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 |
Electronic-Learning, Semantic Web, Ontology, Resource Description Framework (RDF), Web Ontology Language (OWL)
[1] | Adelsberger H. (2003), “The Essen model: a step towards a standard learning process,” http://citeseer.ist.psu.edu/515384.html. |
[2] | Askar, P., Kalinyazgann, K., Altun, A., Pekince, S. (2008): An ontology driven model for E- learning in K-12 education. In: Kidd, T. T., Song, H. (eds.) Handbook of Research on Instructional Systems and Technology, pp. 107-116. IGI Global. |
[3] | Berners-Lee, T., Hendler, J., and Lassila, O. (2001), The Semantic Web. Scientific American Magazine. doi: 10.1038/scientificamerican0501-34. |
[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. |
[6] | Dicheva, D., Mizoguchi, R., and Greer, J., (2009). Semantic Web Technologies for e-Learning: The Future of Learning, vol. 4. IOS Press, Amsterdam A Semantic Web-Based Framework for Information Retrieval 105. |
[7] | Fayed G., Sameh, D. and Ahmad H. (2006), “E-learning Model Based on Semantic Web Technology”. International Journal of Computer and Information Science. |
[8] | Fischer, H., Heise, L., Heinz, M., Moebius, K., and Koehler, T. (2015). How to Identify E-Learning Trends in Academic Teaching: Methodological Approaches and the Analysis of Scientific Discourses. Interactive Technology and Smart Education 12 (1), 31-43. |
[9] | Garbacz, P., (2006), Towards a standard taxonomy of artifact functions, Applied Ontology, 1/3: 221-236. |
[10] | Gruber, T. (1998), A translation approaches to portable ontology specifications” Knowledge Acquisition, vol. 5. |
[11] | Guarino, N. (1998), “Formal ontology and information systems”, In N. Guarino (Ed.), Proceedings FOIS‟98 pp. 3-15, Amsterdam, IOS Press. |
[12] | Guri-Resenblit, S. (2005), “Distance Education in the Digital age: Common Misconceptionsand Challenging tasks”, International Journal of E-learning and Distance Education 23 (2), 105-122. |
[13] | Hisham, M., Saud, M. and Kamin, Kamin, Y. (2018), “E-learning as Cooperative Problem Based Learning (CPBL) Support Elements in Engineering Education”. |
[14] | Lawless, C. (2018). What is e-learning? LearnUpon Available at: https://www.learnupon.com /blog/what-is-elearning/ |
[15] | Liu, Q., Wu, L., Zhou, W., Mao, G., Huang, J. and Huang, H. (2020). A semantic web-based recommendation framework of educational resources in e-learning. Technology, Knowedge and Learning 25 (4), 811-833. |
[16] | 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. |
[17] | McIlraith, S., Son, T. and Zeng, H. (2001). Semantic web services. IEEE Intelligent Systems, 16: 46-53. |
[18] | Monachesi, P., Simov, K., Mossel, E., Osenova, P. and Lemnitzer, L. (2008), What ontologies can do for e-Learning. In: Proceedings of IMCL International Conference on Mobile and Computer Aided Learning, Amman, Jordan. |
[19] | Noy, N. McGuinness, D. (2004) “Ontology Development 101: A Guide to Creating Your First Ontology” Stanford University, Stanford, CA. |
[20] | Sallenaj, B, Salini M. and Siva V. (2010), “A Semantic Approach to Compute a Knowledge Portal For E-Learning Using Ontology. 4th International Conference on Distance Learning and Education. |
[21] | Sikos, L. (2015). Mastering Structured Data on the Semantic Web: From HTML5 Microdata to Linked open data. |
[22] | Stojanovic L, S Staab and R Studer, (2001). E-learning based on the Semantic Web”, WebNet 2001 - World Conference on the WWW and Internet. |
[23] | Rokou, F. P. et al., 2004. Modeling web-based educational systems: process design teaching model. Educat. Technol. Soc., 7: 42-50. |
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
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
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
@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} }
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 SP - 12 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 -