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Human-AI Collaboration for Educational Feedback: From Automation to Hybrid Intelligence
Generative AI is rapidly transforming educational feedback. While recent advances have demonstrated that AI can generate high-quality feedback, the more important question is how humans and AI should collaborate to enhance teaching and learning. This talk presents a research programme that explores this evolution through the lens of human–AI collaboration. Drawing on a systematic review and a series of empirical studies, I examine the progression from AI-generated feedback to AI-supported analysis of feedback quality and ultimately to hybrid intelligence, where educators and AI work together to deliver personalised, learner-centred feedback. The talk concludes with Edvance, a state-of-the-art feedback platform that illustrates how generative AI can move beyond automation to augment educators' expertise.
INVITED SPEAKER
Dr Guanliang CHEN
Senior Lecturer
Centre for Learning Analytics
Monash University
About the Invited Speaker [Researcher Profile]
Dr Guanliang CHEN is a Senior Lecturer at the Centre for Learning Analytics, Monash University. His research interests span Artificial Intelligence in Education, Learning Analytics, and Natural Language Processing, with a particular focus on developing and applying responsible AI technologies to support assessment and feedback at scale in educational contexts. Dr CHEN has authored over 100 peer-reviewed publications and attracted more than 9,000 citations on Google Scholar, with an h-index of 37. Dr CHEN plays an active role in shaping the field through editorial positions in leading journals—including Computers & Education: Artificial Intelligence and the Journal of Learning Analytics—and through his service on the Executive Committee of the International AIED Society, as Vice President of the Society for Learning Analytics Research (SoLAR), and as Programme Co-Chair for the International Conference on Artificial Intelligence in Education (AIED 2026) and the International Conference on Learning Analytics & Knowledge (LAK 2027).
CO-ORGANISERS
