Proceedings of the 2017 2nd International Conference on Automation, Mechanical and Electrical Engineering (AMEE 2017)

Analysis and Research on Learning Behavior Based on LMS

Authors
Shangyu Wu, Junming Ye, Zhifeng Wang, Daxiong Luo, Rong Zhao
Corresponding Author
Shangyu Wu
Available Online September 2017.
DOI
10.2991/amee-17.2017.44How to use a DOI?
Keywords
education big data; online learning; learning analysis
Abstract

With the rapid development of Internet technology, big data has become more and more frequently mentioned. How to use the latest technology to dig valuable information from big data has become a hot topic. In this paper, online learning analysis platform based on education big data integrated the acquisition and analysis of students' data. It allowed teacher to teach online, students and students to learn online. At the meantime, it would gather students' data automatically and filter out effective data based on some requirements. Finally, it would analyze data using learning analysis technology and give teacher a feedback of the analysis results. This system would assist teachers more targeted teaching activities.

Copyright
© 2017, 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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Volume Title
Proceedings of the 2017 2nd International Conference on Automation, Mechanical and Electrical Engineering (AMEE 2017)
Series
Advances in Engineering Research
Publication Date
September 2017
ISBN
10.2991/amee-17.2017.44
ISSN
2352-5401
DOI
10.2991/amee-17.2017.44How to use a DOI?
Copyright
© 2017, 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  - Shangyu Wu
AU  - Junming Ye
AU  - Zhifeng Wang
AU  - Daxiong Luo
AU  - Rong Zhao
PY  - 2017/09
DA  - 2017/09
TI  - Analysis and Research on Learning Behavior Based on LMS
BT  - Proceedings of the 2017 2nd International Conference on Automation, Mechanical and Electrical Engineering (AMEE 2017)
PB  - Atlantis Press
SP  - 214
EP  - 218
SN  - 2352-5401
UR  - https://doi.org/10.2991/amee-17.2017.44
DO  - 10.2991/amee-17.2017.44
ID  - Wu2017/09
ER  -