Uso del Análisis de Género para Detectar Textos Académicos Generados por IA
DOI:
https://doi.org/10.61604/dl.v16i29.377Palabras clave:
Análisis de Género, Textos Generados por IA, Resúmenes Académicos, Comparación Humano-IAResumen
Este estudio investiga las características distintivas entre resúmenes escritos por humanos y resúmenes generados por inteligencia artificial mediante técnicas de análisis de género. La investigación examina resúmenes tipo mini-memoria elaborados por estudiantes de Segundo Año de Máster en Inglés (MA2) en la FLSH Kairouan y los compara con resúmenes generados por IA utilizando el Chat Generative Pre-trained Transformer 3 (ChatGPT). El análisis se centra en la recurrencia de las funciones del texto, específicamente en la frecuencia y calidad de elementos como las declaraciones de propósito, metodología, resultados y contextualización. Los hallazgos revelan que los resúmenes escritos por humanos presentan una presentación más equilibrada y detallada, destacando la contextualización y los resultados comprensivos, mientras que los resúmenes generados por IA tienden a priorizar declaraciones de propósito claras y explícitas, con menos profundidad en los resultados y la información contextual. El estudio propone métodos avanzados de detección, incluyendo herramientas mejoradas de análisis de texto y evaluaciones de contextualización, para diferenciar el contenido generado por IA. También destaca la necesidad de una formación específica para docentes y criterios de evaluación rigurosos para mantener la integridad académica y abordar los desafíos que plantea la IA en la redacción académica.
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Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial-SinDerivadas 4.0.
