By Topic

Application of data mining techniques to regulated learning system

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Brtka, E. ; Tech. Fac. Mihajlo Pupin Comput. Sci., Zrenjanin, Serbia ; Radosav, D. ; Brtka, V.

This paper investigates some theoretical aspects of so called educational data mining, its characteristics and performances. It is well known that different Course Management Systems - CMS are widely available. They can store a vast amount of information about learners and learning objects. It is also well known that the estimation of conformity of learning objects to the learner personal profile is very important. A vast amount of data about learners and learning objects cannot be inspected manually. That is why the usage of a data mining system is necessary in order to gain information “hidden” in data bases created by CMS. The main goal of this work is to investigate some data mining techniques in order to deliver most appropriate learning object to the learner. The proposed application of educational data mining techniques is followed by a case study.

Published in:

Intelligent Systems and Informatics (SISY), 2010 8th International Symposium on

Date of Conference:

10-11 Sept. 2010