AI-SUPPORTED HYBRID LEARNING AND STUDENT ENGAGEMENT: EFFECTS ON SELF-REGULATED LEARNING IN UNDERGRADUATE EDUCATION IN UZBEKISTAN
Abstract
This study investigates the impact of AI-supported hybrid education on student engagement and self-regulated learning (SRL) in undergraduate higher education in Uzbekistan and selected Central Asian universities. Drawing on an integrated theoretical framework that combines Self-Regulated Learning Theory, the Technology Acceptance Model, and the Human-AI Hybrid Adaptivity Framework, the study examines how AI-enhanced learning environments influence student behavior and learning outcomes. Existing research indicates that digitalization significantly improves perceived educational quality and engagement in Uzbek higher education (Abdurashidova et al., 2023), while blended learning environments are strongly associated with enhanced self-regulated learning processes (Luo & Zhou, 2024). At the same time, prior studies highlight a persistent intention–behavior gap in students’ use of AI tools, suggesting that access to technology does not guarantee effective adoption (Polyportis, 2023).
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