| Research objectives: Since the physical health test of college students was carried out,colleges and universities have collected a huge amount of data of students’ physical health test,most of them have only simple statistical analysis of these data,and the mining of the data is not sufficient,based on this,this study uses ANOVA and K-means clustering and Apriori association rule algorithm in R language to study the data of physical health test of North Central University in Shanxi Province.It aims to provide more accurate and scientific data support for promoting students’ physical health and provide more references for schools.Research methods: This study uses literature method,mathematical and statistical methods,including one-way ANOVA of students’ physical test scores in four years,deep mining of physical fitness test data using K-means clustering and Apriori association rule algorithm in R language data mining,and more detailed and in-depth comparative analysis and exploration of intrinsic information of physical test data in four years from 2017-2021 in this university in Shanxi province.Research results:(1)The results of the study found a continuous increase in body mass index for boys and girls in four years,especially after the outbreak of the new crown epidemic,with an increase in obesity rates of 3.6% and 0.8%,and an increase in overweight rates of 2.9% and 1.8%,respectively,for boys and girls in 2020-2021.The rates of normal body mass index decreased by 5.7% and 2.2%,respectively.The percentage of female students with failing spirometry levels increased to 16.1%.It was three times higher than before the outbreak of the new crown.The rate of excellent in physical fitness test,the percentage of good is low.The lowest rate of failing strength quality for male students accounted for 83.3%,and the highest rate of excellent 1.8%.(2)From the analysis of the association rule,the support of "strength grade = fail" for "boys" was above 50% for a long time,and the higher the confidence level,the stronger the association between the preceding and following items,and the higher the value of this rule.In addition,the lowest support for "overall grade = pass" and "sprint grade = pass" and "endurance run grade = pass" were 59.8% and 57.4%,respectively.There was also a high correlation between the total score grade and sprint and endurance running.(3)From the data clustered into five categories,it was found that each category of students had distinct characteristics and large differences.Taking the results of 2020-2021,male students with high total score scores had a heavy body type body mass index class mass heart of 24.848,a high level of lung capacity with a class mass heart of 4691.839 ml,a poor endurance and upper body strength class mass heart of 244.107 s and 4.303 times,male students with a lean body type body mass index mass heart of 22.424,a low level of lung capacity with a class mass heart of 2233.716 ml,the second highest upper body strength score,the class mass heart data is 5.735.the group of students with high total score for girls has a lean body type body mass index class mass heart point at 22.987,poor sprint and endurance running,respectively 9.076 s and 236.445 s,high lung volume level,class mass heart is3752.012 ml,low total score score score for girls with lean body type.The lung capacity level of class mass heart is 1795.763 ml,and the flexibility quality is very poor class mass heart is19.183 cm.Research conclusion:(1)Students should be guided to increase the frequency of physical exercise and appropriately increase their after-school physical education tasks,such as running,swimming and other forms of exercise to improve their physical cardiorespiratory fitness,according to the actual situation;(2)The correlation between 50 m running and 800 or 1000 m running found in the study is strong,and students who fail in sprinting or long-distance running should strengthen their training in these two areas.If their weight is not in the normal range,it is recommended to control their weight to maintain in the normal range first,and then gradually increase the exercise related to running.(3)According to the situation of K-means clustering into 5 categories,these 5 categories of students have obvious characteristics.The overall trend shows that boys and girls are severely underperforming in sprints and endurance runs,and that overall scores are strongly correlated with body index,a trend that has persisted.When carrying out physical health promotion,it is necessary to adjust the plan for different students in time.Suggestions:(1)It is suggested that schools develop online sports courses,provide students with more online guidance through online sports,teach students fitness,nutrition,training and other theories,and guide students to exercise,control diet reasonably and control weight within a reasonable range.Through online physical education courses,different physical education courses are carried out according to the specific situation,gradually cultivating students’ awareness of active participation in sports activities.(2)Students who are allowed to go out during the epidemic prevention and control period in various regions are advised to have outdoor sports,such as ball games,swimming,fitness,running,etc.,under the condition of good self-protection.(3)Root cluster analysis found the weak items of different categories of students,and targeted the weak items as the final assessment content.The analysis found that the strength quality of male students is weak and the number of failing pull-ups is high,so we can add some strength training in class to motivate students to increase the number of exercises.It is suggested that the physical health management center of colleges and universities can explore the hidden rules in the physical health test data with the help of data mining technology.The effective data mining method of K-means cluster analysis and Apriori association rule analysis can provide scientific basis for the decision-making of related sports departments. |
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