Equity in Access to and Participation in K-12 Computer Science Education

Most research on equity in access to and participation in computer science (CS) courses in high school has focused on general, siloed categories of students (e.g., ethnicity, gender). Using logistic regression, this study examines multiple student-, school-, and district-level predictors for access to and participation in CS. We found that the strongest predictors of whether a school offered CS were the racial/ethnic composition of the student population and the percentage of individuals in the community who hold a bachelor's degree. In examining participation in CS, we found significant differences between different intersections of race/ethnicity and gender. These results can inform interventions and policies to increase equity by signaling which factors should be taken into consideration, for whom, and in what situations.