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Ontologies in education – state of the art

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Abstract

Ontologies are used with great success in education because they allow to formulate the representation of a learning domain by specifying all concepts involved, relations between concepts and all properties and conditions that exist. The goal of this paper is to present the field of ontologies and give an overview of recent research in the field, in the context of education. As this paper presents a literature review, papers from the last five years were collected from the IEEE Xplore database, analysed and categorized based on the use of ontologies for: curriculum modelling and management, describing learning domains, learning data, and e-learning services. From the collected papers, a slightly growing trend in the contribution of ontologies to educational systems can be observed. Most studies used ontologies for describing learning domains, and some of the 95 collected papers could not fit in just one category because a system used more than one ontology. Throughout the work, the following contributions have been made: the term ontology was defined, the most common types of ontologies and commonly used methodologies for building ontologies were identified, and an overview of existing systems that use ontologies in the domain of education was given.

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References

  • Akharraz, L., Mezouary, A. E., & Mahani, Z. (2018). To context-aware learner modeling based on ontology. 2018 IEEE Global Engineering Education Conference (EDUCON), (pp. 1326-1334). https://doi.org/10.1109/EDUCON.2018.8363383.

  • Allert, H., Markkanen, H., & Richter, C. (2006). Rethinking the use of ontologies in learning. EC-TEL'06 First European Conference on Technology Enhanced Learning , (pp. 115–125). Crete, Greece.

  • Alsanad, A., Chikh, A., & Mirza, A. (2019). A domain ontology for software requirements change management in global software development environment. IEEE Access, 7, 49352–49361.

    Article  Google Scholar 

  • Al-Yahya, M., George, R., & Alfaries, A. (2015). Ontologies in E-learning: Review of the literature. International Journal of Software Engineering and Its Applications, 9(2), 67–84.

    Google Scholar 

  • Arthi, C. I., Priya, R. L., & Rautela, R. (2018). Analysis and prediction of health issues for teaching profession using semantic techniques. 2018 International Conference on Smart City and Emerging Technology (ICSCET), (pp. 1-5). https://doi.org/10.1109/ICSCET.2018.8537368.

  • Bogdanova, D., & Snoeck, M. (2019). Use of personalized feedback reports in a blended conceptual Modelling course. 2019 ACM/IEEE 22nd International Conference on Model Driven Engineering Languages and Systems Companion (MODELS-C), (pp. 672-679). https://doi.org/10.1109/MODELS-C.2019.00103.

  • Bonk, C. (2016). Keynote: What is the state of E-learning? Reflections on 30 ways learning is changing. Journal of Open, Flexible, and Distance Learning, 20(2), 6–20.

    Google Scholar 

  • Busse, J., Humm, B., Lubbert, C., Moelter, F., Reibold, A., Rewald, M., et al. (2015). Actually, what does “ontology” mean? A term coined by philosophy in the light of different scientific disciplines. Journal of Computing and Information Technology, 23, 29–41.

  • Challco, G., Moreira, D., Bittencourt, I., Mizoguchi, R., & Isotani, S. (2015). Personalization of gamification in collaborative learning contexts using ontologies. IEEE Latin America Transactions, 13(6), 1995–2002.

    Article  Google Scholar 

  • Chandrasekaran, B., Josephson, J. R., & Benjamins, V. R. (1999). What are ontologies and why do we need them? IEEE Intelligent Systems and their Applications, 14(1), 20–26.

    Article  Google Scholar 

  • Cheng, B., Zhang, Y., & Shi, D. (2018). Ontology-based personalized learning path recommendation for course learning. 2018 9th International Conference on Information Technology in Medicine and Education (ITME), (pp. 531-535). https://doi.org/10.1109/ITME.2018.00123.

  • Cheniti-Belcadhi, L., El Khayat, G., & Said, B. (2019). Knowledge engineering for competence assessment on serious games based on semantic web. IEEE Second International Conference on Artificial Intelligence and Knowledge Engineering (AIKE) (pp. 163-166). California, US: IEEE.

