Application of RS and Clustering Algorithm in Distance Education

Author

Qu Zhiming ; Wang Xiaoli

Author_Institution

Sch. of Civil Eng., Hebei Univ. of Eng., Handan

Volume

1

fYear

2008

fDate

21-22 Dec. 2008

Firstpage

7

Lastpage

10

Abstract

Modern distance education is a new Web-based form of education. Enhancing personalized teaching standard of distance learning site is an important and difficult research in the development of modern distance education. Based on rough set (RS), Web learners clustering model, learning features reduction and clustering algorithm are presented, which provides a basis of personalized teaching strategies for distance learning Website. Further research is to mine and process the dynamic personality of learnerpsilas knowledge, and then to provide services on achieving real-time personalized teaching requirement.

Keywords

Web sites; computer aided instruction; data mining; distance learning; pattern clustering; rough set theory; teaching; Web learner clustering model; Web-based education; attribute reduction; clustering algorithm; distance learning Website; learning feature reduction; modern distance education; personalized teaching strategy; rough set; Civil engineering; Clustering algorithms; Clustering methods; Computer aided instruction; Distance learning; Education; Educational technology; Geoscience and remote sensing; Learning systems; Standards development; RS; clustering algorithm; distance education;

fLanguage

English

Publisher

ieee

Conference_Titel

Education Technology and Training, 2008. and 2008 International Workshop on Geoscience and Remote Sensing. ETT and GRS 2008. International Workshop on

Conference_Location

Shanghai

Print_ISBN

978-0-7695-3563-0

Type

conf

DOI

10.1109/ETTandGRS.2008.10

Filename

5070085