Modelo predictivo del riesgo de abandono escolar en educación básica: análisis de factores socioeconómicos y rendimiento académico en niños de 7 a 11 años
DOI:
https://doi.org/10.55204/trc.v6i1.e647Keywords:
Deserción escolar; modelos predictivos; regresión logística; machine learning; inteligencia artificial; analítica educativa.Abstract
La deserción escolar constituye un fenómeno multidimensional asociado a factores académicos, socioeconómicos, familiares, institucionales y contextuales. El presente artículo tiene como objetivo analizar la literatura científica reciente sobre la aplicación de modelos predictivos, regresión logística y técnicas de machine learning en la predicción del abandono escolar. La investigación se desarrolló mediante una revisión bibliográfica narrativa con orientación sistemática, considerando estudios publicados en bases académicas relacionadas con educación, analítica del aprendizaje e inteligencia artificial. Los hallazgos evidencian que la regresión logística destaca por su interpretabilidad, mientras que algoritmos como Random Forest, XGBoost, redes neuronales y máquinas de soporte vectorial presentan alto potencial predictivo. Se concluye que estos modelos pueden fortalecer la detección temprana del riesgo de deserción, siempre que sean aplicados con criterios éticos, explicabilidad y orientación pedagógica.
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