AI-Assisted Critical Reading in Enhancing EFL Students’ Argumentative Writing
A Mixed-Methods Study
Abstract
This study investigates the effect of AI-assisted critical reading on EFL students’ argumentative writing performance. Although previous studies have explored AI in language learning, limited research has specifically examined its role in integrating critical reading with argumentative writing in EFL contexts, particularly using a mixed-methods approach. Employing a mixed-methods approach with an explanatory sequential design, the study involved 50 undergraduate students from Institut Bisnis dan Komputer Indonesia, divided into an experimental group and a control group. The experimental group received instruction through AI-assisted critical reading, while the control group was taught using conventional methods. Data were collected through writing tests (pre-test and post-test) and semi-structured interviews. The quantitative data were analyzed using paired and independent sample t-tests, while the qualitative data were analyzed thematically. The findings revealed that the experimental group showed significantly greater improvement in writing performance compared to the control group, with a large effect size. The results also indicated that AI-assisted critical reading enhanced students’ ability to analyze texts, generate ideas, and organize arguments effectively. In addition, students reported positive perceptions, including increased engagement, confidence, and motivation in learning. This study contributes to the growing body of literature by demonstrating the effectiveness of AI as a cognitive and pedagogical tool that supports the integration of reading and writing processes in EFL contexts.
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