Aplicación del aprendizaje basado en problemas en la educación matemática universitaria: una estrategia para abordar obstáculos académicos
DOI:
https://doi.org/10.71068/qrhgr482Palabras clave:
aprendizaje basado en problemas, educación matemática, educación superior, resolución de problemas, rendimiento académico, aprendizaje activoResumen
Objetivo: Examinar la asociación entre una intervención de aprendizaje basado en problemas (ABP) y el rendimiento matemático en estudiantes universitarios, integrando el conjunto de datos empíricos con un modelo de intervención pedagógicamente explícito.Método: Se analizó un diseño cuasiexperimental cuantitativo de pretest-posttest con un grupo de comparación (N = 180; 90 de intervención, 90 de comparación). Las variables de resultado incluyeron el pretest, el posttest, las puntuaciones de cambio, las subescalas derivadas de seis ítems de participación en ABP y de rendimiento matemático, pruebas de Welch, diferencias de medias estandarizadas, validez estructural de constructo, consistencia interna y un ANCOVA ajustado por el rendimiento basal. También se examinaron los supuestos del modelo, los diagnósticos de influencia y los análisis de sensibilidad.Resultados: El rendimiento basal no difirió significativamente entre los grupos (p = .259). El cambio promedio fue de 9.83 puntos en el grupo de intervención y de 2.70 en el grupo de comparación, lo que generó una diferencia intergrupal de 7.12 puntos (p < .001; d = 1.34). El ANCOVA estimó un efecto de intervención ajustado de 7.18 puntos (IC del 95% [5.61, 8.76], p < .001; R² = .761). La estimación se mantuvo estable tras excluir ocho observaciones potencialmente influyentes y bajo inferencia de muestreo repetido (bootstrap) estratificado y HC3.Conclusión: Dentro del conjunto de datos cuasiexperimentales analizados, la participación en la condición de ABP se asoció con una mejora sustantivamente mayor en el rendimiento matemático. El resultado respalda al ABP estructurado como una estrategia prometedora para las matemáticas universitarias; sin embargo, las afirmaciones causales siguen estando limitadas por el diseño no aleatorizado, a pesar de haber confirmado la validez estructural del instrumento de evaluación.
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Derechos de autor 2024 Luis David Bastidas González (Autor/a)

Esta obra está bajo una licencia internacional Creative Commons Atribución 4.0.

