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Nearly all studies of preschool’s long-run effects examine means-tested programs; little is known about the long-run effects of universal programs. A number of key differences—including population served, scale, and counterfactual options—may cause universal programs to have different effects than previously studied means-tested programs. Using a difference-in-differences framework, I estimate the effects of Georgia’s first-in-the-nation statewide universal pre-K program on adult educational attainment and employment. The program made children 4.5 percent more likely to graduate from high school and 13.7 percent more likely to obtain a bachelor’s degree (although the latter effect is imprecise). I find similar results in a supplemental analysis that uses the synthetic control method. I find no effects on associate degree attainment or employment.
In this paper, I study the causal relationship between violence and human capital accumulation. Due to a power vacuum left in conflict zones of Colombia after the 2016 peace agreement, large spikes in violence were reported in the municipalities of the country dominated by the rebel group FARC. I compare student test scores in municipalities that experienced the increase in violence to the ones that did not, before and after the national peace agreement. I find that a 10 percent increase in the homicide rate reduces average high school test scores by approximately 0.03 standard deviations. However, this impact is greater in the case of poor students who suffered a reduction of about 0.1 standard deviations per subject area, equivalent to 3.3 percentage points out of the final score. I also consider heterogeneity by gender finding a slightly larger negative impact on female students. This disparate effect on women and on the poorest students adds new evidence to the literature on the effects of armed conflict on learning outcomes.
Because high-stakes testing for school accountability does not begin until third grade, accountability ratings for elementary schools do not directly measure students’ academic progress in grades K through 2. While it is possible that children’s test scores in grades 3 and above are highly correlated with children’s outcomes in the untested grades, research provides reasons to believe that this might not be the case in all schools. This study explores whether measures of school quality based on test scores in grades 3 through 5 serve as a strong proxy for children’s academic outcomes in grades K through 2. The results show that directly accounting for children’s test scores in the early grades could lead to meaningful changes in schools’ test-based performance ratings. The findings have important implications for accountability policy.
Standards have been at the heart of state and federal efforts to improve education for several decades. Most recently, standards-based reforms have evolved with a focus on more ambitious "college- and career-ready" (CCR) standards. This paper synthesizes the results of a seven-year national research center focused on the implementation and effects of CCR standards. The paper draws on evidence from a quasi-experimental longitudinal study using NAEP data, a cluster-randomized trial of an alignment feedback intervention, and detailed implementation data from state-representative surveys and case studies of five districts. Situating our work in a "policy attributes theory," we find important gaps in the theory of change underlying current standards-based reform efforts. We conclude that the CCR standards movement is not succeeding in achieving its desired outcomes. We make specific suggestions for improving instructional policy, including a) providing more specific instructional guidance, b) reconceptualizing professional learning, c) building buy-in through the involvement of trusted leaders, d) providing better supports for differentiation, and e) devoting attention and guidance to the intersection of content and pedagogy, and f) addressing persistent deficit thinking among educators.
In recent decades, U.S. education leaders have advocated for more intellectually ambitious mathematics instruction in classrooms. Evidence about whether more ambitious mathematics instruction has filtered into contemporary classrooms, however, is largely anecdotal. To address this issue, we analyzed 93 lessons recorded by a national random sample of middle school mathematics teachers. We find that lesson quality varies, with the typical lesson containing some elements of mathematical reasoning and sense-making, but also teacher-directed instruction with limited student input. Lesson quality correlates with teachers’ use of a textbook and with teachers’ mathematical background. We consider these findings in light of efforts to transform U.S. mathematics instruction.
After near-universal school closures in the United States at the start of the pandemic, lawmakers and educational leaders made plans for when and how to reopen schools for the 2020-21 school year. Educational researchers quickly assessed how a range of public health, political, and demographic factors were associated with school reopening decisions and parent preferences for in-person and remote learning. I review this body of literature, to highlight what we can learn from its findings, limitations, and influence on public discourse. Studies consistently highlighted the influence of partisanship, teachers’ unions, and demographics, with mixed findings on COVID-19 rates. The literature offers useful insight and requires more evidence, and it highlights benefits and limitations to rapid research with large-scale quantitative data.
Analyses that reveal how treatment effects vary allow researchers, practitioners, and policymakers to better understand the efficacy of educational interventions. In practice, however, standard statistical methods for addressing Heterogeneous Treatment Effects (HTE) fail to address the HTE that may exist within outcome measures. In this study, we present a novel application of the Explanatory Item Response Model (EIRM) for assessing what we term “item-level” HTE (IL-HTE), in which a unique treatment effect is estimated for each item in an assessment. Results from data simulation reveal that when IL-HTE are present but ignored in the model, standard errors can be underestimated and false positive rates can increase. We then apply the EIRM to assess the impact of a literacy intervention focused on promoting transfer in reading comprehension on a digital formative assessment delivered online to approximately 8,000 third-grade students. We demonstrate that allowing for IL-HTE can reveal treatment effects at the item-level masked by a null average treatment effect, and the EIRM can thus provide fine-grained information for researchers and policymakers on the potentially heterogeneous causal effects of educational interventions.
To boost college graduation rates, policymakers often advocate for academic supports such as coaching or mentoring. Proactive and intensive coaching interventions are effective, but are costly and difficult to scale. We evaluate a relatively lower-cost group coaching program targeted at first-year college students placed on academic probation. Participants attend a workshop where coaches aim to normalize failure and improve self-confidence. Coaches also facilitate a process whereby participants reflect on their academic difficulties, devise solutions to address their challenges, and create an action plan. Participants then hold a one-time follow-up meeting with their coach or visit a campus resource. Using a difference-in-discontinuity design, we show that the program raises students’ first-year GPA by 14.6% of a standard deviation, and decreases the probability of first-year dropout by 8.5 percentage points. Effects are concentrated among lower-income students who also experience a significant increase in the probability of graduating. Finally, using administrative data we provide the first evidence that coaching/mentoring may have substantial long-run effects as we document significant gains in lower-income students’ earnings 7–9 years following entry to the university. Our findings indicate that targeted, group coaching can be an effective way to improve marginal students’ academic and early career outcomes.
Performance-based funding models for higher education, which tie state support for institutions to performance on student outcomes, have proliferated in recent decades. Some states have designed these policies to also address educational attainment gaps by including bonus payments for traditionally low-performing groups. Using a Synthetic Control Method research design, we examine the impact of these funding regimes on race-based completion gaps in Tennessee and Ohio. We find no evidence that performance-based funding narrowed race-based completion gaps. In fact, contrary to their intended purpose, we find that performance-based funding widened existing gaps in certificate completion in Tennessee. Across both states, the estimated impacts on associate degree outcomes are also directionally consistent with performance-based funding exacerbating racial inequities in associate degree attainment.