Factors Affecting the Physical Education Practice Teaching Effect of University Students

Ji Zhu
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引用次数: 2

Abstract

In the traditional SEM model, density-based clustering method is used to complete the clustering analysis on the influencing factors of university students’ physical education practice teaching effect. The result of clustering analysis is low reliability and time-consuming, which leads to the poor performance of the model analysis of influencing factors. Thus, in this paper, a decision tree model for influencing factors of university students’ physical education practice teaching effect is designed. K-means clustering algorithm is adopted to classify the basic information data on PE practice of university students. According to the results of data clustering combined with the basic ideas and concepts of decision tree, a decision tree model of influencing factors of PE practice teaching effect is constructed using ID3 algorithm. The average clustering accuracy of the designed model is as high as 99.4%. According to the decision-making results of the model, “physical fitness” is the most important factor affecting the effect of university students’ physical education practice teaching.
影响大学生体育实践教学效果的因素
在传统的SEM模型中,采用基于密度的聚类方法完成对大学生体育实践教学效果影响因素的聚类分析。聚类分析结果可靠性低,耗时长,导致模型分析影响因素的性能较差。为此,本文设计了大学生体育实践教学效果影响因素的决策树模型。采用K-means聚类算法对大学生体育实践基本信息数据进行分类。根据数据聚类结果,结合决策树的基本思想和概念,利用ID3算法构建体育实践教学效果影响因素的决策树模型。所设计模型的平均聚类精度高达99.4%。从模型的决策结果来看,“身体素质”是影响大学生体育实践教学效果的最重要因素。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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