  • Conde, A., Larrañaga, M., Arruarte, A., & Elorriaga, J. A. (2019). A combined approach for eliciting relationships for educational ontologies using general-purpose knowledge bases. IEEE Access, 7, 48339–48355. https://doi.org/10.1109/ACCESS.2019.2910079.

    Article  Google Scholar 

  • Corcho, O., Fernández-López, M., & Gómez-Pérez, A. (2003). Methodologies, tools and languages for building ontologies. Where is their meeting point? Data & Knowledge Engineering, 46, 41–64.

    Article  Google Scholar 

  • Dang, F., Tang, J., & Li, S. (2019). MOOC-KG: A MOOC knowledge graph for cross-platform online learning resources. 2019 IEEE 9th International Conference on Electronics Information and Emergency Communication (ICEIEC), (pp. 1-8). https://doi.org/10.1109/ICEIEC.2019.8784572.

  • Demaidi, M. N., Gaber, M. M., & Filer, N. (2018). OntoPeFeGe: Ontology-based personalized feedback generator. IEEE Access, 6, 31644–31664. https://doi.org/10.1109/ACCESS.2018.2846398.

    Article  Google Scholar 

  • Diatta, B., Basse, A., & Ouya, S. (2019a). Bilingual ontology-based automatic question generation. 2019 IEEE Global Engineering Education Conference (EDUCON), (pp. 679-684). https://doi.org/10.1109/EDUCON.2019.8725090.

  • Diatta, B., Basse, A., & Ouya, S. (2019b). PasOnto: Ontology for learning Pascal programming language. 2019 IEEE Global Engineering Education Conference (EDUCON), (pp. 749-754). https://doi.org/10.1109/EDUCON.2019.8725092.

  • Erazo-Garzón, L., Patiño, A., Cedillo, P., & Bermeo, A. (2019). CALMS: A context-aware learning Mobile system based on ontologies. 2019 Sixth International Conference on eDemocracy eGovernment (ICEDEG), (pp. 84-91). https://doi.org/10.1109/ICEDEG.2019.8734423.

  • Fernández, M., Gómez-Pérez, A., & Juristo, N. (1997). METHONTOLOGY: From ontological art towards ontological engineering. Proceedings of the Ontological Engineering AAAI-97 Spring Symposium Series, (pp. 33–40). Stanford, USA.

  • Fernández-López, M., & Gómez-Pérez, A. (2002). Overview and analysis of methodologies for building ontologies. The Knowledge Engineering Review, 17(2), 129–156.

    Article  Google Scholar 

  • Fuchs, K., & Henning, P. A. (2018). Cognitive space time: A model for human-centered adaptivity in E-learning. 2018 IEEE International Conference on Engineering, Technology and Innovation (ICE/ITMC), (pp. 1-9). https://doi.org/10.1109/ICE.2018.8436283.

  • Gasmi, H., & Bouras, A. (2018). Ontology-based education/industry collaboration system. IEEE Access, 6, 1362–1371. https://doi.org/10.1109/ACCESS.2017.2778879.

    Article  Google Scholar 

  • Gómez-Pérez, A., Fernández-López, M., & Corcho, O. (2004). Ontological engineering: With examples from the areas of knowledge management, e-commerce and the semantic web. London: Springer.

    Google Scholar 

  • Goncharow, A., Boekelheide, A., Mcquaigue, M., Burlinson, D., Saule, E., Subramanian, K., & Payton, J. (2019). Classifying pedagogical material to improve adoption of parallel and distributed computing topics. IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW) (pp. 312-319). Rio de Janeiro: IEEE.

  • Grivokostopoulou, F., Perikos, I., Paraskevas, M., & Hatzilygeroudis, I. (2019). An ontology-based approach for user Modelling and personalization in E-learning systems. 2019 IEEE/ACIS 18th International Conference on Computer and Information Science (ICIS), (pp. 1-6). https://doi.org/10.1109/ICIS46139.2019.8940269.

