The Application of Fuzzy Clustering in Teacher-Evaluating Model
In existing teacher-evaluating model, teachers are ranked according to the weighted average score given by students based on the instruction pointers. Although it can reflect the teaching standard in a manner, yet it cannot discover the implicit information in data, such as some teachers are standout in some way. Further more, teachers cannot be sorted by a certain index in this method, which lacks for a more in-depth analysis for sorting data. In this paper, a new method is proposed based on the existing teacher-evaluating model. By taking fuzzy clustering into consideration, this method analyzes existing data deeply to discover the rules implicit in data, and then gives a division of fuzzy equivalence classes. And each class has a reasonable evaluation and interpretation which can be as an authority for evaluating teaching standard.
Fuzzy Clustering The Teacher-Evaluating Model
SHI Nian-yun CHEN Kun LI Chun-hua
School Of Computer Science And Communication Engineering, China University Of Petroleum,Dongying 257 Geophysical Research Institute of Shengli Oil Field, Dongying 257061, P.R.China
国际会议
2009 IEEE International Symposium on IT in Medicine & Education( IEEE 教育与医药信息化国际会议)
济南
英文
872-875
2009-08-14（万方平台首次上网日期，不代表论文的发表时间）