Abstract
This study investigates the impact of artificial intelligence (AI) in adaptive learning systems on student learning experiences through a mixed-methods approach. Qualitative methods included in-depth interviews with seven students and focus group discussions with ten students, identifying key themes: clear expectations, positive reinforcement, effective communication, consistent consequences, and restorative practices. These themes informed the development of a 50-item scale. Quantitative analysis of 200 questionnaire responses using exploratory factor analysis (EFA) revealed five dimensions: adaptive content delivery, real-time feedback and assessment, data-driven insights for educators, personalized learning paths, and lifelong learning and skill development. The 38-item scale demonstrated good internal consistency (Cronbach's Alpha = 0.872), emphasizing AI's critical role in enhancing student learning experiences in adaptive learning systems.