2026 ASEE Annual Conference & Exposition

This paper presents a framework developed through over a decade of collaborative systems change work aimed at broadening participation in computing (BPC) across K–16 education. The work supports multi-state teams in the collaborative development of a common framework for defining, collecting, and analyzing data that drives policy and advocacy for equitable computer science (CS) education. This paper argues for a novel approach to progress monitoring—one that separates “advanced” from “non-advanced” CS coursework, as well as by course type (i.e. programming, cyber security, AI, robotics, etc.)—allowing states to better capture their unique contexts while remaining connected to local and national BPC goals. This distinction, emerging from collaborative decision-making across states, contrasts with national models to measure progress that often homogenize CS course offerings. We describe how this flexible metric structure enables both within-state storytelling and cross-state comparisons, empowering local advocates to make informed decisions about the design and prioritization of CS and emerging AI education. By outlining the evolution of this work, shared definitions, and data sharing tools such as dashboards, we offer a scalable model for aligning grassroots data use with scalable policy change. Ultimately, this work invites computer science teachers, CS education advocates, and policymakers to reconsider how we define and measure “progress” in equitable CS education.