High school computer science impacts college majors and increases earnings

As the U.S. economy becomes more digitalized, employment in computer and information technology occupations is projected to grow by 10% in the next decade. In response to this increasing demand for technology skills, many states are working to expand computer science (CS) learning opportunities across K-12 classrooms. Thirty states have adopted a key part of Code.org Advocacy Coalition’s policy recommendations, which require all high schools to offer CS coursework, while eight states (and counting) have gone a step further in requiring all students to take CS as a high school graduation requirement. Despite heightened policy interest in CS access, however, research is surprisingly sparse on how the expansion of CS coursework affects postsecondary and labor market outcomes.

In a recent working paper, we aim to fill this research gap by investigating the impact of the expansion of high school CS course offerings. The State of Maryland, which is the context of our study, has rapidly expanded CS course offerings over the last decade. A 2018 law further requires all Maryland high schools to offer at least one “high-quality” CS course aligned with rigorous K-12 CS standards. These “high-quality” courses include foundational courses such as Computer Science Essentials, AP courses such as AP Computer Science Principles, and more specialized programming courses. They are also closely aligned with Code.org’s definition of “foundational” CS courses.

Using rich longitudinal data from the Maryland Longitudinal Data System (MLDS) Center, our study is among the first that offers causal evidence on how access to these “high-quality” CS courses in high school affects college major choice and early-career earnings. Our research design exploits the fact that high schools adopted CS courses at different points in time. In a nutshell, we compare cohorts of students who were exposed to CS to prior cohorts of students from the same high school that were not exposed to CS. This design allows us to estimate causal impacts of both CS course offering and CS course-taking.