Model for the monitoring and control of dropout among university students
DOI:
https://doi.org/10.33975/riuq.vol34nS4.1061Keywords:
Accompaniment, BadyG, dropout, orientation, survivalAbstract
In addition to the frustration for the individual, his family and community, dropping out of university studies without obtaining a degree represents a loss of resources for the State and can be seen as a response to individual, socio-cultural, academic, institutional and economic situations of this young population.
Abandoning undergraduate studies without obtaining a degree, represents - besides personal, family and community frustration - a loss of resources for the state. Dropping out can be seen as a response to the individual, socio-cultural, academic, institutional and economic situations of the young population. When facing the task of tackling the undergraduate dropout problem, it is necessary to point out the specificities of the population according to its environment, diagnose the specific institution’s situation and motivate students to complete their professional track. This induces the construction of a model which brings together institutional action to control itself, integrating several university structure dependencies and keeping a close relationship to the quality of education in general. It is a matter which is not solved by periodically reviewing figures from a specialized and high-cost software, but by executing actions aimed at applicants and students, focused on achieving permanence until graduation. In this work we present a high-level description of the setting-up and application of a model to control undergraduate desertion at the University of Quindío in a 10-year observation window. During this time, we achieve a 13% decrease in undergraduate students’ desertion per period.
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References
Díaz, C. (2008). Modelo conceptual para la deserción estudiantil universitaria chilena. Estudios Pedagógicos, 65-86.
Feurestein, R., & Hoffman, M. (2008). Programa de Enriquecimiento Instrumental. Hadassah, Canada:: Research Institute. Jerusalem.
Galvis, D., García, M., Hurtado, L., & Méndez, R. (2016). Modelo para el seguimiento y control de la deserción en la población universitaria (Primera ed.). Armenia: Uniquindío.
González, D., & Girón, L. (2005). Determinantes del rendimiento académico y la deserción estudiantil en el programa de Economía de la Pontificia Universidad Javeriana de Cali. Economía, Gestión y Desarrollo, 173-201.
Holland, J., Fritszsche, B., & Powel, A. (2005). Búsqueda Autodirigida. Lutz Fl. USA: Psychological Assessment.
Hurtado, L., García, M., & López, D. (2015). Ponderación óptima de las áreas evaluadas en las pruebas SABER 11, para calcular el puntaje de ingreso a la universidad. Revista de Investigaciones Universidad del Quindio ISSN: 1794-631X, vol:27 , 75-80.
Kleinbaum, D. (1994). Logistic Regression. New York: Springer Verlag.
Lee, E. a. (2003). Statistical Methods for Survival Analysis. New Jersey: Wiley Series in Probability and Statistics.
Simpson, S. M. (2004). A Study of Attrition in Attrition in Supportive Services. Marshall: Tesis presentada para graduarse de la Universidad de Marshall. Marshal Digital Scholar.
Tinto, V. (1975). Drop out from Higher Education: A Theoretical Synthesis of Recent Research. DOI: 10.2307/1170024.
Tinto, V. (2006). Research and practice of student retention: What next? . Journal of College Student Retention, 1-19.
Velarde, E. (2008). La teoría de la modificabilidad estructural cognitiva de Reuven Feurestein. Investigación Educativa.
Yuste, C., Yuste, D., Galve, D., & Martínez, R. (2004). Batería de Aptitudes Diferenciales y Generales. CEPE.
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