La Inteligencia Artificial y su relación en el rendimiento académico en estudiantes universitarios de Medicina
DOI:
https://doi.org/10.63415/saga.v3i3.410Palabras clave:
Inteligencia artificial, educación médica, rendimiento académico percibido, alfabetización en inteligencia artificialResumen
El presente estudio tuvo como objetivo analizar la relación entre el nivel de preparación en el uso de inteligencia artificial y el rendimiento académico percibido en estudiantes de Medicina de una universidad pública del sur del Ecuador. Se desarrolló bajo un enfoque cuantitativo, con diseño no experimental, de alcance correlacional y corte transversal. La población estuvo conformada por 581 estudiantes matriculados, de los cuales participaron 236, seleccionados mediante muestreo no probabilístico por conveniencia, superando el tamaño muestral previamente calculado. Se utilizaron dos instrumentos validados: la Escala de Preparación en Inteligencia Artificial para estudiantes de Medicina (MAIRS-MS) y la Escala de Rendimiento Académico Universitario (ERAU). El análisis se realizó mediante estadística descriptiva e inferencial, empleando el coeficiente de correlación Rho de Spearman. Los resultados evidenciaron predominio de niveles altos tanto en la Preparación en inteligencia artificial (56,3 %) como en el rendimiento académico percibido (59,7 %). Se identificó una correlación positiva, estadísticamente significativa y de magnitud moderada entre ambas variables (ρ = 0,382; p < 0,001). A nivel dimensional, las asociaciones más consistentes se observaron en cognición y habilidad, mientras que la relación con la organización de los recursos didácticos fue menor. Se concluye que la preparación en inteligencia artificial se relaciona con el rendimiento académico percibido, evidenciando su papel en el proceso de aprendizaje en educación médica.
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Derechos de autor 2026 Josué Chamba León, Jorge Vivanco-Roman (Autor/a)
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