Development Track of Higher Education Based on Big Data

Abstract

The development track of higher education based on big data association analysis rules is studied in this paper. This paper analyzes the big data of six academic journals of higher education in the past 40 years and conducts data association mining. The research finds that: the development of academic research in Higher Education in China has experienced three stages: steady start-up period, rapid development period and adjustment of heavy quality period. China has become a big country of higher education research. The quality of research has been improved, but the academic succession is still weak, and there is an obvious gap compared with the international level. The core force of the research has been formed, which is characterized by small proportion and heavy weight. The cooperation and synergy of research has been strengthened, and scholars' co authorship has become the mainstream, but the inter agency cooperation is relatively weak. The number of empirical research papers has increased significantly, but the total amount is still small and the proportion is small. The cluster of research knowledge is growing steadily and has a good focus. It not only pays attention to the matching with national policies, but also pays attention to the relative independence of disciplines. The method and research results have certain reference value for the research of higher education development trajectory based on big data association analysis rules.