Factors Influencing Preschool Teachers' Continuous Intention to Use AIGC in Education

Artificial Intelligence Generated Content (AIGC) is becoming a valuable tool ineducation. It supports personalized, interactive, and scalable learning. However, little is known about how preschool teachers continue using AIGC in their dailypractice. This study explores the key factors that influence their sustainedintention to use AIGC technologies. It integrates three theoretical models—Technology Acceptance Model (TAM), Expectation ConfirmationModel (ECM), and Flow Theory—into a unified framework. Data were collectedthrough a questionnaire survey of preschool teachers in China. The results wereanalyzed using both Partial Least Squares Structural Equation Modeling(PLS-SEM) and Fuzzy Set Qualitative Comparative Analysis (fsQCA). Findings show that confirmation and perceived usefulness are strong predictors of continuous use. In contrast, perceived ease of use plays a smaller role. The fsQCA results also reveal three distinct combinations of conditions that lead to high usage intention. These findings provide new insights into teacher technology adoption and offer practical guidance for promoting sustainable use of AIGC in early childhood education, especially in developing regions.