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K-12 Education

James S. Kim, Joshua B. Gilbert, Jackie E. Relyea, Patrick Rich, Ethan Scherer, Mary A. Burkhauser, Johanna N. Tvedt.
We investigated the effectiveness of a sustained and spiraled content literacy intervention that emphasizes building domain and topic knowledge schemas and vocabulary for elementary-grade students. The Model of Reading Engagement (MORE) intervention underscores thematic lessons that provide an intellectual structure for helping students connect new learning to a general schema in Grade 1 (animal survival), Grade 2 (scientific investigation of past events like dinosaur mass extinctions), and Grade 3 (scientific investigation of living systems). A total of 30 elementary schools (N = 2,870 students) were randomized to a treatment or control condition. In the treatment condition (i.e., full spiral curriculum), students participated in content literacy lessons from Grades 1 to 3 during the school year and wide reading of thematically related informational texts in the summer following Grades 1 and 2. In the control condition (i.e., partial spiral curriculum), students participated in lessons in only Grade 3. The Grade 3 lessons for both conditions were implemented online during the COVID-19 pandemic school year. Results reveal that treatment students outperformed control students on science vocabulary knowledge across all three grades. Furthermore, intent-to-treat analyses revealed positive transfer effects on Grade 3 science reading (ES = .14), domain-general reading comprehension (ES = .11), and mathematics achievement (ES = .12). Treatment impacts were sustained at 14-month follow-up on Grade 4 reading comprehension (ES = .12) and mathematics achievement (ES = .16). Findings indicate that a content literacy intervention that spirals topics and vocabulary across grades can improve students’ long-term academic achievement outcomes.

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Luke C. Miller, James Soland, Daniel Lipscomb, Daniel W. Player, Rachel S. White.

Many dimensions of teacher working conditions influence both teacher and student outcomes; yet, analyses of schools’ overall working conditions are challenged by high correlations among the dimensions. Our study overcame this challenge by applying latent profile analysis of Virginia teachers’ perceptions of school leadership, instructional agency, professional growth opportunities, rigorous instruction, managing student behavior, family engagement, physical environment, and safety. We identified four classes of schools: Supportive (61%), Unsupportive (7%), Unstructured (22%), and Structured (11%). The patterns of these classes suggest schools may face tradeoffs between factors such as more teacher autonomy for less instructional rigor or discipline. Teacher satisfaction and their stated retention intentions were correlated with their school’s working conditions classes, and school contextual factors predicted class membership. By identifying formerly unseen profiles of teacher working conditions and considering the implications of being a teacher in each, decisionmakers can provide schools with targeted supports and investments.

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Sarah Novicoff, Thomas S. Dee.

While policymakers have demonstrated considerable enthusiasm for “science of reading” initiatives, the evidence on the impact of related reforms when implemented at scale is limited. In this pre-registered, quasi-experimental study, we examine California’s recent initiative to improve early literacy across the state’s lowest-performing elementary schools. The Early Literacy Support Block Grant (ELSBG) provided teacher professional development grounded in the science of reading as well as aligned supports (e.g., assessments and interventions), new funding (about $1000 per student), spending flexibility within specified guidelines, and expert facilitation and oversight of school-based planning. We find that ELSBG generated significant (and cost-effective) improvements in ELA achievement in its first two years of implementation (0.14 SD) as well as smaller, spillover improvements in math achievement.

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David Menefee-Libey, Carolyn Herrington, Kyoung-Jun Choi, Julie Marsh, Katrina Bulkley.

COVID-19 upended schooling across the United States, but with what consequences for the state-level institutions that drive most education policy? This paper reports findings on two related research questions. First, what were the most important ways state government education policymakers changed schools and schooling from the moment they began to reckon with the seriousness of COVID-19 through the first full academic year of the pandemic? Second, how deep did those changes go – are there indications the pandemic triggered efforts to make lasting changes in states’ education policymaking institutions? Using multiple-methods research focused on Colorado, Florida, Louisiana, Michigan, and Oregon, we documented policies enacted during the period from March 2020 through June 2021 across states and across sectors (traditional and choice) in three COVID-19-related education policy domains: school closings and reopenings, budgeting and resource allocation, and assessment and accountability systems. We found that states quickly enacted radical changes to policies that had taken generations to develop. They mandated sweeping school closures in Spring 2020, and then a diverse array of school reopening policies in the 2020/2021 school year. States temporarily modified their attendance-based funding systems and allocated massive federal COVID-19 relief funds. Finally, states suspended annual student testing, modified the wide array of accountability policies and programs linked to the results of those tests, and adapted to new assessment methods. These crisis-driven policy changes deeply disrupted long-established patterns and practices in education. Despite this, we found that state education governance systems remained resilient, and that at least during the first 16 months of the pandemic, stakeholders showed little interest in using the crisis to trigger more lasting institutional change. We hope these findings enable state policymakers to better prepare for future crises.

