THE EFFECTIVENESS OF ARTIFICIAL INTELLIGENCE–BASED INDIVIDUALIZATION IN HIGHER EDUCATION

This thesis examines the effectiveness of individualizing the educational process in higher education institutions through the use of artificial intelligence technologies. By analyzing students’ individual learning characteristics, academic performance, and learning pace, an adaptive learning approach was implemented. Artificial intelligence–based learning analytics and recommendation systems were used to design personalized learning trajectories. The results indicate that AI-driven individualized learning significantly improves students’ academic achievement and learning motivation, demonstrating its practical relevance for modern higher education.