CAREER: Designing for Learning at the Intersection of Sports, Analytics and Physical Computing

Northwestern University will design athletic-centered learning experiences that help student-athletes see the relevance of computing in athletics. This project will focus on ways for connecting computer science with athletics, and will work to uncover strategies for effectively encouraging participation of student-athletes of color in computer science in youth after-school and out-of-school athletics.

Recognizing the important role that coaches play in the development of student-athletes, the research team will conduct interviews with both student-athlete and coaches to better understand their perceptions of computer science. These interviews will also touch on the ways that the youth sports programs are already using technology. The project team will use this information to design new tools and activities that reflect the preferences and perceptions of student-athletes and coaches.

The research team will also organize after-school and summer enrichment programs to teach athletes and coaches about the exciting opportunities for designing sports-related technologies. Some of the experiences will teach participants about designing sports wearables, machine learning and data science. Finally, the research team will use artificial intelligence to assess learning within these participant-facing activities.

By tapping into the large number of youth participating in sports, the research team hopes to identify a possible strategy for broadening participation in computer science.

This project is grounded in the STEM activation framework, which considers the confluence of fascination, competency beliefs, values, scientific sensemaking and participant engagement. Specifically, the project positions participation in athletics as an asset for learning computer science. Moreover, the project aims to disrupt the popularized dichotomy between athletics and academics by developing the pedagogical, technological and analytic tools needed to support athletic-centered computer science learning experiences.

The pedagogical tools include novel learning activities that bridge data science, engineering design, machine learning and physical computing, with athletics. The technological tools include age-appropriate and accessible interfaces for collecting, visualizing and drawing inferences from the multimodal data that students collect. Technological tools also include supporting students in designing and building custom wearables using physical computing.

Finally, the analytic tools leverage the PI’s expertise in Multimodal Learning Analytics (MMLA) to extend and scale elements of the STEM Activation Framework’s Observation and Engagement Protocol via automated feature extraction and data annotation. The project uses an iterative, user-centered and design-based research approach to realize these goals and activities.

This work contributes to research on 1) developing and supporting novel pathways to computing careers, 2) the design and implementation of tools that facilitate collecting, analyzing and learning with multimodal data and physical computing, and 3) leveraging multimodal analytics to identify new ways to characterize learning and engagement in non-traditional learning environments.

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.