大数据背景下学生体质健康分类促进模式的应用研究  

Application Research on the Classification and Promotion Model of Student Physical Health under the Background of Big Data

作　　者：潘立成 黄海滢 张亮 Pan Licheng;Huang Haiying;Zhang Liang(Suzhou High tech Zone Experimental Primary School,Suzhou 215000,Jiangsu China)

机构地区：[1]苏州高新区实验小学校,江苏苏州215000

出　　处：《体育科技文献通报》2023年第6期165-167,261,共4页Bulletin of Sport Science & Technology

基　　金：苏州市教育科学“十四五”规划2022年度一般立项课题(项目编号:2022/LX/02/118/10);苏州高新区教育科学“十四五”规划2022年度重点立项课题(项目编号:SND-2022-ZZZD-001)。

摘　　要：目的:构建基于k-means聚类分析的学生体质健康分类促进模式,为大数据背景下实施学生体质健康促进工作提供有益参考。运用Python编程语言中的数据分析库技术对学生体质测试数据进行方差分析,采用算法k-means聚类对学生数据进行分类。结果表明:学生个体之间的体质健康差异化、数据驱动学校体育工作的范式转变和因材施教的传统教学理念是构建学生体质健康分类促进模式的现实依据;学生体质健康分类促进模式以聚类分析算法为核心方法,应用案例发现低水平学生体质健康水平的结构表现整体优于高水平学生。该模式运用大数据分析方法,能够精确掌握学生健康信息,优化体质健康促进工作方案与效能,创新学生体质健康评价方法,可以为教学评价提供客观依据。Construct a student physical health classification and promotion model based on k-means clustering analysis,providing useful reference for implementing student physical health promotion work in the context of big data.Use the Python programming language data analysis library to perform variance analysis on student physical fitness test data,and use the algorithm k-means clustering to classify student data.The results show that the differentiation of physical health among individual students,the paradigm shift of data-driven school physical education work,and the traditional teaching concept of individualized teaching are the practical basis for constructing a classification and promotion model for students’physical health.The promotion model for student physical health classification uses clustering analysis algorithm as the core method,and the application case shows that the overall structural performance of low-level students’physical health level is better than that of high-level students.This model utilizes big data analysis methods to accurately grasp student health information,optimize the work plan and effectiveness of promoting physical health,innovate student physical health evaluation methods,and provide objective basis for teaching evaluation.

关 键 词：大数据 聚类分析 体质健康 学生 促进模式 

分 类 号：G804.49[文化科学—运动人体科学]