Search EdWorkingPapers
Search EdWorkingPapers by author, title, or keywords.
Search
K-12 Education
In response to the Covid-19 pandemic and school disruption, both the federal and state government have sought to allocate needed funding to schools so they can provide adequate instruction and safe learning spaces to students in North Carolina. These funds, particularly the ESSER III funding through the American Rescue Plan Act of 2021, were provided to individual Public School Units (PSUs) based on applications identifying spending plans. These spending plans, submitted to the state before November 2021, include applications from 112 traditional Local Education Agencies (LEAs) and 177 charter PSUs. Using a mixed methods approach, both the quantitative and qualitative portions of this study independently attempt to identify patterns in the funding priorities of individual PSUs through the narrative in their funding applications, then compare the results to develop a more holistic understanding of these funding priorities. Overall, PSUs prioritized spending plans in the areas of technology, personnel, academic Covid-19 mitigation efforts (combating effects of lost opportunities to learn), and safety Covid-19 mitigation efforts (reducing viral spread and other projects to protect physical health and safety). In reviewing these applications and the results of both studies, we have developed several recommendations for mitigating the impact of the most recent school disruption and preparing for the next school disruption. These recommendations include re-evaluating enrichment programs, addressing the unique needs of various student populations, investing in quality education materials, developing research-based practices and strategies, growing professional networks between PSUs, and prioritizing the physical health and safety of students through regular maintenance of school structures.
In the U.S., state politicians directly influence legislation and budget decisions that can substantially affect public education spending and students. Does the political party of elected officials matter for these outcomes? We use a regression discontinuity design to analyze close house and gubernatorial elections from 1982 to 2016 and find that the impact of Democratic control of state government depends on whether elections occur during a presidential election year. On average, Democratic states spend less per capita on K-12 education. This trend, however, reverses when Democrats secure marginal control during off-cycle elections. Outside of presidential election years, we find increased state expenditures on both K-12 education and higher education. These increases coincided with smaller K-12 class sizes, relatively higher high school diploma rates, and expanded college enrollment. Our results highlight the importance of considering how federal political contexts influence the effects of state-level politics on education finance and outcomes.
Teachers are the most important school-specific factor in student learning. Yet, little evidence exists linking teacher professional development programs and the strategies or activities that comprise them to student achievement. In this paper, we examine a fellowship model for professional development designed and implemented by Leading Educators, a national nonprofit organization that aims to bridge research and practice to improve instructional quality and accelerate learning across school systems. During the 2015-16 and 2016-17 school years, Leading Educators conducted its fellowship program for two cohorts of teachers and school leaders to provide these educators ongoing, collaborative, job-embedded professional development and to improve student achievement. Relying on quasi-experimental methods, we find that a school’s participation in the fellowship program significantly increased student proficiency rates in English language arts and math on state achievement exams. Student achievement benefitted from a more sustained duration of participation in the fellowship program, varied depending on the share of a school’s educators who participated in the fellowship, and differed based on whether fellows independently selected into the program or were appointed to participate by their school leaders. Taken together, findings from this paper should inform professional learning organizations, schools, and policymakers on the design, implementation, and impact of educator professional development.
Teachers' levels of stress and burnout have been high throughout the COVID-19 pandemic, raising concerns about a potential increase in teacher turnover and future teacher shortages. We examine how the COVID-19 pandemic affected teacher turnover in Arkansas from 2018-19 to 2022-23 using administrative data. We find no major changes in turnover entering the first two pandemic years, but a large increase of 5.3 percentage points (26%) entering the third year, with variation by teacher and student characteristics. We also find that increases in teacher turnover are related to instructional mode and that this turnover may partially be explained by the use of COVID-19 relief funds. Additionally, we find evidence that more effective teachers became more likely to leave the education sector after the pandemic as compared to before the pandemic. Our results suggest increased strain and reduced diversity and quality in the Arkansas teacher workforce and raise concerns about the long-term impacts that COVID-19 may have on its stability and quality.
Anecdotal evidence points to the importance of school principals, but the limited existing research has neither provided consistent results nor indicated any set of essential characteristics of effective principals. This paper exploits extensive student-level panel data across six states to investigate both variations in principal performance and the relationship between effectiveness and key certification factors. While principal effectiveness varies widely across states, there is little indication that regulation of the background and training of principals yields consistently effective performance. Having prior teaching or management experience is not related to our estimates of principal value-added.
Purpose: Nearly all schools in the United States closed in spring 2020, at the onset of the COVID-19 pandemic. We analyze traditional public and charter school reopenings for the 2020-21 school year in five urban districts. We provide a rich and theoretically grounded description of how and why educational leaders made reopening decisions in each of our case districts.
