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Multiple outcomes of education
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.
This paper studies the causal impacts of public universities on the outcomes of their marginally admitted students. I use administrative admission records spanning all 35 public universities in Texas, which collectively enroll 10 percent of American public university students, to systematically identify and employ decentralized cutoffs in SAT/ACT scores that generate discontinuities in admission and enrollment. The typical marginally admitted student completes an additional year of education in the four-year sector, is 12 percentage points more likely to earn a bachelor's degree, and eventually earns 5-10 percent more than their marginally rejected but otherwise identical counterpart. Marginally admitted students pay no additional tuition costs thanks to offsetting grant aid; cost-benefit calculations show internal rates of return of 19-23 percent for the marginal students themselves, 10-12 percent for society (which must pay for the additional education), and 3-4 percent for the government budget. Finally, I develop a method to disentangle separate effects for students on the extensive margin of the four-year sector versus those who would fall back to another four-year school if rejected. Substantially larger extensive margin effects drive the results.
This study examines the impact of special education on academic and behavioral outcomes for students with learning disabilities (LD) by using statewide Indiana data covering kindergarten through eighth grade. The results from student fixed effects models show that special education services improve achievement in math and English Language Arts, but they also increase suspensions and absences for students with LD. These effects vary across student subgroups, including gender, race/ethnicity, eligibility for free or reduced-price lunch, and English language learner status. The findings reveal both the significant benefits and unintended consequences of special education services for students with LD, highlighting the complex dynamics and varying effects of special education.
Educational policymakers, leaders, and researchers are paying increasing attention to student attendance and chronic absenteeism, especially in the wake of the COVID-19 pandemic. Though researchers have documented the consequences and causes of absenteeism, there is limited empirical evidence about what schools and districts are actually doing to improve attendance. This study presents evidence about the types of attendance practices that forty-seven high-absenteeism districts in Michigan are planning and implementing. I draw on a combination of quantitative and qualitative data from principal surveys, case studies, observations, and school improvement plans. In the 2022-23 school year, principals reported using communication practices, incentives, and to an extent providing resources to address barriers to attendance. In improvement plans, districts planned to create new organizational infrastructure and hire new personnel, with less emphasis on specific practices. These findings highlight a reliance on communication-based strategies and limited existing organizational infrastructure for addressing attendance. Though these districts have planned to develop new attendance systems and practices, it is unclear whether they will substantially reduce absenteeism, since they do not substantially address social and economic inequalities at the root of high absenteeism rates. I conclude with recommendations for monitoring new attendance practices, addressing root causes, and avoiding counterproductive practices.
Short-term certificate (STC) programs at community colleges represent a longstanding policy priority to align accelerated postsecondary credentials with job opportunities in local labor markets. Despite large investments in developing STCs, little evidence exists about where and when STCs are opened, and whether community colleges open new programs of study in coordination with labor market trends. Using public workforce and postsecondary data, I examine health and manufacturing STC program openings to understand the conditions in which STCs are launched and whether the timing of program openings correspond with labor market activity in related industries. I find that STCs are spatially aligned across labor markets within a state, but not necessarily temporally aligned with county-specific trends. One additional STC per college is associated with labor markets that had 2-3% more employment and 4-6% greater share of employment in related industry.
The landscape of developmental education has experienced significant shifts over the last decade nationwide, as more than 20 states and higher education systems have transitioned from the traditional prerequisite model to corequisite remediation. Drawing on administrative data from Tennessee community colleges from 2010 to 2020, this study examined the heterogeneous effects of corequisite reform for remediation-eligible students with varying levels of academic preparation. Using difference-in-differences and event study designs, we found that corequisite remediation significantly improved gateway and subsequent college-level course completion for students in all placement test score groups below the college-level threshold. For math, the positive effects on college-level course completion were stronger for higher-scoring remedial students than for those with lower placement test scores, whereas the pattern was reversed for English. However, since the corequisite reform, students requiring remediation were more likely to drop out of the public college system, and those with the lowest scores were less likely to earn short-term certificates.
Community colleges are a critical component of the U.S. higher education system, providing access to students from traditionally underserved communities. However, enduring challenges to completion stemming from educational, economic, and social inequities persist. Building on prior work that examines barriers to student success and their relationship to student outcomes, this descriptive study examines the relationship between students’ time utilization, engagement with campus resources, financial and mental well-being, with academic persistence. Specifically, we examine the relative importance of these barriers on students’ educational attainment. We find that the incidence of adverse mental health is comparable to 4-year undergraduate populations. The rates of food and housing insecurity are comparable to previous studies, though strikingly high. While a plurality of respondents engage with multiple campus resources, this engagement is unrelated to their propensity to remain enrolled or complete additional credits. Most notably, mental health conditions were negatively related to persistence and credit accumulation, while the relationship between academic outcomes and measures of food and housing insecurity was smaller and not significant. Our findings suggest that facilitating access to mental health supports is a prominent avenue for supporting student engagement and success.
Children's approaches to learning (AtL) are widely recognized as a critical predictor of educational outcomes, especially in early childhood. Nevertheless, there remains a dearth of understanding regarding the dimensionality of AtL, the reciprocal dynamics between AtL and learning outcomes, and how AtL operates in non-Western contexts. This paper aims to extend the existing AtL literature by both conceptually and empirically investigating the dimensionality of the AtL scale of the International Development and Early Learning Assessment (IDELA) – a globally used measure of early childhood development – based on data from Ghanaian children newly enrolled in formal schooling. Additionally, our research explores reciprocal relationships between AtL subconstructs and academic skills over time. Our analysis identifies two dimensions within the IDELA AtL scale: Self-Regulation (SR) and Motivation. We found that children with higher levels of SR early in schooling demonstrated better literacy and numeracy skills in later grades compared to their peers with low early SR, whereas children's motivation did not predict subsequent literacy and numeracy skills. This study enhances understanding of AtL in non-Western contexts, with implications for culturally appropriate support for children’s engagement in learning.