Research on the Application of Big Data Technology in Student Education Management
- DOI
- 10.2991/978-94-6463-012-1_16How to use a DOI?
- Keywords
- Big Data Technology; Student Management; Management System
- Abstract
With the development of information technology, colleges and universities have widely applied computer technology in educational management. Many modern campuses have begun to build smart campuses, trying to use computer technology to manage students. There are many middle school students in colleges and universities, and the amount of data generated by students is huge, updated quickly, and there are many types of data. Under this premise, the establishment of a smart campus needs to rely on big data technology to collect, clean and organize data, and mine valuable information from a large amount of data. Big data technology can help college administrators and teachers to discover abnormal data of students in time, understand students' psychological state and behavioral characteristics, and help teachers to carry out further targeted education. This paper deeply analyzes the application direction of big data in student education management, and builds a student management platform based on big data technology.
- Copyright
- © 2023 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Jinjin He AU - Limin Qiao PY - 2022 DA - 2022/12/09 TI - Research on the Application of Big Data Technology in Student Education Management BT - Proceedings of the 2022 International Conference on Educational Innovation and Multimedia Technology (EIMT 2022) PB - Atlantis Press SP - 139 EP - 145 SN - 2667-128X UR - https://doi.org/10.2991/978-94-6463-012-1_16 DO - 10.2991/978-94-6463-012-1_16 ID - He2022 ER -