  • Gruber, T. (1993). A translation approach to portable ontology specifications. Knowledge Acquisition, 5(2), 199–220.

    Article  Google Scholar 

  • Guarino, N. (1998). Formal ontology in information systems. Amsterdam: IOS Press.

    Google Scholar 

  • Guarino, N., Uniti, S., & Giaretta, P. (1995). Ontologies and knowledge bases. Towards a terminological clarification. In N. Mars (Ed.), Towards very large knowledge bases (pp. 25–32). Amsterdam: IOS Press.

    Google Scholar 

  • Hafidh, R., Sharif, M., & Alsallal, M. (2019). Smart holistic model for children and youth with special educational needs and disabilities. International Conference on Computing, Electronics & Communications Engineering (iCCECE) (pp. 130-135). London, UK: IEEE.

  • Han, L. (2018). An interdisciplinary intelligent teaching system model based on college Students' cognitive ability. 2018 International Conference on Virtual Reality and Intelligent Systems (ICVRIS), (pp. 259-262). https://doi.org/10.1109/ICVRIS.2018.00070.

  • Heiyanthuduwage, S. R., Schwitter, R., & Orgun, M. (2014). Towards an OWL 2 profile for defining learning ontologies. IEEE 14th International Conference on Advanced Learning Technologies (pp. 553-555). Athens: IEEE.

  • Herre, H., Heller, B., Burek, P., Hoehndorf, R., Loebe, F., & Michalek, H. (2006). General Formal Ontology (GFO): A foundational ontology integrating objects and processes. Leipzig: University of Leipzig.

    Google Scholar 

  • Hnida, M., Idrissi, M. K., & Bennani, S. (2018). Overview of CALEP: A competency based learning path generation system. 2018 17th International Conference on Information Technology Based Higher Education and Training (ITHET), (pp. 1-6). https://doi.org/10.1109/ITHET.2018.8424772.

  • Ibrahim, M. E., Yang, Y., Ndzi, D. L., Yang, G., & Al-Maliki, M. (2019). Ontology-based personalized course recommendation framework. IEEE Access, 7, 5180–5199. https://doi.org/10.1109/ACCESS.2018.2889635.

    Article  Google Scholar 

  • IEEE. (1996). IEEE standard for developing software life cycle processes. In IEEE Std 1074-1995 (pp. 1–106). https://doi.org/10.1109/IEEESTD.1996.79663.

  • Ingavélez-Guerra, P., Robles-Bykbaev, V., Otón, S., Vera-Rea, P., Galán-Men, J., Ulloa-Amaya, M., & Hilera, J. R. (2018). A proposal based on knowledge modeling and ontologies to support the accessibility evaluation process of learning objects. 2018 Congreso Argentino de Ciencias de la Informática y Desarrollos de Investigación (CACIDI), (pp. 1-5). https://doi.org/10.1109/CACIDI.2018.8584355.

  • Issa, L., & Jusoh, S. (2019). Applying ontology in computational creativity approach for generating a story. 2019 2nd International Conference on new Trends in Computing Sciences (ICTCS), (pp. 1-6). https://doi.org/10.1109/ICTCS.2019.8923095.

  • Jabar, M. A., Khalefa, M. S., Abdullah, R. H., & Abdullah, S. (2013). Overview of types of ontology in the software development process. IEEE Conference on Open Systems (ICOS) (pp. 83-88). Kuching: IEEE.

  • Jensen, J. (2017). A systematic literature review of the use of Semantic Web technologies in formal education. British Journal of Educational Technology, 50, 1–13.

  • Jiang, H. (2019). An efficient semantic retrieval method for network education information resources. 2019 11th International Conference on Measuring Technology and Mechatronics Automation (ICMTMA), (pp. 522-526). https://doi.org/10.1109/ICMTMA.2019.00121.

  • Jounaidi, A., & Bahaj, M. (2017). Designing and implementing XML schema inside OWL ontology. International Conference on Wireless Networks and Mobile Communications (WINCOM), (pp. 1-7). Rabat.

