文献类型：期刊文献

英文题名：A decision support model used in teaching estimation system for bachelor course based on RST

作者：Zhao, Rongyong[1]; Li, Cuiling[1]; Tian, Xiangke[1]; Wang, Dong[1]; Hu, Qianshan[1]; Zhang, Qin[2]; Luo, Xiaojuan[3]

机构：[1] College of Electronic and Information Engineering, Tongji University, Shanghai, 201804, China; [2] Electrical Engineering and Automation Department, Shanghai Maritime University, Shanghai, 201306, China; [3] Department of Electronics and Communication Engineering, East China University of Science and Technology, Shanghai, 200237, China

年份：2017

起止页码：2379

外文期刊名：ICNC-FSKD 2017 - 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery

收录：EI(收录号：20183005590499)

语种：英文

外文关键词：Decision theory - Teaching - Decision support systems - Students

摘要：To build a decision support model used in teaching estimation system(TES) from the viewpoint of knowledge engineering, this paper uses the rough set theory(RST) to discover useful rules from the big data of course materials (books, multi-medias, videos, documents etc.), bachelor student information and responses, teacher information stored in a TES. A heuristic clustering model based on self-organizing mapping is used to map the course references, student and teacher characteristics into conditional attributes, and map student score characteristics into decision attribute respectively. Then both the conditional attributes and decision attributes are discretized into symbolic numbers. Further, a novel decision support model based on rough set theory is built. This model is used for supporting decisions during teaching estimation in the example of bachelor course. Thereby this paper has the important theoretical value and application significance to support the scientific decision used in teaching estimation system for bachelor courses. ? 2017 IEEE.