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
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"
Conference_Titel :
Computer Information Systems and Industrial Management Applications, 2008. CISIM ´08. 7th
Print_ISBN :
978-0-7695-3184-7
DOI :
10.1109/CISIM.2008.35