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Enhanced E-learning Platform Using Semantic Web Ontology Technique

Received: 27 January 2022    Accepted: 14 February 2022    Published: 14 April 2022
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Abstract

This paper aims at improving the current electronic learning system by integrating ontology based semantic web into the online learning platform. The system applies semantic web and ontology technology to e-learning environment, thereby providing customized learning based on learners’ need. With this system, learners can access the system anytime, anyplace, thus, they can study at their own pace using learning resources uploaded by instructors. The system also provides facilities such as semantic web search engine and ontology repository which houses knowledge data and their meta data through which students can engage on personalized learning. Through the search engine provided, the learner semantically searches the repository for the required learning resources. The results obtained from the search is filtered according to the learner’s predefined preference by matching them with the learner’s profile. After the filtering, the results that most appropriately satisfy the user’s academic need is presented to the learner. This work will help to encourage self-directed learning as well as saves the students, the time wasted in surfing the network for learning resources, as it narrows the search to specified learner’s preferences. The system will be beneficial to schools and other learning institutions.

Published in American Journal of Information Science and Technology (Volume 6, Issue 2)
DOI 10.11648/j.ajist.20220602.12
Page(s) 24-29
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2022. Published by Science Publishing Group

Keywords

Electronic-learning, Ontology, Repository, Semantic Web, Extensible Markup Language (XML), Uniform Resource Identifier (URI)

References
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[2] Convetini, N., Alanese, D., Marengo, A., Marengo, V., and Scalera, M. (2006), “The OSEL taxonomy for the classification of learning objects”, Interdisciplinary Journal of Knowledge and Learning Objects, 2, 125-138.
[3] Corcho, O., Fernández-López, M. and Gómez-Pérez, A. (2007). Ontology engineering: what are Ontologies and how can we build them, in Cardoso, J. (Ed.). Semantic Web: Theory, Tools and Applications, Information Science Reference London 44-70.
[4] De Nicola, M. (2004), Towards an Ontological Support for e-Learning Courses, OTM Workshops, LNCS 3292, pp. 773–777, 2004. © Springer-Verlag Berlin Heidelberg.
[5] Gotschall, M. (2000), E-learning strategies for executive education and corporate training. Fortune, 141 (10) S5-S59.
[6] Gruber, T. (1998), A translation approaches to portable ontology specifications” Knowledge Acquisition, vol. 5.
[7] Guarino, N. (1998), “Formal ontology and information systems”, In N. Guarino (Ed.), Proceedings FOIS‟98 pp. 3-15, Amsterdam, IOS Press.
[8] Hall, B. (1997). Web-based training cookbook. New York: Wiley.
[9] Hall, B., & Snider, A. (2000) Glossary: The hottest buzz words in the industry.
[10] Hisham, M., Saud, M. and Kamin, Kamin, Y. (2018), “E-learning as Cooperative Problem Based Learning (CPBL) Support Elements in Engineering Education”.
[11] Jovanovic, J., Gasevic, D., Torniai, C. and Devedzic, V. (2009), Using semantic web technologies to provide contextualized feedback to instructors. In: Dicheva, D., Mizoguchi, R.
[12] Karon, R. L. (2000). Bankers go online: Illinois banking company learns benefits of e-training 1 (1) 38-40.
[13] Koper R. (2004), Use of the Semantic Web to Solve Some Basic Problems in Education: Work-load. Journal of Interactive Media in Education.
[14] Markellou p., MousouroulI I., Spiros S, and Tsakalidis A. (2005), Using Semantic Web Mining Technologies for Personalized E-Learning Experiences, Proceedings of the Web-Based Education, Grindelwald.
[15] McIlraith, S., Son, T. and Zeng, H. (2001). Semantic web services. IEEE Intelligent Systems, technologies to provide contextualized feedback to instructors. In: Dicheva, D., Mizoguchi, R., technologies to provide contextualized feedback to instructors. In: Dicheva, D., Mizoguchi, R.,
[16] Stojanovic, L., Staab, S. and Studer, H. (2001). E-learning based on the Semantic Web”,
[17] Urdan, T. A., & Weggen C. C. (2000). Corporate e-learning: Exploring a new frontier. WR Hambrecht + Co.
Cite This Article
  • APA Style

    Oluchukwu Uzoamaka Ekwealor, Sylvanus Okwudili Anigbogu, Ifeoma Mary Ann Orji, Chidi Ukamaka Betrand. (2022). Enhanced E-learning Platform Using Semantic Web Ontology Technique. American Journal of Information Science and Technology, 6(2), 24-29. https://doi.org/10.11648/j.ajist.20220602.12

