{"title":"Factors Affecting the Physical Education Practice Teaching Effect of University Students","authors":"Ji Zhu","doi":"10.1145/3456887.3456932","DOIUrl":null,"url":null,"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.","PeriodicalId":441418,"journal":{"name":"2021 2nd International Conference on Computers, Information Processing and Advanced Education","volume":"136 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 2nd International Conference on Computers, Information Processing and Advanced Education","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3456887.3456932","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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.