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Moodle's Ontology Development from UML for Social Learning Network Analysis

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Published:02 May 2018Publication History

ABSTRACT

The online learning called e-learning is a new learning path that offers to learners to study at their own pace and at the moments that suit them. It is in this perspective that the semantic web has known its emergence in the field of e-learning to offer platforms content more personalized and more adapted to student's and teacher's needs. Since Moodle is the most popular e-learning platform, we propose in this paper to build its OWL ontology by exploring the representative data that we collected from its UML class diagram. The choice of UML class diagram as a basis for data collection for the development of the ontology is justified by the fact that the transition from UML to OWL ontology brings ontology development process closer to the wider software engineering population. The built ontology brings also great benefit in the field of the Social Learning Network Analysis. Because it gives the opportunity to study the behavior of the platform users by giving meaning to their relationships instead of modelling them only as knots and edges.

References

  1. M.F Goodchild. 2007.Citizens As Voluntary Sensors: Spatial Data Infrastructure in The World Of Web 2.0. International Journal of Spatial Data Infrastructures Research, Vol. 2, 24--32.Google ScholarGoogle Scholar
  2. T. Berners-Lee, J. Hendler, and O. Lassila. 2001.The semantic web", Scientific American, vol. 5, no. 284, 34--43.Google ScholarGoogle ScholarCross RefCross Ref
  3. S. Grimm, A. Abecker, J. Völker, and R. Studer. 2011. Ontologies and the Semantic Web. Handbook of Semantic Web Technologies. Springer, Part 1, 507--579.Google ScholarGoogle Scholar
  4. A. Maedche, 2002. Ontology Learning For The Semantic Web. Springer US. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. P.N Pirnay-Dummer. 2012. Ontology And Semantic Web, Encyclopedia of the Sciences of Learning. Springer US. 2507--2510.Google ScholarGoogle Scholar
  6. M. Al-Yahya, R. George, and A. Alfaries. 2015. Ontologies in E-Learning: Review of the Literature, International Journal of Software Engineering and its Applications. Vol 9, No. 2, 67--84.Google ScholarGoogle Scholar
  7. M. Rani, R. Nayak, and O.P Vyas. 2015. An Ontology-Based Adaptive Personalized E-Learning System, Assisted by Software Agents on Cloud Storage. Elsevier, The Journal of Knowledge-Based Systems, Volume 90, 33--48. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. T. Li, H. Yang, J.He, and Y. Ai. 2010. A Social Network Analysis Methods Based on Ontology. IEEE, 3rd International Symposium on Knowledge Acquisition and Modeling.Google ScholarGoogle Scholar
  9. A. Besse, F.Mansur, F, and N.Yusof. 2013. Social Learning Network Analysis Model to Identify Learning Patterns Using Ontology Clustering Techniques and Meaningful Learning. The Journal of computers and Education. Elsevier. Vol 63, 73--86. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. N. Yusuf, A. Besse, and F. Mansur. 2013. Ontology Developpement of E-Learning Moodle for Social Network Analysis. World Academy of Science, Engineering and Technology. Vol:7.Google ScholarGoogle Scholar
  11. K. Rezgui, H. Mhiri, and K.Ghedira. 2014. Extending Moodle Functionalities with Ontology-Based Competency Management. Elsevier. 18th International Conference On Knowledge-based Intelligent Information & Engineering Systems-KES2014, Procedia Computer Science, Volume 35,) 570--579.Google ScholarGoogle Scholar
  12. H. Jia, M.Wanga, W. Ran, S.J.H.Yang, J. Liao, and D. K.W. Chiu. 2011. Design of a Performance-Oriented Workplace E-Learning System Using Ontology. The Journal of Expert Systems with Applications. Elsevier, Volume 38, Issue 4, 3372--3382. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. S. Cakulaa, M. Sedleniecea. 2013. Development of a Personalized E-Learning Model Using Methods Of Ontology. Procedia Computer Science, Volume 26,113--120.Google ScholarGoogle ScholarCross RefCross Ref
  14. N. Arch-int and S. Arch-int.2013. Semantic Ontology Mapping for Interoperability of Learning Resource Systems Using a Rule-Based Reasoning Approach. Expert Systems with Applications. Volume 40, Issue 18, 7428--7443.Google ScholarGoogle Scholar
  15. K. Chu, Ch. Lee, and R. Tsai. 2011.Ontology Technology to Assist Learners' Navigation in The Concept Map Learning System. Expert Systems with Applications, Volume 38, Issue 9, Pages 11293--11299. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. S. Lukichev, M. Diaconescu, and A.Giurca. 2007. Empowering Moodle with Rules and Semantics. Proceedings, Vol. 1. No. 1.Google ScholarGoogle Scholar
  17. M.R.C Louhdi, H. Behja, and S.O El Alaoui. 2013. A Novel Method for Generating an E-Learning Ontology. International Journal of Data Mining& Knowledge Management Process (IJDKP), Vol 3, No 6. 151--169Google ScholarGoogle ScholarCross RefCross Ref
  18. B. Bouihi and M. Bahaj. 2016. Building an E-Learning System's OWL Ontology by Exploring the UML Model, Journal of Theoretical and Applied Information Technology, Vol 87, No 3.Google ScholarGoogle Scholar
  19. K. Curran and N. Curran. 2014. Social Networks Analysis. Big Data and Internet Of Things: A Roadmap for Smart Environments. Volume 546 of the series Studies in Computational Intelligence, 367--378.Google ScholarGoogle Scholar
  20. M. Horridge. 2011. A Practical Guide to Building OWL Ontologies Using Protégé 4 and Co-Ode Tools. Edition 1.3. The University Of ManchesterGoogle ScholarGoogle Scholar

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  • Published in

    cover image ACM Other conferences
    LOPAL '18: Proceedings of the International Conference on Learning and Optimization Algorithms: Theory and Applications
    May 2018
    357 pages
    ISBN:9781450353045
    DOI:10.1145/3230905

    Copyright © 2018 ACM

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    Publication History

    • Published: 2 May 2018

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    LOPAL '18 Paper Acceptance Rate61of141submissions,43%Overall Acceptance Rate61of141submissions,43%

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