Artificial intelligence

Abstract: The experience of organizing the educational process during the quarantine caused by the COVID-19 pandemic is considered. Using of interactive technologies that allow organizing instant audio communication with a remote audience, as well as intelligent tools based on artificial intelligence that can help educational institutions to work more efficiently. Examples of sufficient use of artificial intelligence in distance learning are given. Particular attention is paid to the development of intelligent chatbots intended for use in communications with students of online courses of educational web portals. The use of technologies of ontology formation based on automatic extraction of concepts from external sources is offered, what can lead to greater acceleration of construction of the intellectual component of chatbots. Artificial intelligence tools can become an essential part of distance learning during this global COVID-19 pandemic. While educational institutions are closed to quarantine and many of them transitioned to distance learning lecturers and schoolteachers, as well as students and schoolchildren faced with the necessity to study in this new reality. The impact of these changes depends on people's ability to learn and on the role that the education system will play in meeting the demand for quality and affordable training. The experience of organizing the educational process at the University of Education Management of the National Academy of Pedagogical Sciences of Ukraine in the quarantine caused by the COVID-19 pandemic showed that higher and postgraduate institutions were mostly ready to move to distance learning. However, most distance learning systems, on whatever platform they are organized, need to be supplemented: the ability to broadcast video (at least ‒ one-way streaming), providing fast transmission of various types of information, receiving instant feedback when voting, polls and more. The structure of each section of the training course for the online learning system should fully cover the training material and meet all the objectives of the course. Appropriate language should be used, and wording, syntax, and presentation of tasks should be considered. One of the areas of application of artificial intelligence technologies in online learning is the use of chatbots which are characterrized by the following properties. It is advisable to use computer ontologies to ensure the intellectualization of chatbots. In this case, the metadata must be understandable to both humans and software and meet the requirements of modern standards in the field of information technology. The extraction of concepts from external data sources was carried out to build the ontology.

Keywords: distance education, artificial intelligence, ontology, chatbot, COVID-19

References:

1. Recommendations for the introduction of blended learning in institutions of professional higher and higher education https://mon.gov.ua/storage/app/media/vishcha- osvita/2020/zmyshene%20navchanny/zmishanenav channia-bookletspreads-2.pdf
2. Erica Southgate. 2020. Artificial intelligence, ethics, equity and higher education. Technical Report. National Centre for Student Equity in Higher Education, Curtin University and the University of Newcastle, Callaghan, Australia. 1–20 pages.
3. Kulmanov, M., Smaili, F. Z., Gao, X., & Hoehndorf, R. (2020). Semantic similarity and machine learning with ontologies. Briefings in Bioinformatics. doi:10.1093/bib/bbaa199
4. Petkovič, D., Denić, N. & Perenić, G. (2017). An Ontology-based Model for Contextual Recommendations in e-learning. International Journal of Technology in Education and Science, 1(1), 18-23. Retrieved November 22, 2020 from https://www.learntechlib.org/p/207271.
5. Nuobei SHI, Qin Zeng and Raymond Lee. The design and implementation of Language Learning Chatbot with XAI using Ontology and Transfer Learning. 7th International Conference on Computer Science, Engineering and Information Technology (CSEIT 2020), 26-27 September 2020, Copenhagen (Denmark). DOI:10.5121/CSIT.2020.101124.
6. AI in Eastern Europe Industry Landscape [Еlectronic resource]. – Mode of access: https://mindmaps.dka.global/ai-in-eastern-europe.
7. Nerodenko V. Generation of tests of various complexity levels in e-learning system based on educational text formalization model / Nerodenko V., Tytenko S. // Modern Aspects of Software Development: Proceedings of VI International Scientific and Practical Virtual Conference of Software Development Specialists, June, 24 2019 р. – Kyiv: Igor Sikorsky KPI, 2019. – pp. 121-133.
8. Priadko, Andrii & Osadcha, Kateryna & Khmelnytsky, Bogdan. (2020). Development of a chatbot for informing students of the schedule.
9. Lande DV, Boychenko AV Methods of developing scenarios for the development of the situation based on the analysis of the information space. Information Technology and Security. July- December 2017. Vol. 5. Iss. 2 (9). - P. 5 – 12. DOI: 10.20535/2411-1031.2017.5.2.136921
10. Senchenko VR, Boychenko AV Boychenko OA Research of methods and technologies of integration of ontological model with relational data. Registration, storage and data processing.. − 2017. − T. 20, No 3. – с. 91 – 101.