  • Keet, M. (2018). An introduction to ontology engineering. Cape Town: Maria Keet.

    MATH  Google Scholar 

  • Kim, S., Ahn, K., & Kim, S. (2019). A method of educational quality administration based on hyper Meta ontology. IEEE International Conference on Computational Science and Engineering (CSE) and IEEE International (pp. 237-242). New York, NY, USA, USA : IEEE.

  • Kizilkaya, G., Torunand, E., & Askar, P. (2007). Restructuring E-learning with ontologies. International Conference on Computational Science and its Applications (pp. 161-164). Kuala Lumpur: Springer.

  • Klarin, K., Nazor, I., & Celar, S. (2019). Ontology literature review as guidelines for improving Croatian Qualification Framework . 42nd International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO), (pp. 1402–1407). Opatija.

  • Kubekov, B., Zhaksybaeva, N., Naumenko, V., & Utegenova, A. (2018). Methodology of formation of educational resources on the basis of ontology. 2018 IEEE 12th International Conference on Application of Information and Communication Technologies (AICT), (pp. 1-6). https://doi.org/10.1109/ICAICT.2018.8747069.

  • Lassila, O., & McGuinness, D. (2001). The role of frame-based representation on the Semantic Web. In Electronic Transactions on Artificial Intelligence (ETAI) Journal (vol. 6). KSL Tech Report Number KSL-01-02.

  • Lendyuk, T., Rippa, S., Bodnar, O., & Sachenko, A. (2018). Ontology application in context of mastering the knowledge for students. 2018 IEEE 13th International Scientific and Technical Conference on Computer Sciences and Information Technologies (CSIT), 2, pp. 123-126. https://doi.org/10.1109/STC-CSIT.2018.8526710.

  • Liao, S. (2005). Expert system methodologies and applications—A decade review from 1995 to 2004. Expert Systems with Applications, 28(1), 93–103.

    Article  Google Scholar 

  • Liu, Y., Ren, Y., Hu, L., & Liu, Z. (2012). Study on highway geological disasters knowledge base for remote sensing images interpretation. IEEE International Geoscience and Remote Sensing Symposium (pp. 6126-6129). Munich: IEEE.

  • Maffei, A., Giudici, M., & Samir, K. (2019). An ontological framework to support the creation and use of phenomenograpical knowledge. 2019 IEEE World Conference on Engineering Education (EDUNINE), (pp. 1-5). https://doi.org/10.1109/EDUNINE.2019.8875801.

  • Martínez-Ramírez, Y., Ramírez-Noriega, A., Zayas-Esquer, M., Miranda-Mondaca, S., Armenta-Bojorquez, J., Quintero-Fonseca, M., . . . Cortes-Velázquez, C. (2018). Architecture of mathematical knowledge management system in education: Ontology-based and case-based. 2018 International Symposium on Computers in Education (SIIE), (pp. 1-5). https://doi.org/10.1109/SIIE.2018.8586771.

  • Mitsis, K., Zarkogianni, K., Bountouni, N., Athanasiou, M., & Nikita, K. S. (2019). An ontology-based serious game Design for the Development of nutrition and food literacy skills. 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), (pp. 1405-1408). https://doi.org/10.1109/EMBC.2019.8856604.

  • Mizoguchi, R., Welkenhuysen, J., & Ikeda, M. (1995). Task ontology for reuse of problem solving knowledge. In Towards very large knowledge bases (pp. 46–59). Amsterdam: IOS Press.

  • Mosharraf, M., & Taghiyareh, F. (2019). Automatic syllabus-oriented remixing of open educational resources using agent-based modeling. In IEEE transactions on learning technologies. https://doi.org/10.1109/TLT.2019.2937084.

  • Nahhas, S., Bamasag, O., Khemakhem, M., & Bajnaid, N. (2019a). Bridging education and labor skills by a novel competency-based course linked-data model. IEEE Access, 7, 119087–119098. https://doi.org/10.1109/ACCESS.2019.2937233.

