Exploring factors influencing preschool teachers’ behavioral intention to use AI technologies in early childhood settings

With the rapid advancement of artificial intelligence (AI) and its increasing integration into education, the early childhood education sector has begun to explore the potential of AI integration. As key agents in the classroom integration of technology, preschool teachers' willingness to use AI directly impacts the effectiveness of AI implementation in early childhood education. Grounded in an extended framework of the Technology Acceptance Model, this study investigates the mechanisms through which perceived usefulness (PU), perceived ease of use (PEOU), subjective norm (SN), AI anxiety (AIA), and AI self-efficacy (AISE) influence preschool teachers' behavioral intention (BI) to use AI. A survey was conducted with 270 in-service preschool teachers, and the hypothesized paths were tested using structural equation modeling. The results indicate that AISE, SN, and PU have significant positive effects on BI, with AISE exerting the strongest influence. While PEOU and AIA showed no significant direct effects on BI, PEOU indirectly influenced intention by enhancing PU. Subjective norm positively influenced both PEOU and AISE. Based on these findings, this study offers practical recommendations across four dimensions: teacher professional development, institutional support mechanisms, value communication strategies, and pre-implementation ethical review processes. These recommendations provide an empirical foundation for the prudent introduction and effective application of AI tools in early childhood education contexts.