Research on College Class Style Evaluation Based on Big Data
Yanfei Chen, Chunying Huang, Xinhong Chen, Guitian Liu, Zhiwei Zheng, Ruijia Liu, Xiaohua Li
Available Online October 2019.
- https://doi.org/10.2991/aermt-19.2019.24How to use a DOI?
- big data, class style evaluation, entropy weight method, factor analysis
- Class style is an important indicator affecting the quality of talent training in colleges and universities. How to establish an effective class style evaluation model is of great significance to promote the formation of excellent class style and provide decision support for university personnel training programs. Compared with previous studies, this paper comprehensively considers the factors affecting the evaluation based on the principle of combining subjectivity with objectivity. With the changes of higher education reform, we have prospectively incorporated the indicators that may reflect the status of the work style into the evaluation system. On the basis of these innovative principles, this paper realized low-cost data collection with digital campus, and combined entropy weight method, high-order factor analysis method and similarity cosine calculation method to build a class evaluation analysis model based on big data.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Yanfei Chen AU - Chunying Huang AU - Xinhong Chen AU - Guitian Liu AU - Zhiwei Zheng AU - Ruijia Liu AU - Xiaohua Li PY - 2019/10 DA - 2019/10 TI - Research on College Class Style Evaluation Based on Big Data BT - Proceedings of the 2019 International Conference on Advanced Education Research and Modern Teaching (AERMT 2019) PB - Atlantis Press SP - 99 EP - 102 SN - 2352-5398 UR - https://doi.org/10.2991/aermt-19.2019.24 DO - https://doi.org/10.2991/aermt-19.2019.24 ID - Chen2019/10 ER -