Artificial Intelligence Reshapes Music Teaching: Application Scenarios and Practical Challenges

Abstract

In the current digital transformation of education, music instruction, as a key component of quality-oriented education, is leveraging artificial intelligence to break through traditional limitations. Traditional music instruction relies on teacher experience, resulting in a lack of standardized content, insufficient personalized instruction, and limited interaction. However, AI, leveraging its strengths in data processing, adaptive learning, and human-computer interaction, can analyze learning data in real time, dynamically adjust instructional content, and construct diverse scenarios, injecting vitality into teaching innovation. This article, through literature research and inductive analysis, identifies diverse applications of AI in music instruction: personalized learning programs tailored to students' foundation, goals, and interests; interactive instruction leveraging gamification and real-time feedback to enhance engagement; immersive experiences using VR/AR technology to visualize abstract knowledge; creative assistance lowers the barrier to entry and stimulates innovation; and teaching evaluation leverages AI-based quantitative analysis for more scientific and efficient evaluation. However, there are also prominent problems with the application of technology: AI teaching tools are not sufficiently compatible with music subjects, making it difficult to meet artistic guidance needs such as emotional expression and timbre control; teachers' AI literacy varies, and some people's cognitive and application abilities lag behind; students' excessive reliance on AI may weaken their independent learning and innovation capabilities; in addition, issues such as unclear AI music copyrights, lack of student data privacy, and imbalanced teaching ethics also restrict the deep integration of the two. Based on these issues, this article proposes targeted solutions to provide practical references for educators, facilitate the deep integration of AI and music teaching, promote the quality improvement and sustainable development of music education, and provide support for the deepening of quality-oriented education.