Comprehensive evaluation of teaching websites based on intelligence methods

Author

Chen, Mi ; Fu, Yingchun

Author_Institution

Coll. of Educ. Technol., Capital Normal Univ., Beijing, China

fYear

2010

fDate

16-18 April 2010

Firstpage

177

Lastpage

181

Abstract

The teaching websites provide a good supplement to the conventional teaching methods as they offer the teachers and students a platform to share rich educational resources and exchange ideas timely. Evaluation of the teaching websites offers an effective way to enhance their qualities and improve the efficiency of learning. This paper applies intelligence method of backpropagation neural network and support vector machines for evaluating the teaching websites comprehensively. The evaluating indicator system of the teaching websites is established firstly, and the weight of each target is calculated by the analytic hierarchy process method, then the intelligence methods of backpropagation neural network and support vector machines for classification and regression are applied to solve the comprehensive evaluation of the teaching websites. Experimental results show that the methods for evaluation of the teaching websites are effective.

Keywords

Web sites; backpropagation; computer aided instruction; neural nets; pattern classification; regression analysis; support vector machines; backpropagation neural network; classification method; comprehensive evaluation; intelligence methods; regression method; support vector machines; teaching Websites; Artificial neural networks; Backpropagation; Data envelopment analysis; Education; Educational institutions; Educational technology; Intelligent networks; Learning systems; Support vector machine classification; Support vector machines; backpropagation neural network; comprehensive evaluation; indicator system; support vector machines; teaching website;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Management and Engineering (ICIME), 2010 The 2nd IEEE International Conference on

Conference_Location

Chengdu

Print_ISBN

978-1-4244-5263-7

Electronic_ISBN

978-1-4244-5265-1

Type

conf

DOI

10.1109/ICIME.2010.5477521

Filename

5477521