The more capability, the better behavioural intention? Empirical evidence on the relation between institutes’ artificial intelligence capability and pre-service teachers’ behavioural intentions to design artificial intelligence assisted teaching

The field of education has witnessed a rapid expansion in the utilization of Artificial Intelligence (AI) technologies, fundamentally transforming classroom instruction. Thus, it is critical for pre-service teachers to implement AI-powered technology in their future teaching. This study was conducted in six higher education institutions (HEIs) in China and is grounded in resource-based theory, the technology acceptance model (TAM), and relevant literature. SmartPLS 4.0 was utilized to develop a partial least squares structural equation model (PLS-SEM) to examine the relationships among AI capability (AIC), creativity, self-efficacy, Technological Pedagogical Content Knowledge (TPACK), and pre-service teachers’ behavioural intentions towards AI-assisted teaching. The findings indicated that HEIs’ AIC is a significant predictor of pre-service teachers’ behavioural intentions towards designing AI-assisted teaching. It also predicts their creativity, self-efficacy, and TPACK. Furthermore, creativity, self-efficacy, and TPACK were found to mediate the relationships between HEIs’ AIC and pre-service teachers’ behavioural intentions. These findings suggest that HEIs should support the development of pre-service teachers by enhancing AIC, including resources (data and technology) and awareness (reform and innovation), providing insights into AI integration in higher education within the Asia-Pacific context.