A SYSTEMIC APPROACH TO AI-SUPPORTED ACADEMIC READING STRATEGY FORMATION

This study presents a systemic approach to understanding the formation of academic reading strategies in AI-supported learning environments. Drawing on systems theory and educational research, we develop a comprehensive model that conceptualizes reading strategy formation as an emergent property of interactions between learners, AI tools, and contextual factors. Through qualitative analysis of student-AI interactions and expert interviews, we identify key system components and their dynamic relationships. The findings reveal that effective strategy formation depends on the alignment of AI affordances with learner characteristics, instructional design, and institutional support structures. The proposed systemic model offers a framework for designing and evaluating AI-supported reading interventions that promote sustainable strategy development.