Building and Assessing Human Capability for Productive Human-AI Interaction

Abstract:

Al holds considerable promise for improving human performance and productivity. Growing evidence, however, suggests that gains in performance with AI assistance can be accompanied by weaker learning when Al reduces the cognitive and metacognitive engagement needed to develop durable knowledge and skills. This creates an important challenge for productive human-AI interaction. This talk examines different patterns of human-AI interaction, from overreliance to synergistic mastery, and considers the role of metacognition in shaping how people engage with AI assistance. It will explore how selective delegation, verification of AI contributions, and the internalization of Al-assisted activity can help translate successful performance with Al into durable human capability. Drawing on evidence from empirical studies, this talk discusses implications for designing AI systems, learning environments, and assessment practices supporting human learning while benefiting from AI capabilities.

About the Speaker:

Prof. Dragan Gašević is Chair Professor in Faculty of Education and School of Computing and Data Science at the University of Hong Kong. His research focuses on data analytics, artificial intelligence, and design methods for advancing understanding of self-regulated and collaborative learning. He was previously Distinguished Professor of Learning Analytics and Founding Director of the Centre for Learning Analytics at Monash University, and held professorial positions at the University of Edinburgh and Athabasca University. He is a founder and former President of the Society for Learning Analytics Research and a founding Editor-in-Chief of the Journal of Learning Analytics and Computers & Education: Artificial Intelligence. He is a Distinguished Member of the ACM and recipient of the Society for Learning Analytics Research Lifetime Member Award.