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How much school students attend is a powerful indicator of their wellbeing and a strong predictor of their future success in school. Popular media has reported significant increases in chronic absenteeism during the first full school year of the COVID-19 pandemic (2020-21). This sequential explanatory mixed-methods study describes how experiences during the pandemic and socioeconomic circumstances in general shaped Detroit student attendance during this critical school year and how the district responded to attendance issues. We found that 70% of students were chronically absent, with 40% of parents reporting that computer problems contributed to absenteeism. Despite significant investment in technology, the district’s strategies for engaging students were not sufficient in overcoming economic hardships and the new challenges of remote learning.
Given recent evidence challenging the replicability of results in the social and behavioral sciences, critical questions have been raised about appropriate measures for determining replication success in comparing effect estimates across studies. At issue is the fact that conclusions about replication success often depend on the measure used for evaluating correspondence in results. Despite the importance of choosing an appropriate measure, there is still no wide-spread agreement about which measures should be used. This paper addresses these questions by describing formally the most commonly used measures for assessing replication success, and by comparing their performance in different contexts according to their replication probabilities – that is, the probability of obtaining replication success given study-specific settings. The measures may be characterized broadly as conclusion-based approaches, which assess the congruence of two independent studies’ conclusions about the presence of an effect, and distance-based approaches, which test for a significant difference or equivalence of two effect estimates. We also introduce a new measure for assessing replication success called the correspondence test, which combines a difference and equivalence test in the same framework. To help researchers plan prospective replication efforts, we provide closed formulas for power calculations that can be used to determine the minimum detectable effect size (and thus, sample sizes) for each study so that a predetermined minimum replication probability can be achieved. Finally, we use a replication dataset from the Open Science Collaboration (2015) to demonstrate the extent to which conclusions about replication success depend on the correspondence measure selected.
In this paper I study how school desegregation by race following Brown v. Board of Education affected White individuals’ racial attitudes and politics in adulthood. I use geocoded nationwide data from the General Social Survey and differences-in-differences to identify causal impacts. Integration significantly reduced White individuals’ political conservatism as adults in the U.S. South but not elsewhere. I observe similar geographic impact heterogeneity for individuals’ attitudes towards Blacks and policies promoting racial equity, but positive effects emerge less consistently across specifications. Results suggest that this heterogeneity may depend on the effectiveness of integration policies. In the south, Black-White exposure was greater following desegregation, and White disenrollment was lower. My study provides the first causal evidence on how different theories concerning intergroup contact and racial attitudes (i.e., the contact and racial threat hypotheses) may have applied to school contexts following historic court mandates to desegregate.
The federal government and many individual organizations have invested in programs to support diversity in the STEM pipeline, including STEM summer programs for high school students, but there is little rigorous evidence of their efficacy. We fielded a randomized controlled trial to study a suite of such programs targeted to underrepresented high school students at an elite, technical institution. The STEM summer programs differ in their length (one week, six weeks, or six months) and modality (on-site or online). Students offered seats in the STEM summer programs are more likely to enroll in, persist through, and graduate from college, with gains in institutional quality coming from both the host institution and other elite universities. The programs also increase the likelihood that students graduate with a degree in a STEM field, with the most intensive program increasing four-year graduation with a STEM degree attainment by 33 percent. The shift to STEM degrees increases potential earnings by 2 to 6 percent. Program-induced gains in college quality fully account for the gains in graduation, but gains in STEM degree attainment are larger than predicted based on institutional differences.
Nearly all schools in the United States closed in spring 2020, at the onset of the COVID-19 pandemic. With a micropolitical lens, we analyze traditional public and charter schools reopenings for the 2020-21 school year in five urban districts. Districts’ adherence to and strategic uses of public health guidance, as well as a combination of union-district relations and labor market dynamics, influenced reopening. Parents, city and state lawmakers, and local institutional conditions also played a role, helping to explain differences across cases. We provide a rich description of reopening decisions in each of our case districts, and offer theoretically-grounded explanations for how factors identified in prior studies—which were interrelated and varied across local contexts—influenced district decision-making.
