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Semantic Web Ontology Technology and Its Impact on E-Learning

Received: 21 September 2021     Accepted: 27 October 2021     Published: 10 November 2021
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Abstract

This paper aims at portraying the imparts of integrating semantic web ontology technology into conventional online learning platform. This semantic e-learning system will have all the features of existing e-learning system as well as additional feature of semantic web ontology technology, which provides an adaptable, personalized and intelligent learning environment. With the incorporation of this technology, students can access the learning materials uploaded on the learning environment by the instructors as well as engage on self-directed learning by searching the ontology backbone of the semantic web. The ontology repository within the e-learning platform helps to maintain learners’ personalization details, as well as learning resources pertaining to different domains of knowledge and with the help of intelligent search engine, learners can semantically search through the ontology for learning materials based on their preferences, thus they are not placed at the mercy of the learning materials provided by the instructors. This semantic web ontology will be very helpful in promoting customized learning, thereby replacing the existing instructor centric e-learning systems. This paper has been able to show the tremendous improvement in electronic learning, following the integration of semantic web ontology approach and it will be very helpful to schools and other learning institutions in providing a sophisticated and adaptable learning environment for their students or learners.

Published in American Journal of Embedded Systems and Applications (Volume 8, Issue 2)
DOI 10.11648/j.ajesa.20210802.11
Page(s) 12-16
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), 2021. Published by Science Publishing Group

Keywords

Electronic-Learning, Semantic Web, Ontology, Resource Description Framework (RDF), Web Ontology Language (OWL)

References
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[4] Colchester, K., Hagras, H., Alghazzawi, D. and Aldabbagh, G. (2016). A Survey of Artificial Intelligence Techniques Employed for Adaptive Educational Systems within E-Learning Platforms,” J. Artif. Intell. Soft Comput. Res., vol. 7, no. 1, pp. 47–64.
[5] Dicheva, D. (2008), Ontologies and semantic web for E-learning. In: Adelsberger, H., Kinshuk, Pawlowski, J. M., Sampson, D. G. (eds.) Handbook on Information Technologies for Education and Training, pp. 47-65. Springer, Heidelberg https://doi.org/ 10.1007/978-3- 540-74155-8_3.
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Cite This Article
  • APA Style

    Oluchukwu Uzoamaka Ekwealor, Sylvanus Okwudili Anigbogu, Ifeoma Mary Ann Orji, Chukwuemeka Micheal Okafor. (2021). Semantic Web Ontology Technology and Its Impact on E-Learning. American Journal of Embedded Systems and Applications, 8(2), 12-16. https://doi.org/10.11648/j.ajesa.20210802.11

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    ACS Style

    Oluchukwu Uzoamaka Ekwealor; Sylvanus Okwudili Anigbogu; Ifeoma Mary Ann Orji; Chukwuemeka Micheal Okafor. Semantic Web Ontology Technology and Its Impact on E-Learning. Am. J. Embed. Syst. Appl. 2021, 8(2), 12-16. doi: 10.11648/j.ajesa.20210802.11

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    AMA Style

    Oluchukwu Uzoamaka Ekwealor, Sylvanus Okwudili Anigbogu, Ifeoma Mary Ann Orji, Chukwuemeka Micheal Okafor. Semantic Web Ontology Technology and Its Impact on E-Learning. Am J Embed Syst Appl. 2021;8(2):12-16. doi: 10.11648/j.ajesa.20210802.11

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  • @article{10.11648/j.ajesa.20210802.11,
      author = {Oluchukwu Uzoamaka Ekwealor and Sylvanus Okwudili Anigbogu and Ifeoma Mary Ann Orji and Chukwuemeka Micheal Okafor},
      title = {Semantic Web Ontology Technology and Its Impact on E-Learning},
      journal = {American Journal of Embedded Systems and Applications},
      volume = {8},
      number = {2},
      pages = {12-16},
      doi = {10.11648/j.ajesa.20210802.11},
      url = {https://doi.org/10.11648/j.ajesa.20210802.11},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajesa.20210802.11},
      abstract = {This paper aims at portraying the imparts of integrating semantic web ontology technology into conventional online learning platform. This semantic e-learning system will have all the features of existing e-learning system as well as additional feature of semantic web ontology technology, which provides an adaptable, personalized and intelligent learning environment. With the incorporation of this technology, students can access the learning materials uploaded on the learning environment by the instructors as well as engage on self-directed learning by searching the ontology backbone of the semantic web. The ontology repository within the e-learning platform helps to maintain learners’ personalization details, as well as learning resources pertaining to different domains of knowledge and with the help of intelligent search engine, learners can semantically search through the ontology for learning materials based on their preferences, thus they are not placed at the mercy of the learning materials provided by the instructors. This semantic web ontology will be very helpful in promoting customized learning, thereby replacing the existing instructor centric e-learning systems. This paper has been able to show the tremendous improvement in electronic learning, following the integration of semantic web ontology approach and it will be very helpful to schools and other learning institutions in providing a sophisticated and adaptable learning environment for their students or learners.},
     year = {2021}
    }
    

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  • TY  - JOUR
    T1  - Semantic Web Ontology Technology and Its Impact on E-Learning
    AU  - Oluchukwu Uzoamaka Ekwealor
    AU  - Sylvanus Okwudili Anigbogu
    AU  - Ifeoma Mary Ann Orji
    AU  - Chukwuemeka Micheal Okafor
    Y1  - 2021/11/10
    PY  - 2021
    N1  - https://doi.org/10.11648/j.ajesa.20210802.11
    DO  - 10.11648/j.ajesa.20210802.11
    T2  - American Journal of Embedded Systems and Applications
    JF  - American Journal of Embedded Systems and Applications
    JO  - American Journal of Embedded Systems and Applications
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    EP  - 16
    PB  - Science Publishing Group
    SN  - 2376-6085
    UR  - https://doi.org/10.11648/j.ajesa.20210802.11
    AB  - This paper aims at portraying the imparts of integrating semantic web ontology technology into conventional online learning platform. This semantic e-learning system will have all the features of existing e-learning system as well as additional feature of semantic web ontology technology, which provides an adaptable, personalized and intelligent learning environment. With the incorporation of this technology, students can access the learning materials uploaded on the learning environment by the instructors as well as engage on self-directed learning by searching the ontology backbone of the semantic web. The ontology repository within the e-learning platform helps to maintain learners’ personalization details, as well as learning resources pertaining to different domains of knowledge and with the help of intelligent search engine, learners can semantically search through the ontology for learning materials based on their preferences, thus they are not placed at the mercy of the learning materials provided by the instructors. This semantic web ontology will be very helpful in promoting customized learning, thereby replacing the existing instructor centric e-learning systems. This paper has been able to show the tremendous improvement in electronic learning, following the integration of semantic web ontology approach and it will be very helpful to schools and other learning institutions in providing a sophisticated and adaptable learning environment for their students or learners.
    VL  - 8
    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, Nnamdi Azikiwe University, Awka, Nigeria

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