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    ACS Style

    Oluchukwu Uzoamaka Ekwealor; Sylvanus Okwudili Anigbogu; Ifeoma Mary Ann Orji; Chidi Ukamaka Betrand. Enhanced E-learning Platform Using Semantic Web Ontology Technique. Am. J. Inf. Sci. Technol. 2022, 6(2), 24-29. doi: 10.11648/j.ajist.20220602.12

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    AMA Style

    Oluchukwu Uzoamaka Ekwealor, Sylvanus Okwudili Anigbogu, Ifeoma Mary Ann Orji, Chidi Ukamaka Betrand. Enhanced E-learning Platform Using Semantic Web Ontology Technique. Am J Inf Sci Technol. 2022;6(2):24-29. doi: 10.11648/j.ajist.20220602.12

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  • @article{10.11648/j.ajist.20220602.12,
      author = {Oluchukwu Uzoamaka Ekwealor and Sylvanus Okwudili Anigbogu and Ifeoma Mary Ann Orji and Chidi Ukamaka Betrand},
      title = {Enhanced E-learning Platform Using Semantic Web Ontology Technique},
      journal = {American Journal of Information Science and Technology},
      volume = {6},
      number = {2},
      pages = {24-29},
      doi = {10.11648/j.ajist.20220602.12},
      url = {https://doi.org/10.11648/j.ajist.20220602.12},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajist.20220602.12},
      abstract = {This paper aims at improving the current electronic learning system by integrating ontology based semantic web into the online learning platform. The system applies semantic web and ontology technology to e-learning environment, thereby providing customized learning based on learners’ need. With this system, learners can access the system anytime, anyplace, thus, they can study at their own pace using learning resources uploaded by instructors. The system also provides facilities such as semantic web search engine and ontology repository which houses knowledge data and their meta data through which students can engage on personalized learning. Through the search engine provided, the learner semantically searches the repository for the required learning resources. The results obtained from the search is filtered according to the learner’s predefined preference by matching them with the learner’s profile. After the filtering, the results that most appropriately satisfy the user’s academic need is presented to the learner. This work will help to encourage self-directed learning as well as saves the students, the time wasted in surfing the network for learning resources, as it narrows the search to specified learner’s preferences. The system will be beneficial to schools and other learning institutions.},
     year = {2022}
    }
    

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  • TY  - JOUR
    T1  - Enhanced E-learning Platform Using Semantic Web Ontology Technique
    AU  - Oluchukwu Uzoamaka Ekwealor
    AU  - Sylvanus Okwudili Anigbogu
    AU  - Ifeoma Mary Ann Orji
    AU  - Chidi Ukamaka Betrand
    Y1  - 2022/04/14
    PY  - 2022
    N1  - https://doi.org/10.11648/j.ajist.20220602.12
    DO  - 10.11648/j.ajist.20220602.12
    T2  - American Journal of Information Science and Technology
    JF  - American Journal of Information Science and Technology
    JO  - American Journal of Information Science and Technology
    SP  - 24
    EP  - 29
    PB  - Science Publishing Group
    SN  - 2640-0588
    UR  - https://doi.org/10.11648/j.ajist.20220602.12
    AB  - This paper aims at improving the current electronic learning system by integrating ontology based semantic web into the online learning platform. The system applies semantic web and ontology technology to e-learning environment, thereby providing customized learning based on learners’ need. With this system, learners can access the system anytime, anyplace, thus, they can study at their own pace using learning resources uploaded by instructors. The system also provides facilities such as semantic web search engine and ontology repository which houses knowledge data and their meta data through which students can engage on personalized learning. Through the search engine provided, the learner semantically searches the repository for the required learning resources. The results obtained from the search is filtered according to the learner’s predefined preference by matching them with the learner’s profile. After the filtering, the results that most appropriately satisfy the user’s academic need is presented to the learner. This work will help to encourage self-directed learning as well as saves the students, the time wasted in surfing the network for learning resources, as it narrows the search to specified learner’s preferences. The system will be beneficial to schools and other learning institutions.
    VL  - 6
    IS  - 2
    ER  - 

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Author Information
  • Department of Computer Science, Nnamdi Azikiwe University, Awka, Nigeria

  • Department of Computer Science, Nnamdi Azikiwe University, Awka, Nigeria

  • Department of Computer Science, Nnamdi Azikiwe University, Awka, Nigeria

  • Department of Computer Science, School of Information and Communication Technology, Federal University of Technology, Owerri, Nigeria

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