AI Prompts: Tools for Optimizing Scientific Research
DOI:
https://doi.org/10.37843/rted.v18i1.616
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Abstract
En la última década, la Inteligencia Artificial (IA) ha emergido como un agente transformador en la producción de conocimiento científico, incidiendo de manera transversal en múltiples disciplinas. La investigación tuvo como propósito analizar el impacto de los prompts basados en IA en la optimización del procesamiento y estructuración de datos. Se adoptó un enfoque cualitativo, sustentado en el paradigma interpretativo y método hermenéutico, con un diseño descriptivo de corte transversal. La muestra representativa estuvo conformada por 25 investigadores académicos. Para la recopilación de información, se emplearon entrevistas semiestructuradas, cuyo análisis se efectuó mediante codificación abierta y el uso del software NVivo, permitiendo la identificación de patrones emergentes y tendencias significativas. Los resultados evidencian que los prompts de IA no solo incrementan la eficiencia en la gestión de datos, sino que también favorecen la identificación de nuevas líneas de indagación científica. Además, se observó una notable reducción en los tiempos de procesamiento y un incremento en la precisión del análisis de grandes volúmenes de información. En consecuencia, las herramientas se consolidan como recursos notables para la investigación contemporánea, particularmente en contextos donde el manejo de datos masivos y la optimización de metodologías comparativas resultan determinantes. Se recomienda su incorporación en todas las fases del proceso de generación de conocimiento y se sugiere establecer marcos éticos y normativos que regulen el uso de la IA en la investigación, promoviendo su integración como una herramienta complementaria y no como un sustituto del razonamiento humano en la construcción del conocimiento científico.
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