Faith is Like a Rock, Teaching is Based on Things, and Virtue is Reflected in It---Empowering AI: Promoting the Potential and Win-Win of Path Exploration and Practice Framework ---A Case Study of School of Information Engineering, Xi’an Eurasia University Education is Like a Tree Shaking Another Tree, a Cloud Pushing Another Cloud, and a Soul Awakening Another Soul. ---Inscription

As the rapid advancement of information technology, AI has become a crucial support in various fields. As for education, the application of AI is becoming increasingly widespread, especially in enhancing and evaluating the comprehensive quality of students. This study will delve into how AI is being utilized to enhance and assess the overall academic performance of students, with its significance growing more apparent analyze its advantages and challenges, and propose corresponding countermeasures and suggestions. The construction of study style is an important guarantee for the quality of talent cultivation in Colleges and universities. The traditional management mode relies on ex post intervention and empirical judgment, which is difficult to deal with the new challenges of the complexity of student groups and the massive amount of behavior data. The rise of machine learning technology provides a new possibility for the construction of study style from “passive response” to “active early warning”, and from “experience driven” to “data driven”. Taking the school of information engineering of Xi’an Eurasia University as the background, this paper discusses the application path of machine learning in the construction of study style: build an academic early warning model to identify risk students, realize the accurate portrait of students’ behavior through cluster analysis, promote teaching according to their aptitude with the help of personalized learning support system, and optimize teaching strategies based on data feedback. At the same time, this paper analyzes the ethical challenges in the application of technology, including privacy protection, algorithm fairness and interoperability. The research believes that machine learning can effectively improve the scientifically and accuracy of learning style management, but it needs to take education ethics as the bottom line to realize the deep integration of technology and education. This paper provides a practical framework and thinking direction of technology application for university student affairs managers. education[2][8]. This paper provides a practical framework and thinking direction of technology application for university student affairs managers.