An Intelligent Service-Based Layered Architecture for eLearning and eAssessment

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

Authors and Affiliations

Qaiser Javaid, Muhammad Arif, Shahnawaz Talpur, Umair Ahmed Korai, Munam Ali Shah

Keywords

Related Articles

A Novel Approach for Blind Estimation of Reverberation Time using Rayleigh Distribution Model

In this paper a blind estimation approach is proposed which directly utilizes the reverberant signal for estimating the RT (Reverberation Time).For estimation a very well-known method is used; MLE (Maximum Likelihood Est...

Sustainability Assessment for Dry, Conventional and Cryogenic Machining in Face Milling of Ti-6Al-4V

Sustainability achievement in difficult-to-machine materials is major concern now-a-days. This paper presents sustainability assessment of machining titanium alloy Ti-6Al-4V. Face milling of Ti-6Al-4V hardened to 55 HRC...

Cloud Based Remote FPGA Lab Platform: An Application of Internet of Things

IoT (Internet of Things) is the next generation of the Internet. The main goal of IoT is to connect each and every physical object to the Internet Cloud. This concept is introduced by bringing IoT technology to the labor...

Effect of Intercritical Heat Treatment on Mechanical Properties of Reinforcing Steel Bars

Intercritical heat treatments attempts were made to enhance the mechanical properties of reinforcing steel bars milled from scrap metal. For this, two grades of steel bars were obtained from different steel mills and the...

A New Hybrid Metaheuristic Algorithm for Wind Farm Micrositing

This work focuses on proposing a new algorithm, referred as HMA (Hybrid Metaheuristic Algorithm) for the solution of the WTO (Wind Turbine Optimization) problem. It is well documented that turbines located behind one ano...

Download PDF file
  • EP ID EP196175
  • DOI 10.22581/muet1982.1701.10
  • Views 86
  • Downloads 0

How To Cite

Qaiser Javaid, Muhammad Arif, Shahnawaz Talpur, Umair Ahmed Korai, Munam Ali Shah (2017). An Intelligent Service-Based Layered Architecture for eLearning and eAssessment. Mehran University Research Journal of Engineering and Technology, 36(1), 97-116. https://europub.co.uk/articles/-A-196175