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Multiple outcomes of education
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Limited scholarship examines districtwide turnaround reforms beyond the first few years of implementation or efforts to replicate successes in new contexts. We study Massachusetts, home to a state takeover of the Lawrence school district that led to academic gains in early reform years, and where state leaders attempted to replicate this success in three additional communities. We use statewide student-level administrative data (2006-07 to 2018- 19) and event study methods to estimate medium-term impacts on student outcomes across four districts. We find the initial improvements were largely sustained in Lawrence. We observe evidence of successful replication in Springfield but not Holyoke or Southbridge. The two turnarounds with positive outcomes both struck a unique balance between state and local input into decision-making.
The academic and economic benefits of school spending are well-established, but focusing on these outcomes may underestimate the full social benefits of school spending. Recent increases in U.S. child mortality are driven by injuries and raise questions about what types of social investments could reduce child deaths. We use close school district tax elections and negative binomial regression models to estimate effects of a quasi-random increase in school spending on county child mortality. We find consistent evidence that increased school spending from passing a tax election reduces child mortality. Districts that narrowly passed a proposed tax increase spent an additional $243 per pupil, mostly on instruction and salaries, and had 4% lower child mortality after spending increased (6-10 years after the election). This increased spending also reduced child deaths of despair (due to drugs, alcohol, or suicide) by 5% and child deaths due to accidents or motor vehicle accidents by 7%. Estimates predicting potential mechanisms suggest that lower child mortality could partly reflect increases in the number of teachers and counselors, higher teacher salaries, and improved student engagement.
Hybrid school enrollments are trending up and many parents express a diverse range of reasons for enrolling their children in hybrid schools. Yet little is known about the pedagogical goals pursued by hybrid schools. We aim to help close this gap in the literature with a stated preferences experiment of hybrid school leaders’ perceptions of program success. Sixty-three school leaders participated in a survey experiment in which we randomly assigned attributes to hypothetical programs and asked school leaders to identify the most successful program. We find that hybrid school leaders consider a broad range of student outcomes when evaluating program success, including labor market outcomes, civic outcomes, and family life. Students’ religious observance produced the largest effect sizes, a reasonable finding considering that roughly two-thirds of the schools represented in our sample have some religious affiliation. We do not find evidence that test score outcomes and higher education matriculation contribute meaningfully to perceived success.
There is substantial variation in the returns to a college degree. One determinant is whether a worker’s employment is “matched” with their education. With a novel education-industry crosswalk and panel data on 295,000 graduates, we provide the first estimates of an education-industry match premium leveraging within-person variation in earnings. We document which majors have the most and least matching, how earnings premia vary across fields and gender, and how premia evolve over time. With robust estimators, we show that workers in industries “matched” with their degree experience an average earnings premium of 7-11%, with variation by degree level and major.
Students in the foster care system tend to have lower educational outcomes than their peers, including more frequent disciplinary events. However, few studies have explored how transitions into and out of foster care placements are associated with educational outcomes. Using longitudinal data from four California school districts, this study investigated the dynamics of entering versus exiting foster care to predict school discipline and how this relationship ultimately influences absenteeism. Our findings suggest that students in foster care are more likely than their peers to face disciplinary action, especially exclusionary discipline, particularly when entering foster care. We also find suggestive evidence that disciplinary actions upon entry increase student absenteeism for students in foster care.
A later school start time policy has been recommended as a solution to adolescents’ sleep deprivation. We estimated the impacts of later school start times on adolescents’ sleep and substance use by leveraging a quasi-experiment in which school start time was delayed in some regions in South Korea. A later school start time policy was implemented in 2014 and 2015, which delayed school start times approximately 30-90 minutes. We applied difference-in-differences and event-study designs to longitudinal data on a nationally-representative cohort of adolescents from 2010 to 2015, which annually tracked sleep and substance use of 1,133 adolescents from grade 7 through grade 12. The adoption of a later school start time policy was initially associated with a 19-minute increase in sleep duration (95% CI, 5.52 to 32.04), driven by a delayed wake time and consistent bedtime. The policy was also associated with statistically significant reductions in monthly smoking and drinking frequencies. However, approximately a year after implementation, the observed increase in sleep duration shrank to 7-minute (95% CI, -12.60 to 25.86) and became statistically nonsignificant. Similarly, the observed reduction in smoking and drinking was attenuated a year after. Our findings suggest that policies that increase sleep in adolescents may have positive effects on health behaviors, but additional efforts may be required to sustain positive impacts over time. Physicians and education and health policymakers should consider the long-term effects of later school start times on adolescent health and well-being.
Do residential neighbors affect each others' schooling choices? We exploit oversubscription lotteries in Chile's centralized school admission system to identify the effect of close neighbors on application and enrollment decisions. A student is 5-7% more likely to rank a high school as their first preference and to attend that school if their closest neighbor attended it the prior year. These effects are stronger among boys and applicants with lower parents' education and prior academic achievement, measured by previous scores in national standardized tests. Lower-achieving applicants are more likely to follow neighbors when their closest neighbor's test scores are higher. A neighbor enrolling in a school with one s.d. higher school effectiveness, peer composition, or school climate induces increases of 0.02-0.04 s.d. in the applicant's attended school. Our findings suggest that targeted policies aimed at increasing information to disadvantaged families have the potential to alleviate these frictions and generate significant multiplier effects.
In-person tutoring has been shown to improve academic achievement. Though less well-researched, virtual tutoring has also shown a positive effect on achievement but has only been studied in grade five or above. We present findings from the first randomized controlled trial of virtual tutoring for young children (grades K-2). Students were assigned to 1:1 tutoring, 2:1 tutoring, or a control group. Assignment to any virtual tutoring increased early literacy skills by 0.05-0.08 SD with the largest effects for 1:1 tutoring (0.07-0.12 SD). Students initially scoring well below benchmark and first graders experienced the largest gains from 1:1 tutoring (0.15 and 0.20 SD, respectively). Effects are smaller than typically seen from in-person early literacy tutoring programs but still positive and statistically significant, suggesting promise particularly in communities with in-person staffing challenges.
Assessing instruction quality is a fundamental component of any improvement efforts in the education system. However, traditional manual assessments are expensive, subjective, and heavily dependent on observers’ expertise and idiosyncratic factors, preventing teachers from getting timely and frequent feedback. Different from prior research that focuses on low-inference instructional practices, this paper presents the first study that leverages Natural Language Processing (NLP) techniques to assess multiple high-inference instructional practices in two distinct educational settings: in-person K-12 classrooms and simulated performance tasks for pre-service teachers. This is also the first study that applies NLP to measure a teaching practice that has been demonstrated to be particularly effective for students with special needs. We confront two challenges inherent in NLP-based instructional analysis, including noisy and long input data and highly skewed distributions of human ratings. Our results suggest that pretrained Language Models (PLMs) demonstrate performances comparable to the agreement level of human raters for variables that are more discrete and require lower inference, but their efficacy diminishes with more complex teaching practices. Interestingly, using only teachers’ utterances as input yields strong results for student-centered variables, alleviating common concerns over the difficulty of collecting and transcribing high-quality student speech data in in-person teaching settings. Our findings highlight both the potential and the limitations of current NLP techniques in the education domain, opening avenues for further exploration.