Applied Mathematics and Nonlinear Sciences
Journal license

Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 9, Issue 1


Published
on

July 20, 2024


Pages


DOI

Article

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

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Authors

Zhibin Ge Affiliation:
Sport Art College, Guangzhou Sport University, Guangzhou, 510500, China.
and Qionghua Xia Affiliation:
Department of Physical Education, Guangdong University of Foreign Studies, Guangzhou 510420, China.


Abstract

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.


Keywords

data mining blended learning motion analysis aerobics, 68P15


Citation

Ge, Z. & Xia, Q. (2024). Research on action analysis and guidance in aerobics blended learning based on data mining. Applied Mathematics and Nonlinear Sciences, 9(1). https://doi.org/10.2478/amns-2024-1844

Published by: Engineering Journals

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