An Intelligent Service-based Layered Architecture for elearning and eAssessment.

Qaisar Javaid; Muhammad Arif; Shah Nawaz Talpur; Umaira Hmed Korai; Munamali Shah

Author(s)

Qaisar Javaid Department of Computer Science & Software Engineering, International Islamic University, Islamabad, Pakistan

Muhammad Arif Department of Computer Science, University of Gujrat, Pakistan

Shah Nawaz Talpur Department of Computer Systems Engineering, Mehran University of Engineering & Technology, Jamshoro. Pakistan

Umaira Hmed Korai Department of Telecommunication Engineering, Mehran University of Engineering & Technology, Jamshoro. Pakistan

Munamali Shah Department of Computer Science, COMSATS Institute of Information Technology, Islamabad, Pakistan

Abstract

The rapid advancement in ICT (Information & Communication Technology) is causing a paradigm shift in eLearning domain. Traditional eLearning systems suffer from certain shortcomings like tight coupling of system components, lack of personalization, flexibility, and scalability and performance issues. This study aims at addressing these challenges through an MAS (Multi Agent System) based multi-layer architecture supported by web services. The foremost objective of this study is to enhance learning process efficiency by provision of flexibility features for learning and assessment processes. Proposed architecture consists of two sub-system namely eLearning and eAssesssment. This architecture comprises of five distinct layers for each sub-system, with active agents responsible for miscellaneous tasks including content handling, updating, resource optimization, load handling and provision of customized environments for learners and instructors. Our proposed architecture aims at establishment of a facilitation level to learners as well as instructors for convenient acquisition and dissemination of knowledge. Personalization features like customized environments, personalized content retrieval and recommendations, adaptive assessment and reduced response time, are believed to significantly enhance learning and tutoring experience. In essence characteristics like intelligence, personalization, interactivity, usability, laidback accessibility and security, signify aptness of proposed architecture for improving conventional learning and assessment processes. Finally we have evaluated our proposed architecture by means of analytical comparison and survey considering certain quality attributes.

Publication Details

Page(s) 97-116

DOI DOI not available

Published Journal: Mehran University Research Journal of Engineering and Technology, Volume: 36, Issue: 1, Year: 2017

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