AI-Based Feedback Systems for Improving Grammar Accuracy: An Experimental Study in EFL Context
DOI:
https://doi.org/10.58421/gehu.v5i4.1785Keywords:
AI-Based feedback , EFL Writing , Grammatical accuracy, Quasi-Experimental Design , Language LearningAbstract
This study aims to investigate the effectiveness of Artificial Intelligence (AI)-based feedback in improving the grammatical accuracy of English as a Foreign Language (EFL) learners. The study employed a quantitative quasi-experimental design using a pre-test–post-test control group. The participants consisted of 60 university students, who were divided into an experimental group receiving AI-based feedback and a control group receiving conventional teacher feedback. Data were collected through essay writing tests and analyzed using descriptive statistics, paired-sample t-tests, and independent-sample t-tests. The findings revealed that both groups demonstrated improvement; however, the experimental group showed a significantly greater increase in grammatical accuracy (from 65.4 to 82.6) compared to the control group (from 66.1 to 74.3). The results of the independent-sample t-test indicated a statistically significant difference between the two groups (p < 0.001). These findings suggest that AI-based feedback provides immediate and individualized corrective input that effectively enhances learners’ grammatical performance. Nevertheless, teacher feedback remains essential in providing contextual and pedagogical support. Therefore, the integration of AI and teacher feedback is recommended to achieve optimal learning outcomes in EFL writing.
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Namaziandost, “Integrating Flipped Learning in AI-Enhanced Language Learning: Mapping the Effects on Metacognitive Awareness, Writing Development, and Foreign Language Learning Boredom,” Computers and Education: Artificial Intelligence, 2025. doi:10.1016/j.caeai.2025.100446.
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