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Análisis predictivo de la autoeficacia creativa de los estudiantes universitarios basado en el modelo de árbol de

Minyue Hong¹, Xueli Wan², Leixiao Fu³

¹Faculty of Arts and Social Sciences, University of Malaya; hmy.lexi@outlook.com.

Journal of visualized experiments : JoVE

|August 25, 2025

Resumen

Este estudio usó un modelo de árbol de decisión para predecir la autoeficacia creativa en estudiantes universitarios. La confianza psicológica, la membresía escolar, la autoeficacia académica y el comportamiento innovador se identificaron como predictores clave.

Área de la Ciencia:

Psicología
Psicología educativa
Ciencia de datos en las ciencias sociales

Sus antecedentes:

La creatividad es un área clave en la investigación psicológica.
Comprender la autopercepción de la creatividad de los estudiantes universitarios es crucial para el desarrollo.
Existe una investigación limitada sobre la predicción de la autoeficacia creativa (CSE) en este grupo demográfico utilizando modelos computacionales.

Objetivo del estudio:

Evaluar un modelo de árbol de decisión C5.0 modificado para predecir el CSE en estudiantes universitarios.
Identificar los predictores significativos de la EEC entre los estudiantes universitarios.
Mejorar la comprensión y el apoyo a la creatividad de los estudiantes universitarios.

Principales métodos:

Se desarrolló un modelo de árbol de decisión C5.0 modificado.
607 estudiantes universitarios completaron el Cuestionario de fortalezas y dificultades (SDQ) con subescalas para resiliencia psicológica, autoeficacia académica, membresía escolar, comportamiento innovador y CSE.
El DTM fue entrenado, validado y evaluado utilizando la precisión y la puntuación F1.

Principales resultados:

El C5.0 DTM revisado predijo efectivamente el CSE.
Los predictores clave de CSE, en orden de importancia, fueron la confianza psicológica, el sentido psicológico de la pertenencia a la escuela, la autoeficacia académica y el comportamiento innovador.
El modelo demostró una mejora de 10 veces después de la validación cruzada.

Conclusiones:

El modelo de árbol de decisión resulta eficaz para predecir la autoeficacia creativa de los estudiantes universitarios.
Los predictores identificados ofrecen información sobre los factores que influyen en el CSE.
Esta investigación apoya las intervenciones para mejorar la creatividad y la CSE en la educación superior.

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