AI optimization algorithms enhance higher education management and personalized teaching through empirical analysis

This research investigates the application of artificial intelligence (AI) optimization algorithms in higher education management and personalized teaching. Through a comprehensive literature review, theoretical analysis, and empirical study, the potential, effectiveness, and challenges of integrating AI algorithms into educational processes and systems are explored. The study demonstrates that AI optimization algorithms can effectively solve complex educational management problems and enable personalized learning experiences. An empirical study conducted over one academic semester shows significant improvements in students' learning outcomes, engagement, satisfaction, and efficiency when using AI-driven personalized teaching compared to traditional approaches. The research also identifies challenges and limitations, including data privacy issues, algorithmic bias, and the need for human-AI interaction. Recommendations for future research directions are provided, emphasizing the importance of developing more adaptive algorithms, investigating long-term effects, and establishing ethical frameworks for AI in education.