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We estimate the education and earnings returns to enrolling in technical two-year degree programs at community colleges in Missouri. A unique feature of the Missouri context is the presence of a highly regarded, nationally ranked technical college: State Technical College of Missouri (State Tech). We find that enrolling in a technical program in Missouri increases the likelihood of associate degree attainment and post-enrollment earnings, but that the positive effects statewide are driven largely by students who attend State Tech. These findings demonstrate the potential for a high-performing community college to change students’ education and labor market trajectories. At the same time, they exemplify the potential for substantial institutional heterogeneity in the returns to postsecondary education.
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.
We examine the state of the U.S. K-12 teaching profession over the last half century by compiling nationally representative time-series data on four interrelated constructs: occupational prestige, interest among students, the number of individuals preparing for entry, and on-the-job satisfaction. We find a consistent and dynamic pattern across every measure: a rapid decline in the 1970s, a swift rise in the 1980s extending into the mid 1990s, relative stability, and then a sustained decline beginning around 2010. The current state of the teaching profession is at or near its lowest levels in 50 years. We identify and explore a range of hypotheses that might explain these historical patterns including economic and sociopolitical factors, education policies, and school environments.
This study investigates the role of college major choices in labor market outcomes, with a focus on racial minorities and immigrants. Drawing upon research on school-to-work linkages, we examine two measures, linkage, the connection between college majors and specific occupations in the labor market, and match, the alignment of workers’ occupations with their college majors. Analyzing data from the American Community Survey, 2013-2017, we show that linkage positively predicts earnings, particularly for workers in matched occupations, and negatively predicts unemployment. Notably, Black, Hispanic, and foreign-born workers in matched occupations benefit more from linkage strength than their White and U.S.-born counterparts. This advantage is more pronounced in states that are popular destinations for immigrants. Our findings suggest that earnings and unemployment disparities experienced among racial minorities and immigrants may diminish if they pursue majors closely tied to jobs in the labor market and secure jobs related to their college majors.
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.
We study the extent and consequences of biases against immigrants exhibited by high school teachers in Finland. Compared to native students, immigrant students receive 0.06 standard deviation units lower scores from teachers than from blind graders. This effect is almost entirely driven by grading penalties incurred by high-performing immigrant students and is largest in subjects where teachers have more discretion in grading. While teacher-assigned grades on the matriculation exam are not used for tertiary enrollment decisions, we show that immigrant students who attend schools with biased teachers are less likely to continue to higher education.
This paper describes a 12-week cluster randomized controlled trial that examined the efficacy of BookNook, a virtual tutoring platform focused on reading. Cohorts of first- through fourth-grade students attending six Rocketship public charter schools in Northern California were randomly assigned within grades to receive BookNook. Intent-to-Treat models indicate that students in cohorts assigned to BookNook outperformed their control-group peers by roughly 0.05 SDs. Given the substantial variability in usage rates among students enrolled in BookNook cohorts, we also leveraged Treatment-on-the-Treated approaches. These models suggest that students who completed 10 or more BookNook sessions experienced a reading advantage of 0.08 SDs, while those who completed 20 or more sessions—the recommended dosage—experienced a 0.26 SD developmental advantage.
This study found that the MATC Promise increased college attainment by encouraging Milwaukee high school students to access state and federal aid, and to consider matriculating to their local two-year college. The MATC Promise exemplifies the last-dollar model of college aid. If seniors at Milwaukee area public high schools complete academic milestones, apply for financial aid, qualify based on low family income, and matriculate to Milwaukee Area Technical College (MATC), then the Promise covers any remaining tuition charges. The message promoting free college was the program’s main element, since the funding support for eligible students came primarily from existing state and federal aid. We studied outcomes for the first four graduating classes after the Promise was launched, compared to the trend in Milwaukee for the previous six graduating classes. The rate of matriculation to MATC increased from 10 percent to 15 percent. There was no such increase in matriculation to other technical college districts around the state, suggesting that the increase was caused by the Promise. The increase in enrollment was larger among lower-income students and those in the urban Milwaukee Public Schools. Those students were more likely to apply for financial aid earlier, regardless of whether they ultimately qualified for the Promise, and their rate of matriculation to any college increased from 45 percent to 49 percent. There was no indication that attracting additional students to college led to lower graduation rates, though we were limited to examining credentials earned in two years or less.
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.
Vocational Education and Training (VET) programs are prevalent in a European context, but often struggle with drop-out rates that exceed those of general upper-secondary education. Using Danish administrative data, we study the effects of reform-induced reductions in shares of VET students who did not pass their lower secondary final exams on passing GPA VET students. We find that passing students have a higher probability of remaining enrolled in VET after the first year of studies when entering a VET school with a higher share of below-passing peers. Studying outside options, we find that students become less likely to drop out of education entirely. The results are consistent with models of peer effects in which particularly unmotivated students become points of comparison for their peers, increasing their motivation and likelihood of remaining enrolled.