The impact of generative artificial intelligence (GenAI) on university students’ learning agency: A mixed-methods study

Learning agency provides a core framework for understanding how university students’ engagement with generative artificial intelligence (GenAI) and informing corresponding instructional adaptations. However, existing studies have typically relied on a single analytical approach and have often lacked an explicit theoretical framework to guide analysis, resulting in a partial examination of learning agency. To provide a comprehensive understanding of learning agency in GenAI-supported contexts, this study adopted a mixed-methods approach grounded in a three-dimensional theoretical framework. Seventy-eight participants were assigned to a GenAI group or a control group. Quantitative results showed that GenAI facilitated learning agency by enhancing self-regulated learning propensities. In contrast, qualitative results indicated that although the GenAI group produced more arguments than the control group, they exhibited excessive reliance and uncritical reproduction of AI-generated content. This study offers both theoretical and practical insights into how learning agency can be understood and supported in GenAI-enhanced learning environments.