Research on the innovation of education management mode and personalized development of students based on artificial intelligence

Nowadays, “Artificial Intelligence + Education” is transforming teaching and learning. In this study, we employ AI-based data mining to innovate educational management by designing an academic monitoring system using K-means clustering and developing an early warning model through stacking multi-model superposition. Targeted management measures, including personalized video recommendations, are implemented based on the model’s predictions to promote individualized student development. By analyzing daily behavior data from 500 college students, the K-means algorithm effectively classified them into four groups, and the academic alert model achieved a prediction accuracy of 84.19%, outperforming single base models. The implementation of this personalized management method significantly improved student performance compared to traditional approaches, demonstrating its potential to enhance educational outcomes.