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Post-secondary education
Short-cycle higher education programs (SCPs) can play a central role in skill development and higher education expansion, yet their quality varies greatly within and among countries. In this paper we explore the relationship between programs’ practices and inputs (quality determinants) and student academic and labor market outcomes. We design and conduct a novel survey to collect program-level information on quality determinants and average outcomes for Brazil, Colombia, Dominican Republic, Ecuador, and Peru. Categories of quality determinants include training and curriculum, infrastructure, faculty, link with productive sector, costs and funding, and practices on student admission and institutional governance. We also collect administrative, student-level data on higher education and formal employment for SCP students in Brazil and Ecuador and match it to survey data. Using machine learning methods, we select the quality determinants that predict outcomes at the program and student levels. Estimates indicate that some quality determinants may favor academic and labor market outcomes while others may hinder them. Two practices predict improvements in all labor market outcomes in Brazil and Ecuador—teaching numerical competencies and providing job market information—and one practice—teaching numerical competencies—additionally predicts improvements in labor market outcomes for all survey countries. Since quality determinants account for 20-40 percent of the explained variation in student-level outcomes, quality determinants might have a role shrinking program quality gaps. Findings have implications for the design and replication of high-quality SCPs, their regulation, and the development of information systems.
This paper estimates a dynamic model of college enrollment, progression, and graduation. A central feature of the model is student effort, which has a direct effect on class completion and an indirect effect mitigating risks on class completion and college persistence. The estimated model matches rich administrative data for a representative cohort of college students in Colombia. Estimates indicate that effort has a much greater impact than ability on class completion. Failing to consider effort as an input to class completion leads to overestimating ability’s role by a factor of two or three. It also promotes tuition discounts based on a pre-determined student trait—ability—rather than effort, which can be affected through policy, thus limiting higher education’s potential for social mobility.
Despite the growing popularity of free college proposals, countries with higher college subsidies tend to have higher enrollment rates but not higher graduation rates. To capture this evidence and evaluate potential free college policies, we rely on a dynamic model of college enrollment, performance, and graduation estimated using rich student-level data from Colombia. In the model, student effort affects class completion and mitigates the risk of performing poorly or dropping out. Among our simulated policies, universal free college expands enrollment the most but has virtually no effect on graduation rates, helping explain the cross-country evidence. Performance-based free college triggers a more modest enrollment expansion but delivers a higher graduation rate at a lower fiscal cost. While both programs lower student uncertainty relative to the baseline, performance-based free college does it to a lower extent, which in turn promotes better student outcomes. Overall, free college programs expand enrollment but have limited impacts on graduation and attainment due to their limited impact on student effort.
We used Critical Discourse Analysis to examine the racial discourse within recent attempts to reauthorize the Higher Education Act. Specifically, we interrogated congressional markup hearings to understand how members frame student debt and the racialized dynamics embedded within. Our findings highlight three types of discourse: “All Students” Matter, Paternalistic, Race-Evasive, and Explicit Racial Discourse. We offer recommendations for research and policymaking.
Prediction algorithms are used across public policy domains to aid in the identification of at-risk individuals and guide service provision or resource allocation. While growing research has investigated concerns of algorithmic bias, much less research has compared algorithmically-driven targeting to the counterfactual: human prediction. We compare algorithmic and human predictions in the context of a national college advising program, focusing in particular on predicting high-achieving, lower-income students’ college enrollment quality. College advisors slightly outperform a prediction algorithm; however, greater advisor accuracy is concentrated among students with whom advisors had more interactions. The algorithm achieved similar accuracy among students lower in the distribution of interactions, despite advisors having substantially more information. We find no evidence that the advisors or algorithm exhibit bias against vulnerable populations. Our results suggest that, especially at scale, algorithms have the potential to provide efficient, accurate, and unbiased predictions to target scarce social services and resources.
Many policies in higher education are intended to improve college access and degree completion, yet often those policies fall short of their aims by making it difficult for prospective or current college students to access benefits for which they are eligible. Barriers that inhibit access to policy benefits, such as cumbersome paperwork, can weigh more heavily on members of marginalized communities, including racially minoritized students. Such administrative burdens can thus reinforce patterns of inequity. In this paper, we present a conceptual framework for examining administrative burdens embedded in higher education policies that can negatively affect prospective and current college students, especially those who are racially minoritized. With the use of our proposed framework, researchers can improve the understanding of ethnoracial disparities in higher education, inform policymakers’ design of racially equitable policies for higher education, and enable practitioners to implement those policies to promote racial equity.
Colleges across the United States are now placing most or all students directly into college-level courses and providing supplementary, aligned academic support alongside the courses, also known as “corequisite remediation.” Developmental education reforms like corequisite remediation could advance racial and ethnic equity in postsecondary education by facilitating early academic progression. However, there is limited evidence available on differential impacts of corequisite models by race and ethnicity. To better understand the potential for differential impacts of English corequisites for Latinx students, this study leverages data from a randomized control trial across five large urban community colleges across Texas. We also utilize student survey data to develop a deeper understanding of how corequisites shape the experiences of Latinx students in their college-level English courses. Latinx students in our study colleges saw larger benefits from taking corequisite English than non-Latinx students in terms of gateway course completion. The survey findings suggest that corequisites provided an environment where Latinx students felt less academically overwhelmed and less bored relative to patterns observed for traditional DE course enrollees. However, Latinx students in corequisites also reported being less likely to participate in class discussions and ask questions relative to their non-Latinx peers.
This paper provides one of the first natural experimental evidence on the consequences of a transition from college-major (early specialization) to college-then-major (late specialization) choice mechanism. Specifically, we study a recent reform in China that allows college applicants to apply to a meta-major consisting of different majors and to declare a specialization late in college instead of applying to a specific major. Using administrative data over 18 years on the universe of college applicants in a Chinese province, we examine the impacts of the staggered adoption of the reform across institutions on student composition changes. We find substantial heterogeneous effects across institutions and majors despite the aggregate null effects. This paper provides important policy implications regarding college admissions mechanism designs.
One of the most important mechanism design policies in college admissions is to let students choose a college major sequentially (college-then-major choice) or jointly (college-major choice). In the context of the Chinese meta-major reforms that transition from college-major choice to college-then-major choice, we provide the first experimental evidence on the information frictions and heterogeneous preferences that students have in their response to the meta-major option. In a randomized experiment with a nationwide sample of 11,424 high school graduates, we find that providing information on the benefits of a meta-major significantly increased students’ willingness to choose the meta major; however, information about specific majors and assignment mechanisms did not affect student major choice preferences. We also find that information provision mostly affected the preferences of students who were from disadvantaged backgrounds, lacked accurate information, did not have clear major preferences, or were risk loving.
While the COVID-19 pandemic necessitated the short-term use of online courses, colleges’ experiences with COVID-era online course delivery may also affect the way that they offer and approach online courses going forward. We draw on interviews with 35 distance education leaders from the California Community Colleges system to provide insights into how the use of online education may change in the system going forward. Leaders predicted that post-pandemic, colleges would increase their online course offerings, and that many instructional innovations to online courses from the pandemic—such as the use of synchronous courses—would persist. They hoped that a more prominent position for online education within the system would be matched by more resources to provide supports for online learning.