Title :
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
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;
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
DOI :
10.1109/ETTandGRS.2008.10
