Design of College Student Information Management System based on Big Data
- DOI
- 10.2991/978-94-6463-674-1_19How to use a DOI?
- Keywords
- Big Data; Student Management System; Browser/Server Architecture
- Abstract
The study aims to present an integrated overview of one holistic college students’ affairs management system, which is designed to tap into big data with a view to enhancing educational administration. It adopts the B/S architecture, allowing real-time interactive operation of the data through web-based interfaces. It mainly includes basic information management of students, academic affairs, and student affairs supported by a solid data processing layer based on Hadoop components. It integrates various data sources, such as the tracking of student locations using RFID technology, in an attempt to monitor academic performance, campus activities, and even mental health. By employing advanced data mining techniques, the system aims to provide timely insights and early warnings to both students and counselors, thereby fostering a supportive educational environment. This innovative approach not only smooths the administrative processes but enriches the in-school experience due to personalized support and data-driven decisions.
- Copyright
- © 2025 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 - Jiayi Lin PY - 2025 DA - 2025/03/17 TI - Design of College Student Information Management System based on Big Data BT - Proceedings of the 2024 Seminar on Educational Technology and Management Information Systems (ETMIS 2024) PB - Atlantis Press SP - 168 EP - 177 SN - 2352-5398 UR - https://doi.org/10.2991/978-94-6463-674-1_19 DO - 10.2991/978-94-6463-674-1_19 ID - Lin2025 ER -