Research on Algorithm of MOOC Automatic Rolling System Based on Big Data Analysis
Authors
Yong Luo, Xuchong Liu, Wei Zhao, Xiao Xiao
Corresponding Author
Yong Luo
Available Online May 2018.
- DOI
- 10.2991/ammsa-18.2018.19How to use a DOI?
- Keywords
- MOOC; rolling system; Gaussian distribution; standard template
- Abstract
At present, the credibility of the MOOC certificate is facing serious questions. Unscientific testing is one of the main reasons. This article analyzes the characteristics of MOOC test results data. Based on the distribution it obeys, an algorithm for automatically generating test papers is constructed. According to the probability of normal distribution, determine the number of questions, and a standardized test template was designed. Using the knowledge point parameters, the knowledge coverage of the test paper can be guaranteed. This algorithm can improve the reliability of MOOC testing. It can increase the social acceptance of MOOC certificates, promote the development of MOOC.
- 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/).
Cite this article
TY - CONF AU - Yong Luo AU - Xuchong Liu AU - Wei Zhao AU - Xiao Xiao PY - 2018/05 DA - 2018/05 TI - Research on Algorithm of MOOC Automatic Rolling System Based on Big Data Analysis BT - Proceedings of the 2018 2nd International Conference on Applied Mathematics, Modelling and Statistics Application (AMMSA 2018) PB - Atlantis Press SP - 88 EP - 91 SN - 1951-6851 UR - https://doi.org/10.2991/ammsa-18.2018.19 DO - 10.2991/ammsa-18.2018.19 ID - Luo2018/05 ER -