2014 IEEE 14th International Conference on Advanced Learning Technologies (ICALT) (2014)
July 7, 2014 to July 10, 2014
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICALT.2014.29
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.
Adaptation models, Data mining, Least squares approximations, Adaptive systems, Data models, Heuristic algorithms, Electronic learning
Ioannis Karagiannis, Maya Satratzemi, "Comparing LMS and AEHS: Challenges for Improvement with Exploitation of Data Mining", 2014 IEEE 14th International Conference on Advanced Learning Technologies (ICALT), vol. 00, no. , pp. 65-66, 2014, doi:10.1109/ICALT.2014.29