The Role of Technophilia, Positive Experience and Flow in Enhancing Learning Efficiency in <scp>AI</scp> ‐Based Music Education: A Self‐Determination Theory Approach

ABSTRACT Artificial Intelligence (AI) is transforming music education by providing adaptive learning tools and personalised feedback. However, existing research has primarily focused on technological outcomes, with limited attention to the affective and motivational processes that drive effective AI‐assisted music learning. This study aims to examine how technophilia and positive experience influence flow and perceived learning efficiency in AI‐based music education. A quantitative survey of 941 music major students was conducted, and Structural Equation Modelling (SEM) was used to test a conceptual model grounded in Self‐Determination Theory. The results indicate that both technophilia and positive experience significantly enhance flow and learning efficiency, with flow also serving as a key mediator. These findings underscore the importance of addressing psychological and emotional factors when designing AI‐driven music learning environments. This study contributes to the literature by highlighting how learner‐centred, emotionally supportive design can foster deeper engagement and improved learning outcomes in AI‐supported creative education.