Title :
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
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;
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
DOI :
10.1109/ICIME.2010.5477521
