Predictive Model to Identify College Students with High Dropout Rates

Jhoan Keider Hoyos Osorio; Genaro Daza Santacoloma

doi:10.24320/redie.2023.25.e13.5398

Autores

Jhoan Keider Hoyos Osorio Universidad Tecnológica de Pereira https://orcid.org/0000-0002-7169-7963
Genaro Daza Santacoloma Universidad Tecnológica de Pereira https://orcid.org/0000-0002-1429-5925

DOI:

https://doi.org/10.24320/redie.2023.25.e13.5398

Palabras clave:

deserción escolar, estudiante universitario, previsión, análisis de regresión

Resumen

Disminuir la tasa de deserción estudiantil es uno de los principales objetivos de las instituciones de educación superior; para lograrlo, las universidades deben identificar con precisión a los estudiantes con mayor riesgo de abandonar los estudios antes de graduarse y centrar sus esfuerzos en ellos. De ahí surge la necesidad de implementar modelos predictivos capaces de identificar a los estudiantes que finalmente desertarán. En este trabajo se presenta un sistema de alerta temprana para identificar a los estudiantes de primer semestre con alto riesgo de deserción; el sistema se basa en un modelo de aprendizaje automático entrenado a partir de datos históricos de estudiantes de primer semestre. Los resultados muestran que el sistema puede identificar a los estudiantes “en riesgo” con una sensibilidad del 61.97%, lo que permite ofrecerles atención temprana y reducir la tasa de abandono.

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