From the weight room to the classroom: student-generated data as a catalyst for engagement

This study investigates the impact of student-generated data on engagement and motivation in a sports analytics course at a Division III college. Using wearable fitness bands, force plate technology, and performance visualization software, students collected and analyzed data related to their own or their peer’s athletic performance. Guided by Experiential Learning Theory and Self-Determination Theory, the course was designed to foster deeper learning through hands-on, personally relevant experiences. Survey responses and course evaluations revealed that students reported higher motivation, stronger conceptual understanding, and greater enjoyment when analyzing data they helped generate. Thematic analysis highlighted evidence of autonomy, competence, and relatedness, key dimensions of intrinsic motivation. Instructor observations further supported that familiarity with the data streamlined instruction and increased student engagement. Importantly, the study demonstrates that Division III institutions can implement high-impact, data-driven learning experiences despite resource limitations. These findings offer a scalable model for integrating active learning into sport analytics and related disciplines.