This study explores how teacher-led professional learning communities (PLCs) facilitate the diffusion of AI-integrated teaching practices in Korean schools. Employing a qualitative multiple case study design, the research involved 37 master teachers, each leading a small PLC composed of four general teachers. Over six collaborative sessions, participants designed and implemented AI-integrated lessons in their own classrooms, reflected on their teaching, and shared feedback within their communities. Data were collected from teachers’ lesson plans, reflective journals, satisfaction surveys, and semi-structured interviews. Thematic analysis identified four major patterns: (1) the diffusion of voluntary practices initiated by teachers, (2) the deepening of practice through collaborative reflection, (3) contextual adaptation and reconstruction of AI-integrated lessons across subjects and school contexts, and (4) the emergence of sustainable, teacher-led structures for continued innovation. These findings indicate that bottom-up professional learning—anchored in teacher agency, peer feedback, and contextual diversity—plays a critical role in sustaining the diffusion of AI-integrated teaching. The study proposes a field-based model that positions teachers as key agents of educational innovation in the era of artificial intelligence and digital transformation.

Authors:
Haeun Kim, Pusan National University, South Korea
Suhong Park, Pusan National University, South Korea

About the Presenter(s)
Ha-Eun Kim is a doctoral candidate in Educational Technology at Pusan National University, Busan, Republic of Korea. Her research focuses on teacher re-education programs to enhance teachers’ competencies in AI and digital convergence education.

See this presentation on the full schedule – Sunday Schedule

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