- Cory Koedel
Search EdWorkingPapers by author, title, or keywords.
We examine the potential to expand and diversify the production of university STEM degrees by shifting the margin of initial enrollment between community colleges and 4-year universities. Our analysis is based on statewide administrative microdata from the Missouri Department of Higher Education and Workforce Development covering enrollees in all public postsecondary institutions statewide. We find that the potential for shifting the enrollment margin to expand degree production in STEM fields is modest, even at an upper bound, because most community college students are not academically prepared for bachelor’s degree programs in STEM fields. We also find that shifting the enrollment margin is unlikely to improve racial/ethnic diversity among university STEM degree recipients. This is because community college students at the enrollment margin are less diverse than their peers who enter universities directly.
We evaluate the effects of grade retention on students’ academic, attendance, and disciplinary outcomes in Indiana. Using a regression discontinuity design, we show that third grade retention increases achievement in English Language Arts (ELA) and math immediately and substantially, and the effects persist into middle school. We find no evidence of grade retention effects on student attendance or disciplinary incidents, again into middle school. Our findings combine to show that Indiana’s third grade retention policy improves achievement for retained students without adverse impacts along (measured) non-academic dimensions.
Measures of student disadvantage—or risk—are critical components of equity-focused education policies. However, the risk measures used in contemporary policies have significant limitations, and despite continued advances in data infrastructure and analytic capacity, there has been little innovation in these measures for decades. We develop a new measure of student risk for use in education policies, which we call Predicted Academic Performance (PAP). PAP is a flexible, data-rich indicator that identifies students at risk of poor academic outcomes. It blends concepts from emerging “early warning” systems with principles of incentive design to balance the competing priorities of accurate risk measurement and suitability for policy use. PAP is more effective than common alternatives at identifying students who are at risk of poor academic outcomes and can be used to target resources toward these students—and students who belong to several other associated risk categories—more efficiently.
We study the conditional gender wage gap among faculty at public research universities in the U.S. We begin by using a cross-sectional dataset from 2016 to replicate the long-standing finding in research that conditional on rich controls, female faculty earn less than their male colleagues. Next, we construct a data panel to track the evolution of the wage gap through 2021. We show that the gap is narrowing. It declined by more than 50 percent over the course of our data panel to the point where by 2021, it is no longer detectable at conventional levels of statistical significance.
We estimate the education and earnings returns to enrolling in technical two-year degree programs at community colleges in Missouri. A unique feature of the Missouri context is the presence of a highly-regarded, nationally-ranked technical college: State Technical College of Missouri (State Tech). Compared to enrolling in a non-technical community college program, we find that enrolling in a technical program at State Tech greatly increases students’ likelihoods of graduation and earnings. In contrast, there is no evidence that technical education programs at other Missouri community colleges increase graduation rates, and our estimates of the earnings impacts of these other programs are much smaller than for State Tech. Our findings exemplify the importance of institutional differences in driving the efficacy of technical education and suggest great potential for high-quality programs to improve student outcomes.
Free and reduced-price meal (FRM) eligibility is commonly used in education research and policy applications as an indicator of student poverty. However, using multiple data sources external to the school system, we show that FRM status is a poor proxy for poverty, with eligibility rates far exceeding what would be expected based on stated income thresholds for program participation. This is true even without accounting for community eligibility for free meals, although community eligibility has exacerbated the problem in recent years. Over the course of showing the limitations of using FRM data to measure poverty, we provide promising validity evidence for a new, publicly-available measure of school poverty based on local-area family incomes.
The Community Eligibility Provision (CEP) is a policy change to the federally-administered National School Lunch Program that allows schools serving low-income populations to classify all students as eligible for free meals, regardless of individual circumstances. This has implications for the use of free and reduced-price meal (FRM) data to proxy for student disadvantage in education research and policy applications, which is a common practice. We document empirically how the CEP has affected the value of FRM eligibility as a proxy for student disadvantage. At the individual student level, we show that there is essentially no effect of the CEP. However, the CEP does meaningfully change the information conveyed by the share of FRM-eligible students in a school. It is this latter measure that is most relevant for policy uses of FRM data.
Note: Portions of this paper were previously circulated under the title “Using Free Meal and Direct Certification Data to Proxy for Student Disadvantage in the Era of the Community Eligibility Provision.” We have since split the original paper into two parts. This is the first part.
Textbooks are a widely used educational intervention that can affect student achievement, and the marginal cost of choosing a more effective textbook is typically small. However, we know little about how textbooks get from the publisher to the classroom. We use a lens of institutional theory and interviews with district leaders in a stratified random sample of 34 California school districts to investigate the ways mathematics textbook adoption practices vary and predict adoption decisions. We find isomorphic, highly formalized adoption processes in most districts. However, we observe some differences along dimensions of district size, technological interest/infrastructure, and English learner concentration. We recommend states produce and update lists of high quality materials early and often, and that they use a highly rigorous evaluation process. We also recommend states experiment with encouraging similar districts to partner on textbook evaluation and adoption to respond to district demands for information and capacity building around curricula.