An ecological music education model based on deep learning: a blend of tradition and innovation

Abstract

With the improvement of the status of music education, the reform of music education mode is imminent. The intersection of tradition and innovation is achieved by combining ecological education and deep learning concepts to construct an environmental music education model based on the traditional music education model. The research mainly focuses on intelligent music generation and its auxiliary effects in ecological music education. The steps are to complete the intelligent generation of multi-track music through the HL-MTMG model by combining the blended learning module and reward feedback module after defining the problems of music rhythm and melody problems. In analyzing the efficacy of ecological music education based on deep learning, it was concluded that the satisfaction rate of the generated music samples ranged from 66% to 72%, and the average score of students’ satisfaction with the classroom teaching of the ecological music teaching model based on deep learning ranged from 3.313 to 4.253. The environmental music education model through deep learning can significantly enhance the impact of music education and encourage students’ interest in music learning.

Keywords

• deep learning
• blended learning
• reward feedback
• hl-mtmg model
• ecological music education
• 00a35