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K-12 Education
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Each year, over a thousand public schools in the US close due to declining enrollments and chronic low performance, displacing hundreds of thousands of students. Using Texas administrative data and empirical strategies that use within-student across-time and within-school across-cohort variation, I explore the impact of school closures on students' educational and labor market outcomes. The findings indicate that experiencing school closures results in disruptions in both test scores and behavior. While the drop in test scores is recovered within three years, behavioral issues persist. This study further finds decreases in post-secondary education attainment, employment, and earnings at ages 25–27. These impacts are particularly pronounced among students in secondary education, Hispanic students, and those from originally low-performing schools and economically disadvantaged families.
Teacher shortages are a persistent challenge in the United States. I evaluate the effectiveness of an innovative pilot program that allowed principals to hand-select experienced staff members and paraeducators already working in schools to lead classrooms. Pilot educators are predominantly Black or African American. Districts reported randomly assigning students to teachers, and my analysis cannot reject randomization. Controlling for demographics and baseline scores, I find that students assigned to these pilot teachers perform just as well as those assigned to traditionally licensed teachers on average and outperform their peers in math. My results point to an untapped resource of potential teachers and underscore the value of principals’ local knowledge to identify capable candidates for teaching positions.
Why do employers offer pensions? We empirically explore two theoretical rationales, namely that pensions may improve worker effort and worker selection. We examine these hypotheses using administrative measures on effort and output in public schools around the pension-eligibility notch. When workers cross the notch their effective compensation falls significantly, but we observe no reduction in worker effort and output. This implies that pension payments do not increase effort. As for selection, we find that pensions retain low-value-added and high-value-added workers at the same rate, suggesting pensions have little or no influence on selection.
Do residential neighbors affect each others' schooling choices? We exploit oversubscription lotteries in Chile's centralized school admission system to identify the effect of close neighbors on application and enrollment decisions. A student is 5-7% more likely to rank a high school as their first preference and to attend that school if their closest neighbor attended it the prior year. These effects are stronger among boys and applicants with lower parents' education and prior academic achievement, measured by previous scores in national standardized tests. Lower-achieving applicants are more likely to follow neighbors when their closest neighbor's test scores are higher. A neighbor enrolling in a school with one s.d. higher school effectiveness, peer composition, or school climate induces increases of 0.02-0.04 s.d. in the applicant's attended school. Our findings suggest that targeted policies aimed at increasing information to disadvantaged families have the potential to alleviate these frictions and generate significant multiplier effects.
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 instructional leaders, such as department chairs, mentor teachers, instructional coaches, and assistant principals, 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. The positive impact was concentrated in the first cohort and in just one of three regions, and approximately 80 percent of treated schools were charters. 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.
Longitudinal models of individual growth typically emphasize between-person predictors of change but ignore how growth may vary within persons because each person contributes only one point at each time to the model. In contrast, modeling growth with multi-item assessments allows evaluation of how relative item performance may shift over time. While traditionally viewed as a nuisance under the label of “item parameter drift” (IPD) in the Item Response Theory literature, we argue that IPD may be of substantive interest if it reflects how learning manifests on different items or subscales at different rates. In this study, we present a novel application of the Explanatory Item Response Model (EIRM) to assess IPD in a causal inference context. Simulation results show that when IPD is not accounted for, both parameter estimates and their standard errors can be affected. We illustrate with an empirical application to the persistence of transfer effects from a content literacy intervention on vocabulary knowledge, revealing how researchers can leverage IPD to achieve a more fine-grained understanding of how vocabulary learning develops over time.
In-person tutoring has been shown to improve academic achievement. Though less well-researched, virtual tutoring has also shown a positive effect on achievement but has only been studied in grade five or above. We present findings from the first randomized controlled trial of virtual tutoring for young children (grades K-2). Students were assigned to 1:1 tutoring, 2:1 tutoring, or a control group. Assignment to any virtual tutoring increased early literacy skills by 0.05-0.08 SD with the largest effects for 1:1 tutoring (0.07-0.12 SD). Students initially scoring well below benchmark and first graders experienced the largest gains from 1:1 tutoring (0.15 and 0.20 SD, respectively). Effects are smaller than typically seen from in-person early literacy tutoring programs but still positive and statistically significant, suggesting promise particularly in communities with in-person staffing challenges.
Many decentralized matching markets experience high rates of instability due to information frictions. This paper analyzes these frictions in a particularly unstable U.S. market, the labor market for first-year school teachers. We develop and estimate a dynamic, partial equilibrium model of labor mobility that incorporates non-pecuniary information frictions for school climate and teacher workload. In terms of reducing turnover, a policy that improves information outperforms each alternative considered, including targeted wage premiums at hard-to-staff schools, large retention bonuses, and relaxed tenure requirements. Replicating the gains made through information revelation requires retention bonuses valued at 35% of teachers’ current salaries.
The National Assessment of Educational Progress (NAEP) has tested the civic, or citizenship knowledge of students across the nation at irregular intervals since its very inception. Despite advancements in reading and mathematics, evidenced by results from the National Assessment of Educational Progress (NAEP), civics proficiency has remained consistently low, which raises concerns among educators and policymakers. This study attempts to provide those educators and policymakers with state-level predictions, not currently provided for the civics assessment. This research addresses this gap in state-level civics education data by applying multilevel regression with poststratification (MRP) to NAEP's nationally representative civics scores, yielding state-specific estimates that account for student demographics. A historical analysis of NAEP's development underscores its significance in national education and highlights the challenges of transitioning to state-level reporting, particularly for civics, which lacks state-level generalizability. Furthermore, this paper evaluates NAEP's frameworks, questioning their alignment with civics education's evolving needs, and investigates the presence of opportunity gaps in civics knowledge across gender and racial/ethnic lines. By comparing MRP estimates with published NAEP results, the study validates the method's credibility and emphasizes the potential of MRP in educational research. The findings reveal persistent racial/ethnic disparities in civic knowledge, with profound implications for civics instruction and policy. The research concludes by stressing the necessity for state-specific data to inform education policy and practice, advocating for teaching methods that enhance civic understanding and engagement, and suggesting future research directions to address the uncovered disparities.
Mounting evidence supporting the advantages of a diverse teacher workforce prompts policymakers to scrutinize existing recruitment pathways. Following four cohorts of Maryland public high-school students over 12 years reveals several insights. Early barriers require timely interventions, aiding students of color in achieving educational milestones that are prerequisites for teacher candidacy (high school graduation, college enrollment). While alternative pathways that bypass traditional undergraduate teacher preparation may help, current approaches still show persistent racial disparities. Data simulations underscore the need for race-conscious policies specifically targeting or differentially benefiting students of color, as race-neutral strategies have minimal impact. Ultimately, multiple race-conscious policy solutions addressing various educational milestones must demonstrate significant effects—approximately 30% increases—to reshape the teacher workforce to align with student body demographics.