Unpacking teachers’ engagement in generative AI-facilitated workplace learning: insights from the AIDUA model

Abstract Although generative AI is increasingly integrated into education, little is known about what factors influence teachers’ adoption of generative AI for workplace learning. This study therefore investigates the factors influencing teachers’ engagement in generative AI-facilitated workplace learning (GenAI-WL), an emerging domain of professional development. Guided by the Artificial Intelligence Device Use Acceptance (AIDUA) model, the study employed a cross-sectional survey design. Survey data were collected from 225 primary school teachers in mainland China who had experience with GenAI-WL. Six constructs were examined: social influence, hedonic motivation, anthropomorphism, performance expectancy, effort expectancy, and emotion. Structural equation modelling revealed that hedonic motivation was the strongest predictor of GenAI-WL, followed by performance and effort expectancy. Emotion mediated the influence of motivation and expectancy on engagement. While anthropomorphism had a negative direct effect, it also exerted positive indirect effects through expectancy beliefs. These findings contribute to the scholarship on teacher technology adoption behaviours and carry practical implications: education programmes should purposefully guide teachers to leverage GenAI in their daily workplace learning, foster sustained engagement by drawing on hedonic motivation, and employ scaffolded approaches that manage anthropomorphism and reduce effort expectancy.