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Abstract: For working adult learners, developing interpreting competence requires extensive practice in listening comprehension, note-taking, and message reformulation. However, limited classroom time and heavy academic workloads often restrict students' opportunities for sustained practice. In this context, AI-generated microlearning listening materials, implemented through flexible practice schedules, progress tracking, and reflective activities, offer a practical way to extend learning beyond the classroom. This study explores the integration of AI-generated microlearning listening materials into Interpretation 1, a hybrid undergraduate course. In this study, eighteen participants voluntarily joined an AI-supported autonomous practice model involving weekly practice with short AI-generated listening videos, progress tracking, and self-reflection. The research data were collected from pre- and post-tests, practice logs, and reflective Google Form responses. Rather than being viewed as a direct determinant of interpreting performance, AI was conceptualized as a pedagogical tool for extending autonomous practice beyond the classroom. The findings suggest that regular engagement with AI-supported learning materials was associated with greater learner confidence, improved listening comprehension, note-taking skills, and interpreting fluency. The study also proposes a practical approach to integrating AI into interpreting instruction to foster learner agency and autonomous learning in hybrid interpreting courses.
Key words: AI-generated microlearning, autonomous practice, learner agency, interpreting competence, hybrid learning
