Examining the Relationships Among Teacher Characteristics, Collaboration, AI-Integrated TPACK, and Teacher Enthusiasm: A Multi-Group Analysis by Gender

Abstract

The aim of this study was to examine the relationships among teacher characteristics, collaboration, the level of artificial intelligence-integrated technological pedagogical content knowledge (AI-TPACK), and teacher enthusiasm, and to comparatively evaluate these relationships through multi-group analysis (MGA) based on gender. The research model was tested using Partial Least Squares–Structural Equation Modelling (PLS-SEM) to analyse the structural relationships among the variables. Data were collected from 323 teachers working at various school levels across the seven geographical regions of Türkiye, representing diversity in terms of educational background, professional experience, and subject area. In addition to the Demographic Information Form, the AI-TPACK Scale, Teacher Enthusiasm Scale, and Teacher Collaboration Scale were used during the data collection process. The findings of the study reveal that teacher collaboration has significant and positive effects on both TPACK and AI-TPACK components. However, age, educational level, professional experience, and school type did not significantly predict teacher collaboration. Pedagogical knowledge (PK), pedagogical content knowledge (PCK), and AI-based technological knowledge (AI-TK) had significant effects on teacher enthusiasm, whereas content knowledge (CK), AI-based technological content knowledge (AI-TCK), AI-based technological pedagogical knowledge (AI-TPK), and AI-TPACK did not show any significant effect. Contextual variables such as ICT usage competence, AI usage experience, and AI usage intensity did not have a significant effect on teacher enthusiasm. Gender-based analysis results revealed that the effects of teacher collaboration on PK, CK, PCK, and AI-TPACK components differed significantly between male and female teachers, whereas the effects on AI-TCK and AI-TPK components were significant only among female teachers. It was found that PK significantly predicted teacher enthusiasm only among female teachers, while AI-TK significantly predicted teacher enthusiasm only among male teachers.