A Quasi-Experimental Study of Inquiry-Based Learning for Enhancing Motivation and Reflective Thinking in EFL Recount Writing - Ikha Listyarini; Davron Aslonqulovich Juraev; Sri Wahyuni; Nur Hidayat; Muhammad Arief Budiman (International Journal of Education and Teaching Zone, 2026)
This study investigated the effectiveness of ChatGPT-assisted Inquiry-Based Learning (IBL) in enhancing English as a Foreign Language (EFL) students' writing performance, reflective thinking, and motivation. A quasi-experimental pretest–posttest non-equivalent control group design was employed with 80 undergraduate EFL students assigned to either a conventional IBL group or a ChatGPT-assisted IBL group. Data were collected through IELTS-based writing assessments and validated questionnaires on reflective thinking and motivation and analyzed using descriptive and inferential statistics. The findings showed that students in the ChatGPT-assisted IBL group significantly outperformed those in the conventional IBL group in writing performance, reflective thinking, and motivation. Positive associations were also observed among the three learning outcomes, suggesting that integrating generative AI into inquiry-based instruction supports both cognitive and affective aspects of learning. These findings highlight the pedagogical potential of ChatGPT to enrich inquiry-based writing instruction by promoting reflective learning, increasing student motivation, and improving writing quality. Although the quasi-experimental design limits causal inference, the study provides empirical evidence supporting the integration of generative AI into EFL teaching and offers practical implications for AI-enhanced language learning in higher education.