We study the distributional effects of remote learning. Our approach combines newly collected data on parental preferences with administrative data from Los Angeles. The preference data allow us to account for selection into remote learning while also studying selection patterns and treatment effect heterogeneity. We find a negative average effect…

Student mobility is highly prevalent in the United States and has negative impacts on students' academic performance. Within-year mobility may be especially disruptive. However, research on the impacts of within-year mobility is limited, and less is known how impacts may vary across different geographies, such as differences between urban and…

The COVID-19 pandemic resulted in substantial unfinished learning for U.S. students, but to differing degrees for various subgroups. For example, students of color, from low-income families, or who attended high-poverty schools experienced greater unfinished learning. In this study we examined the degree of unfinished learning for students who…

We extend teacher evaluation research by estimating a reformed evaluation system's plausibly causal average effects on rural student achievement, identifying the settings where evaluation works, and incorporating evaluation expenditures. That the literature omits these contributions is concerning as research implies it hinders evidence-based…

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…

Generative AI, particularly Language Models (LMs), has the potential to transform real-world domains with societal impact, particularly where access to experts is limited. For example, in education, training novice educators with expert guidance is important for effectiveness but expensive, creating significant barriers to improving education…

The segregation of students by socioeconomic status has been on the rise in American public education between schools during the past several decades. Recent work has demonstrated that segregation is also increasing within schools at the classroom level. In this paper, we contribute to our understanding of the determinants of this increase in…

We examine the relationship between absenteeism and achievement since the onset of COVID-19. Applying first-differences models to North Carolina administrative data, we estimate that each absence was associated with a 0.0032 standard deviation (SD) decline in math achievement in 2022-23. As students averaged 3.3 more absences in 2022-23 than…

This paper reports math and reading academic achievement and growth in grades 2 to 8 for Hispanic participants and nonparticipants of a Spanish-English dual language program. I apply a piecewise multilevel growth model to administrative data from a large school district that enrolls a substantial English Learner student population. Dual language…

With 55 million students in the United States out of school due to the COVID-19 pandemic, education systems are scrambling to meet the needs of schools and families, including planning how best to approach instruction in the fall given students may be farther behind than in a typical year. Yet, education leaders have little data on how much…

Nearly one in five U.S. students attends a rural school, yet we know very little about achievement gaps and academic growth in rural schools. This study leverages a unique dataset that includes longitudinal test scores for more than five million 3rd to 8th grade students in approximately 17,000 public schools across the 50 states, including…

Over the past three decades, children from low-income families and those from more affluent families have increasingly been attending different public schools. While recent work has helped us understand patterns of income segregation between districts and schools within districts, we know very little about segregation of students as they…

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…

Education has faced unprecedented disruption during the COVID-19 pandemic; evidence about the subsequent effect on children is of crucial importance. We use data from an oral reading fluency (ORF) assessment--a rapid assessment taking only a few minutes that measures a fundamental reading skill--to examine COVID's effects on children's reading…