Banca de DEFESA: GUILHERME VIANA FERREIRA

Uma banca de DEFESA de DOUTORADO foi cadastrada pelo programa.
STUDENT : GUILHERME VIANA FERREIRA
DATE: 26/05/2025
TIME: 15:30
LOCAL: Remoto
TITLE:

Dynamics of permanent dropout from higher education: taxonomic proposal, its determinants and the importance of interoperability of educational data

KEY WORDS:

Higher Education. Student dropout. Multilevel logistic regression. Database integration. Interoperability of educational data.

PAGES: 26
BIG AREA: Ciências Sociais Aplicadas
AREA: Economia
SUMMARY:

enrollments between 2016 and 2023, contrasts with the modest 17.4% growth in graduates in the same period, revealing a structural imbalance aggravated by high student dropout rates. OECD data on adults with higher education indicate that the country remains with lower rates than its Latin American neighbors, such as Peru, Chile, and Colombia, in addition to also having one of the highest salary premiums for undergraduate studies. In this context, permanent dropout from the higher education system emerges as a critical phenomenon, compromising public and private investments while reflecting structural inequalities in access to educational opportunities. The thesis begins by establishing a multidimensional taxonomic framework for dropout in higher education, integrating granularity (course, institution, and system) and temporality (immediate, temporary, and permanent) with qualifiers (area of knowledge, shift, modality), overcoming fragmented approaches and offering a robust analytical tool for accurate diagnoses. Next, it is evident that permanent dropout from the system affects 45% of students who have already completed their studies in the 2005 to 2022 cohorts, with high rates associated with unfavorable socioeconomic conditions (family income, parental occupation), institutional characteristics (night courses, distance learning, private for-profit institutions) and personal factors (male gender, self-declared black/brown/indigenous, disability), in addition to revealing regional and institutional heterogeneity, with higher values in private institutions. Using stratified sampling in two stages, of the identified microdata from INEP, and multilevel logistic regression, the study demonstrated that parental occupation in groups of greater complexity reduces the chances of dropout by 14.5%, while high family income reduces the propensity by 13.4%, corroborating the structural weight of inequalities, represented by the socioeconomic and personal dimensions. The thesis concludes by discussing the interoperability of educational databases, and reinforces that the fragmentation of systems such as the Higher Education Census, Basic Education Census and Enem limits the accurate longitudinal monitoring of dropout, highlighting the need for semantic integration and data governance to support effective public policies.

COMMITTEE MEMBERS:
Presidente - 1963493 - ANDREA FELIPPE CABELLO
Externa ao Programa - 404700 - ANA MARIA NOGALES VASCONCELOS - UnBExterno à Instituição - CARLOS EDUARDO MORENO SAMPAIO
Externo à Instituição - ADRIANO SOUZA SENKEVICS - IPEA