The National Science Foundation has awarded a team led by Education Policy, Organization and Leadership assistant professor Paul Bruno, PI, nearly $500K for a three-year project examining Collaborative Research: Impacts of State Policy on Computer Science Participation and Teacher Preparation. Associate professor Colleen Lewis of the Grainger College of Engineering's Department of Computer Science joins Bruno as Co-PI on the project, along with Tuan Nguyen of Kansas State University.
From the project abstract:
States have increasingly adopted and invested in policies to broaden participation in computer science (CS) coursework and the availability of qualified CS teachers, but there is no clear evidence on the extent to which these policies have succeeded. This project will perform a policy analysis to determine if state policies aimed at broadening participation in CS education have the intended impacts on high school and undergraduate CS course taking and on the production of qualified (e.g., certified) high school CS teachers. To link these varied state policies to testable hypotheses, we classify policies based on whether they are likely to have their most direct impacts on (1) promoting CS course taking, (2) expanding the CS teacher supply, or (3) demonstrating a general commitment to CS education (i.e., without reference to achieving any specific outcome). To evaluate the impacts of these policies, we will collect data on the adoption dates for specific CS education-related policies in each state. These data sets include a combination of data on high school course taking, undergraduate enrollments, current high school teachers, and teacher certification, along with state-level demographic, social, and economic markers. This unique, longitudinal data set spanning the years 2000-2022 will allow us to statistically link specific policies to specific outcomes by taking advantage of the fact that different states adopted different policies at different times. We will do this using recent advancements in “event study” modeling, a causal inference method that allows us to measure both the short- and long-term impacts of policies.
There is continued and intense interest in further expanding CS educational opportunities among state policymakers, school district leaders, and CS education advocates. To date, these actors have had access to little credible information about the impacts of specific policies. Our results will provide policymakers with guidance about which policies to prioritize to accomplish specific goals in their contexts. Our findings will therefore be well positioned to inform changes in CS education policy and practice. Moreover, there is good evidence that CS educational opportunity has been constrained disproportionately for specific groups of historically marginalized students, for example on the basis of race and gender. Our results will point to specific policy levers that are effective for addressing the inequities that have been well documented in CS education. In sum, our proposed study can contribute directly to the effective, efficient, and equitable expansion of CS education at the secondary and post-secondary levels. This, in turn, will help to provide the benefits to society – and to students themselves – that motivate these expansions in the first place.
