Research On Curriculum Correlation Analysis And Its Application Based On Data Mining Technology

Currently,the existing curriculum is mainly devoted to analyze the correlation of the course content itself,which helps to arrange the teaching order,credit hours,credit points and more,but lacking in information about the value of the courses which is reflected by the data produced in actual teaching in such kind of curriculum system.While with the development of the educational informationization,the teaching data from various schools is increasing gradually.And the issue “How to properly use the existing information to make scientific teaching decisions” is the very concern of every educator.Data mining can utilize related algorithms to analyze large data sets,which contributes to find the valuable information hiding behind the data.Applying data mining to curriculum correlation analysis enables researchers to collect information that is valuable to course setting from the massive teaching data provided,which helps to optimize the curriculum plan reasonably,further enhance the teaching effect,and improve the quality of personnel training.This research,which is based on the massive teaching data,will find the curriculum correlation reflected by the actual situation of the courses offered in our school with the help of SPSS and Weka these two data mining platforms and simple correlation analysis,canonical correlation analysis and association rule analysis.What's more,this paper will further discuss how to use the curriculum correlation we discovered(in the statistical sense)to provide basis for course setting and how to use the analytic results to guide students on course choosing,provide performance warning against students,import training scheme,and even optimize individualized recommendation system,and more.Finally,it will probe into how to provide decision-making basis for improving course setting of Educational Technology in our school based on the analytic results.The main content of this paper includes the following three parts:First of all,by studying the theory of data mining,the advantages of data mining applied to educational data is understood.With the understanding as the theoretical basis,the methods and tools that are suitable for correlation analysis in our school is confirmed.In addition,the teaching data collected is pre-processed to acquire the data source suits correlation analysis and association rule analysis.Then,the main content of applying data mining to curriculum correlation analysis covers three parts.Part 1 shows the correlation analysis of the courses of the same kind using simple correlation analysis in SPSS and concludes the courses that are obviously related.After that,further analysis and explanation is executed to these courses to get the reasons why they are related from the statistical point of view and then summarize the curriculum correlation that is founded already,newly founded and to be studied.Part 2 details the overall correlation of courses in different categories gained using canonical correlation analysis in SPSS and the canonical variables that reflects every kind of course and the correlation between the courses from the overall correlation.Part 3 introduces the association rules of various courses discovered by using association rule analysis in Weka,the mutual impact among courses,the antecedent courses that may influence the student's learning effect of follow-up courses,and how to pertinently guide students.Last but not least,by using both correlation analysis and association rule analysis,the actual use of curriculum correlation analysis,including optimizing course setting,guiding students on course choosing and more,is presented.Then,suggestions on systematic course optimization based on the actual course setting in our school from the aspects of course construction and personnel training are proposed.