Show simple item record

dc.contributor.authorBallera, Melvin
dc.contributor.authorLukandu, Ismail A.
dc.contributor.authorAbdalla, Radwan
dc.date.accessioned2015-07-20T14:00:21Z
dc.date.available2015-07-20T14:00:21Z
dc.date.issued2014-09
dc.identifier.isbn978-1-4799-6247-1
dc.identifier.urihttp://hdl.handle.net/11071/4002
dc.descriptionConference paperen_US
dc.description.abstractE-learning poses a challenge in a pedagogical perspective such as finding ways on how to motivate the students to learn in spite of the absence of a human instructor. Many researchers in the field have proposed and implemented various mechanisms to improve the learning process such as individualization and personalization. The main objectives is to maximize learning by dynamically selecting the closest teaching operation in order to achieve the learning goals. In this paper, a revolutionary technique has been proposed and implemented to perform individualization and personalization using reversed roulette wheel selection algorithm that runs at O(n). The technique is simpler to implement and is algorithmically less expensive compared to other revolutionary algorithms since it collects the dynamic real time performance such as examinations, reviews and study matrices. Results show that the implemented system is capable of recommending new learning sequences that lessens time of study based on their prior knowledge and real performance matrix.en_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.subjectPersonalized learning sequenceen_US
dc.subjectfitness valueen_US
dc.subjectgenetic algorithmsen_US
dc.subjectpersonalizationen_US
dc.subjectreversed roulette wheel selection algorithmsen_US
dc.titlePersonalizing E-learning curriculum using: reversed roulette wheel selection algorithmen_US
dc.typePresentationen_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record