Design and Application of Experiential Music Teaching System based on Java 2 Enterprise Edition Architecture

With the rapid advancement of artificial intelligence (AI) and web-based technologies, music education has evolved beyond conventional teaching methodologies, offering more interactive and adaptive learning experiences. This paper presents the design and application of an Experiential Music Teaching System based on J2EE (Java 2 Enterprise Edition) architecture, integrating AI-driven techniques to enhance personalized learning, automatic assessment, and real-time feedback. The system is structured using a three-tier architecture, consisting of a presentation layer (UI), business logic layer (middleware), and data layer (database), ensuring scalability, flexibility, and seamless user interaction. To deliver personalized learning experiences, AI algorithms Reinforcement Learning (RL) are leveraged to recommend music lessons tailored to an individual's progress, learning style, and skill level. The AI models analyse user performance data, adjusting lesson plans dynamically to optimize the learning curve. Additionally, deep learning techniques enable automatic assessment of instrumental and vocal performances, analyzing audio features such as pitch, rhythm, and tone for accurate evaluation. The J2EE-based system ensures seamless integration of AI models through RESTful APIs, allowing real-time data exchange between the front-end and back-end services. This architecture facilitates an efficient and responsive environment where students can practice, receive instant feedback, and track their progress over time. By merging AI-powered analytics with modern music pedagogy, the system bridges the gap between traditional music instruction and digital learning environments, offering students an interactive, self-paced, and feedback-driven approach to mastering musical skills. Future enhancements may incorporate gesture recognition for instrument training, AI-assisted composition tools, and adaptive tutoring strategies to further refine the learning process.