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Emily K. Penner, Dan Ma.

We examine access to high school Ethnic Studies in California, a new graduation requirement beginning in 2029-30. Data from the California Department of Education and the University of California Office of the President indicate that roughly 50 percent of public high school students in 2020-21 attend a school that offers Ethnic Studies or a related course, but as of 2018-19, only 0.2 percent of students were enrolled in such a course. Achieving parity with economics, a current graduation requirement, requires more than doubling the number of Ethnic Studies teachers relative to 2018-19. We also examine school and community factors that predict offering Ethnic Studies and provide descriptive information about the Ethnic Studies teaching force across the state.

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Paul T. von Hippel.

Educational researchers often report effect sizes in standard deviation units (SD), but SD effects are hard to interpret. Effects are easier to interpret in percentile points, but conversion from SDs to percentile points involves a calculation that is not intuitive to educational stakeholders. We point out that, if the outcome variable is normally distributed, simply multiplying the SD effect by 37 usually gives an excellent approximation to the percentile-point effect. For students in the middle three-fifths of a normal distribution, the approximation is always accurate to within 1.6 percentile points (and usually accurate to within 1 percentile point) for effect sizes of up to 0.8 SD (or 29 to 30 percentile points). Two examples show that the approximation can work for empirical effects estimated from real studies.

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Brendan Bartanen, Aliza N. Husain, David D. Liebowitz.

School principals are viewed as critical actors to improve student outcomes, but there remain important methodological questions about how to measure principals’ effects. We propose a framework for measuring principals’ contributions to student outcomes and apply it empirically using data from Tennessee, New York City, and Oregon. As commonly implemented, value-added models misattribute to principals changes in student performance caused by unobserved time-varying factors over which principals exert minimal control, leading to biased estimates of individual principals’ effectiveness and an overstatement of the magnitude of principal effects. Based on our framework, which better accounts for bias from time-varying factors, we find that little of the variation in student test scores or attendance is explained by persistent effectiveness differences between principals. Across contexts, the estimated standard deviation of principal value-added is roughly 0.03 student-level standard deviations in math achievement and 0.01 standard deviations in reading.

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Melanie Rucinski.

Prior research has found that economic downturns have positive effects on new teacher quality, but has not been able to determine the extent to which this relationship arises from a supply response (increased quantity or positive selection of teaching candidates) vs. a demand response (selection in hiring enabled by falling demand). In this paper, I use longitudinal data on students and teachers in Massachusetts to describe the effects of higher unemployment rates on both supply and demand for teachers. I show that students who graduate from college when unemployment rates are higher are more likely to take a teacher certification test, and that this effect is stronger among students who were higher achieving while in high school. On the demand side of the market, higher unemployment reduces new teacher hiring and the overall number of teachers employed, but I find no evidence that schools differentially employ higher achieving teaching candidates during economic downturns. While I cannot definitively rule out changes in demand-side selection, I show that much of the positive relationship between unemployment rates and teacher quality can be explained by positively selected supply. My results suggest that economic incentives impact both the quantity and the quality of new teaching candidates, with implications for attracting and retaining high-quality teachers outside of economic downturns.

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Beth Schueler, Liz Nigro, John Wang.

The improvement of low-performing school systems is one potential strategy for mitigating educational inequality. Some evidence suggests districtwide reform may be more effective than school-level change, but limited research examines district-level turnaround. There is also little scholarship examining the effects of turnaround reforms on outcomes beyond the first few years of implementation, on outcomes beyond test scores, or on the effectiveness of efforts to replicate district improvement successes beyond an initial reform context. We study these topics in Massachusetts, home to the Lawrence district representing a rare case of demonstrated improvements in the early years of state takeover and turnaround and where state leaders have since intervened in three other contexts as a result. We use statewide student-level administrative data (2006-07 to 2018-19) and event study methods to estimate medium-term reform impacts on test and non-test outcomes across four Massachusetts-based contexts: Lawrence, Holyoke, Springfield, and Southbridge. We find substantial district improvement was possible although sustaining the rate of gains was more complicated. Replicating gains in new contexts was also possible but not guaranteed. 

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Joshua B. Gilbert, Luke W. Miratrix, Mridul Joshi, Benjamin W. Domingue.

Analyzing heterogeneous treatment effects plays a crucial role in understanding the impacts of educational interventions. A standard practice for heterogeneity analysis is to examine interactions between treatment status and pre-intervention participant char- acteristics, such as pretest scores, to identify how different groups respond to treatment. This study demonstrates that identical observed patterns of heterogeneity on test score outcomes can emerge from entirely distinct data-generating processes. Specifically, we describe scenarios in which treatment effect heterogeneity arises from either variation in treatment effects along 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 as such outcomes are insufficient to identify the relevant generating process. 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 heterogeneity 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.

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