Construction of Western Music Theory Teaching Model Based on Machine Learning
Mar 19, 2025
About this article
Published Online: Mar 19, 2025
Received: Oct 16, 2024
Accepted: Feb 10, 2025
DOI: https://doi.org/10.2478/amns-2025-0408
Keywords
© 2025 Ruijie Liao, published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
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Correlation result
| Service flow | Pearson correlation coefficient | P value |
|---|---|---|
| September traffic | -0.102 | 0.002 |
| October usage | -0.169 | 1.65 e-04 |
| November traffic | -0.185 | 1.75e-05 |
| December traffic | -0.171 | 1.79e-02 |
| January traffic | -0.319 | 9.27e-16 |
| Total traffic | -0.235 | 2.45e-09 |
Characteristics of student behavior
| Eigenvalue | Meaning |
|---|---|
| X1 | Learning duration |
| X2 | Student music cognitive level |
| X3 | Learn the needs of music learning |
| X4 | Students’ interest in music learning |
| X5 | Student music learning skills |
| X6 | Pre-class music preview |
| X7 | Professional skill level |
| X8 | Enthusiasm for classroom teaching |
| X9 | Student interaction |
| X10 | Musical learning skills |
| X11 | Product quality evaluation |
| X12 | Enthusiasm for music learning |
| X13 | Self-learning music |