Impact of Computing Education by School Type and County on K12 Students’ AI Literacy

• In Event: Bridging the AI Literacy Gap: Systems-Level Approaches to K-12 CS Education

Abstract

Introducing computational thinking to K-12 students generally relies on the availability of computer science (CS) classes and varies by school type and location. This study focuses on how the area a K-12 student comes from and the type(s) of school(s) they attend impact their CS education and their resulting AI literacy. 2024-2025 AI literacy survey and focus group interview responses provided by students and CS curriculums of varying schools are analyzed. ANOVA and post-hoc Tukey tests were performed to compare AI literacy levels of students attending different types of schools. Based on the ANOVA tests and students’ verbal statements, school type and county were significant at the p < 0.1 cutoff suggesting they impact a student’s AI literacy.

Authors

• Ally Fu, University of Maryland - University College

• Kristina Kramarczuk, University of Maryland