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K-12 Education

Emily Rauscher, Yifan Shen.

The equity-efficiency tradeoff and cumulative return theories predict larger returns to school spending in areas with higher previous investment in children. Equity – not efficiency – is therefore used to justify progressive school funding: spending more in communities with fewer financial resources. Yet it remains unclear how returns to school spending vary across areas by previous investment. Using county-level panel data 2009-2018 from the Stanford Education Data Archive, the F-33 finance survey, and National Vital Statistics, we estimate achievement returns to school spending and test whether returns vary between counties with low and high levels of initial human capital (measured as birth weight), child poverty, and previous spending. Spending returns are higher among counties with low previous investment (counties that also have a high percent of Black students). Evidence of diminishing returns by previous investment documents another way that schools increase equality and establishes another argument for progressive school funding: efficiency.

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David Blazar, Cynthia Pollard.

The pursuit of multiple educational outcomes makes teaching a complex craft subject to potential conflicts and competing commitments. Using a dataset in which teachers were randomly assigned to students paired with videotapes of instruction, we both document and unpack such a tradeoff. Upper-elementary teachers who excel at raising students’ math test scores often are less successful at improving student-reported engagement in class (and vice versa). Further, the teaching practices that improve math test scores (e.g., cognitively demanding content) can simultaneously decrease engagement. At the same time, paired quantitative and qualitative analyses reveal two areas of practice that support both outcomes: active mathematics with opportunities for hands-on participation; and established routines and procedures to proactively organize the classroom environment. In addition to guiding practice-based teacher education, our mixed-methods analysis can serve as a model for rigorously studying and identifying dimensions of “good” teaching that promote multidimensional student development.

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Leigh Wedenoja, John Papay, Matthew A. Kraft.

We examine the dynamic nature of student-teacher match quality by studying the effect of having a teacher for more than one year. Using data from Tennessee and panel methods, we find that having a repeat teacher improves achievement and decreases absences, truancy, and suspensions. These results are robust to a range of tests for student and teacher sorting. High-achieving students benefit most academically and boys of color benefit most behaviorally. Effects increase with the share of repeat students in a class suggesting that classroom assignment policies intended to promote sustained student-teacher relationships such as looping may have even larger benefits.

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Andrew Camp, Gema Zamarro, Josh B. McGee.

The COVID-19 pandemic has been a trying period for teachers. Teachers had to adapt to unexpected conditions, teaching in unprecedented ways. As a result, teachers' levels of stress and burnout have been high throughout the pandemic, raising concerns about a potential increase in teacher turnover and future teacher shortages. We use administrative data for the state of Arkansas to document the effects of the COVID-19 pandemic on teachers’ mobility and attrition during the years 2018-19 to 2021-2022. We find stable turnover rates during the first year of the pandemic (2020-2021) but an increase in teacher mobility and attrition in the second year (2021-2022). Teacher mobility and attrition increased by 2 percentage points (10% relative increase) this second year but with heterogeneous effects across regions and depending on the teacher and school characteristics. Our results raise concerns about increased strain in areas already experiencing teacher shortages and a potential reduction in the diversity of the Arkansas teacher labor force.

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Christopher A. Candelaria, Shelby M. McNeill, Kenneth A. Shores.

School finance reforms are not well defined and are likely more prevalent than the current literature has documented. Using a Bayesian changepoint estimator, we quantitatively identify the years when state education revenues abruptly increased for each state between 1960 and 2008 and then document the state-specific events that gave rise to these changes. We find 108 instances of abrupt increases in state education revenues across 43 states; about one-quarter of these changes had been undocumented. Half of the abrupt increases that occurred post-1990 were preceded by litigation-prompted legislative activity, and Democrat-party control of a state increases the probability of a changepoint occurring by 8 percentage points.

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Daniel Rodriguez-Segura, Beth E. Schueler.

