MOOC Course Evaluation Based on Big Data Analysis
Yong Luo, Jianping Li, Zheng Xie, Guochang Zhou, Xiao Xiao
Available Online February 2018.
- https://doi.org/10.2991/csece-18.2018.75How to use a DOI?
- MOOC; big data analysis; course evaluation; normal distribution
- 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.
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 -