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<p>With the development of the times, the cultivation of students’ comprehensive ability has been widely emphasized, among which the cultivation of music appreciation ability is more and more important. The purpose of this paper is to develop a framework for a multi-intelligences music appreciation ‘immersion’ teaching mode, which is based on the teaching reform of the music appreciation course. Our process involved collecting and pre-processing data related to music emotion, extracting music emotion features, and building a model for music emotion appreciation using long and short-term memory networks. The construction of a multi-featured memory network knowledge tracking model involved cross-fertilizing students’ responses to music appreciation difficulty and ability. Through the effect test of the memory network knowledge tracking model and the practical analysis of music appreciation curriculum reform, it can be seen that the average effect of the knowledge tracking model proposed in this paper is higher than that of the traditional knowledge tracking model by 0.15~0.21. The total score of the experimental class’s music appreciation ability is 10.21, while the control class’s score is 7.78, and the experimental class based on the teaching music appreciation curriculum of multiple intelligences is higher than that of the control class by 2.43%. This paper provides a reform direction for the teaching reform of music appreciation courses based on the multiple intelligences music appreciation teaching program, which is of practical significance for the development of music appreciation teaching.</p>
</abstract>

With the development of the times, the cultivation of students’ comprehensive ability has been widely emphasized, among which the cultivation of music appreciation ability is more and more important. The purpose of this paper is to develop a framework for a multi-intelligences music appreciation ‘immersion’ teaching mode, which is based on the teaching reform of the music appreciation course. Our process involved collecting and pre-processing data related to music emotion, extracting music emotion features, and building a model for music emotion appreciation using long and short-term memory networks. The construction of a multi-featured memory network knowledge tracking model involved cross-fertilizing students’ responses to music appreciation difficulty and ability. Through the effect test of the memory network knowledge tracking model and the practical analysis of music appreciation curriculum reform, it can be seen that the average effect of the knowledge tracking model proposed in this paper is higher than that of the traditional knowledge tracking model by 0.15~0.21. The total score of the experimental class’s music appreciation ability is 10.21, while the control class’s score is 7.78, and the experimental class based on the teaching music appreciation curriculum of multiple intelligences is higher than that of the control class by 2.43%. This paper provides a reform direction for the teaching reform of music appreciation courses based on the multiple intelligences music appreciation teaching program, which is of practical significance for the development of music appreciation teaching.

Exploring the Teaching Reform of Music Appreciation Course in Polytechnic Institutions Combined with Students’ Memory Characteristics

University of Electronic Science and Technology of China

Applied Mathematics and Nonlinear Sciences

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

With the development of the times, the cultivation of students’ comprehensive ability has been widely emphasized, among which the cultivation of music...

Exploring the Teaching Reform of Music Appreciation Course in Polytechnic Institutions Combined with Students’ Memory Characteristics

Online veröffentlicht: 31. Jan. 2024

Seitenbereich: -

Eingereicht: 26. Dez. 2023

Akzeptiert: 04. Jan. 2024

DOI: https://doi.org/10.2478/amns-2024-0302

Schlüsselwörter
Emotion feature extraction, Music recognition model, Memory network, Knowledge tracking, Music appreciation

© 2024 Han Yue, published by Sciendo

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

Exploring the Teaching Reform of Music Appreciation Course in Polytechnic Institutions Combined with Students’ Memory Characteristics

Online veröffentlicht: 31. Jan. 2024

Seitenbereich: -

Eingereicht: 26. Dez. 2023

Akzeptiert: 04. Jan. 2024

DOI: https://doi.org/10.2478/amns-2024-0302

SchlüsselwörterEmotion feature extraction, Music recognition model, Memory network, Knowledge tracking, Music appreciation

© 2024 Han Yue, published by Sciendo

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

Schlüsselwörter
Emotion feature extraction, Music recognition model, Memory network, Knowledge tracking, Music appreciation