Modelo institucional para o desenvolvimento do acompanhamento de egressos: uma proposta fundamentada na análise da maturidade institucional, desenvolvida a partir da experiência da ESTES/UFU

Abstract

Graduate tracking is a relevant activity for institutional development, but it may present different levels of organization and consolidation across institutions. This research aimed to develop an Institutional Model for Graduate Tracking (MIAE), grounded in the analysis of institutional maturity and developed from the experience of ESTES/UFU. This is an applied research study with a predominantly qualitative approach, oriented toward the development and application of an institutional model. To operationalize it, FADI-IA was developed as a hybrid methodological framework for the collection, organization, processing, and analysis of public institutional evidence. The model was applied to an analytical universe of 58 institutions, after excluding six units that did not meet the established criteria. The analysis was structured around 11 factual criteria, operationalized into nine institutional-capacity variables that compose the Global Capacity Index (IGC), while maturity was classified through the Institutional Maturity Requirements (RMI), defined by deterministic precedence rules. The application produced Scenario 1, resulting from the automated execution of FADI-IA, and Scenario 2, following verification and supplementation of evidence by the researcher in selected cases. The results revealed heterogeneity in institutional capacities, highlighting the weakness of “Update,” with a mean of 0.19 in Scenario 1 and 0.43 in Scenario 2, and the highest relative performance of “Engagement,” with means of 0.57 and 1.16, respectively. The comparison demonstrated the influence of the qualification of the factual evidence base on the maturity diagnosis, with a reduction in RMI-1 from 37 to 19 institutions and an increase in RMI-5 from 1 to 6. The results demonstrate the feasibility of operationalizing the MIAE through FADI-IA and the complementarity between automation and human intervention, also highlighting the importance of the availability and locatability of institutional evidence for automated processing. It is concluded that the MIAE provides a structure for diagnosing capacities, recognizing different levels of maturity, and supporting the institutional development of graduate tracking.