Proceedings of the 2018 International Conference on Computer Science, Electronics and Communication Engineering (CSECE 2018)

MOOC Course Evaluation Based on Big Data Analysis

Authors
Yong Luo, Jianping Li, Zheng Xie, Guochang Zhou, Xiao Xiao
Corresponding Author
Yong Luo
Available Online February 2018.
DOI
https://doi.org/10.2991/csece-18.2018.75How to use a DOI?
Keywords
MOOC; big data analysis; course evaluation; normal distribution
Abstract
The rapid development of MOOC, more and more same courses appear on the MOOC platform. For learners without the guidance of course selection, a lot of time wasted in the course to browse and try to learn. At the same time, lack of evaluation led to a decline in the quality of the course. In this paper, MOOC learning behavior data is used to construct a evaluation algorithm based on data distribution. Through theoretical analysis and data experiment, a standard model based on normal distribution is constructed. The evaluation algorithm is based entirely on learning data. Objective and dynamic real-time gives the standard points for each course. Not only help learner select the right courses, but also be able to promote the builders improve the lesson.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Proceedings
Part of series
Advances in Computer Science Research
Publication Date
February 2018
ISBN
978-94-6252-487-3
ISSN
2352-538X
DOI
https://doi.org/10.2991/csece-18.2018.75How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Yong Luo
AU  - Jianping Li
AU  - Zheng Xie
AU  - Guochang Zhou
AU  - Xiao Xiao
PY  - 2018/02
DA  - 2018/02
TI  - MOOC Course Evaluation Based on Big Data Analysis
PB  - Atlantis Press
SP  - 349
EP  - 352
SN  - 2352-538X
UR  - https://doi.org/10.2991/csece-18.2018.75
DO  - https://doi.org/10.2991/csece-18.2018.75
ID  - Luo2018/02
ER  -