A Multi-weight Adaptive Analysis Method of Students' Learning Behavior

DOI

10.2991/wartia-16.2016.372How to use a DOI?

Keywords

Data mining, K-means algorithm, Behavior analysis

Abstract

With the development of Internet information technology, all aspects of society are in development to digital, information-oriented. Student management system is widely used in Colleges and Universities. Student management system contains a lot of valuable data, and has not been fully excavated. This article is aimed at the university student attendance system. An algorithm of students' learning behavior analysis is designed. In the experiment, the number of the students is 423. Students are divided into four categories. The numbers of students in the four categories were: 7, 267, 112 and 24 respectively. The average scores of all the students in each category were: 107, 113, 117 and 123 respectively. This algorithm can effectively analyze students' learning behavior and provide effective support for students' management.

Copyright

© 2016, 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/).

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TY  - CONF
AU  - Enqiang Shen
AU  - Ran Wei
AU  - Jin Ding
AU  - Quanyin Zhu
PY  - 2016/05
DA  - 2016/05
TI  - A Multi-weight Adaptive Analysis Method of Students' Learning Behavior
BT  - Proceedings of the 2016 2nd Workshop on Advanced Research and Technology in Industry Applications
PB  - Atlantis Press
SP  - 1877
EP  - 1880
SN  - 2352-5401
UR  - https://doi.org/10.2991/wartia-16.2016.372
DO  - 10.2991/wartia-16.2016.372
ID  - Shen2016/05
ER  -