The Future of Feedback: How Can AI Help Transform Feedback to Be More Engaging, Effective, and Scalable?
It addresses the problem of making feedback more engaging and effective for learners and educators in digital settings, but is incremental as it reports on existing discussions without new empirical results.
The paper synthesizes interdisciplinary perspectives on using generative AI to provide scalable, real-time feedback in digital learning environments, highlighting its potential to reshape educational experiences and identifying key challenges and future research directions.
With digital learning environments becoming more prevalent, the ease with which generative AI enables the scalable production of real-time, automated feedback holds the potential to reshape learning and teaching experiences. This meeting report synthesizes the interdisciplinary perspectives of 50 scholars from educational psychology, computer science, science education, and the learning sciences on the use of generative AI for feedback and its promises and risks in educational practice. We highlight points of convergence in the scholarship, identify areas of debate and unresolved challenges, and outline open questions and future directions for research and educational practice that emerged from structured small-group activities designed to bridge disciplinary barriers.