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Multiple outcomes of education
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The Long-Run Impacts of Universal Pre-K with Equilibrium Considerations
Since 1995, publicly funded pre-K with universal eligibility has proliferated across the U.S. Universal pre-K (UPK) operates at great scale and serves children with a wide range of alternative childcare options. Because these programs are relatively young, very little is known about their long-run impacts on children. In this paper, I use a difference-in-differences (DiD) design to estimate the long-run impacts of Georgia UPK, the first statewide program. Children exposed to UPK were 1.7% more likely to graduate high school, 11.1% less likely to receive SNAP benefits as adults, and girls were 10.6% less likely to have children as teenagers. To help interpret those results, I develop a simple conceptual framework that considers how public pre-K expansions can affect the entire childcare market. For instance, greater competition could force private centers to adjust prices and quality, or to close entirely—creating spillover impacts on children not enrolled in public pre-K. Empirically, I find evidence consistent with large spillovers in Georgia, suggesting that a focus on UPK enrollees would miss a key part of the program’s overall impact. Further, I show that conventional DiD estimates of treatment effects on the treated may be substantially biased in the presence of spillovers—in the Georgia context and in others.
The Role of Comprehensive Student Support Interventions during School Turnaround
The persistence of underperformance in schools within large urban districts remains a significant challenge in the U.S. K-12 education system. Education policymakers have enacted legislation aiming at improving these schools through ``turnaround'' initiatives. However, students attending underperforming schools face multifaceted challenges that extend beyond the classroom. Therefore, restructuring the underperforming schools without addressing critical out-of-school factors appears to be insufficient to achieve the goal of these legislative efforts. In this study, we focus on a large urban school district in Massachusetts with many underperforming schools undergoing school turnaround. During the turnaround process, some schools implemented a comprehensive student support intervention while others did not. The variation in supplementing school turnaround with comprehensive student support intervention and the timing of the implementation of the intervention allows us to explore whether comprehensive student support aiming at addressing out-of-school factors enhances student performance during the school turnaround process. Employing difference-in-differences and event studies research designs, our findings reveal that schools and grades implementing the comprehensive student support intervention during their turnaround efforts demonstrate improvement in math and English language arts compared to those not implementing the intervention. These results provide valuable insights for policymakers, emphasizing the essential role of comprehensive student support in enhancing the success of school turnaround.
Are Community College Students Increasingly Choosing High-Paying Fields of Study? Evidence from Massachusetts
The labor-market payoff to workers with associate degrees in healthcare and STEM occupations is very high in Massachusetts. We examine whether this induced a growing proportion of students in MA community colleges (MACCs) to earn an associate degree (AD) in one of these fields. We do this by using multinomial logit analysis to compare trends across 12 cohorts of MACC entrants in the proportion of students who earned an AD in a healthcare or STEM program within six years of entry.
We find a substantial increase across cohorts in the proportion of students who earned an AD in a STEM program, but not in the proportion who earned an AD in a healthcare program. We found differences in degree attainment by student gender, race/ethnicity, family income, and 10th-grade mathematics score. Interviews with MACC program leaders revealed that supply constraints hinder expansion of many healthcare AD programs, but not STEM programs.
The Returns to Education over time and the Effect of COVID-19
This paper examines the effects of the COVID-19 pandemic on the returns to education in the United States. Using data from the Current Population Survey 2011-2022, the analysis reveals that, after a period of decline, returns to education increased significantly because of COVID, particularly for men and those with university education. The returns to university for men increased by 1 percentage points. The results underscore the importance of continued investment in education to mitigate the adverse effects of future crises.
