Justice T. Walker, Amanda Barany(*), Alex Acquah, Sayed Mohsin Reza(**), Karen Del Rio Guzman, Michael Johnson(***), Omar Badreddin(****), Alan Barrera, University of Texas at El Paso, University of Pennsylvania(*), Pennsylvania State University(**), University of North Texas(***), Northeastern University(****)
Given an increased focus on computer science education as a valuable context to teach data science—due in part to the potential of computing for accessing, processing, and analyzing digital datasets—there have been steady efforts to develop kindergarten through 12th grade (K-12) curricula that productively engage learners in these academic areas. Bootstrap: Data Science and Exploring Computer Science (ECS) are prominent curricular examples designed to support high school data science access in computing contexts. While these vital efforts have found success bridging computer and data science, there remain growing concerns about how we can ensure that such learning experiences support the demographic and intellectually diverse cohorts of students needed for field innovation, occupational attainment, and public literacy. Challenges to these efforts often persist because existing data sources and activities offered to students are typically shaped by others (e.g., curriculum designers, teachers, etc.) rather than by learners themselves.