A Multinomial and Predictive Analysis of Factors Associated with University Dropout

 

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Detalles Bibliográficos
Autores: Fernández-Martín, Tatiana, Solís-Salazar, Martín, Hernández-Jiménez, María Teresa, Moreira-Mora, Tania Elena
Formato: artículo
Estado:Versión publicada
Fecha de Publicación:2019
Descripción:The phenomenon of dropout, by its complexity and educational and social impact, has been extensively studied to understand the specific causes. In this line of research, the purpose of this study was to analyze explanatory and predictive models of student dropout from university studies at the Instituto Tecnológico de Costa Rica (TEC), based on many variables recorded in the institutional system indicators. The first stage of the analysis considered multinomial regression models to identify the influence of these variables on the dropout. In the second analysis, six machine learning algorithms were evaluated in order to find a model that would predict student dropout. Data analysis showed that the probability of dropping out is related to sociodemographic variables, study program, academic history, scholarship and other benefits, and performance after first semester. In addition, the best predictor of dropout algorithm was the “random forest”, a probability of 0.83 to predict the dropout correctly and to capture 34% of the actual student dropout. These results are the first step toward building a more robust predictive model of dropout, which will contribute to preventive decision making in this university.
País:Portal de Revistas UNA
Institución:Universidad Nacional de Costa Rica
Repositorio:Portal de Revistas UNA
Lenguaje:Español
Inglés
Portugués
OAI Identifier:oai:ojs.www.una.ac.cr:article/9038
Acceso en línea:https://www.revistas.una.ac.cr/index.php/EDUCARE/article/view/9038
Access Level:acceso abierto
Palabra clave:Multinomial
student dropout
predictor models
higher education
institutional and student’s factors
modelos predictivos
educación superior
deserción estudiantil
factores institucionales y estudiantiles
modelos preditivos
educação superior
deserção de estudantes
fatores institucionais e estudantis