The factors influencing teacher education students’ willingness to adopt artificial intelligence technology for information-based teaching

This study, rooted in the Technology Acceptance Model (TAM), investigates the multifaceted factors that influence teacher education students in Information-Based Teaching to embrace artificial intelligence technologies. To enrich the TAM framework, we have incorporated elements such as Artificial Intelligence Literacy (AIL), Subjective Norms (SN), and Output Quality (OQ), with the aim of examining their respective effects on the willingness of teacher education students to adopt AI technologies. To substantiate this theoretical framework, we conducted empirical research involving teacher education students from various Chinese universities. Our findings affirm the robustness of the TAM in explaining the inclination of teacher education students, engaged in the actual teaching process within a digitized educational environment, to adopt AI technologies. Through this model, our study underscores the pivotal role of Artificial Intelligence Literacy (AIL) in influencing educators' acceptance of AI technologies, establishing a foundational cornerstone for subsequent explorations within the theoretical landscape of the TAM. In this study, we identify Perceived Usefulness (PU) and Artificial Intelligence Literacy (AIL) as the primary factors affecting Behavioral Intention (BI) to use AI technologies. Consequently, to foster broader adoption of AI technologies by educators, it is essential to emphasize their tangible benefits and superiority in teaching, with the goal of promoting the extended utilization of AI in digitalized instruction.