MOOC Course Evaluation Based on Big Data Analysis

DOI

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.

Copyright

© 2018, 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  - 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
BT  - Proceedings of the 2018 International Conference on Computer Science, Electronics and Communication Engineering (CSECE 2018)
PB  - Atlantis Press
SP  - 349
EP  - 352
SN  - 2352-538X
UR  - https://doi.org/10.2991/csece-18.2018.75
DO  - 10.2991/csece-18.2018.75
ID  - Luo2018/02
ER  -