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Short-cycle higher education programs (SCPs), lasting two or three years, capture about a quarter of higher education enrollment in the world and can play a key role enhancing workforce skills. In this paper, we estimate the program-level contribution of SCPs to student academic and labor market outcomes, and study how and why these contributions vary across programs. We exploit unique administrative data from Colombia on the universe of students, institutions, and programs to control for a rich set of student, peer, and local choice set characteristics. We find that program-level contributions account for about 60-70 percent of the variation in student-level graduation and labor market outcomes. Our estimates show that programs vary greatly in their contributions, across and especially within fields of study. Moreover, the estimated contributions are strongly correlated with program outcomes but not with other commonly used quality measures. Programs contribute more to formal employment and wages when they are longer, have been provided for a longer time, are taught by more specialized institutions, and are offered in larger cities.
Short-cycle higher education programs (SCPs) form skilled human capital in two or three years and could be key to upskilling and reskilling the workforce, provided their supply responds fast and nimbly to local labor market needs. We study determinants of SCP entry and exit in Colombia for markets defined by geographic location and field of study. We show greater dynamism in the market for SCPs than bachelor’s program, with greater turnover or “churn” of programs. Exploiting data on local economic activity and employment by field of study, we find that higher education institutions open new SCPs in response to local labor market demand as well as competition and costs. SCPs are more responsive to local labor market demand than bachelor’s programs; among SCP providers, private and non-university institutions are the most responsive. While private SCP entry is deterred by the presence of competitors and responds to cost considerations, these responses are weaker among public SCPs. Further, institutions often open and close programs simultaneously within a field, perhaps reflecting capacity constraints. These findings have implications for the regulation and funding of SCP providers.
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 study examines the effects of the MATC Promise, a public-private partnership that offered to pay tuition at Milwaukee Area Technical College (MATC) for local high school graduates. The MATC Promise exemplifies the most common type of college promise program, a last-dollar community college tuition promise. If students completed academic milestones, applied for state and federal aid, and qualified based on low family income, then the Promise would cover any remaining tuition charges. In practice, the message of a promise was the main treatment, since most eligible students would not have any tuition charges remaining for the program to cover after applying state and federal aid. We evaluate the effects of the Promise on increasing college enrollment and degree completion after its introduction in 2016. Milwaukee is unique within the Wisconsin, making it difficult to find relevant comparison groups in statewide data. Examining the interrupted time series within the city’s school districts shows an increase in enrollment at MATC from 10 percent of high school graduates to 15 percent after the Promise was introduced. About half of the increase came from students who would not have enrolled at all, with the rest diverting from enrolling at other colleges and universities. These effects were concentrated among lower-income students and those in the inner city. These results indicate that the Promise positively influenced college attainment by encouraging students to access state and federal aid they already qualified for. We conclude that the message of college affordability was effective at encouraging students to overcome application barriers and enroll in college.
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.