Análisis del éxito académico mediante aprendizaje automático: adicción y ChatGPT
Resumen
En este trabajo, se analiza la incidencia de las variables adicción al teléfono, a la pornografía, número de veces que se desbloquea el teléfono a cada hora y nivel de confianza en ChatGPT sobre el éxito académico de un grupo de 4278 estudiantes de ocho universidades de Ecuador. Se emplean los siguientes métodos: árboles de decisión (DT), random forest (RF) y support vector machine (SVM). Los resultados obtenidos señalan niveles similares en la precisión alcanzada en los tres algoritmos, respecto a la exactitud, en caso de SMOTE, los DT son el algoritmo que presenta mayor exactitud (accuracy = 0,64); y, en el caso de RandomOverSampler, el algoritmo SVM muestra mayor exactitud (accuracy = 0,59).
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Última actualización: 03/05/21