Search EdWorkingPapers

Search EdWorkingPapers by author, title, or keywords.

K-12 Education

Christopher D. Brooks, Matthew G. Springer.

We analyzed the proposed spending data for the American Recovery Plan’s Elementary and Secondary Emergency Relief III (ESSER III) fund from the spring of 2021 of nearly 3,000 traditional public-school districts in the United States to (1) identify trends in the strategies adopted and (2) to test whether spending strategies were observably heterogeneous across district characteristics. We found that districts proposed a breadth of spending patterns with ESSER III. Moreover, there was a clear prioritization on spending related to academic learning recovery and facilities and operations spending, with the latter being particularly emphasized in higher-poverty districts. This divergent spending pattern may have important equity implications for short-term academic learning recovery for students affected by the COVID-19 pandemic.

More →


Sarah Ruth Morris, Andy Parra-Martinez, Jonathan Wai, Robert Maranto.

This mixed-methods study synthesizes Standards-Based Grading (SBG) literature, analyzes 249 Arkansas administrators' survey responses using OLS regressions, and identifies themes through in-vivo coding of qualitative feedback. Results show more SBG support among liberal, elementary-level administrators in larger, economically diverse districts. Qualitative insights highlight structural barriers and mindsets against SBG, emphasizing its importance for mastery-focused assessment and grading alignment. These findings underscore the influence of principals' beliefs on SBG support and suggest researching the contextual and ideological factors influencing SBG's implementation.

More →


Matthew A. Kraft, Sarah Novicoff.

We examine the fundamental and complex role that time plays in the learning process. We begin by developing a conceptual framework to elucidate the multiple obstacles schools face in converting total time in school into active learning time. We then synthesize the causal research and document a clear positive effect of additional time on student achievement typically of small to medium magnitude depending on dosage, use, and context. Further descriptive analyses reveal how large differences in the length of the school day and year across public schools are an underappreciated dimension of educational inequality in the United States. Finally, our case study of time loss in one urban district demonstrates the potential to substantially increase instructional time within existing constraints.

More →


Joshua Bleiberg, Eric Brunner, Erica Harbatkin, Matthew A. Kraft, Matthew G. Springer.

Federal incentives and requirements under the Obama administration spurred states to adopt major reforms to their teacher evaluation systems. We examine the effects of these reforms on student achievement and attainment at a national scale by exploiting their staggered implementation across states. We find precisely estimated null effects, on average, that rule out impacts as small as 0.017 standard deviations for achievement and 1.2 percentage points for high school graduation and college enrollment. We highlight five factors that likely limited the efficacy of teacher evaluation at scale: political opposition, decentralization, capacity constraints, limited generalizability, and the absence of compensating wages.

More →


Isaac M. Opper, Umut Özek.

We use a marginal treatment effect (MTE) representation of a fuzzy regression discontinuity setting to propose a novel estimator. The estimator can be thought of as extrapolating the traditional fuzzy regression discontinuity estimate or as an observational study that adjusts for endogenous selection into treatment using information at the discontinuity. We show in a frequentest framework that it is consistent under weaker assumptions than existing approaches and then discuss conditions in a Bayesian framework under which it can be considered the posterior mean given the observed conditional moments. We then use this approach to examine the effects of early grade retention. We show that the benefits of early grade retention policies are larger for students with lower baseline achievement and smaller for low-performing students who are exempt from retention. These findings imply that (1) the benefits of early grade retention policies are larger than have been estimated using traditional fuzzy regression discontinuity designs but that (2) retaining additional students would have a limited effect on student outcomes.

More →


Deven Carlson, Adam Shepardson.

