Preschool Teachers’ Intentions to Use GenAI: Extending UTAUT

Abstract

Against the backdrop of the rapid development of generative artificial intelligence (GenAI), exploring preschool teachers’ willingness to adopt technology is critical for advancing their educational applications. However, this area remains underexplored. To address this gap, this study draws on the Unified Theory of Acceptance and Use of Technology (UTAUT) to develop a research model incorporating performance expectancy, effort expectancy, social influence, facilitating conditions, perceived risks, and tech-savviness. Using a sequential mixed-methods design, we recruited 434 teachers to participate in a GenAI teaching-application workshop, collected 399 valid questionnaires for structural equation modeling, and conducted 15 in-depth interviews. Quantitative results indicate that performance expectancy, social influence, and tech-savviness are positively associated with preschool teachers’ intention to use GenAI, while perceived risk is negatively associated; effort expectancy and facilitating conditions show no significant association. Due to methodological limitations including high inter-construct correlations and potential common method bias, these findings should be viewed as exploratory rather than conclusive. Qualitative interviews support these relationships and provide further explanatory insights. The mixed-methods results offer preliminary hypotheses regarding GenAI adoption among preschool teachers, and future confirmatory research is needed to verify their generalizability, especially in collectivist cultural contexts.