Research on action analysis and guidance in aerobics blended learning based on data mining

被引：0

作者：

Ge, Zhibin ^{[1
]}

Xia, Qionghua ^{[2
]}

机构：

[1] Sport Art College, Guangzhou Sport University, Guangzhou

[2] Department of Physical Education, Guangdong University of Foreign Studies, Guangzhou

来源：

Applied Mathematics and Nonlinear Sciences | 2024年 / 9卷 / 01期

关键词：

data mining blended learning motion analysis aerobics;

D O I：

10.2478/amns-2024-1844

中图分类号：

学科分类号：

摘要：

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. © 2024 Zhibin Ge and Qionghua Xia, published by Sciendo.

引用