Human, AI, and Combined Corrective Feedback in EFL Writing: A Mixed Methods Comparative Study with Iranian Learners
الموضوعات :
Kolsoum Ghasemi
1
,
Shahram Afraz
2
,
Maryam Habouti
3
1 - Department of English, Hormozgan University of Medical Sciences, Bandar Abbas, Iran
2 - Department of English Language Teaching, Qe.C. , Islamic Azad University, Qeshm, Iran
3 - Ministry of Education, Bandar Anzali, Iran
الکلمات المفتاحية: AI feedback, automated writing evaluation, EFL learners, human corrective feedback, Iranian students, writing performance,
ملخص المقالة :
Corrective Feedback is a critical factor in enhancing EFL students' writing ability. This research contrasted the impact of the AI-generated, human-created, and blended written corrective feedback on Iranian EFL university students' academic writing proficiency, focusing on both surface-level accuracy and higher-order writing skills, such as coherence and organization. 384 intermediate-level students were randomly distributed across three groups and provided with feedback on their weekly writing assignments over on six weeks. To that end, IELTS-aligned rubrics were used to measure their writing performance, and students' views were probed through focus group interviews. Based on the quantitative data analyses, all three groups improved statistically. In fact, the combined written corrective feedback condition was the best, with the largest gain score and largest effect size, and the AI-generated written corrective feedback also led to robust gains, particularly on expanding grammatical range and lexical accuracy, while the human-only written corrective feedback yielded moderate-to-large effects, particularly on coherence and idea development. All groups showed statistically significant improvement in their writing performances. However, thе combined fееdback group outperformed both AI-generated and human-only groups, with thе highest gain score. Four major themes and seven subthemes were extracted based on the qualitative data analysis of the focus group interviews with 30 interviews, Thematic analysis revealed that AI-generated WCF enhanced efficiency and reduced anxiety, human-generated WCF provided deeper conceptual guidance, and the combined WCF led to greater clarity, confidence, and more effective revision strategies among EFL learners. The findings suggest additional research and practice to see if the long-term influence of feedback modality and efficacy for learners with different proficiency levels and backgrounds holds.
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