Study On Student Achievement Analysis Based On Association Rules Mining

One popular saying is that "we live in the information age." However,in fact,we live in the data age.Every day massive amounts of data from commerce,community,science,engineering and medicine,and our daily lives are injected into our World Wide Web or storage devices.The explosive growth of data,widespread availability and enormous numbers make our time a true data age.There is an urgent need for powerful and versatile tools to discover valuable information from vast amounts of data and turn it into organized knowledge.This demand led to the birth of data mining.The development of data mining technology has been and will continue to contribute to the journey of our era of writing information.Since the end of the 20th century,when the policy of "rejuvenating our country through science and education" has been put forward,the education industry in our country has been developing rapidly with an increasing number of schools,an increasing scale of running schools,a gradual increase in the number of students and an improvement in the quality of teaching.However,the traditional way of teaching management is difficult to adapt to the current social requirements.We need to apply science and technology to promote teaching progress.At present,data mining has been successfully applied in all walks of life,especially in the neighborhood and financial applications.In the field of education,there is also a large amount of data generated daily,such as students' learning data and living data.At present,the use of these data is still relatively small.If we can use data mining techniques to dig out useful information for students to guide and alert students,this will not only benefit students' learning and life,but also promote The school's traditional teaching methods to the scientific process.This paper studies the related theories of data mining,discusses the basic concepts and processes of association rules,and analyzes several classical association rules algorithms in detail from the aspects of algorithms and their advantages and disadvantages.Then,an improved scheme is proposed.Finally,the improved algorithm is applied to the student grade analysis.Through the preprocessing of student grades,the improved algorithm is used to mine the association rules between student grades,and the results of the association rules are analyzed and explained.The rules can be used to make early warning to students so that students can clarify their future learning tasks.At the same time,it helps teachers to make plans and improve teaching quality reasonably.The application of association rules in college grades is of great value.