The week's pick
Reseach Article
E-Learner’s Collective Intelligent System Framework: Web Mining for Personalization in E-Learning 2.0 Ecosystem using Web 2.0 Technologies
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 66 - Number 4 |
| Year of Publication: 2013 |
| Authors: Hasnat Ahmad Hussny, Ahmed Mateen, Tasleem Mustafa, Muhammad Murtaza Nayyer |
10.5120/11069-5987
|
Hasnat Ahmad Hussny, Ahmed Mateen, Tasleem Mustafa, Muhammad Murtaza Nayyer . E-Learner’s Collective Intelligent System Framework: Web Mining for Personalization in E-Learning 2.0 Ecosystem using Web 2.0 Technologies. International Journal of Computer Applications. 66, 4 ( March 2013), 1-9. DOI=10.5120/11069-5987
Abstract
E-Learning 2. 0 ecosystem has turn out to be a trend in the world nowadays. The term E-Learning 2. 0 ecosystem was coined that came out during the emergence of Web 2. 0 technologies. Most of the researches overlook a deep-seated issue in the e-learner's foregoing knowledge on which the valuable intelligent systems are based. This research utilizes the e-Learner's collective intelligence knowledge and extracts useful information for appropriate target courses or resources as a part of a personalization procedure to construct the e-Learner's collective intelligent system framework for recommendation in e-learning 2. 0 ecosystem. This research based on a novel web usage mining techniques and introduces a novel approach to collective intelligence with the use of mashup and web 2. 0 technology approach to build a framework for an E-Learning 2. 0 ecosystem. It is incorporated in predictive model efficiently based on back-propagation network (BPN). A prototype system, named E-learner's Collective Intelligence System Framework, has been proposed which has features such as self-regulation, reusability, lightweight, end user oriented, and openness. To evaluate the proposed approach, empirical research is conducted for the performance evaluation.
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