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In lieu of ongoing efforts to broaden participation in computing education, we explore a curriculum that integrates sports and computer science, aiming to engage students by drawing on their experiences in both domains. Through an in-school implementation with 5th-grade learners, we examine their engagement by analyzing their attitudes toward sports and computing. Using clustering analysis of student survey responses, we identify four distinct groups, each reflecting different motivations tied to the integration of sports. Our findings highlight how the curriculum's design provided varying levels of access to computer science for different groups of learners. 

The showcase will display a programmable sensor in action for understanding a person’s relationship to embodied data collection practices. The activity design is called a Data Scavenger Hunt, where participants record data and search through the data to identify different actions within automated graphs. The sensor can be adapted to record many variables from acceleration to light level. Our activity is designed for 8th to 12th graders in out-of-school contexts, so that they explore their physical movement as it relates to data and subsequent visualizations of that data. With this embodied data, there is an inherent relationship to the data, and we explore how that relationship creates opportunities for learning about agency in data collection processes. As such, we highlight the process of active data production rather than passive data collection in our activity. In initial testing, we see how learners are navigating discrepancies between their experiences and the data. 

For the past several years, our team has been developing and implementing curriculum and tools for integrating sports in data science learning experiences. We have developed a collection of activities and tools that we are eager to share with the larger data science community. The purpose of this session is to give participants an opportunity to explore some of these tools and activities in community with other data science educators and learners. The workshop will also serve as a space to try designing some new activities and ideate future directions for this work within the specific contexts of each workshop participant. Hence, we propose this workshop as a set of resources and a community that might spur new ideas that participants can adapt and extend based on the goals, needs, and affordances of their respective contexts.