Tutor CoPilot: A Human-AI Approach for Scaling Real-Time Expertise
Generative AI, particularly Language Models (LMs), has the potential to transform real-world domains with societal impact, particularly where access to experts is limited. For example, in education, training novice educators with expert guidance is important for effectiveness but expensive, creating significant barriers to improving education quality at scale. This challenge disproportionately hurts students from under-served communities, who stand to gain the most from high-quality education and are most likely to be taught by inexperienced educators. We introduce Tutor CoPilot, a novel Human-AI approach that leverages a model of expert thinking to provide expert-like guidance to tutors as they tutor. This study presents the first randomized controlled trial of a Human-AI system in live tutoring, involving 900 tutors and 1,800 K-12 students from historically under-served communities. Following a preregistered analysis plan, we find that students working on mathematics with tutors randomly assigned to have access to Tutor CoPilot are 4 percentage points (p.p.) more likely to master topics (p<0.01). Notably, students of lower-rated tutors experienced the greatest benefit, improving mastery by 9 p.p. relative to the control group. We find that Tutor CoPilot costs only $20 per-tutor annually, based on the tutors’ usage during the study. We analyze 550,000+ messages using classifiers to identify pedagogical strategies, and find that tutors with access to Tutor CoPilot are more likely to use strategies that foster student understanding (e.g., asking guiding questions) and less likely to give away the answer to the student, aligning with high-quality teaching practices. Tutor interviews qualitatively highlight how Tutor CoPilot’s guidance helps them to respond to student needs, though tutors flag common issues in Tutor CoPilot, such as generating suggestions that are not grade-level appropriate. Altogether, our study of Tutor CoPilot demonstrates how Human-AI systems can scale expertise in real-world domains, bridge gaps in skills and create a future where high-quality education is accessible to all students.
Overpoliced? A Descriptive Portrait of School-Based Targeted Police Interventions in New York City
This study provides a descriptive analysis of police intervention as a response to student behavior in New York City public schools. We find that between the 2016/17 and 2021/22 academic years, arrests and juvenile referrals decreased while non-detainment-based and psychiatric police interventions increased. However, Black students, especially those enrolled in schools located in predominantly White police precincts experiencing a shrinking White student population, experienced disproportionate rates of arrests, juvenile referrals, and police-involved psychiatric interventions. Schools serving more Black students experienced higher rates of interventions relative to schools with fewer Black students, but these higher rates of intervention are not explained by differences in observable student behavior and characteristics. Instead, differences in teacher characteristics and resources contribute to the excess use of police interventions in predominantly Black schools.
Accelerating Opportunity: The Effects of Instructionally Supported Detracking
The pivotal role of Algebra in the educational trajectories of U.S. students continues to motivate controversial, high-profile policies focused on when students access the course, their classroom peers, and how the course is taught. This random-assignment partnership study examines an innovative district-level reform—the Algebra I Initiative—that placed 9th-grade students with prior math scores well below grade level into Algebra I classes coupled with teacher training instead of a remedial pre-Algebra class. We find that this reform significantly increased grade-11 math achievement (ES = 0.2 SD) without lowering the achievement of classroom peers eligible for conventional Algebra I classes. This initiative also increased attendance, district retention, and overall math credits. These results suggest that higher expectations for the lowest-performing students coupled with aligned teacher supports is a promising model for realizing students’ mathematical potential.
Falling Behind as Peers Age Up: The Effects of Peer Age on Student Cognitive and Non-Cognitive Outcomes
Understanding the factors that influence student outcomes is crucial for both parents and schools when designing effective educational strategies. This paper explores the impact of peer age on both cognitive and non-cognitive outcomes using a randomized sample of middle school students. By analyzing how exogenous variations in peer age affect students' academic performance, self-expectations and confidence, health perceptions, behavioral traits, and social development, we highlight the important role that peer age plays in educational contexts. Our findings reveal that an increase in the average age of classmates results in negative effects on both cognitive and non-cognitive outcomes of a student. We also identify significant heterogeneous effects based on student relative age and gender. We delve into potential mechanisms behind these effects and study inputs from the perspective of student themselves, parents, teachers, and the school within the framework of the education production function. The results suggest that students' persistence in their studies, the quality of friendships, and the school environment they are exposed to are the primary drivers of our main findings. These findings underscore the importance of addressing age disparities within classrooms to enhance students' cognitive and non-cognitive development.
School and Crime
Criminal activity is seasonal, peaking in the summer and declining through the winter. We provide the first evidence that arrests of children and reported crimes involving children follow a different pattern: peaking during the school year and declining in the summer. We use a regression discontinuity design surrounding school start dates and an excess crime calculation to show that the school environment increases reported crimes involving children by roughly 50% annually. School exacerbates preexisting inequality in criminal interactions, increasing the Black-white and male-female gaps in reported juvenile crime and arrest rates by more than 40%.