AN ANALYSIS OF CLASSROOM INTERACTION BY USING FLANDER INTERACTION ANALYSIS CODE (FIAC) MODEL
Keywords:
Classroom interaction; FIAC model; Teacher talk; Student participation; English language teachingAbstract
Purpose: This study investigates the impact of AI-powered writing assistants on the academic writing performance of EFL students in higher education and explores students’ perceptions of these tools as part of their learning process.
Design/methodology/approach: A convergent mixed-methods design was employed involving 25 undergraduate students from the English Education Program at STKIP Muhammadiyah Sungai Penuh. Students participated in pretest–posttest writing tasks using Grammarly Premium and ChatGPT, followed by semi-structured interviews. Writing performance was assessed using a rubric adapted from IELTS Task 2, and data were analyzed using paired-samples t-tests and thematic analysis.
Findings: The results revealed a statistically significant improvement in students’ academic writing, with the mean score increasing from 63.0 to 80.5 (p < .001, d = 1.75). Gains were particularly strong in task response, coherence, and lexical resource. Interview data showed that students perceived AI tools as supportive and non-threatening, increasing their confidence, writing autonomy, and awareness of academic tone. However, concerns were raised regarding over-reliance and ethical usage.
Originality/value: This study contributes to the growing literature on AI in language learning by providing empirical evidence on the effectiveness and perception of AI-assisted writing in EFL contexts. It also highlights the importance of guided, ethical, and reflective integration of AI tools in writing instruction to maximize pedagogical outcomes.
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