From individual to collective agency: tracing a rural student’s development of learner agency in AI-supported learning environments

While prior research has acknowledged the importance of learner agency in technology-enhanced learning, most studies have focused on short-term, observable behaviors and individual-level accounts, with limited attention to the longitudinal, internal, and socially situated dimensions of agency development. Research has also paid limited attention to agency development among rural learners, whose experiences are shaped by distinct sociocultural and material constraints. Addressing these gaps, this study investigates how a rural university student’s learner agency developed over three years in AI-supported learning environments, including AI-enabled feedback tools, intelligent tutoring systems, and AI-supported collaborative platforms. This study adopts a narrative inquiry approach. Data were collected through three annual in-depth interviews and reflective learning journals. Analysis was conducted in four interconnected phases. Findings reveal a three-phase developmental process: emerging and fragile individual agency, adaptive and reflective agency through selective engagement with AI feedback, and increasingly collective enactments of agency through peer collaboration and shared critical engagement with AI systems. The study highlights how rural backgrounds, infrastructural limitations, and sustained engagement interact to shape agency in AI-mediated learning. It concludes with implications for fostering equitable and supportive AI-mediated learning designs that recognize agency as a dynamic, contextually embedded, and collective phenomenon.