Collaborative Research: From Pathways to Progressions: Empowering Districts to Equip K-12 Computational Thinkers with Data Science and Machine Learning Foundations

Broward Education Foundation, Inc, Fort Lauderdale FL

Investigators

Abstract

Data science is a vital link in bridging computational thinking with artificial intelligence and machine learning. Therefore, it is essential that all students have an entry level comprehension of data science for their future careers and civic life. This CSforAll Pathways project is a research-practice partnership between Digital Promise, in collaboration with Looking Glass Ventures, Data Science 4 Everyone, and four school districts across four different states: Broward County (FL), Indian Prairie (IL), Iowa City (IA), and Talladega County (AL) that aims to support school districts in developing practical and scalable pathways for teaching data science from early elementary through high school. The project helps districts design and implement instructional progressions that integrate data science with computational thinking and core academic subjects. Key to the work is adapting each district’s specific existing computational pathways and considering specific context needs, while also holding to a common trajectory and key data science concepts. The project contributes to new knowledge about how districts can design and scale data science pathways. Grounded in a research practice partnership model, the project examines how district leaders adapt and extend existing computational thinking pathways to incorporate data science and machine learning. The research focuses on understanding the conditions that support integration, including district-level planning structures, instructional tools, and cross-district collaboration. Using a mixed-methods approach, the study analyzes implementation artifacts, district leader and teacher feedback, and course data to identify scalable practices and assess their impact on instructional coherence and district-level capacity. By comparing implementation approaches across four districts, the project advances models for sustainable, peer-driven expansion of integrated computing and data science education, contributing to the growing evidence base on how to support innovation at the systems level. 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.