    Article  Google Scholar 

  • Nahhas, S., Bamasag, O., Khemakhem, M., & Bajnaid, N. (2019b). Leveraging linked data to propel competency-based education based on labour skills. 2019 2nd International Conference on Computer Applications Information Security (ICCAIS), (pp. 1-6). https://doi.org/10.1109/CAIS.2019.8769503.

  • NSF/IEEE-TCPP Curriculum Working Group. (2012). Curriculum initiative on parallel and distributed computing. Retrieved from NSF/IEEE-TCPP: https://tcpp.cs.gsu.edu/curriculum/. Accessed 14 Feb 2020.

  • Nurjanah, D. (2018). LifeOn, a ubiquitous lifelong learner model ontology supporting adaptive learning. 2018 IEEE Global Engineering Education Conference (EDUCON), (pp. 866-871). https://doi.org/10.1109/EDUCON.2018.8363321.

  • O'Leary, D. E. (1998). Using AI in knowledge management: Knowledge bases and ontologies. IEEE Intelligent Systems and their Applications, 13(3), 34–39.

    Article  Google Scholar 

  • Park, J., Sung, K., & Moon, S. (2008). Developing graduation screen ontology based on the METHONTOLOGY approach. Fourth International Conference on Networked Computing and Advanced Information Management (pp. 375-380). IEEE.

  • Piedra, N., & Caro, E. T. (2018). LOD-CS2013: Multileaming through a semantic representation of IEEE computer science curricula. 2018 IEEE Global Engineering Education Conference (EDUCON), (pp. 1939-1948). https://doi.org/10.1109/EDUCON.2018.8363473.

  • Rami, S., Bennani, S., & Idrissi, M. K. (2018). A novel ontology-based automatic method to predict learning style using Felder-silverman model. 2018 17th International Conference on Information Technology Based Higher Education and Training (ITHET), (pp. 1-5). https://doi.org/10.1109/ITHET.2018.8424774.

  • Raud, Z., Vodovozov, V., Petlenkov, E., & Serbin, A. (2018). Ontology-based design of educational trajectories. 2018 IEEE 59th International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON), (pp. 1-4). https://doi.org/10.1109/RTUCON.2018.8659893.

  • Robles-Bykbaev, V., Arévalo-Illescas, C., Carrera-Hidalgo, P., Robles-Bykbaev, Y., Tigre-Andrade, G., Ochoa-Fajardo, D., . . . Martínez-Gutiérrez, J. (2019). e-Ucumari: A multimedia device based on ontologies and embedded systems for pedagogical support of children with multi-disabilities. 2019 IEEE Colombian Conference on Communications and Computing (COLCOM), (pp. 1-6). https://doi.org/10.1109/ColComCon.2019.8809182.

  • Roussey, C., Pinet, F., Kang, M., & Corcho, O. (2011). An introduction to ontologies and ontology engineering. In G. Falquet, C. Métral, J. Teller, & C. Tweed (Eds.), Ontologies in urban development projects (pp. 9–38). London: Springer-Verlag.

    Chapter  Google Scholar 

  • Salem, A., & Nikitaeva, A. (2019). Knowledge engineering paradigms for smart education and learning systems. 42nd International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO) (pp. 1571-1574). Opatija: IEEE.

  • Samia, Z., Khaled, R., & Warda, Z. (2018). Multi-agent systems and ontology for supporting management system in smart school. 2018 3rd International Conference on Pattern Analysis and Intelligent Systems (PAIS), (pp. 1-8). doi:https://doi.org/10.1109/PAIS.2018.8598505.

  • Šarić, I., & Šerić, L. (2018, 9). Time spent online as an online learning behavior variable in a blended learning environment with an ontology-based intelligent tutoring system. 2018 26th International Conference on Software, Telecommunications and Computer Networks (SoftCOM), (pp. 1-6). https://doi.org/10.23919/SOFTCOM.2018.8555854.

