Description:
Title: AI Unmasked: How Transparency Shapes Student Trust in AI Feedback
Presenter: Tatjana Nazaretsky
Summary: Formative feedback enhances learning outcomes, helping individuals assess and improve their performance. In higher education, however, delivering timely and personalized feedback is challenging due to large and diverse student populations, often leading to delays and generalized responses. Recent advances in generative Artificial Intelligence (AI) provide a promising solution by enabling scalable and immediate feedback tailored to individual learning needs.
In this lunch&LEARN session, Tatjana Nazaretsky (Machine Learning for Education Laboratory) discusses a comprehensive study conducted at EPFL with 457 students across multiple disciplines, focusing on integrating generative AI into educational feedback systems. It examines students’ perceptions of AI-generated versus human-created feedback and the impact of revealing the feedback source on their evaluations.
The findings indicate that the identity of the feedback provider significantly influences student preferences and perceptions, affecting their receptivity to the feedback.
The session explores these outcomes and their implications for developing and implementing AI-based feedback systems in higher education. It particularly emphasizes the critical role of human factors in successfully integrating and accepting AI technologies and suggests specific strategies for institutions to enhance transparency and build trust in AI systems, providing actionable insights for improving educational practices with AI.
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