DocumentCode :
3628130
Title :
Data Mining Techniques in e-Learning CelGrid System
Author :
Pawel B. Myszkowski;Halina Kwasnicka;Urszula Markowska-Kaczmar
Author_Institution :
Wroclaw Univ. of Technol., Warsaw
fYear :
2008
Firstpage :
315
Lastpage :
319
Abstract :
The paper presents e-learning an system as a source of large datasets that can be analyzed by data mining techniques. Proposed data mining techniques can be used as a didactic content recommendation system, feedback tool, intrusion detection tools etc. All techniques are applied to make learning process more effective (taking into account time consuming aspects and resource usage). The paper describes data mining tasks and techniques that can be applied to CelGrid system. A particular attention is given to the active learning paradigm as an e-learning system is mostly a source of unlabeled data.
Keywords :
"Data mining","Electronic learning","Databases","Statistics","Data analysis","Feedback","Intrusion detection","Student activities","Machine learning","Management information systems"
Publisher :
ieee
Conference_Titel :
Computer Information Systems and Industrial Management Applications, 2008. CISIM ´08. 7th
Print_ISBN :
978-0-7695-3184-7
Type :
conf
DOI :
10.1109/CISIM.2008.35
Filename :
4557883
Link To Document :
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