Dr. Do Youn Won is currently the Director of the AI Education Research Center at Taejae University, where he leads initiatives in AI-enhanced teaching and learning, educational program design, and the development of AI-based learning tools. He earned his Ph.D. in Economics from the University of Utah and previously served as a visiting professor at Korea University’s Institute for Liberal Education. His research spans money and financial markets, political economy, and interdisciplinary work bridging economics, philosophy, and the humanities. More recently, his work has focused on transformations in educational paradigms and socioeconomic institutions in the AX era, together with the ethical challenges of the post-AI era. His current work explores these issues through both research and educational program development.
AI-Augmented Active Learning: Keeping Learners in the Reasoning Loop
The emergence of generative AI is reshaping not only educational tools but also the very conditions under which learners think, reason, and make judgments. Traditional Active Learning, operating largely within a teacher–learner dichotomy, emphasized Learning by Doing. In the AI era, however, AI increasingly participates alongside learners in cognitive activities such as generating questions, searching for information, constructing arguments, and evaluating claims, thereby altering the configuration of actors involved in the educational process. At the same time, when AI’s contribution to learning remains insufficiently visible, final outputs alone reveal little about what learners themselves have actually thought through, evaluated, or decided, leaving the learning process vulnerable to becoming a black box. The central challenge of AI-Augmented Active Learning is therefore to preserve learner agency while ensuring that learners remain ‘epistemic agents,’ capable of forming, examining, revising, and ultimately taking responsibility for their own judgments.
This presentation conceptualizes this shift as an extension from Learning by Doing to Learning by Reasoning with AI and frames the curricular integration of AI along two complementary dimensions: “pedagogical embedding” and “systemic embedding.” Drawing on the ‘Human First → AI Second → Peer Check → Reflection’ structure developed through the “Inside Taejae” program experiment, together with cases of AI-enabled learning tools, the presentation argues that the aim of AI-Augmented Active Learning should extend beyond greater efficiency or participation. Its central purpose is to keep learners in the reasoning loop, enabling them to form, examine, revise, and take responsibility for their own judgments in collaboration with AI, and thereby to develop as ‘epistemic agents.’