A Survey on the Application of Generative Artificial Intelligence by Primary and Secondary School Teachers from the Perspective of Innovation Diffusion

The rapid advancement of Generative Artificial Intelligence has presented novel opportunities for innovation and practice in the field of education. This study utilizes a questionnaire survey approach to examine the factors influencing the application of Generative Artificial Intelligence in teachers' educational instruction, grounded in Diffusion of Innovation Theory. The research proposes hypotheses that teachers' adoption of Generative Artificial Intelligence in educational instruction is influenced by seven factors: relative advantage, compatibility, complexity, trialability, visibility, information channels, and teachers' personal innovativeness. Through correlation analysis, it is discovered that these influencing factors are significantly correlated with teachers' adoption and application of Generative Artificial Intelligence in educational instruction. Regression analysis further reveals that compatibility and visibility have significant positive predictive effects on teachers' adoption of Generative Artificial Intelligence. Based on the data results, this study proposes corresponding strategies to further enhance the diffusion of Generative Artificial Intelligence, aiming to improve the quality and efficiency of teachers' educational instruction, reduce their workload, and promote educational equity and high-quality balanced development.