Understanding how pre-service teachers and faculty design and implement an AI-integrated science course in interdisciplinary lesson study: a social epistemic network signature approach
摘要
Interdisciplinary lesson study plays a significant role in promoting pre-service teachers’ professional development, and has been recognized as a critical approach to improve high-level interdisciplinary education. However, due to the dynamic and complicated process of the interdisciplinary lesson study, there is a lack of research on its procedural mechanism and dynamics. As teachers’ collaborative talk gains attention, the framework of Pedagogically Productive Talk has been established to facilitate the talk analysis, with talk serving as procedural data that facilitates a deeper understanding of collaborative patterns among teachers. This study employed Social Epistemic Network Signature approach to analyze collaborative talk patterns and social ties within a team comprising 7 pre-service science teachers, 5 pre-service information technology teachers, and 3 faculty members during an offline interdisciplinary lesson study involved designing and implementing an AI-integrated science course. The findings reveal that this interdisciplinary lesson study team exhibited the characteristics of Community of Practice. A nuanced interpretation of the collaborative talk across different stages of the interdisciplinary lesson study revealed that the team focused primarily on identifying and resolving practical problems, while the faculty members played a crucial role in maintaining friendly team relationship. Suggestions are provided for facilitating collaboration in the interdisciplinary lesson study to effectively integrate AI into science curricula.