Understanding Teachers’ Adoption of AI Technologies: An Empirical Study from Chinese Middle Schools - Jin Zhao; Siyi Li; Jianjun Zhang (Systems)
The advancements in artificial intelligence (AI) technologies and the implementation of government policies are accelerating educational reform in China. In this context, understanding the critical factors influencing middle school teachers’ adoption of AI technologies for classroom instruction is essential for fostering the deep integration of these technologies into teaching and improving teaching efficiency in middle schools. Grounded in the structural equation model (SEM) approach, this research integrates the Innovation Diffusion Theory, the Technology Acceptance Model (TAM), and the Unified Theory of Acceptance and Use of Technology (UTAUT), and proposes a structural model comprising 10 latent variables. A measurement model is then developed for each latent variable, forming the basis of a survey questionnaire. Through empirical research using the questionnaires of 202 middle school teachers, a validated structural equation model with strong model fitting is established. The findings indicate that the most influential factors positively affecting teachers’ willingness to use AI technologies, in descending order, are Interpersonal Relationships, Innovativeness, Mass Media, Compatibility, Perceived Usefulness, and Perceived Ease of Use. Similarly, factors positively influencing teachers’ actual usage behavior, ranked by impact, include teachers’ willingness, Facilitating Conditions, Career Aspiration, and Perceived Usefulness. Results involving the impact of teachers’ Interpersonal Relationships can update the theoretical understanding of the factors driving the integration of AI into teaching, and be used to put forward specific directions such as social network embedding for actionable practice recommendations.