The Current Situation of the Implementation of College Admission System and the Way of Reform in the Digital Age

Abstract

With the progress of science and technology and social changes, higher education in China is experiencing unprecedented challenges and opportunities. The digital era has not only changed teaching methods but has also profoundly affected the enrollment system of colleges and universities. The study uses a decision tree-based enrollment information mining algorithm and a gray prediction model to construct a data mining model of the current status of enrollment system implementation. Through the data mining model, the data mining and analysis of the student source status of college enrollment are used to propose targeted reform proposals. The number of female students in School Z has been increasing each year, while the number of male students has decreased significantly. The number of students with grades A and B is much lower than that of students with grades B and C. Among the special types of enrollment sources, the enrollment of national defense students and high-level athletes has decreased year by year, while the enrollment of the poverty special program has shown a yearly increasing trend. During the four years, the enrollment of national defense students was 61, 54, 46, and 39, and the enrollment of high-level athletes was 15, 14, 12, and 10. The enrollment in special programs for people experiencing poverty increased from 9 to 47 during the four years. The reform of the college enrollment system should focus on reforming the content of the examination, and government departments to do a good job of coordinating planning, improving laws and regulations, and putting an end to malpractice and irregularities.

Keywords

• decision tree
• gray predictive model
• data mining
• college admissions
• 11a63