entropia Revista Entropía Educativa Rev. Entropía Educ. 2981-4723 Entropía Educativa CI SAS 10.5281/zenodo.23507019 Beyond the Tool: Ethical and Pedagogical Challenges of Using Generative AI in Medical Research Training Más allá de la herramienta: desafíos éticos y pedagógicos del uso de la IA generativa en la formación en investigación médica Parada Romero Laura Belkis Universidad Cooperativa de Colombia 0000-0003-2990-0515 Díaz Vergara Leonardo Fabio UNIVERSIDAD COOPERATIVA DE COLOMBIA 0009-0001-9053-8415 Alonso Rozo Omar Alexis Universidad Cooperativa de Colombia 0009-0003-4661-8957 30 06 2026 4 6

Este estudio tuvo como objetivo analizar las percepciones de estudiantes de medicina y docentes sobre el uso de la inteligencia artificial generativa en la investigación formativa, con especial atención a los desafíos éticos y pedagógicos asociados con su incorporación en la formación universitaria en investigación. Se empleó un diseño cualitativo de alcance exploratorio, que combinó encuestas estructuradas aplicadas a estudiantes de medicina y docentes con una revisión sistemática de literatura académica reciente sobre inteligencia artificial generativa en educación superior y ciencias de la salud. Los hallazgos evidencian una percepción generalmente favorable, aunque cautelosa, frente al uso de la inteligencia artificial generativa. Los participantes reconocieron su potencial para apoyar la organización de ideas, la escritura académica y el desarrollo de tareas investigativas; sin embargo, también manifestaron reservas sobre la calidad, profundidad, pertinencia e implicaciones éticas del contenido generado por estas herramientas. Los resultados sugieren que la integración de la inteligencia artificial generativa en la formación investigativa médica no debe entenderse únicamente como un asunto tecnológico, sino como un desafío ético y pedagógico que exige alfabetización digital crítica, lineamientos institucionales claros y mediación docente activa. El estudio concluye que la inteligencia artificial generativa puede contribuir a la formación en investigación médica cuando se emplea como recurso complementario en entornos pedagógicamente orientados y éticamente regulados. Su integración efectiva depende del fortalecimiento del pensamiento crítico, la autonomía investigativa y las políticas institucionales que prevengan la dependencia tecnológica y promuevan prácticas académicas responsables.Palabras clave: saberes locales, educación decolonial, identidad cultural, currículo contextualizado, aprendizaje significativo.

This study aimed to analyze the perceptions of medical students and faculty regarding the use of generative artificial intelligence in formative research, with particular attention to the ethical and pedagogical challenges associated with its incorporation into university-based research training. An exploratory qualitative design was employed, combining structured surveys administered to medical students and faculty with a systematic review of recent academic literature on generative artificial intelligence in higher education and health sciences. Results: The findings reveal a generally favorable but cautious perception of generative artificial intelligence. Participants recognized its potential to support idea organization, academic writing, and research-related tasks; however, they also expressed reservations regarding the quality, depth, relevance, and ethical implications of AI-generated content. The results suggest that the integration of generative artificial intelligence in medical research training should not be understood merely as a technological issue, but as an ethical and pedagogical challenge that requires critical digital literacy, clear institutional guidelines, and active teacher mediation. The study concludes that generative artificial intelligence can contribute to research training in medical education when used as a complementary resource within pedagogically guided and ethically regulated environments. Its effective integration depends on strengthening critical thinking, research autonomy, and institutional policies that prevent technological dependency and promote responsible academic practice.

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