Analysis of Postgraduates’ Behavior and Learning Achievements based on Clustering Method
- https://doi.org/10.2991/erss-18.2019.35How to use a DOI?
- Hierarchical Clustering, Big Data, Ecards, Students’ Behavior.
With the rapid development of information technology, the application of big data in the education management has attracted more and more scholars’ attention. The widespread use of information recognition methods, especially the Ecards’ swiping technology provides an important support for the collection of students’ data. In this paper, the data of dormitory access, library access, breakfast consumption, published paper and course grades are combined to describe the characteristics of graduate students. Then academic graduate students are clustered into seven categories, from which data portraits for "straight A student" and "top researcher" are obtained. The colleges are divided into three categories according to the nature of their students’ paper, thus we can explore the differences of students’ behavior in different colleges. The research shows the prospect of machine learning in education management, and provides some inspiration to managers in this field.
- © 2019, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Yongchao Shen AU - Jiawen Li AU - Menghua Huo PY - 2019/01 DA - 2019/01 TI - Analysis of Postgraduates’ Behavior and Learning Achievements based on Clustering Method BT - Proceedings of the 2018 International Workshop on Education Reform and Social Sciences (ERSS 2018) PB - Atlantis Press SP - 177 EP - 180 SN - 2352-5398 UR - https://doi.org/10.2991/erss-18.2019.35 DO - https://doi.org/10.2991/erss-18.2019.35 ID - Shen2019/01 ER -