Accelerating Practical Knowledge Sharing in Teachers' Communities with Human-aware Artificial Intelligence

In the era of digital transformation, the integration of artificial intelligence (AI) technologies presents unprecedented opportunities for understanding and utilizing teachers' professional knowledge. This study explores the potential of AI-powered approaches to extract, analyze, and leverage teachers' practical knowledge shared within online professional communities. Through a series of carefully crafted research questions, we examine how advanced data mining techniques and human-aware intelligence can effectively identify, categorize, and synthesize teachers' practical knowledge from online discussions and interactions. Our research addresses three key questions: the effectiveness of AI algorithms in extracting meaningful pedagogical knowledge from online teacher communities and the development of intelligent recommendation systems that connect teachers with relevant professional knowledge. By analyzing large-scale data from teacher online communities and employing sophisticated natural language processing techniques, we aim to bridge the gap between theoretical understanding and practical application of teachers' professional knowledge. This study contributes to both the methodological advancement in researching teacher knowledge and the practical development of AI-supported professional learning communities for educators.