Special Session

Special Session 2: Teacher Agency in the Age of AI: Professional Development and Human-AI Collaboration Models

Session Overview

In the rapidly evolving landscape of education, artificial intelligence is reshaping how teachers design lessons, conduct research, and manage student affairs. Yet, the success of any AI application in education ultimately depends on the active role of teachers. This special session highlights the importance of teacher agency in the age of AI, emphasizing that technology should serve as a collaborator rather than a replacement.
We will explore how AI can support teaching practice by enhancing creativity and personalization, how it can empower educational research through new forms of data analysis and collaboration, and how it can strengthen student affairs by improving support services and monitoring well-being. Across these scenarios, the central message is clear: without teacher agency, even the most advanced AI systems cannot make education successful. Teachers must remain the decision-makers, ensuring that AI amplifies human judgment, empathy, and professional expertise.
This session invites scholars, practitioners, and policymakers to discuss models of human-AI collaboration that reinforce teacher autonomy while unlocking the potential of AI to benefit both educators and learners.

Topics of Interest

We will explore teacher agency in three major scenarios: teaching practice, educational research, and student affairs. The Special Session welcomes submissions on, but is not limited to, the following topics:

  1. Teaching Practice

    AI-supported lesson design: How teachers can co-create curricula with AI while maintaining pedagogical control.

    Adaptive assessment with teacher oversight: Using AI to personalize testing while ensuring teachers remain the final evaluators.

    Human-AI co-teaching models: Practical frameworks where AI assists in instruction but teachers retain creative and ethical agency.

  2. Educational Research

    AI in educational data analysis: Empowering teachers to use AI for classroom-based research without losing interpretive authority.

    Collaborative teacher-AI research networks: Building communities where teachers and AI systems jointly investigate learning outcomes.

    Ethical research with AI: Ensuring transparency, fairness, and teacher-led decision-making in AI-driven studies.

  3. Student Affairs

    AI-assisted student support services: Leveraging AI for counseling, advising, and monitoring student well-being while preserving human empathy.

    Teacher agency in AI-driven student monitoring: Balancing efficiency with privacy and professional judgment in managing student affairs.

Session Chair

Assoc. Prof. LAN Min
Zhejiang Normal University, China
Dr. Min Lan is an Associate Professor and Master’s Supervisor at Zhejiang Normal University, serving as Deputy Director of the Institute of Educational Technology. He is also a member of the Zhejiang Provincial Key Laboratory of Intelligent Educational Technology and Applications, and a Research Fellow at the Tin Ka Ping Moral Education Research Center. With academic training spanning Zhejiang Normal University, the University of Hong Kong, and postdoctoral research at HKU, Dr. Lan’s work focuses on self-regulated learning theory, particularly in areas of learning analytics, AI-assisted teaching, gamified learning, and digital/AI literacy. He has led and participated in numerous national and provincial research projects, published extensively in top-tier journals such as Educational Research Review, npj Science of Learning, and Computers in Human Behavior, and contributed to policy frameworks on teacher AI literacy in China. In addition to his research, Dr. Lan teaches across undergraduate, master’s, and doctoral programs, and actively engages in international academic communities, including the American Educational Research Association.