As students are exposed to extreme temperatures with ever-increasing frequency, it is important to understand how such exposure affects student learning. In this paper we draw upon detailed student achievement data, combined with high-resolution weather records, to paint a clear portrait of the effect of temperature on student learning across a six-year period for students in Tulsa, Oklahoma. The detailed, longitudinal nature of our data allows us to estimate the effects of both test-day and longer-term temperature on student test performance, and to examine how the effects of both temperature measures vary across seasons, student background, and the distribution of student achievement. Our results show that test-day temperature has no significant effect on student test performance in fall or winter, but a clear negative effect on students’ spring performance, particularly in math. Second, we find that summer temperature has a positive, statistically significant, and substantively meaningful effect on student performance on the fall MAP assessment—these effects appear in both math and reading. The results also illustrate that 90-day temperature affects math performance in winter and spring, but these estimates are modest in substantive magnitude.

More →


Joshua B. Gilbert.
When analyzing treatment effects on test scores, researchers face many choices and competing guidance for scoring tests and modeling results. This study examines the impact of scoring choices through simulation and an empirical application. Results show that estimates from multiple methods applied to the same data will vary because two-step models using sum or factor scores provide attenuated standardized treatment effects compared to latent variable models. This bias dominates any other differences between models or features of the data generating process, such as the use of scoring weights. An errors-in-variables (EIV) correction removes the bias from two-step models. An empirical application to data from a randomized controlled trial demonstrates the sensitivity of the results to model selection. This study shows that the psychometric principles most consequential in causal inference are related to attenuation bias rather than optimal scoring weights.

More →


Brian A. Jacob.

Media reports suggest that parent frustration with COVID school policies and the growing politicization of education have increased community engagement with local public schools. However, there is no evidence to date on whether these factors have translated into greater engagement at the ballot box. This paper uses a novel data set to explore how school board elections changed following the start of the COVID-19 pandemic. I find that school board elections post-COVID were more likely to be contested, and that voter turnout in contested elections increased. These changes were large in magnitude and varied with several district characteristics.

More →


Lucy C. Sorensen, Andrea Headley, Stephen B. Holt.

Involvement with the juvenile justice system carries immense personal costs to youth: 30% of detained youth drop out of school (relative to 5% nationally) and 55% are re-arrested within one year. These personal costs are compounded by societal costs – both directly in $214,000 of expenses per confined youth per year – and indirectly in lost social and economic productivity. While much of the extant research on the “school-to-prison pipeline” focuses on school disciplinary practices such as suspension, less attention has been given to understanding the impact of school referrals to the juvenile justice system on students’ relationship with school. Using novel administrative data from North Carolina, we link 3 years of individual educational and disciplinary infraction records to juvenile justice system records to identify the effect of juvenile justice referrals for school-based offenses on student academic and behavioral outcomes. We find that, even for the same offense type and circumstance, relative to students only punished for infractions internally in the school, students referred to juvenile justice experience lower academic achievement, increased absenteeism, and are more likely to be involved in future juvenile system contact. We show that these juvenile referrals are not inevitable and instead reflect a series of discretionary choices made by school administrators and law enforcement. Moreover, we examine demographic disparities in school-based referrals to juvenile justice and find that female students, Black students, and economically disadvantaged students are more likely to receive referrals even for the same offense type and circumstances.

More →


Joshua B. Gilbert, Luke W. Miratrix, Mridul Joshi, Benjamin W. Domingue.
Analyzing heterogeneous treatment effects (HTE) plays a crucial role in understanding the impacts of educational interventions. A standard practice for HTE analysis is to examine interactions between treatment status and pre-intervention participant characteristics, such as pretest scores, to identify how different groups respond to treatment. This study demonstrates that identical patterns of HTE on test score outcomes can emerge either from variation in treatment effects due to a pre-intervention participant characteristic or from correlations between treatment effects and item easiness parameters. We demonstrate analytically and through simulation that these two scenarios cannot be distinguished if analysis is based on summary scores alone. We then describe a novel approach that identifies the relevant data-generating process by leveraging item-level data. We apply our approach to a randomized trial of a reading intervention in second grade, and show that any apparent HTE by pretest ability is driven by the correlation between treatment effect size and item easiness. Our results highlight the potential of employing measurement principles in causal analysis, beyond their common use in test construction.

More →