The Analysis And Prediction Of Educational Data

The center of school work is teaching,with the emphasis on improving the quality of education and teaching.The most direct and important criterion for measuring teaching effectiveness is student achievement.Through data mining on the basic information of teachers and students in the school database,it is possible to find the relationship between teachers and students and their achievements,as well as the relationship between the results of students in each subject.It can provide decision support for educators,better arrange teaching resources,and improve the effectiveness of education and teaching.The main work of this paper is as follows:(1)Apply the Bayesian classification method to the student database in combination with actual work.Analyze and predict student's development direction and graduation choices,establish a graduation choice model,and use it to predict and guide students' graduation choices in the future.(2)Apply association rules mining Apriori algorithm to education and teaching evaluation.Study the influence of the quality of teachers on teaching effectiveness,and help the education management department to arrange the teaching staff reasonably.The association rules between students' academic achievements will be excavated and the core curriculum will be identified.Once there are warning signs of repetition and withdrawal,early warning will be given.(3)This paper combines data mining with education.Dig out the part of the educational data that contains value.To guide future work arrangements.