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:
-
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.
-
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.
-
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
