Quality & Quantity

, Volume 49, Issue 6, pp 2435–2458 | Cite as

RETRACTED ARTICLE: An architecture of agent-based multi-layer interactive e-learning and e-testing platform

  • Muhammad ArifEmail author
  • Manzoor Illahi
  • Ahmad Karim
  • Shahaboddin Shamshirband
  • Khubaib Amjad Alam
  • Shahid Farid
  • Salman Iqbal
  • Zolkepli Buang
  • Valentina Emilia Balas


E-learning is the synthesis of multimedia and social media platforms powered by Internet and mobile technologies. Great popularity of e-learning is encouraging governments and educational institutions to adopt and develop e-learning cultures in societies in general and universities in particular. In traditional e-learning systems, all components (agents and services) are tightly coupled into a single system. In this study, we propose a new architecture for e-learning with two subsystems, namely, e-learning and e-testing. The motivation of the research is to improve the effectiveness of the learning process by extracting relevant features for elastic learning and testing process. We employ a multi-agent system because it contains five-layer architecture, including agents at various levels. We also propose a novel method for updating content through question and answer between e-learners and intelligent agents. To achieve optimization, we design a system that applies various technologies, which guarantee various dynamic features for e-learning systems, such as intelligence, distributed nature, adaptive attitude, interaction, accessibility, and security. Agent assisted e- learning enable the users to collect the quantifiable and sensible material; examine, and distribute customized knowledge from multiple e-learning sources. Intelligent agents, being program helper or assistants, are deployed at different levels of abstraction in this architecture to manage information overload and create environment for learners. Moreover, this proposed system is designed by keeping in view several characteristics specific to e-learning system such as interaction, personalization, adaptation, intelligence, interoperability, accessibility and security. The architecture is designed to support instructional design, to retrieve relevant learning materials, to process and analyses data to enable meaningful e-learning recommendations for instructors and learners by considering all issues that existing e-learning architectures don’t address. Most of the existing e-learning architectures don’t consider all the features in a single system so there is a need for a generic architecture that should support all the features to make the e-learning system more efficient. The outcome of this approach is to provide flexible and lightweight systems for e-learning environments.


E-learning Multi agents Architecture Collaborative Personalized Intelligent Adaptive Distributed Resource agent 


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Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  • Muhammad Arif
    • 1
    • 2
    Email author
  • Manzoor Illahi
    • 2
  • Ahmad Karim
    • 1
  • Shahaboddin Shamshirband
    • 3
    • 4
  • Khubaib Amjad Alam
    • 1
  • Shahid Farid
    • 1
  • Salman Iqbal
    • 1
  • Zolkepli Buang
    • 5
  • Valentina Emilia Balas
    • 6
  1. 1.Faculty of Computer Science and Information TechnologyUniversity of MalayaKuala LumpurMalaysia
  2. 2.Departmnet of Computer ScienceCOMSATS Institute of Information Technology IslamabadIslamabadPakistan
  3. 3.Faculty of Computer Science and Information Technology, Department of Computer System and TechnologyUniversity of MalayaKuala LumpurMalaysia
  4. 4.Department of Computer ScienceChalous Branch, Islamic Azad University (IAU), ChalousMazandaranIran
  5. 5.Universiti Teknikal Malaysia MelakaDurian TunggalMalaysia
  6. 6.Department of Automation and Applied InformaticsUniversity of AradAradRomania

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