Title :
Comparing LMS and AEHS: Challenges for Improvement with Exploitation of Data Mining
Author :
Karagiannis, Ioannis ; Satratzemi, Maya
Author_Institution :
Dept. of Appl. Inf., Univ. of Macedonia, Thessaloniki, Greece
Abstract :
E-learning systems can be divided in two categories according to the personalization level they offer. LMS and AEHS are representative systems of the above categories. LMS have more capabilities than AEHS but, on the other hand, AEHS consider student´s differences and offer personalized learning to achieve better results. Our research findings led us to embed adaptivity techniques in Moodle, with adoption of a hybrid dynamic user model, which is built with techniques that are based both upon knowledge and behaviour of learner.
Keywords :
data mining; hypermedia; learning management systems; AEHS; LMS; Moodle; adaptive educational hypermedia systems; data mining; e-learning systems; electronic learning systems; hybrid dynamic user model; learner behavior; learner knowledge; learning management systems; Adaptation models; Adaptive systems; Data mining; Data models; Electronic learning; Heuristic algorithms; Least squares approximations; AEHS; LMS; adaptivity; distance education; dynamic student modelling; e-learning; educational data mining; educational systems; learning styles;
Conference_Titel :
Advanced Learning Technologies (ICALT), 2014 IEEE 14th International Conference on
Conference_Location :
Athens
DOI :
10.1109/ICALT.2014.29