Evaluar un trabajo escrito calificado en la universidad: comparación entre la evaluación humana y la evaluación por un modelo de inteligencia artificial generativa
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La inteligencia artificial generativa (IAG) puede apoyar el juicio evaluativo formulado por el profesorado sobre las producciones de los estudiantes. Sin embargo, su uso plantea cuestiones que van más allá, en particular, de la concordancia de las calificaciones. Para comprender mejor las condiciones de este apoyo por parte de la IAG, este artículo presenta una experimentación exploratoria realizada en un curso universitario de francés escrito. El estudio compara la evaluación humana y la evaluación por la IAG de una misma producción escrita con función diagnóstica. El análisis se basa en un marco de referencia del juicio evaluativo articulado en tres ejes: las funciones de la evaluación, sus etapas y su dimensión ética, inseparable de la responsabilidad de la persona evaluadora. Los resultados muestran una convergencia global entre ambos modos de evaluación en cuanto a las calificaciones y al número de errores señalados, pero revelan diferencias significativas en la identificación, la categorización de los errores y en la articulación entre diagnóstico, calificación y retroalimentación cuando aumenta la complejidad de los errores. Este estudio muestra que la IAG no puede sustituir al juicio evaluativo. No obstante, constituye una ayuda para determinadas operaciones, siempre que se apoye en balizas metodológicas, institucionales y éticas claras, combinadas con la formación del profesorado y una vigilancia profesional constante. Asimismo, abre perspectivas de investigación, entre otras, hacia la comparación de diferentes modelos generativos.
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