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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.
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.
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.
New York City’s universal pre-kindergarten program, which increased full-day enrollment from 19,000 to almost 70,000 children, is ambitious in both scale and implementation speed. We provide new evidence on the distribution of pre-K quality in NYC by student race/ethnicity, and investigate the extent to which observed differences are associated with the spatial distribution of higher-quality providers. Relative to other jurisdictions, we find the average quality of public pre-K providers is high. However, we identify large disparities in the average quality of providers experienced by black and white students, which is partially explained by differential proximity to higher-quality providers. Taken together, current racial disparities in the quality of pre-K providers may limit the program’s ability to reduce racial achievement gaps.
India took a decisive step toward universal basic education by proclaiming a constitutionally-guaranteed Right to Education (RTE) Act in 2009 that called for full access of children aged 6-14 to free schooling. This paper considers the offsetting effects to RTE from induced expansion of private tutoring in the educationally competitive districts of India. We develop a unique database of registrations of new private educational institutions offering tutorial services by local district between 2001-2015. We estimate the causal impact of RTE on private supplemental education by comparing the growth of these private tutorial institutions in districts identified a priori as having very competitive educational markets to those that had less competitive educational markets. We find a strong impact of RTE on the private tutoring market and show that this holds across alternative definitions of highly competitive districts and a variety of robustness checks, sensitivity analyses, and controls. Finally, we provide descriptive evidence that these private tutoring schools do increase the achievement (and competitiveness) of students able to afford them.
Narrative accounts of classroom instruction suggest that external interruptions, such as intercom announcements and visits from staff, are a regular occurrence in U.S. public schools. We study the frequency, nature, and duration of external interruptions in the Providence Public School District (PPSD) using original data from a district-wide survey and classroom observations. We estimate that a typical classroom in PPSD is interrupted over 2,000 times per year, and that these interruptions and the disruptions they cause result in the loss of between 10 to 20 days of instructional time. Administrators appear to systematically underestimate the frequency and negative consequences of these interruptions. We propose several organizational approaches schools might adopt to reduce external interruptions to classroom instruction.
This study examines the relationship between county-level estimates of implicit racial bias and black-white test score gaps in U.S. schools. Data from over 1 million respondents from across the United States who completed an online version of the Race Implicit Association Test (IAT) were combined with data from the Stanford Education Data Archive covering over 300 million test scores from U.S. schoolchildren in grades 3 through 8. Two key findings emerged. First, in both bivariate and multivariate models, counties with higher levels of racial bias had larger black-white test score disparities. The magnitude of these associations were on par with other widely accepted predictors of racial test score gaps, including racial gaps in family income and racial gaps in single parenthood. Second, the observed relationship between collective rates of racial bias and racial test score gaps was explained by the fact that counties with higher rates of racial bias had schools that were characterized by more racial segregation and larger racial gaps in gifted and talented assignment as well as special education placement. This pattern is consistent with a theoretical model in which aggregate rates of racial bias affect educational opportunity through sorting mechanisms that operate both within and beyond schools.
We study racial bias and the persistence of first impressions in the context of education. Teachers who begin their careers in classrooms with large black-white score gaps carry negative views into evaluations of future cohorts of black students. Our evidence is based on novel data on blind evaluations and non-blind public school teacher assessments of fourth and fifth graders in North Carolina. Negative first impressions lead teachers to be significantly less likely to over-rate but not more likely to under-rate black students’ math and reading skills relative to their white classmates. Teachers' perceptions are sensitive to the lowest-performing black students in early classrooms, but non-responsive to highest-performing ones. This is consistent with the operation of confirmatory biases. Since teacher expectations can shape grading patterns and sorting into academic tracks as well as students’ own beliefs and behaviors, these findings suggest that novice teacher initial experiences may contribute to the persistence of racial gaps in educational achievement and attainment.
A vast research literature documents racial bias in teachers’ evaluations of students. Theory suggests bias may be larger on grading scales with vague or overly-general criteria versus scales with clearly-specified criteria, raising the possibility that well-designed grading policies may mitigate bias. This study offers relevant evidence through a randomized web-based experiment with 1,549 teachers. On a vague grade-level evaluation scale, teachers rated a student writing sample lower when it was randomly signaled to have a Black author, versus a White author. However, there was no evidence of racial bias when teachers used a rubric with more clearly-defined evaluation criteria. Contrary to expectation, I found no evidence that the magnitude of grading bias depends on teachers’ implicit or explicit racial attitudes.
Tens of millions of Americans have lost their jobs in the wake of the COVID-19 health and economic crisis, and a sizable share of these job losses may be permanent. Unemployment rates are particularly high among adults without a college degree. Recent state policy efforts have focused on increasing re-enrollment and credentialing among adults with some college but no degree (SCND); these efforts are likely to accelerate given the COVID-19 disruptions to the U.S. economy. Yet little is actually known about the background characteristics, academic experiences, or labor market trajectories of this population. Using data from the Virginia Community College System (VCCS), we provide the first detailed profile on the academic, employment, and earnings trajectories of the SCND population, and how these compare on key measures to VCCS graduates. We also develop a framework for prioritizing which segments of the SCND population states might target for re-enrollment and completion interventions. This framework may be particularly useful to states that need to fill critical workforce shortages in healthcare and other sectors or re-train their workforce in the wake of mass unemployment and economic disruption stemming from the COVID-19 crisis.