DocumentCode :
2778026
Title :
Data mining techniques for teaching result analysis using rough set theory
Author :
Ramasubramanian, P. ; Iyakutti, K. ; Thangavelu, P. ; Jeya, G. Jegadeeswari ; Begam, S. Shameera
Author_Institution :
Dept. of CSE, Infant Jesus Coll. of Eng., Keelavallanadu
fYear :
2008
fDate :
18-20 Dec. 2008
Firstpage :
1
Lastpage :
8
Abstract :
The development of IT and WWW provides different teaching strategies, which are chosen by teachers. Students can acquire knowledge through different learning models. The problem based learning is a popular teaching strategy for teachers. Based on the educational theory, student´s increases learning motivation, which can increase learning effectiveness. This paper proposes a concept map for each student and staff and finds the result of the subjects and also recommending for sequence of remedial teaching. This paper uses rough set theory for dealing with uncertainty in the hidden pattern of data. For each competence the lower and upper approximations are calculated based on the brainstorm.
Keywords :
data encapsulation; data mining; educational computing; rough set theory; teaching; brainstorm map; concept map; data hiding; data mining; educational theory; knowledge acquisition; problem-based learning; remedial teaching sequence; rough set theory; teaching result analysis; Cognitive science; Data mining; Education; Educational institutions; Feedback; Set theory; Storms; Strontium; Uncertainty; World Wide Web; Educational System; Feedback; Problem Based Learning; Rough set;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computing, Communication and Networking, 2008. ICCCn 2008. International Conference on
Conference_Location :
St. Thomas, VI
Print_ISBN :
978-1-4244-3594-4
Electronic_ISBN :
978-1-4244-3595-1
Type :
conf
DOI :
10.1109/ICCCNET.2008.4787681
Filename :
4787681
Link To Document :
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