Teaching Quality Evaluation Of Primary And Secondary School In A Region Based On The Internet

In recent years,education has received more and more attention from society and family.It is estimated that China's education market in 2020 will reach near 3000 billion yuan scale.Although parents are very concerned about the child's education,most of them just blindly value the course results,and blindly hope that through a variety of remedial classes to improve the results.They ignore to explore the child's all-round development and the results which are not ideal reasons.The purpose of this thesis is to analyze the root causes of students' problems in education.This thesis mainly uses the methods of empirical analysis to select the eight systems of cognitive ability which include 25 indicators,learning motivation,learning strategies and emotional intelligence in 19 districts and counties with a total of 98 schools and 30961 students in 2016.Based on the descriptive analysis,principal component analysis and clustering analysis of multivariate statistical analysis,the students in this area are classified and analyzed,and the corresponding opinions are put forward.This thesis first evaluates the credibility of the student education evaluation scores in the region by the Cronbach alpha coefficient.The evaluation scores are used to describe the differences between the indicators through descriptive statistics and calculate the differences between the indicators correlation coefficient.Because of the high correlation between some of the indicators,we have analyzed the data in the principal component.Then,the K-Means clustering of the data after the principal component analysis is carried out.Firstly,the optimal clustering number is determined by minimizing the square sum of the distance in the cluster.When the initial class is selected,we set a calculation method of distance between the samples: the contribution of the principal component analysis as a weight,into the calculation of the distance.Finally,we classify the data after dimension reduction by the selected initial point,and analyze the results of the clustering and make suggestions.