Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

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The rapid integration of Generative AI (GenAI) into higher education presents both opportunities and systemic challenges, particularly in domains where feedback is central to learning. This study investigates the capacity of a large language model to generate formative feedback for student-created UML diagrams in a university software engineering course. Across two cohorts (N = 262), AI-generated, teacher-generated, and no-feedback conditions were compared, analyzing student perceptions, learning outcomes, and grading reliability. Results show that while students rated GenAI feedback as beneficial and often comparable to human comments, teacher feedback remained more effective in supporting...

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