Study On The Correlation Between The Employment Dimensions Of College Students And The Courses Based On The Grey System Theory

With the increase of college graduates’ employment, employment data and course performance data is also increasing exponentially. Under certain circumstances, there are certain rules among these data. There is somehow instructive for the school students and future students in study, graduation and employment. However, there is relatively less study on this aspect.This paper is mainly divided into several following parts. Firstly, this paper divides the whole course of undergraduate study into eight categories and establishes a complete curriculum classification index system model based on the analysis of the general characteristics of the teaching objectives and requirements of the undergraduate level education in China. Secondly, on the basis of the discussion of the gray of the evaluation system of undergraduate employment, two grey models o f undergraduate employment evaluation system are established in different levels:the DLSP grey model is based on the different level school and professional, and the SLSP grey model is based on the same level of school and professional. Thirdly, the author proposes a standardized correlation algorithm model on the basis of the original grey correlation degree algorithm, and it overcomes defects of the Deng’s Grey Relational Algorithms, because different data sequence quantity leads to different association results. The experimental results of this paper show that the improved algorithm is feasible. Fourthly, this paper constructs a prototype system based on.NET technology and gray system theory to study the correlation between employment dimensions of college students and curriculum. By using this prototype system, the data processing time consuming problem has been solved and the data processing of intelligent and accurate rate has been improved. Fifthly, this paper conducts a case study on five majors such as Computer Science and Technology(normal) of Computer Science Stitute in G ua ngdo ng Polytechnic Normal University. It analyzes the correlation between emplo yment data and curriculum classification system by using Grey Correlation Analysis Prototype System of Employment and Grades as well as analyzing relevance between curriculum categories and curriculum categories, and relations between curriculum and curriculum by using the Grey Comprehensive Correlation Algorithm. The analysis results have shown that: in the analysis of the employment dimensions and the category of curriculum, There is a strong correlation between employment salary and professional courses, employment salary and professional basic courses, employment salary and public basic courses, while there also exists a strong relationship between employment city and professional courses, employment city and professional basic courses, employment salary and public basic courses; There is the strongest correlation between professional courses and graduation design, while the strength of correlation between prac tical courses and graduation design as well as the strength of correlation between practical courses and graduation design are inferior to the strength of correlation between professional courses and graduation design in the comprehensive analysis of the curriculum categories.With the analysis above, mark warning, graduation warning and employment tips would be put forward for student timely to reduce the rate of failing exams and delaying graduation. In conclusion, it is transmitted into layers from the analysis of the employment dimensions and curriculum categories to analysis course category and the category, then from analysis course category and the category to analysis of curriculum and curriculum. It provides students with some suggestions for learning, graduation and employment as well as offering certain reference for curriculum design.