The current study replicated and extended the previous findings of content-integrated literacy intervention focusing on its effectiveness on first- and second-grade English learners’ (N = 1,314) reading comprehension, writing, vocabulary knowledge, and oral proficiency. Statistically significant findings were replicated on science and social studies vocabulary knowledge (ES = .51 and .53, respectively) and argumentative writing (ES = .27 and .41, respectively). Furthermore, treatment group outperformed control group on reading (ES = .08) and listening comprehension (ES = .14). Vocabulary knowledge and oral proficiency mediated treatment effects on reading comprehension, whereas only oral proficiency mediated effects on writing. Findings replicate main effects on vocabulary knowledge and writing, while also extending previous research by highlighting mechanisms underlying improved reading comprehension and writing.
Disparities in gifted representation across demographic subgroups represents a large and persistent challenge in U.S. public schools. In this paper, we measure the impacts of a school-wide curricular intervention designed to address such disparities. We implemented Nurturing for a Bright Tomorrow (NBT) as a cluster randomized trial across elementary schools with the low gifted identification rates in one of the nation’s largest school systems. NBT did not boost formal gifted identification or math achievement in the early elementary grades. It did increase reading achievement in select cohorts and broadly improved performance on a gifted identification measure that assesses nonverbal abilities distinct from those captured by more commonly used screeners. These impacts were driven by Hispanic and female students. Results suggest that policymakers consider a more diverse battery of qualifying exams to narrow disparity gaps in gifted representation and carefully weigh tradeoffs between universal interventions like NBT and more targeted approaches.
The Coronavirus Aid, Relief and Economic Security (CARES) Act passed by Congress in 2020 included significant aid to state education systems. These included direct aid to K-12 districts and higher education institutions, and funds to be used at the discretion of Governors through the Governor’s Emergency Education Relief Fund (GEER). We examine the factors influencing where and how GEER funding was distributed across state K-12 systems and what inequities were introduced in its spending. Using a mixed methods analysis of state GEER spending plans and district-level finance data, we focus specifically on how governors sought to target schools serving disadvantaged student groups. We find that several state leaders decided to send their GEER funds to school districts via funding formulas, and that some Governors made decisions to direct their GEER funds towards certain student groups. State spending patterns were not strongly related to governor political ideology or the states’ existing funding formulas or inter-district resource allocation patterns. We discuss the implications of this policy related to two state case examples, California and New York, and provide insight for future education stimulus funding proposals.
To address the challenge of improving third grade reading comprehension, we developed and evaluated the long-term effects of a sustained content literacy intervention called the Model of Reading Engagement (MORE), which emphasizes building domain and topic knowledge schemas from Grade 1 to Grade 3. The MORE intervention emphasizes thematic lessons that provide an intellectual framework for helping students connect new learning to a general schema (e.g., how scientists study past events, how systems function properly). Over three years, the treatment group students participated in (a) spring Grade 1 thematic content literacy lessons in science and social studies, (b) fall to spring Grade 2 thematic content literacy lessons in science, (c) remote Grade 3 thematic content literacy lessons in science, and (d) wide reading of thematically related informational texts in the summer months following Grade 1 and Grade 2. During the third grade school year (SY 2020-21), the COVID-19 pandemic required remote schooling to be in place from fall to spring and the Grade 3 MORE was provided to both treatment and control students. Accordingly, we examine long-term effects on third graders’ outcomes comparing a treatment group that received the Grade 1, Grade 2, and Grade 3 MORE treatment to a control condition that received the Grade 3 MORE treatment. Intent-to-treat estimates show that the students randomly assigned to the treatment condition outperformed control students in reading comprehension (ES = 0.11) and mathematics (ES = 0.14) on third grade state standardized assessments. Subgroup analyses also revealed positive impacts for student living in low- to moderate-socioeconomic status neighborhoods on both reading comprehension (ES = .13) and mathematics (ES = .20). Findings indicate that a sustained content literacy intervention may be a scalable approach for accelerating and equalizing third-graders’ reading comprehension and math outcomes.