A Real Student Network Analysis and Mining in Class Teaching
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- Education; Student-student interrelation networks; Directed Graph; Visualization
The educational data has a wealth of information. In this paper, we construct Student-Student Interrelation Networks (SSIN) to analyze and find meaningful information from student relation data during class teaching. We collect a group of data about students in a new teaching class, then we use adjacency matrixes to represent student-student interrelations. In order to have a better visualization, we construct the directed graph with respect to adjacency matrixes. Then we analyze community structures and their hiding information. It is benefit for improving teaching & learning activities and make related plans for guiding student development.
- © 2015, 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 - Xianhua Zeng AU - Shengwei Qu AU - Zhilong Wu AU - Xu Cheng AU - Jingjing Nie PY - 2015/01 DA - 2015/01 TI - A Real Student Network Analysis and Mining in Class Teaching BT - Proceedings of the International Conference on Education, Management, Commerce and Society PB - Atlantis Press SP - 90 EP - 94 SN - 2352-5398 UR - https://doi.org/10.2991/emcs-15.2015.20 DO - https://doi.org/10.2991/emcs-15.2015.20 ID - Zeng2015/01 ER -