Modelo de gestão do conhecimento para acompanhamento de tendência à evasão em cursos de graduação presencial

• Ano de defesa: 2017
• Autor(a) principal: Flores, Evandro Gomes
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Santa Maria; Brasil; Engenharia de Produção; UFSM; Programa de Pós-Graduação em Engenharia de Produção; Centro de Tecnologia
• Palavras-chave em Português: Evasão; Gestão do conhecimento; Análise fatorial exploratória; College dropouts; Knowledge management; Exploratory factor analysis; CNPQ::ENGENHARIAS::ENGENHARIA DE PRODUCAO
• Link de acesso: http://repositorio.ufsm.br/handle/1/13652

Dropouts at university is a complex phenomenon and represents a concern in the management of universities. However, knowledge about the causes of evasion has been explored in various ways in different studies in recent years, making it difficult to plan effective combat actions. The objective of this research is to present a knowledge management model that, through the combination of these several studies, allowed the identification of the most critical factors of dropouts. Through the collected information (causes of evasion), this information was combined through a factorial statistical analysis where the main contributing causes for evasion in UFSM were identified. The experiment demonstrated that the proposed model is appropriate to identify dropout critical factors in the institution as a whole, unlike most of the approaches that are commonly used in a specific course in their case studies, and demonstrates that this approach has a generic approach and can be applied to other universities. In this way, the obtained results will provide important subsidies to the Knowledge Management, especially in IES, so that they can serve as a basis for the elaboration of new student retention strategies.