SELF-REGULATED WRITING STRATEGIES IN AI-ENHANCED ACADEMIC WRITING: INSIGHTS FROM INDONESIAN EFL DOCTORAL STUDENTS

Abstract

This article reports on self-regulated writing strategies in AI-enhanced academic writing among EFL doctoral students in Indonesia. The study aimed to identify the level of strategy use and to examine its application, as well as the challenges and solutions, across the stages of the academic writing process. A mixed-methods design was employed, combining a survey of 54 EFL doctoral students and semi-structured interviews with six participants from a public university in Indonesia. Quantitative findings showed a high level of self-regulated writing strategies, particularly in motivational self-talk, goal monitoring and evaluating, text processing, idea planning, emotional control, feedback handling, and interest enhancement, while course memory was moderate. These results suggest strong self-awareness and autonomy in sustaining motivation, organizing ideas, monitoring progress, and regulating emotions. Qualitative data revealed that students engaged in a systematic, cyclical writing process encompassing planning, execution, and evaluation, with writer-generated ideas enhanced by AI during planning, writer control, voice preservation, and feedback during execution, and self-monitoring and critical review during evaluation. Despite the benefits, challenges stemming from AI’s limitations in personal and contextual writing persist, prompting students to adopt critical, controlled use of AI as a practical solution. This study provides insights into EFL doctoral students’ self-regulated writing and their critical, controlled use of AI to address its limitations.