TITLE:
Constructing an Application Framework for Educational AI Agents to Promote Deep Integration of Teacher TPACK
AUTHORS:
Jinying Chen
KEYWORDS:
Educational AI Agents, TPACK, Teacher Professional Development, Deep Integration, Application Framework
JOURNAL NAME:
Journal of Computer and Communications,
Vol.13 No.11,
November
26,
2025
ABSTRACT: As artificial intelligence technology permeates the educational landscape, the autonomous and adaptive characteristics of Educational AI Agents present new opportunities for teacher professional development. However, current technological applications often remain superficial, failing to effectively promote the deep integration of teachers’ Technological Pedagogical Content Knowledge (TPACK). This study, grounded in a deep analysis of the TPACK theoretical construct and a deconstruction of the core capabilities of Educational AI Agents, aims to construct an application framework for Educational AI Agents oriented towards deep TPACK integration (the AIA-TPACK Framework). This framework is centered on “Teacher-Agent Collaboration” and unfolds across three dynamic stages: “Contextual Awareness and Diagnosis,” “Scaffolding-in-Practice,” and “Reflective Practice and Iteration.” The framework delineates the multifaceted roles of Educational AI Agents in assisting instructional design, coordinating classroom practice, empowering teaching assessment, and guiding professional reflection. This study posits that the implementation of this framework can help shift AI technology from merely empowering singular knowledge domains to facilitating the systematic integration and co-evolution of all TPACK elements, thus providing a theoretical model and practical pathway for future teacher professional development.