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What Makes a Program Good? Evidence from Short-Cycle Higher Education Programs in Five Developing Countries. EdWorkingPaper No. 23-710

Title: What Makes a Program Good? Evidence from Short-Cycle Higher Education Programs in Five Developing Countries. EdWorkingPaper No. 23-710
Language: English
Authors: Lelys Dinarte-Diaz; Maria Marta Ferreyra; Sergio Urzua; Marina Bassi; Annenberg Institute for School Reform at Brown University
Source: Annenberg Institute for School Reform at Brown University. 2023.
Availability: Annenberg Institute for School Reform at Brown University. Brown University Box 1985, Providence, RI 02912. Tel: 401-863-7990; Fax: 401-863-1290; e-mail: annenberg@brown.edu; Web site: https://annenberg.brown.edu/
Peer Reviewed: N
Page Count: 95
Publication Date: 2023
Document Type: Reports - Research
Education Level: Higher Education; Postsecondary Education; Two Year Colleges
Descriptors: Foreign Countries; Higher Education; Educational Quality; College Programs; Program Evaluation; Program Effectiveness; Predictor Variables; Outcomes of Education; Associate Degrees
Geographic Terms: Colombia; Dominican Republic; Ecuador; Peru; Brazil
Abstract: 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.
Abstractor: As Provided
Entry Date: 2025
Accession Number: ED672197
Database: ERIC