DocumentCode
2088787
Title
LRMDCR: A Learner´s Role-Based Multi Dimensional Collaborative Recommendation for Group Learning Support
Author
Wan, Xin ; Ninomiya, Toshie ; Okamoto, Toshio
Author_Institution
Grad. Sch. of Inf. Syst., Univ. of Electro-Commun., Chofu
fYear
2008
fDate
1-5 July 2008
Firstpage
603
Lastpage
605
Abstract
In order to improve the ldquoeducational provisionrdquo to implement the e-learning recommender system, we propose a new recommendation approach which has been proven to be more suitable to realize personalized recommendation based on not only learning histories but also learning activities and learning processes which is defined as LRMDCR (a learnerpsilas role-based multidimensional collaborative recommendation). In the approach, firstly we use the Markov chain model to divide the group learners into advanced learners and beginner learners by using the learnerspsila learning activities and learning processes. Secondly we use the multidimensional collaborative filtering to decide the recommendation learning objects to every learner of the group.
Keywords
Markov processes; computer aided instruction; information filters; LRMDCR; Markov chain model; e-learning recommender system; group learning support; learner role-based multi dimensional collaborative recommendation; multidimensional collaborative filtering; Collaborative work; Educational technology; Electronic learning; Filtering; History; Information systems; International collaboration; Multidimensional systems; Recommender systems; Wide area networks; Markov Chain Model; multidimensional collaborative filtering; role-based;
fLanguage
English
Publisher
ieee
Conference_Titel
Advanced Learning Technologies, 2008. ICALT '08. Eighth IEEE International Conference on
Conference_Location
Santander, Cantabria
Print_ISBN
978-0-7695-3167-0
Type
conf
DOI
10.1109/ICALT.2008.63
Filename
4561780
Link To Document