Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

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While feedback is essential for guiding student learning, providing timely and personalized guidance in large-scale educational settings remains a significant challenge. Generative AI offers a scalable solution, yet little is known about students’ perceptions of AI-generated feedback. In this paper, we aim to investigate how the identity of the feedback provider (human vs. AI) affects students’ ability to assess feedback quality and whether their judgments are biased. We propose a comprehensive rubric for assessing the pedagogical quality of formative feedback. We use it to compare the objective quality of AI-generated and human-crafted feedback (N = 979). Next, using data collected from...

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