DOI: 10.3390/educsci16081312 ISSN: 2227-7102

Institutional Conditions Associated with Youth Motivation and Retention in Technical and Vocational Education and Training: A Critical Narrative Review and Conceptual Framework for Dropout Diagnosis and Prevention

Juliana Dalla Martha Rodriguez

Background: Technical and vocational education and training (TVET) in Brazil faces persistent retention challenges despite growing demand for qualified workers. Although Self-Determination Theory (SDT) offers a framework for understanding motivation, dropout research has often emphasized individual and socioeconomic factors, giving less attention to institutional conditions. Methods: This critical narrative review synthesizes theoretical, empirical, and policy-oriented literature on SDT, TVET, motivation, engagement, and dropout prevention, anchored mainly in Brazilian studies, educational statistics, and policy documents. A transparent, non-systematic search informed by SANRA organized the evidence around three institutional dimensions: curriculum, teaching practices, and student support and belonging. Complementary theories clarified the explanatory scope and limits of SDT. Results: Motivation in Brazilian TVET emerges as context-dependent and institutionally co-produced. Curricular organization, teaching practices, support structures, and equity policies may support or frustrate autonomy, competence, and relatedness and are associated with differences in engagement and vulnerability to dropout. The review proposes a three-level conceptual diagnostic architecture and five evidence-informed prevention axes. The architecture organizes candidate measures and contextual indicators; it is not an empirically validated predictive model. Conclusions: TVET dropout should not be interpreted solely as individual failure but may also be examined as a possible indicator of institutional motivational climate. The framework is calibrated to Brazilian TVET and requires prospective, multicenter, equity-sensitive validation against observed dropout outcomes before use for individual risk prediction or broader international adaptation.

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