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K-12 Education
Reclassification can be an important juncture in the academic experience of English Learners (ELs). Literature has explored the potential for reclassification to influence academic outcomes like achievement, yet its impact on social-emotional learning (SEL) skills, which are as malleable and important to long-term success, remains unclear. Using a regression discontinuity design, we examine the causal effect of reclassification on SEL skills (self-efficacy, growth mindset, self-management, and social awareness) among 4th to 8th graders. In the districts studied, reclassification improved academic self-efficacy by 0.2 standard deviations for students near the threshold. Results are robust to alternative specifications and analyses. Given this evidence, we discuss ways districts might establish practices that instill more positive academic beliefs among ELs.
A pervasive issue in the school choice literature is whether schools of choice cream-skim students by enrolling high-achieving, less challenging, or less costly students. Similarly, schools of choice may “pushout” low-achieving, more challenging, or more costly students. Using longitudinal student-level data from Indiana, we created multiple measures to examine whether there is evidence consistent with the claims of voucher-participating private schools cream skimming the best students from public schools or pushing out voucher-receiving students. We do not find evidence consistent the claim of cream skimming. However, we find evidence consistent with the claim of private schools pushing out the lowest achieving voucher students.
Responsive teaching is a highly effective strategy that promotes student learning. In math classrooms, teachers might funnel students towards a normative answer or focus students to reflect on their own thinking, deepening their understanding of math concepts. When teachers focus, they treat students’ contributions as resources for collective sensemaking, and thereby significantly improve students’ achievement and confidence in mathematics. We propose the task of computationally detecting funneling and focusing questions in classroom discourse. We do so by creating and releasing an annotated dataset of 2,348 teacher utterances labeled for funneling and focusing questions, or neither. We introduce supervised and unsupervised approaches to differentiating these questions. Our best model, a supervised RoBERTa model fine-tuned on our dataset, has a strong linear correlation of .76 with human expert labels and with positive educational outcomes, including math instruction quality and student achievement, showing the model’s potential for use in automated teacher feedback tools. Our unsupervised measures show significant but weaker correlations with human labels and outcomes, and they highlight interesting linguistic patterns of funneling and focusing questions. The high performance of the supervised measure indicates its promise for supporting teachers in their instruction.
Teachers are critical to student learning, but adequately staffing classrooms has been challenging in many parts of the country. Even though teacher shortages are being reported across the U.S., teacher shortages are poorly understood. Determining and addressing teacher shortages is difficult due to the lack of data. Neither the federal government nor the majority of states have provided sufficient information on teacher shortages. To address this gap, we systematically examine news reports, department of education data, and publicly-available information on teacher shortages for every state in the U.S. We find there are at least 36,000 vacant positions along with at least 163,000 positions being held by underqualified teachers, both of which are conservative estimates of the extent of teacher shortages nationally. We discuss the implications of our findings for a robust data system, including more specific and consistent reporting of shortage, as well as implications for teacher preparation and education in the United States.
Counselors are a common school resource for students navigating complicated and con- sequential education choices. I estimate counselors’ causal effects using quasi-random assignment policies in Massachusetts. Counselors vary substantially in their effectiveness at increasing high school graduation and college attendance, selectivity, and persistence. Counselor effects on educational attainment are similar in magnitude to teacher effects, but they flow through improved information and assistance more than cognitive or non-cognitive skill development. Counselor effectiveness is most important for low-income and low-achieving students, so improving access to effective counseling may be a promising way to increase educational attainment and close socioeconomic gaps in education.
The COVID-19 pandemic upended the U.S. education system and the economy in ways that dramatically affected the jobs of K-12 educators. However, data limitations have led to considerable uncertainty and conflicting reports about the nature of staffing challenges in schools. We draw on education employment data from the Bureau of Labor Statistics (BLS) and State Education Agencies (SEA) to describe patterns in K-12 education employment and to highlight the limitations of available data. Data from the BLS suggest overall employment in the K-12 labor market declined by 9.3 percent at the onset of the pandemic and remains well below pre-pandemic levels. SEA data suggest that teachers have not (yet) left the profession in mass as many predicted, but that turnover decreased in the summer of 2020. We explore possible explanations for these patterns including (1) weak hiring through the summer of 2020 and (2) high attrition among K-12 instructional support staff. State vacancy data also suggest that schools are facing substantial challenges filling open positions during the 2021-22 academic year. Our analyses illustrate the imperative to build more timely, detailed, and nationally representative data systems on the K-12 education labor market to better inform policy.
Levels of governance (the nation, states, and districts), student subgroups (racially and ethnically minoritized and economically disadvantaged students), and types of resources (expenditures, class sizes, and teacher quality) intersect to represent a complex and comprehensive picture of K-12 educational resource inequality. Drawing on multiple sources of the most recently available data, we describe inequality in multiple dimensions. At the national level, racially and ethnically minoritized and economically disadvantaged students receive between $30 and $800 less in K-12 expenditures per pupil than White and economically advantaged students. At the state and district levels, per-pupil expenditures generally favor racially and ethnically minoritized and economically disadvantaged students compared to White and economically advantaged students. Looking at nonpecuniary resources, minoritized and economically disadvantaged students have smaller class sizes than their subgroup counterparts in the average district, but these students also have greater exposure to inexperienced teachers. We see no evidence that district-level spending in favor of traditionally disadvantaged subgroups is explained by district size, average district spending, teacher turnover, or expenditures on auxiliary staff, but Black and Hispanic spending advantage is correlated with the relative size of the Black and Hispanic special education population.
We estimate the longer-run effects of attending an effective high school (one that improves a combination of test scores, survey measures of socio-emotional development, and behaviors in 9th grade) for students who are more versus less educationally advantaged (i.e., likely to attain more years of education based on 8th-grade characteristics). All students benefit from attending effective schools, but the least advantaged students experience larger improvements in high-school graduation, college going, and school-based arrests. This heterogeneity is not solely due to less-advantaged groups being marginal for particular outcomes. Commonly used test-score value-added understates the long-run importance of effective schools, particularly for less-advantaged populations. Patterns suggest this partly reflects less-advantaged students being relatively more responsive to non-test-score dimensions of school quality.
Scholars argue the “racial achievement gap” frame perpetuates deficit mindsets. Previously, we found teachers gave lower priority to racial equity when disparities were framed as “achievement gaps” versus “inequality in educational outcomes.” In this brief, we analyze data from two survey experiments using a teacher sample and an MTurk sample. We find: (1) the effect of “achievement gap” (AG) language on equity prioritization is moderated by implicit bias, with larger negative effects among teachers holding stronger anti-Black/pro-White stereotypes, (2) the negative effect of AG language replicates with non-teachers, and (3) AG language causes respondents to express more negative racial stereotypes.