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

<p>The teaching of chorus and command is an important basic course for Musicology Majors in applied universities. It is also regarded as a basic subject in many art performance courses. The teaching of chorus and command affects the teaching effect of art majors and the quality of talent training to a certain extent. Based on DM(data mining), this paper studies the design and effectiveness analysis of the College chorus and conducting the course. The research shows that the DM algorithm in this paper has the highest support in college chorus and conducting course design, with an average support of 60.39%. The average support of AI(artificial intelligence) and ant colony algorithm is 45.48% and 34.04% respectively. It can be seen that the DM algorithm in this paper is more suitable for the research of the support degree of the chorus and Command Course Design in Universities and colleges. Through DM, students are trained to skillfully and accurately master the skills of chorus and command, can correctly express the author’s creative intention, and can recreate the work data in time during the rehearsal. At the same time, they can constantly summarize teaching experience, accumulate a certain number of teaching data tracks, and enhance their ability to grasp large-scale music tracks.</p>
</abstract>

The teaching of chorus and command is an important basic course for Musicology Majors in applied universities. It is also regarded as a basic subject in many art performance courses. The teaching of chorus and command affects the teaching effect of art majors and the quality of talent training to a certain extent. Based on DM(data mining), this paper studies the design and effectiveness analysis of the College chorus and conducting the course. The research shows that the DM algorithm in this paper has the highest support in college chorus and conducting course design, with an average support of 60.39%. The average support of AI(artificial intelligence) and ant colony algorithm is 45.48% and 34.04% respectively. It can be seen that the DM algorithm in this paper is more suitable for the research of the support degree of the chorus and Command Course Design in Universities and colleges. Through DM, students are trained to skillfully and accurately master the skills of chorus and command, can correctly express the author’s creative intention, and can recreate the work data in time during the rehearsal. At the same time, they can constantly summarize teaching experience, accumulate a certain number of teaching data tracks, and enhance their ability to grasp large-scale music tracks.

Design and Effectiveness Analysis of Chorus and Conducting Courses in Colleges and Universities Based on Data Mining

Applied Mathematics and Nonlinear Sciences

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

The teaching of chorus and command is an important basic course for Musicology Majors in applied universities. It is also regarded as a basic subject in many...

Design and Effectiveness Analysis of Chorus and Conducting Courses in Colleges and Universities Based on Data Mining

Data publikacji: 13 cze 2024

Zakres stron: -

Otrzymano: 23 lut 2024

Przyjęty: 05 maj 2024

DOI: https://doi.org/10.2478/amns-2024-1490

Słowa kluczowe
Chorus and conducting courses, Effectiveness analysis, Data mining

© 2024 Li Ailing et al., published by Sciendo

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

Design and Effectiveness Analysis of Chorus and Conducting Courses in Colleges and Universities Based on Data Mining

Data publikacji: 13 cze 2024

Zakres stron: -

Otrzymano: 23 lut 2024

Przyjęty: 05 maj 2024

DOI: https://doi.org/10.2478/amns-2024-1490

Słowa kluczoweChorus and conducting courses, Effectiveness analysis, Data mining

© 2024 Li Ailing et al., published by Sciendo

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

Słowa kluczowe
Chorus and conducting courses, Effectiveness analysis, Data mining