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Improving schools depends on attracting talented teachers and fostering retention, both made possible by appealing to teacher preferences. I deploy a discrete-choice experiment in a setting where teachers have reason to reveal their preferences. Those data allow me to calculate willingness-to-pay for a comprehensive set of workplace attributes including salary structure, retirement benefits, performance pay, class size, and time-to-tenure. Schools can improve the appeal of teaching by shifting compensation into vehicles with greater WTP-to-cost ratios. Highly rated teachers have stronger preferences for schools offering performance pay, which may be used to differentially attract and retain them. Under various criteria, schools seem to underpay in salary and performance pay while overpaying in retirement benefits.
Younger siblings take more advanced high school course end of year exams when their older siblings perform better in those same exams. Using a regression discontinuity and data from millions of siblings who take Advanced Placement (AP) exams, we show that younger siblings with older siblings who marginally “pass” an AP exam are more likely to take at least one AP exam, increase the total number of AP exams, and are more likely to take the same exam as their sibling. The largest impacts are found among sisters, but we do not see differential effects in coursework where females are underrepresented.
We study personnel flexibility in charter schools by exploring how teacher retention varies with teacher and school quality in Massachusetts. Charters are more likely to lose their highest and lowest value-added teachers. Low performers tend to exit public education, while high performers tend to switch to traditional public schools. To rationalize these findings, we propose a model in which educators with high fixed-costs use charter schools to explore teaching careers before obtaining licenses required for higher paying public sector jobs. The model suggests charter schools create positive externalities for traditional public schools by increasing the average quality of available teachers.
We use high frequency internet search data to study in real time how US households sought out online learning resources as schools closed due to the Covid-19 pandemic. By April 2020, nationwide search intensity for both school- and parent-centered online learning resources had roughly doubled relative to baseline. Areas of the country with higher income, better internet access and fewer rural schools saw substantially larger increases in search intensity. The pandemic will likely widen achievement gaps along these dimensions given schools' and parents' differing engagement with online resources to compensate for lost school-based learning time. Accounting for such differences and promoting more equitable access to online learning could improve the effectiveness of education policy responses to the pandemic. The public availability of internet search data allows our analyses to be updated when schools reopen and to be replicated in other countries.
Since their introduction in the 1990s, charter schools have grown from a small-scale experiment to a ubiquitous feature of the public education landscape. The current study uses the legislative removal of a cap on the maximum number of charters, and the weakening of regulations on these new schools, in North Carolina as a natural experiment to assess the intensive impacts of charter school growth on teacher quality and student composition in traditional public schools (TPS) at different levels of local market penetration. Using an instrumental variable difference-in-differences approach to account for endogenous charter demand, we find that intensive local charter entry reduces the inflow of new teachers at nearby TPS, leading to a more experienced and credentialed teaching workforce on average. However, we find that the entry of charters serving predominantly White students leads to reductions in average teacher experience, effectiveness, and credentials at nearby TPS. Overall these findings suggest that the composition of the teacher workforce in TPS will continue to change as charter schools further expand, and that the spillover effects of future charter expansion will vary by the types of students served by charters.
COVID-19 has forced essentially all schools in the country to close their doors to inperson activities. In this study, we provide new evidence about variation in school responses across school types. We focus on five main constructs of school activity during COVID-19: personalization and engagement in instruction, personalization and engagement in other school communication with students, progress monitoring (especially assignment grading), breadth of services (e.g., counseling and meals), and equitable access (to technology and services for students with special needs). We find that the strongest predictor of the extent of school activities was the education level of parents and other adults in schools’ neighborhoods. Internet access also predicts school responses. Race, parent/adult income, and school spending do not predict school responses. Private schools shifted to remote learning several days faster than traditional public schools, though others eventually caught up. On some measures, charter schools exceeded the responses of other schools; in other cases, traditional public schools had the highest overall measures. States in the Midwest responded more aggressively than those in other regions, especially the South, even after controlling for the full set of additional covariates. Learning management systems were reported by a large majority of schools, followed by video communication tools and tutorial/assessment programs. Several methods are proposed and implemented to address differential website use. We discuss potential implications of these findings for policy and effects on student outcomes.
Despite empirical evidence suggesting the important influence school leaders have on learning conditions and student outcomes in schools, relatively little is understood about the professional pathways they take into their roles. In this descriptive paper, we document the professional experiences, personal characteristics and instructional effectiveness of Oregon's principals and assistant principals between 2006 and 2019. We highlight the diversity of roles educators assume prior to entering school leadership. We find that school leaders who have prior teaching experience in tested grades and subjects do not raise student achievement at substantively or statistically meaningful higher rates than their peers. We document that female principals and assistant principals have become more representative of the teaching workforce, but that there have been almost no changes in the racial/ethnic composition of school leaders in Oregon. Finally, we observe minimal differences in female and non-White assistant principals' time-to-entry into the principalship. Our findings provide insights on potential points of intervention during the educator career trajectory to attract and develop more effective and demographically representative school leaders.
We investigate the determinants and consequences of increased school choice by analyzing a 22-year school panel matched to county-level demographic, economic, and political data. Using an event-study design exploiting the precise timing of charter school enrollment change, we provide robust evidence that charter enrollment growth increases racial and especially socioeconomic school segregation, a finding that is partially explained by non-poor students’ transition from the private to public sector. Charter growth drives public sector incorporation, while also increasing within-public sector segregation. To assess the effects of disparate choice policies on segregation, we replicate this analysis for magnet schools, which have admissions practices intended to increase diversity, and find no evidence that magnet enrollment growth increases segregation.
Researchers decompose test score “gaps” and gap-changes into within- and between-school portions to generate evidence on the role that schools play in shaping educational inequality. However, existing decomposition methods (a) assume an equal-interval test scale and (b) are a poor fit to coarsened data such as proficiency categories. We develop two decomposition approaches that overcome these limitations: an extension of V, an ordinal gap statistic (Ho, 2009), and an extension of ordered probit models (Reardon et al., 2017). Simulations show V decompositions have negligible bias with small within-school samples. Ordered probit decompositions have negligible bias with large within-school samples but more serious bias with small within-school samples. These methods are applicable to decomposing any ordinal outcome by any categorical grouping variable.
Many kindergarten teachers place students in higher and lower “ability groups” to learn math and reading. Ability group placement should depend on student achievement, but critics charge that placement is biased by socioeconomic status (SES), gender, and race/ethnicity. We predict group placement in the Early Childhood Longitudinal Study of the Kindergarten class of 2010-11, using linear and ordinal regression models with classroom fixed effects. The best predictors of group placement are test scores, but girls, high-SES students, and Asian Americans receive higher placements than their test scores alone would predict. One third of students move groups during kindergarten, and some movement is predicted by changes in test scores, but high-SES students move up more than score gains would predict, and Hispanic children move up less. Net of SES and test scores, there is no bias in the placement of African American children. Differences in teacher-reported behaviors explain the higher placement of girls, but do little to explain the higher or lower placement of other groups. Although achievement is the best predictor of ability group placement, there are signs of bias.