<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>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.</p>
</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.

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

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

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...

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

Publié en ligne: 03 mai 2024

Pages: -

Reçu: 08 avr. 2024

Accepté: 16 avr. 2024

DOI: https://doi.org/10.2478/amns-2024-0909

Mots clés
Deep learning, Blended learning, Reward feedback, HL-MTMG model, Ecological music education

© 2024 Weixin Zheng, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

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

Publié en ligne: 03 mai 2024

Pages: -

Reçu: 08 avr. 2024

Accepté: 16 avr. 2024

DOI: https://doi.org/10.2478/amns-2024-0909

Mots clésDeep learning, Blended learning, Reward feedback, HL-MTMG model, Ecological music education

© 2024 Weixin Zheng, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Mots clés
Deep learning, Blended learning, Reward feedback, HL-MTMG model, Ecological music education