Equity in high school computer science: Beyond access

Abstract

Little is known about the extent to which expansions of K-12 computer science (CS) have been equitable for students of different racial backgrounds and gender identities. Using longitudinal course-level data from all high schools in California between the 2003–2004 and 2018–2019 school years we find that 79% of high school students in California, including majorities of all racial groups, are enrolled in schools that offer CS, up from 45% in 2003. However, while male and female students are equally likely to attend schools that offer CS courses, CS courses represent a much smaller share of course enrollments for female students than for male students. Non-Asian students enroll in relatively few CS courses, and this is particularly true for Black, Hispanic, and Native American students. Race gaps in CS participation are to a substantial degree explicable in terms of access gaps, but gender gaps in CS participation are not. Different groups of students have access to CS teachers with similar observable qualifications, but CS teachers remain predominantly white and male. Consequently, white and male CS students are much more likely than other students to have same-race or same-gender instructors. Our findings and the implications we draw for practice will be of interest to administrators and policymakers who, over and above needing to ensure equitable access to CS courses for students, need to attend carefully to equity-related course participation and staffing considerations.

Computer Science Trends and Trade-offs in California High Schools

“…We suspect that the expected direction of this bias is positive because expansions in CS course offerings may be driven in part by demand by more privileged families for access to coursework thought to advantage students in college and the later labor market. This would be consistent with evidence indicating that CS courses are more likely to be offered in the schools of students from groups that tend to score relatively highly on standardized tests (e.g., white and Asian students; Bruno and Lewis, forthcoming), and would tend to positively bias our estimates. As also discussed above, we find some evidence that CS course offerings expand along with other CTE courses.…”

“…For example, the teacher characteristics available in our data are at best rough proxies for teacher quality. As students spend more time in CS courses, it will be increasingly important to develop better measures of CS teacher quality that can be used to assess both the average strength of CS teachers and the prevalence of gaps in CS teacher quality between different groups of students (Bruno & Lewis, forthcoming). And because we observe enrollments at the course level and annual test scores only at the school level, we cannot link CS participation to outcomes for individual students, or even to aggregate outcomes other than test scores.…”

“…To account for economies of scale and school capacity to offer a wide variety of courses, we control for school enrollment, which we subject to a natural log transformation to account for skew and nonlinearities in the effects of enrollment. X also includes school demographic characteristics known to be related to CS course availability and participation, including the percentages of students that are neither white nor Asian (Bruno & Lewis, forthcoming), that are eligible for free or reduced-price lunch (Scott et al, 2019), or that are English language learners (Martin et al, 2015). We control again for school and year fixed effects to control for average differences between schools and average statewide changes across years.…”

“…Answering those questions is important for understanding whether expansions of K-12 CS education are ultimately effective for students, schools, and society. Studying how schools have been affected by challenges and trade-offs related to staffing, curriculum, and accountability may also highlight which constraints on CS expansion are truly binding and help to explain why CS has expanded more for some students than others, variation that appears highly inequitable (Bruno & Lewis, forthcoming; Code.org Advocacy Coalition, 2019, 2020; Scott et al, 2019). These issues are likely to become only more salient as administrators and policymakers face continuing pressure to expand K-12 CS education.…”

“…Importantly, California’s high-school CS expansions have not been equitable (Scott et al, 2019). For example, Bruno and Lewis (forthcoming) find that Black, Hispanic, and Native American students are less likely than students of other races to be enrolled in CS, and this can be explained in large part by the lack of availability of CS courses at their schools. They also find that women are less likely to be enrolled in a high-school CS class despite having similar access to CS courses at their high schools as men on average, though they do not consider women of color specifically.…”