Examining Chinese preservice mathematics teachers’ adoption of AI chatbots for learning: Unpacking perspectives through the UTAUT2 model

Integrating AI Chatbots into teaching and learning activities is a growing trend, and understanding the readiness of preservice mathematics teachers to use AI Chatbots is crucial for successful implementation in educational settings. This study examines the factors influencing the adoption of AI Chatbots by preservice mathematics teachers in China, employing the UTAUT2 model and Structural Equation Modeling (SEM) to analyze data from 322 participants. This study’s findings reveal that preservice mathematics teachers have unique characteristics where performance expectancy (PE) is the single factor that significantly influences their behavioral intention (BI) to use AI Chatbots. This underscores the importance of fostering a high-performance expectancy, which, in turn, influences their likelihood to utilize AI Chatbots with enthusiasm, thereby translating into positive usage behavior. These insights bear significant implications for educators, highlighting the need to underscore the practical benefits of AI Chatbots and conduct workshops on effective utilization strategies to enhance teaching and learning performance in mathematics, thereby fostering personalized and engaging learning experiences.