies: An International Journal, 3(1), 22-36.
Weigle, S. C. (2010). Validation of automated scores of TOEFL iBT tasks against non-test indicators of writing ability. Language Testing, 27(3), 335-353. doi:https://doi.org/10.1177/0265532210364406
Weigle, S. C. (2013). English as a second language writing and automated essay evaluation. Handbook of automated essay evaluation: Current applications new directions, 36-54. doi:https://www.routledgehandbooks.com/doi/10.4324/9780203122761.ch3
Shute, V. J. (2008). Shute, V. J. (2008). Focus on formative feedback. Review of educational research, 78(1), 153–189.
Shi, H. & Aryadoust, V. (2024). A systematic review of AI-based automated written feedback research. ReCALL 36(2): 187–209. https://doi.org/10.1017/S0958344023000265
Strobl, C., et al. (2019). Computer-assisted writing support tools: Their effectiveness and implications for future development. Computers and Composition.
Wang, C. (2024). Exploring Students’ Generative AI-Assisted Writing Processes: Perceptions and Experiences from Native and Nonnative English Speakers. Tech Know Learn. https://doi.org/10.1007/s10758-024-09744-3
Dr. Bilel Elmotri holds a Ph.D. in Linguistics from Tunisia and is a faculty member at Northern Border University, Saudi Arabia. His research focuses on EMI, ESP, EFL, artificial Intelligence, and technology’s role in language learning, mainly through Automated Writing Corrective Feedback tools. Elmotri has published articles and presented papers at conferences.
ORCID ID: https://orcid.org/0000-0001-5744-0224.
Radhia Harizi is a faculty member in the Department of Languages and Translation at the Northern Border University in Saudi Arabia. She received a Master’s degree in Linguistics from the University of Sfax, Tunisia, and is currently pursuing a Ph.D. Her research centers on issues related to second-language learning, individual differences and emotional variables in second-language acquisition, pragmatics, EFL, artificial intelligence, and technology`s role in learning. Harizi has published a number of articles. E-mail:Rafifradhia@gmail.com ORCID ID: https://orcid.org/0009-0009-1621-3530
Amel Boujlida is an experienced lecturer with 15 years of teaching expertise, 10 of which were spent at Northern Borders University. The academic contributions include writing several articles focused on the field of linguistics. Department of Languages and Translation, Northern Border University, Arar, Saudi Arabia E-mail:amelb.graa@hotmail.com
ORCID: https://orcid.org/0009-0008-9247-0523
Yasir M. Elyasa is a teaching staff member of the Department of Languages and Translation, Faculty of Arts and Humanities, Northern Border University, KSA. He holds a PhD. in English literature from the University of Khartoum, Sudan. His research revolves around topics related to literature and applied linguistics, as in some published articles. Email: Yasir.Elyasa@nbu.edu.sa
ORCID https://orcid.org/0000-0002-3415-9306
Sihem Garrouri is an Assistant Professor of English at Northern Border University, Saudi Arabia. She studied at the University of Caen Normandy, France. Her research interests include Renaissance studies, the Elizabethan era, and history of thoughts and politics. Garrouri’s recent publications include “Queen Elizabeth I: The Rhetoric of a Unique Paradoxical Image”, “Mythologizing the Memory of Gloriana”, and “Elizabeth I’s Royal Progresses: A Study of Formal Orations and Poetic Recitations”.Email:sihem.garrouri@gmail.com ORCID ID: https://orcid.org/0000-0001-6600-4870
Farid Amri is currently teaching in the Department of Languages and Translation at the Northern Border University, KSA. He received a PhD from the University of Mannuba, Tunisia. His research centers on discourse analysis, second-language acquisition, and the role of artificial intelligence in language learning. Email: ferid9002@yahoo.com
ORCID: https://orcid.org/0000-0003-3745-3479
Dr. Fakhar Malik has PhD in Interpersonal Linguistics. He is specialisd in Lingustics & Applied Ling, TESOL. He has diverse experience in the universities of NUML, UIIT, IU, AIOU & NBU. His interests of research are in both Lingustics & Applied Linguistics.He works in the College of Humanities & Social Sciences, NBU. Email: awanhassnain@gmail.com
ORCID: http://Orcid.org/0000.0001-7501-4325
Mustafa Ahmed Al-humari is an Assistant Professor of Linguistics in the Department of Languages and Translation, Faculty of Humanities and Social Sciences, Arar, Northern Border University, Saudi Arabia. His primary research areas include morphosyntactic and syntax-semantic interface issues in languages with a focus on English and Arabic. He has also conducted research on English language learning and acquisition. Email: mustafa4008@gmail.com ORCID: https://orcid.org/0000-0002-1054-4752