DocumentCode :
3294025
Title :
Content personalization in e learning environment
Author :
Benhamdi, S. ; Seridi, Hamid
Author_Institution :
Dept. of Comput. Sci., 8th May 1945 Univ., Guelma, Algeria
fYear :
2011
fDate :
4-6 Aug. 2011
Firstpage :
1
Lastpage :
6
Abstract :
For facilitating the use of e learning environments by teachers, we have proposed an approach that aid them to propose documents for learners taking in account their preferences and abilities, so allowing the personalization of these environments. This approach combines a pedagogical scenario design approach, using one of most used modelling languages IMS Learning Design (IMSLD), and taxonomy based one which is boosted-CSHTRL (Boosted Cold Start Hybrid Taxonomy Recommender for e Learning), developed to generate recommendation to learners, taking into consideration their preferences and abilities in order to motivate them, and consequently, improve efficiency and increase veracity of learner in the learning situation.
Keywords :
computer aided instruction; recommender systems; simulation languages; IMS learning design; IMSLD modelling language; boosted cold start hybrid taxonomy recommender; content personalization; e-learning environment; pedagogical scenario design approach; Educational institutions; Electronic learning; Graphical user interfaces; Measurement; Recommender systems; Taxonomy; Content personalization; IMSLD; recommender system; taxonomy;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Technology Based Higher Education and Training (ITHET), 2011 International Conference on
Conference_Location :
Kusadasi, Izmir
Print_ISBN :
978-1-4577-1673-7
Type :
conf
DOI :
10.1109/ITHET.2011.6018692
Filename :
6018692
Link To Document :
بازگشت