  • Silva, V. J., & Dorça, F. A. (2019). An automatic and intelligent approach for supporting teaching and learning of software engineering considering design smells in object-oriented programming. 2019 IEEE 19th International Conference on Advanced Learning Technologies (ICALT), 2161-377X, pp. 321-323. https://doi.org/10.1109/ICALT.2019.00100.

  • Smith, B. (2004). Ontology. In L. Floridi (Ed.), The Blackwell guide to the philosophy of computing and information (pp. 153–166). Oxford: Blackwell Publishing Ltd..

    Google Scholar 

  • Somadasa, K., Karunadhipathi, M., Wickramasinghe, N., Subasingha, S., Kodagoda, N., & Suriyawansa, K. (2018). Online learning resources finder based on computer programming domain. 2018 IEEE International Conference on Information and Automation for Sustainability (ICIAfS), (pp. 1-5). https://doi.org/10.1109/ICIAFS.2018.8913365.

  • Soomro, S., Hafeez, A., Shaikh, A., & Musavi, S. H. A. (2014). Ontology based requirement interdependency representation and visualization. In: F. Shaikh, B. Chowdhry, S. Zeadally, D. Hussain, A. Memon, M. Uqaili (Eds.), Communication technologies, information security and sustainable development. IMTIC 2013. Communications in computer and information science (vol. 414). Cham: Springer.

  • The Joint Task Force on Computing Curricula. (2013). Computer Science Curricula 2013 - ACM. Retrieved January 17, 2020, from ACM: https://www.acm.org/binaries/content/assets/education/cs2013_web_final.pdf. Accessed 14 Feb 2020.

  • Uschold, M., & Gruninger, M. (1996). Ontologies: Principles, methods and applications. Knowledge Engineering Review, 11(2), 1–63.

    Article  Google Scholar 

  • van Heijst, G., van der Spek, R., & Kruizinga, E. (1996). Organizing corporate memories. In Tenth knowledge acquisition for knowledge (pp. 42.1–42.17). Banff: Gaines BR.

    Google Scholar 

  • W3C. (2013). OWL. Retrieved from W3C Semantic Web: https://www.w3.org/OWL/. Accessed 14 Feb 2020.

  • Wang, Y., & Zatarain, O. A. (2018). Design and implementation of a knowledge base for machine knowledge learning. 17th International Conference on Cognitive Informatics & Cognitive Computing (pp. 70-77). Berkeley, CA: IEEE.

  • Wang, Y., Wang, Z., Hu, X., Bai, T., Yang, S., & Huang, L. (2019). A courses ontology system for computer science education. 2019 IEEE International Conference on Computer Science and Educational Informatization (CSEI), (pp. 251-254). https://doi.org/10.1109/CSEI47661.2019.8938930.

  • Yessenova, K., Parker, J., Sadvakasova, Z., Syrgakbaeva, A., & Tazhina, G. (2020). Kazakhstani E-learning practice in higher education: The key trends and challenges. International Journal of Adult Education and Technology (IJAET), 11(1), 24–44.

    Article  Google Scholar 

  • Zhao, J., & Guo, J. (2019). Online distance learning precision service technology based on big data analysis. 2019 IEEE 4th International Conference on Cloud Computing and Big Data Analysis (ICCCBDA), (pp. 39-43). https://doi.org/10.1109/ICCCBDA.2019.8725711.

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The research has been co-funded by University of Rijeka (Croatia) under the project “uniri-drustv-18-182”.

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Throughout the work, the following contributions have been made: term ontology was defined; the most common types of ontologies and commonly used methodologies for building ontologies were identified; an overview of existing systems that use ontologies in the domain of education was given.

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Correspondence to Kristian Stancin.

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Stancin, K., Poscic, P. & Jaksic, D. Ontologies in education – state of the art. Educ Inf Technol 25, 5301–5320 (2020). https://doi.org/10.1007/s10639-020-10226-z

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