Breaking Boundaries Exploring the Driving Mechanisms of Artificial Intelligence in Enhancing Pre-service Teachers' Teaching Skills

The rapid development of artificial intelligence in education is making it increasingly difficult to adapt traditional methods of training teachers in pre-service to the needs of professional change.Based on constructivistic learning theory and Technology Adoption Model (Tam), this study builds a model of the driving mechanism " perceived utility — motivation for learning — improving teaching skills " and establishing the frequency of use of artificial intelligence tools as exogenous variables.After analyzing data from 213 pre-service teachers,it was found that the frequent use of AI tools can effectively increase perceived value and encourage motivation for learning, as well as encourage growth in teaching abilities.At the same time, motivation to learn plays an intermediate function in this process.The above results can serve as some theoretical basis and practical rationale for the integration of AI into education aimed at improving the use of learning models using AI and playing a catalytic role in improving the quality of teacher training.