When TPACK meets artificial intelligence: Analyzing TPACK and AI-TPACK components through structural equation modelling

The integration of AI into TPACK frameworks is crucial for enhancing teacher readiness in an increasingly technology-driven educational environment. However, a significant gap exists in literature regarding assessing preservice teachers' knowledge on the integration of AI into their pedagogical practices based on the TPACK framework. This study investigates TPACK and AI-TPACK skills among English preservice teachers, addressing a significant gap in understanding their readiness to utilize AI tools in education. Employing a quantitative cross-sectional survey approach with structural equation modeling, the research examined 304 ELT preservice teachers. Findings reveal varying proficiency levels across TPACK and AI-TPACK components. In TPACK, participants demonstrated high competence in independent components like Technology Knowledge (TK) and Technological Pedagogical Knowledge (TPK), but lower abilities in integrated Technological Pedagogical Content Knowledge (TPACK). For AI-TPACK, preservice teachers exhibited above-average competence across all areas, with highest proficiency in Intelligent Technology Knowledge (AI-TK) and lowest in ethics. Gender and prior AI experience significantly influenced AI-TPACK skills. Strong positive correlations between traditional TPACK and AI-TPACK components were observed, suggesting simultaneous skill development is feasible. This study highlights the need for customized teacher training curricula that enhance integrated knowledge and ethical considerations of AI in teaching.