A significant share of education and development research uses data collected by workers called “enumerators.” It is well-documented that “enumerator effects”—or inconsistent practices between the individual people who administer measurement tools— can be a key source of error in survey data collection. However, it is less understood whether this is a problem for academic assessments or performance tasks. We leverage a remote phone-based mathematics assessment of primary school students and survey of their parents in Kenya. Enumerators were randomized to students to study the presence of enumerator effects. We find that both the academic assessment and survey was prone to enumerator effects and use simulation to show that these effects were large enough to lead to spurious results at a troubling rate in the context of impact evaluation. We therefore recommend assessment administrators randomize enumerators at the student level and focus on training enumerators to minimize bias.

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Min Sun, Christopher A. Candelaria, David Knight, Zachary LeClair, Sarah E. Kabourek, Katherine Chang.

Knowing how policy-induced salary schedule changes affect teacher recruitment and retention will significantly advance our understanding of how resources matter for K-12 student learning. This study sheds light on this issue by estimating how legislative funding changes in Washington state in 2018-19—induced by the McCleary court-ordered reform—affected teacher salaries and labor market outcomes. By embedding a simulated instrumental variables approach in a mixed methods design, we observed that local collective bargaining negotiations directed new state-level funding allocations toward certificated base salaries, particularly among more senior teachers. Variability in political power, priorities, and interests of both districts and unions led to greater heterogeneity in teacher salary schedules. Teacher mobility rate was reduced in the first year of the reform, and subsequently new hiring rate was reduced in the second year. Suggestive evidence indicates that a $1,000 salary increase would have larger effects on junior teachers’ hiring and their transfers between districts to a greater extent than late-career teachers.

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David Blazar, Beth Schueler.

What guidance does research provide school districts about how to improve system performance and increase equity? Despite over 30 years of inquiry on the topic of effective districts, existing frameworks are relatively narrow in terms of disciplinary focus (primarily educational leadership perspectives) and research design (primarily qualitative case studies). To bridge this gap, we first review the theoretical literatures on how districts are thought to affect student outcomes, arguing that an expanded set of disciplinary perspectives—organizational behavior, political science, and economics—have distinct theories about why districts matter. Next, we conduct a systematic review of quantitative studies that estimate the relationship between district-level inputs and performance outcomes. This review reveals benefits of district-level policies that cross disciplinary perspectives, including higher teacher salaries and strategic hiring, lower student-teacher ratios, and data use. One implication is that future research on district-level policymaking needs to consider multiple disciplinary perspectives. Our review also reveals the need for significant additional causal evidence and provides a multidisciplinary map of theorized pathways through which districts could influence student outcomes that are ripe for rigorous testing.

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Edward J. Kim.

This study introduces the signal weighted teacher value-added model (SW VAM), a value-added model that weights student-level observations based on each student’s capacity to signal their assigned teacher’s quality. Specifically, the model leverages the repeated appearance of a given student to estimate student reliability and sensitivity parameters, whereas traditional VAMs represent a special case where all students exhibit identical parameters. Simulation study results indicate that SW VAMs outperform traditional VAMs at recovering true teacher quality when the assumption of student parameter invariance is met but have mixed performance under alternative assumptions of the true data generating process depending on data availability and the choice of priors. Evidence using an empirical data set suggests that SW VAM and traditional VAM results may disagree meaningfully in practice. These findings suggest that SW VAMs have promising potential to recover true teacher value-added in practical applications and, as a version of value-added models that attends to student differences, can be used to test the validity of traditional VAM assumptions in empirical contexts.

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Tammy Kolbe, Elizabeth Dhuey, Sara Menlove Doutre.

The formula used to allocate federal funding for state and local special education programs is one of the Individual with Disabilities Act’s most critical components. The formula not only serves as the primary mechanism for dividing available federal dollars among states, it also represents policymakers’ intent to equalize educational opportunities for students with disabilities nationwide. In this study, we evaluate the distribution of IDEA Part B(611) funding in the wake of changes to the formula that were instituted at the law’s 1997 reauthorization. We find that the revised formula generated large and concerning disparities among states in federal special education dollars. We find that, on average, states with proportionally larger populations of children and children living in poverty, children identified for special education, and non-White and Black children receive fewer federal dollars, both per pupil and per student receiving special education. We present policy simulations that illustrate how changes to the existing formula might improve the fairness and efficiency with which federal IDEA Part B funding is allocated to states.

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