THE DEVELOPMENT OF LEARNER AUTONOMY THROUGH STRUCTURED AI INTEGRATION IN UNIVERSITY EFL INSTRUCTION
Keywords:
Learner autonomy; artificial intelligence in education; EFL instruction; self-regulated learning; metacognitive development; instructional design; technology-enhanced learning; higher education.Abstract
This study examines the impact of structured artificial intelligence (AI) integration on the development of learner autonomy in a university English as a Foreign Language (EFL) context. While AI tools are increasingly present in higher education, their pedagogical value in fostering autonomous learning remains insufficiently explored. Grounded in theories of learner autonomy and self-regulated learning, the research investigates whether guided AI use can enhance students’ goal-setting, strategic planning, self-monitoring, and self-evaluation skills. A quasi-experimental mixed-method design was implemented with sixty B2-level university students divided into experimental and control groups. Over a six-week instructional period, the experimental group engaged in structured AI-supported learning activities designed to promote reflective and strategic engagement, whereas the control group followed traditional instructional practices. Quantitative data were collected through a validated learner autonomy questionnaire administered before and after the intervention, complemented by qualitative insights from focus-group interviews. The findings demonstrate statistically significant improvement in overall autonomy scores within the experimental group, particularly in metacognitive dimensions such as planning and monitoring. The results suggest that AI tools, when embedded within a clearly defined pedagogical framework, can function as cognitive scaffolds that support autonomous learning behaviors. The study highlights the central role of instructional design in determining the educational value of emerging technologies and provides practical implications for responsible AI integration in language education.
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