Construction of College Students’ Management Informatization Ecosystem Based on Data Analysis Technology

Abstract

College students’ management informatization ecosystem can help college students better manage information and resources, thus improving learning and life efficiency. It’s important to introduce data technology into the college student management informatization ecosystem, which can better realize the extraction of student behavior fluctuation information and achieve more targeted student management decisions. The current research lacks consideration of its future development trend, such as the impact of the application of technologies, including artificial intelligence, big data Fenix, and the Internet of Things. This paper studies the construction of college students’ management informatization ecosystem based on data analysis technology. Firstly, the design of the data fusion scheme applied to the college students’ management informatization ecosystem is carried out, and the idea of the scheme is given. Aiming at the big data of students’ learning and living behaviors, this paper digs deep into the value of data information, and extract historical student behavior characteristics, providing a basis for short-term student behavior prediction and management decision-making planning and implementation for the college students’ management informatization ecosystem. Based on historical student behavior data and its characteristic data, the XGboost algorithm is used to quantify and extract the importance of each influencing factor on student behavior fluctuations. Experimental results verify the effectiveness of the method proposed in this paper.

Multi-Level Text Clustering in Subject Knowledge Library and its Visualization

“…A huge amount of data has been accumulated in the teaching field of business administration major with the progress of informationization and networking, and it covers many subjects that have complex relationships and hierarchical structures [1][2][3]. How to effectively manage, structure, and use these subject data so as to make efficient and accurate decisions has become an important challenge for modern society [4][5][6][7]. For instance, companies need to quickly and accurately acquire, analyze, and process information on various business subjects to improve the accuracy and efficiency of their decisions, and in the meantime, as the size of knowledge libraries gets bigger, how to enable the users to quickly locate and acquire the knowledge they need is also an urgent issue to be solved [8].…”