Collaborative Research: An Equity-Focused Approach to Integrating Physical Activity and CS Education for K-8 Learners

This project brings instruction in computing and data science to an elementary school with a predominantly Hispanic population through Project SMART, a digital educational game that uses students’ in-school physical activity to motivate student learning. Students record their physical activity during the school day, whether in physical education class, at recess, or at other teacher-provided opportunities for physical activity. An elementary school class plays collaboratively; the physical activity of all the students in the class is converted to a distance traveled along an extended virtual journey. The learning modules are defined by teachers and directly connected to the core curriculum. Key to the approach is that the computational learning activities provided introduce data collection, analysis, and prediction questions using the students’ own physical activity data. As such, the project explores research questions that are advancing the field's understanding about how to engage students in computer science. It also is investigating whether students are more engaged in, motivated by, and successful at computational thinking learning objectives if these objectives relate to data that is relevant to them: their physical activity, their interests, their environment, and, importantly, their own collected data. This project expands and strengthens the Project SMART researcher-practitioner partnership (RPP), engaging researchers and teachers in collaborative efforts to identify strategies for computer science and computational thinking instruction that engages an elementary student population and addresses instructional challenges. These challenges include pressures to adhere to state standards that make it difficult to integrate additional content, a lack of at-home internet infrastructure that limits out-of-school student engagement, and teachers' lack of experience with and confidence in computer science content knowledge. Conjectures that orient the research plan explicate a premise that contextualizing computer science within the students' own physical activity during the regular school day as an integrated core subject lesson will help to address these challenges. In addition to advancing the field's understanding of a contextualized approach to data science instruction, this project also creates shareable learning modules that present data science learning activities that use the students' own physical activity to enable data modeling and prediction; guide students in hardware-software co-design to create wearable physical activity monitors that can improve data collection; and enable students to write code that extends the functions available in the game. This project is funded by the CS for All: Research and RPPs program. 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.