Evolving Teacher Professional Development in the Age of AI: Revisiting PCK, TPACK, and the DECODE Model

Abstract

Current teacher professional development (TPD) models often face challenges of sustainability, contextual adaptability, and limited integration of emerging technologies. This study introduces the DECODE model, a cyclical, AI-supported professional development (PD) framework designed to enhance teachers' Technological Pedagogical Content Knowledge (TPACK), academic resilience, and instructional competence in post-pandemic contexts. Grounded in TPACK, Pedagogical Content Knowledge (PCK), and self-regulated learning, the DECODE model includes four phases: DEMO, CO-design/teach, feedback, and DEbriefing. AI is integrated to provide adaptive feedback, automate lesson analysis, and scale individualized coaching. Synthesizing five empirical studies conducted across Taiwan, Indonesia, India, and Vietnam, the findings confirm DECODE's positive impact on TPACK development, reflective thinking, and adaptive instruction. Participants reported increased technological confidence, resilience, and engagement. The study highlights DECODE's scalability and potential for AI-enhanced teacher education in diverse cultural contexts, with future directions focusing on embedding DECODE into formal TPD systems and institutional practices.