Research Methods: We used data from a multiple-case study from March 2020 to July 2021. The research team conducted 56 interviews with school, district, and system-level leaders; triangulated with publicly available data; and also drew on interview data from a subsample of parents and guardians in each of our sites. We analyzed these data through qualitative coding and memo writing, and conducted detailed single- and cross-case analyses.
Findings: School system leaders in our case sites generally consulted public health authorities, accounted for state-level health and educational guidance, and engaged with and were responsive to the interests of different stakeholders. Districts’ adherence to and strategic uses of public health guidance, as well as a combination of union-district relations and labor market dynamics, influenced reopening. Parents, city and state lawmakers, and local institutional conditions also played a role, helping to explain differences across cases.
Implications: In contrast to the “politics or science” framing that has dominated research and public discourse on school reopening, we show that local pandemic conditions and local political dynamics both mattered and in fact were interrelated. Our findings have some implications for how educational leaders might navigate future crises.
Greater school choice leads to lower demand for private tutoring according to various international studies, but this has not been explicitly tested for the U.S. context. To estimate the causal effect of charter school appearances on neighboring private tutoring prevalence, we employ a comparative event study model combined with a longitudinal matching strategy to accommodate differing treatment years. In contrast to findings from other countries, we estimate that charter schools increase, rather than decrease, tutoring prevalence in the United States. We further find that the effect varies considerably based on the characteristics of the treated neighborhood: areas with the highest income, educational attainment, and proportion Asian show the greatest treatment impacts, while the areas with the least show null effects. Moreover, methodologically this investigation offers a pipeline for flexibly estimating causal effects with observational, longitudinal, geographically located data.
Researchers use test outcomes to evaluate the effectiveness of education interventions across numerous randomized controlled trials (RCTs). Aggregate test data—for example, simple measures like the sum of correct responses—are compared across treatment and control groups to determine whether an intervention has had a positive impact on student achievement. We show that item-level data and psychometric analyses can provide information about treatment heterogeneity and improve design of future experiments. We apply techniques typically used in the study of Differential Item Functioning (DIF) to examine variation in the degree to which items show treatment effects. That is, are observed treatment effects due to generalized gains on the aggregate achievement measures or are they due to targeted gains on specific items? Based on our analysis of 7,244,566 item responses (265,732 students responding to 2,119 items) taken from 15 RCTs in low-and-middle-income countries, we find clear evidence for variation in gains across items. DIF analyses identify items that are highly sensitive to the interventions—in one extreme case, a single item drives nearly 40% of the observed treatment effect—as well as items that are insensitive. We also show that the variation of item-level sensitivity can have implications for the precision of effect estimates. Of the RCTs that have significant effect estimates, 41% have patterns of item-level sensitivity to treatment that allow for the possibility of a null effect when this source of uncertainty is considered. Our findings demonstrate how researchers can gain more insight regarding the effects of interventions via additional analysis of item-level test data.
Books shape how children learn about society and norms, in part through representation of different characters. We introduce new artificial intelligence methods for systematically converting images into data and apply them, along with text analysis methods, to measure the representation of skin color, race, gender, and age in award-winning children’s books widely read in homes, classrooms, and libraries over the last century. We find that more characters with darker skin color appear over time, but the most influential books persistently depict characters with lighter skin color, on average, than other books, even after conditioning on race; we also find that children are depicted with lighter skin than adults on average. Relative to their growing share of the U.S. population, Black and Latinx people are underrepresented in these same books, while White males are overrepresented. Over time, females are increasingly present but appear less often in text than in images, suggesting greater symbolic inclusion in pictures than substantive inclusion in stories. We then present analysis of the supply of, and demand for, books with different levels of representation to better understand the economic behavior that may contribute to these patterns. On the demand side, we show that people consume books that center their own identities. On the supply side, we document higher prices for books that center non-dominant social identities and fewer copies of these books in libraries that serve predominantly White communities. Lastly, we show that the types of children's books purchased in a neighborhood are related to local political beliefs.
This paper conceptualizes segregation as a phenomenon that emerges from the intersection of public policy and individual decision-making. Contemporary scholarship on complex decision-making describes a two-step process—1) Editing and 2) Selection— and has emphasized the individual decision-maker’s agency in both steps. We build on this work by exploring, both theoretically and empirically, how policy can structure the choices individuals face at each step. We conduct this exploration within the empirical context of enrollment decisions among families in the Wake County Public School System (WCPSS), which used a controlled school choice system to help achieve diversity aims. We first investigate the schooling choice sets that WCPSS constructed for families and then examine families’ schooling selections. We find that families were offered choice sets containing schools varying racial compositions, but that the racial makeup of schools in families’ choice set systematically varied by schooling type and student race/ethnicity. We further show that a majority of families enrolled in their district-assigned default school, with Black and Hispanic families more likely than white or Asian families to attend this option. Finally, we demonstrate that white or Asian families enroll in their default school at lower rates as the share of Black students increases.