A study on the Impact of Big DATA on Education Management in Chinese Universities and Countermeasures

Abstract

Big data is significantly impacting all aspects of human society, leading to a transformation in people's cognitive, operational, and lifestyle patterns. Furthermore, it alters the productivity and production relationships within society and is considered a valuable asset for the future, comparable to "new oil," "new gold mine," "new resources," and an "innovation engine." It is considered a very valuable asset for the future, comparable to "new oil,” “new gold mine,"  "new resources,"  and a "new engine" for innovation. Since 2012, the United States, the United Kingdom, France, Japan, South Korea, and other developed nations have prioritized big data as a key component of their national strategies. In 2015, China explicitly stated its objective of "implementing the national big data strategy" during the Fifth Plenary Session of the 18th CPC Central Committee. To address the challenges posed by the era of big data, the government must collaborate closely with corporations, universities, and research organizations and harness society's collective strength to actively participate. In and universities will play a significant role and exert influence in this current era of big data. Despite the numerous challenges faced by China's education big data sector, university big data research possesses distinct advantages, making the future of big data research and application in education administration highly promising. Management is a form of productivity that can be more crucial than other elements in certain situations. The integration of big data into education management indicates a significant advancement in the field of education management in colleges and universities. Utilizing big data enables us to forecast trends, extract value, and encourage colleges and universities to generate new knowledge more intelligently. In contrast to big data applications in the business sector, big data in universities primarily emphasizes the exploration of correlations and the subsequent identification of causal linkages.