AI-ASSISTED PERSONALIZED LEARNING: EVIDENCE FROM EMPIRICAL STUDIES AND IMPLICATIONS FOR EDUCATIONAL PRACTICE - Azimova Sayyora Khusanboyevna (International Journal of Literature and Language Studies, 2026)
Artificial intelligence-assisted personalized learning is becoming an important direction in modern education. AI systems can analyze learner performance, provide immediate feedback, adapt task difficulty, and support self-paced learning. This article examines the effectiveness of AI-assisted personalized learning based on real empirical studies, including randomized controlled trials and large-scale evaluations. The findings show that AI-supported learning can improve student outcomes when it is pedagogically designed, aligned with curriculum goals, and supported by teachers. However, successful implementation depends on teacher readiness, learner motivation, data privacy, system accuracy, and equal access. The article argues that AI should not replace teachers, but should serve as a tool to support diagnosis, feedback, and differentiated instruction.