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Career and technical education (CTE) has existed in the United States for over a century, and only in recent years have there been opportunities to assess the causal impact of participating in these programs while in high school. To date, no work has assessed whether the relative costs of these programs meet or exceed the benefits as described in recent evaluations. In this paper, we use available cost data to compare average costs per pupil in standalone high school CTE programs in Connecticut and Massachusetts to the most likely counterfactual schools. Under a variety of conservative assumptions about the monetary value of known educational and social benefits, we find that programs in Massachusetts offer clear positive returns on investment, whereas programs in Connecticut offer smaller, though mostly non-negative expected returns. We also consider the potential cost effectiveness of CTE programs offered in other contexts to address questions of generalizability.
Schools often track students to classes based on ability. Proponents of tracking argue it is a low-cost tool to improve learning since instruction is more effective when students are more homogeneous, while opponents argue it exacerbates initial differences in opportunities without strong evidence of efficacy. In fact, little is known about the pervasiveness or determinants of ability tracking in the US. To fill this gap, we use detailed administrative data from Texas to estimate the extent of tracking within schools for grades 4 through 8 over the years 2011-2019. We find substantial tracking; tracking within schools overwhelms any sorting by ability that takes place across schools. The most important determinant of tracking is heterogeneity in student ability, and schools operationalize tracking through the classification of students into categories such as gifted and disabled and curricular differentiation. When we examine how tracking changes in response to educational policies, we see that schools decrease tracking in response to accountability pressures. Finally, when we explore how exposure to tracking correlates with student mobility in the achievement distribution, we find positive effects on high-achieving students with no negative effects on low-achieving students, suggesting that tracking may increase inequality by raising the ceiling.
Using daily lunch transaction data from NYC public schools, I determine which students frequently stand next to one another in the lunch line. I use this `revealed' friendship network to estimate academic peer effects in elementary school classrooms, improving on previous work by defining not only where social connections exist, but the relative strength of these connections. Equally weighting all peers in a reference group assumes that all peers are equally important and may bias estimates by underweighting important peers and overweighting unimportant peers. I find that students who eat together are important influencers of one another's academic performance, with stronger effects in math than in reading. Further exploration of the mechanisms supports my claim that these are friendship networks. I also compare the influence of friends from different periods in the school year and find that connections occurring around standardized testing dates are most influential on test scores.
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.
We exploit historical natural experiments to test whether universities increase economic mobility and equality. We use "runner-up’" counties that were strongly considered to become university sites but were not selected for as-good-as-random reasons as counterfactuals for university counties. University establishment causes greater intergenerational income mobility but also increases cross-sectional income inequality. We highlight four findings to explain this seeming paradox: universities hollow out the local labor market and provide greater opportunities to achieve top incomes, both of which increase cross-sectional inequality, and increase educational attainment and connections to high-SES people, which prevent inequality from perpetuating into intergenerational immobility.
Prior research has found that financial investments in North Carolina’s pre-kindergarten (pre-K) program generated positive effects on student reading and math achievement through eighth grade (Bai et al., 2020). The current study examined the interaction between NC Pre-K funding and two key dimensions of the subsequent educational environment students experience in their school districts: average achievement and achievement growth. In relation to student reading and math achievement in eighth grade, the benefits of NC Pre-K funding were found to be additive to the benefits of school-district average achievement. The benefits of NC Pre-K funding were also found to interact with the benefits of school-district achievement growth such that the NC Pre-K effect was larger in school districts with lower rates of growth in academic achievement. These findings suggest that public investments in early childhood education may be particularly beneficial in the long term for children who subsequently experience low-growth schooling environments compared to children in high-growth environments.
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.