The Application Of Data Warehouse And Data Mining In Grade Analysis Of Students Majoring In Computer Application In Secondary Vocational School

In the Implementation Plan for Accelerating the Modernization of Education(2018-2022),it is proposed to make full use of information technology,carry out the reform of personnel training mode and teaching method,and strengthen the digital recording and analysis of students' learning behavior data,so that information technology can help improve the quality of vocational education.The emergence and application of learning analysis based on big data technology have exerted a positive effect on the development of educational informatization in China.However,according to the existing research literature,it is found that the research of learning analysis based on big data technology is mostly concentrated in the field of higher education,and it needs further promotion and in-depth research in secondary vocational education.Although students' learning data can also be analyzed using the traditional teaching method and the results can have an impact on students' learning effect,the traditional way has a long cycle and low level of informationization.The application of learning analysis technology can make up for these shortcomings.Therefore,based on the reality and characteristics of computer application major students in a secondary vocational school,this paper analyzes and researches the application of data warehouse and data mining in learning analysis using the literature research method.The main work is as follows: firstly,building a learning analysis model applied to computer application major in a secondary vocational school;designing and building the data warehouse based on the related data of computer application major students in the First Vocational Technical School of Dianjiang County,Chongqing;mining the students' performance data with the association rule algorithm and obtaining the relevance and sequential order advice of courses;considering the influence of individual factors on student's performance in the analysis process,and making cluster analysis of the student's data with K-means,and putting forward some specific teaching suggestions according to the characteristics of clustering results.In order to better apply the mining results to the actual teaching,this paper puts forward a new method that integrates the association rule and clustering.The course relevance obtained from the association rule and the performance factors from cluster analysis constitute a new mining attribute,complete the low-score early warning of students' performance,and feed back to teachers in the form of Web visualization,thus realizing the early intervention of students' learning behavior.In this paper,data warehouse and data mining technologies are adopted to analyzethe data of computer application major students in a secondary vocational school,so as to provide useful ways and methods for the teaching and management of computer application major in secondary vocational schools.Visualized early warning of low-score students can further provide more accurate and scientific basis for teachers to intervene students' behavior,thereby improving the overall quality of students,carrying out targeted teaching work,and optimizing teaching effects.