Migration Dynamics and Academic Trajectory in Higher Education: The Case of Students at the Universidade da Integracao Internacional da Lusofonia Afro-Brasileira
Inter-program migration; Academic trajectory; Higher Education; UNILAB
The analysis of migratory dynamics between academic courses in higher education is crucial for understanding the factors influencing the trajectories of university students and for shaping policies aimed at academic retention and success. These transitions reflect individual choices influenced by interests, social conditions, and institutional structures, carrying significant implications for both students and universities. By examining how students distribute and redistribute themselves across courses, it becomes possible to identify patterns of internal migration, evaluate the attractiveness of various fields of study, and propose strategies to support course completion. This thesis conducts a case study at the Universidade da Integracao Internacional da Lusofonia Afro-Brasileira (UNILAB) to explore inter-course migratory dynamics and academic trajectories. An origin-destination matrix, analogous to those used in migration studies, was constructed to investigate inter-course migration dynamics. Based on the derived indicators, two courses with the highest academic immigration rates and two with the lowest were selected for detailed analysis. The academic trajectories were analyzed using the Multi-State Method, applied to the four selected courses, generating multi-state survival tables to estimate transition probabilities and academic life expectancy. The findings reveal that Nursing and Biological Sciences attract the highest number of students, while Humanities and Physics show lower academic immigration rates. Nursing and Biological Sciences also exhibit the highest transition probabilities, whereas Humanities and Physics have lower transition probabilities. Additionally, academic life expectancy in the analyzed courses exceeds the regular completion time, suggesting factors that prolong students' stay—a finding critical for guiding future research. These results provide valuable insights into the factors driving both student attraction and lower retention rates, contributing to the development of more effective academic support strategies.