Developing and Investigating Data Science Interventions Connected to University Athletics to Address Systemic Racism in Undergraduate STEM Education

University Of Maryland, College Park, College Park MD

Investigators

Abstract

This project aims to serve the national interest by investigating how athletic contexts can be leveraged to advance data literacy, strengthen STEM identities, and expand participation in science, technology, engineering, and mathematics (STEM). College athletes across the United States consistently engage with data practices such as reviewing statistics, projecting outcomes, and making evidence-based decisions. However, these data-rich experiences are rarely recognized or integrated into formal education, creating a missed opportunity to connect existing practices with STEM pathways. DataGOAT (Greatest Of All Time) will co-design an innovative educational infrastructure that connects sport performance and health data to academic coursework in data science. Students will learn to collect, analyze, visualize, and interpret data through applied experiences grounded in athletics, helping them to recognize themselves as data practitioners while developing important STEM competencies. The project will include new university courses, experiential learning opportunities, and a customized data analysis platform to support teaching and learning. The research will address three central questions: (1) What structural and socio-cultural factors influence athletes’ engagement with data literacy in higher education? (2) How can technology-integrated courses be designed to strengthen data literacy and STEM identity among student populations? and (3) What models of curricular integration most effectively bridge applied data practices in sport with broader academic and career pathways in STEM? Through longitudinal interviews, ethnographic observation, co-design workshops, and quantitative surveys, the project will generate new knowledge on how data literacy develops in applied, non-traditional learning environments. Outcomes include the creation of openly licensed curricula, a data analysis environment, and dissemination of findings to higher education institutions and K-12 partners. The project is expected to directly engage more than 350 students across multiple universities, with potential for broad replication nationwide. By linking the cultural relevance of sport with data science, DataGOAT has the potential to expand STEM participation, prepare our future workforce, and contribute to national competitiveness in science and engineering. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.