2026/5/27
Hamid Reza Dowlatabadi

Hamid Reza Dowlatabadi

Academic rank: Assistant Professor
ORCID: https://orcid.org/0000-0002-7763-6678
Education: PhD.
H-Index:
Faculty: Literature and Languages
ScholarId:
E-mail: H-Dowlatabadi [at] araku.ac.ir
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Phone:
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Research

Title
The Effect of Artificial Intelligence on Personalized Writing Feedback for ESL Learners
Type
Thesis
Keywords
Artificial Intelligence, Writing Performance, EFL Learners, AI Feedback, ChatGPT, Grammarly, Academic Writing
Year
2026
Researchers Hamid Reza Dowlatabadi(PrimaryAdvisor)، Hamid Varmazyari(Advisor)، Manal Nihad Jasim Aldulaimi(Student)

Abstract

This study investigated the effect of Artificial Intelligence (AI)-based personalized feedback on the writing performance of Iraqi EFL learners at Al-Mustansiriyah University. The purpose was to examine whether AI tools such as ChatGPT and Grammarly could enhance students’ writing skills more effectively than traditional teacher feedback. A quantitative quasi-experimental design was employed, involving sixty (60) undergraduate students majoring in English. Participants were divided into two equal groups: an experimental group that received AI-based feedback and a control group that received traditional feedback from instructors. Data were collected through pre- and post-writing tests, along with an English proficiency test (Oxford Placement Test) administered to ensure group equivalence. Statistical analyses were conducted using SPSS (Version 28), including descriptive statistics, independent and paired samples t-tests, and Pearson correlation analysis. The[h1.1] results revealed a statistically significant difference between the experimental and control groups in post-test writing scores, indicating that students who received AI-assisted feedback performed better in areas such as organization, vocabulary, grammar, and coherence. Gender-based analysis showed no significant differences between male and female learners, suggesting that AI feedback benefits both genders equally. Moreover, a strong positive correlation (r = .821, p < .01) was found between learners’ proficiency levels and their post-writing performance, highlighting that higher proficiency enables more effective utilization of AI-generated feedback. The study concludes that AI-based feedback is an effective pedagogical tool for improving EFL writing skills. It promotes learner autonomy, reduces teachers’ workload, and enhances the quality of feedback. The findings suggest that integrating AI into language teaching can significantly improve the learning process if used responsibly and in combination with human instruction. Recommendations are made for incorporating AI technologies into EFL curricula, providing teacher training, and conducting further research on long-term impacts of AI in language education.