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International Journal of Educational Innovation and Science, 2024, 5(1); doi: 10.38007/IJEIS.2024.050103.

Applying PCA and Clustering Algorithm to Analyze the Current Situation of Teaching Ability of Physical Education Teachers in Local Universities


Yuan Shao

Corresponding Author:
Yuan Shao

School of Computer and Electrical Engineering, Hunan University of Arts and Science, Changde 415000, Hunan, China


Local applied universities aim to cultivate applied and high-quality professional talents in the local area, and the key to this goal lies in the practical teaching ability of teachers. However, while current universities emphasize practical teaching, they overlook the practical teaching ability of teachers. The analysis of the teaching ability of school teachers is more complex, as it may affect the teaching ability of teachers and require analysis of various characteristic data of teachers, such as age, family, personality, graduation institution, etc. Therefore, for the quantitative analysis of the teaching ability of university teachers, experiments require a large amount of data to construct mathematical models, and a single machine algorithm may encounter the problem of high data dimensions. This article used PCA (principal component analysis) technology to analyze the importance of various indicators that affect the teaching ability of physical education teachers in local universities, reducing the data dimension of clustering analysis algorithm. Then, K-means algorithm was used to cluster the teaching ability of physical education teachers. The experimental results showed that the average running time of PCA-K-mean on the dataset was 0.345 seconds, which was less than the K-mean algorithm.


Physical Education Teachers in Local Universities, Current Status of Teaching Ability, PCA Technology, Clustering Algorithm

Cite This Paper

Yuan Shao. Applying PCA and Clustering Algorithm to Analyze the Current Situation of Teaching Ability of Physical Education Teachers in Local Universities. International Journal of Educational Innovation and Science (2024), Vol. 5, Issue 1: 20-28. https://doi.org/10.38007/IJEIS.2024.050103.


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