Volume 4,Issue 4
Innovation of Music Education Model Supported by Information Technology
With the rapid development of information technology and intelligent tools in education, university music education faces the dual demands of personalized instruction and innovative classroom models. However, traditional music teaching methods have limitations in resource utilization, learning feedback, and creative guidance, such as difficulty in personalized content delivery, limited classroom interaction, and subjective evaluation of student works. To address this issue, this paper introduces network technology, micro-courses, and artificial intelligence-assisted teaching. Through the integration of multimedia resources, real-time learning data analysis, and the application of AI composition and intelligent evaluation systems, it achieves refined management and personalized guidance for student music learning. In the experiment, students' learning interest, creative ability, classroom participation, and musical knowledge mastery are significantly improved. The average interest score of students in experimental group A (micro-courses + online resources) is 4.5 points, an increase of approximately 1 point compared to the control group. This indicates that micro-courses combined with rich online resources can effectively stimulate students' learning interest, make them more actively engaged in class, and significantly enhance their exploratory learning of musical knowledge and skills. The results indicate that the integration of information technology and artificial intelligence can effectively optimize university music education models and provide practical reference for personalized, interactive, and refined teaching.
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