Research on the biomechanical mechanisms of digital music teaching resources in enhancing students’ musical expressivity

The goal of this study is to explore the biomechanical mechanism of digital music teaching resources in improving students’ musical expression, and to study how to optimize music teaching effect by means of technical means. By introducing collaborative filtering (CF) algorithm into the field of music education, a individualized teaching resource recommendation system is constructed. The system deeply analyzes students’ learning behavior, interest preference and learning effect, so as to achieve accurate matching of resources. In order to verify the effectiveness of digital teaching resources and recommendation system, a semester-long empirical study was designed and implemented. Select 100 music majors and divide them into traditional teaching resources group and digital teaching resources group. The study focuses on the differences between the two groups in mastering music theory, improving practical skills (especially musical expression in biomechanics) and stimulating learning interest. The results show that the students’ musical expressive power (especially the skills related to biomechanical mechanism) and learning interest in the digital teaching resource group are significantly improved, and the effect is far better than that in the traditional teaching resource group, which proves the great potential of digital teaching resources and individualized recommendation system in music education.