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Promoting Equitable CS and AI Education: Strategies to Expand Capacity and Access

Fri, April 10, 11:45am to 1:15pm PDT (11:45am to 1:15pm PDT), Los Angeles Convention Center, Floor: Level Two, Room 515A

Session Type: Structured Poster Session

Abstract

Despite the last decade’s expansion of K-12 computer science (CS) and artificial intelligence (AI) education, many schools lack capacity for CS education and all students do not have access to CS learning experiences. Gaps in CS and AI education capacity and access do not affect all students equally and disparities persist along historical lines of racial, gender, and socioeconomic inequity. This structured poster session examines barriers and facilitators to equitable CS and AI education, focusing on the Capacity and Access components of the CAPE (Capacity, Access, Participation, and Experience) framework, an analytic tool that enables systematic examination of equity in CS education. Presenters will share research-and-practice-based insights on state-level CS initiatives, professional learning models, and broadening access to CS education.

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