Research on action analysis and guidance in aerobics blended learning based on data mining
Online veröffentlicht: 20. Juli 2024
Eingereicht: 07. Apr. 2024
Akzeptiert: 22. Juni 2024
DOI: https://doi.org/10.2478/amns-2024-1844
Schlüsselwörter
© 2024 Zhibin Ge et al., published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.
Teaching has gradually become more important, no matter which aspect of teaching must be continuously improved and kept up with the pace of development. Aerobics teaching has not been paid much attention by the masses, and many remain in the traditional teaching mode, which will delay the development of aerobics. This paper conducts an in-depth study of aerobics mixed teaching and action analysis guidance under data mining: (1) The blended learning and data mining are fully explained, and only when the two are integrated can better research be carried out. (2) The research on aerobics movements is very complicated. The process and form of the movements are analyzed through the skeleton time graph convolution and spatial graph convolution, and the action probability PCA model is established to facilitate the public study. (3) Blended learning and traditional learning of aerobics After in-depth comparison, it is found that blended learning has more advantages than traditional learning in many aspects. The learning mode should keep pace with the times, and blended learning can better teach.