Analysis For Students' Performance Based On Data Mining Technology

In the current society,the term "big data" is more and more widely used in our life.Data mining technology arises and develops rapidly along with the information technology.In the field of education,the application of "big data" is gradually paid more attention.This paper is the integration of large data into education,through functional requirements,technical requirements and data needs to make in-depth analysis and integration,and then according to the classification rules to design formula and assign different minimum confidence and minimum support.The design and analysis of association rules avoid the imbalance and other issues caused by insufficient data.In the school,the student's grades,daily performance and future employment are the focus of the school.Through data mining technology schools can easily capture the overlooked details,analyze the relevant information,and draw the appropriate conclusions and methods for a better service and management.For example,to give an early warning to the students who have the risk of dropping out of school,to provide matching learning methods to the students with learning difficulties,and to do career planning for the students who will be employed.Based on data mining technology for the students' performance and other related data analysis,the contents and conclusions of this paper are as follows:First,collect the data related to the students' performance.The students' performance management system is developed through the steps of needs analysis,general design,detailed design,coding and debugging.The system realizes the functions of system management,teaching resource,student status management,teacher management,perfonnance management,grade statistics,performance data mining and grade inquiry.Thanks to the system,the teachers can maintain their own information,type in and inquire the students' grades;the students can maintain personal information and check grades;the educational administrators can manage the information of students,teachers and courses and analyze the students' performance data mining statistics at the same time.Second,make designing of performance analysis and grading in the view of association rules with the input of the students' data in the system,and provide a more flexible threshold setting of support,confidence and elevation degree.The frequent item sets algorithm is used to analyze the correlation between the data so as to find out the related factors that affect the students' academic performance.Third,put forward the early warning model of the students' performance.The score is a key indicator that evaluates a student's academic performance.Scores can reflect how hard the student studies,the quality of the teachers' courses,and the difficulties of the courses and so on.The examination procedures are different in most colleges and universities in the country.If a student fails in an exam,he will be provided an opportunity in the next or a near seminar to re-study the course and take the exam.Through the data mining technology analysis,this article,focusing on the re-study issue,builds the early warning model of the students' performance,and finds out the students who maybe encounter the re-study problem in advance by applying the association rules into the students' historical data so that such students can do a good early review and preparation,and their teachers can also pay an early attention,warn and help the students.