Research on the Pathways and Mechanisms of AI Agents Empowering Teacher TPACK Development

Abstract

With the increasing penetration of artificial intelligence technology in the educational field, AI Agents, as intelligent entities characterized by autonomy, adaptability, and interactivity, are presenting new opportunities for teacher professional development. Technological Pedagogical Content Knowledge (TPACK) is the core competency that determines whether technology can be effectively integrated into teaching practice. This study aims to explore the multi-dimensional pathways through which AI agents empower teacher TPACK development, with a focus on discerning the deep-seated mechanisms behind this empowerment. Theoretically, the research deepens the understanding of a threefold mechanism: “Diagnosis-Feedback,” “Situation-Reflection,” and “Collaboration-Generation.” It further constructs an implementation strategy framework encompassing micro (Human-Agent collaboration), meso (organizational support), and macro (ecosystem construction) levels. This study endeavors to provide theoretical support for understanding and designing teacher professional development intervention programs based on AI agents.