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Assessing Ukrainian education security in the context of artificial intelligence integration for accelerated post-war recovery

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Category: Content №6 2024

Last Updated on 28 December 2024

Published on 30 November -0001

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Authors:

V.D.Zalizko*, orcid.org/0000-0001-5362-8270, National Academy of Security Service of Ukraine, Kyiv, Ukraine; Zurich University of Teacher Education, Zurich, Switzerland, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

A.M.Cherniak, orcid.org/0000-0002-4958-783X, National Academy of Security Service of Ukraine, Kyiv, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

D.W.Nowak, orcid.org/0000-0001-7448-6101, Poznan University of Economics and Business, Poznan, the Republic of Poland, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

V.Y.Artemov, orcid.org/0000-0002-5290-4496, National Academy of Security Service of Ukraine, Kyiv, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

* Corresponding author e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

повний текст / full article

Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu. 2024, (6): 119 - 128

https://doi.org/10.33271/nvngu/2024-6/119

Abstract:

Purpose. Integral assessment of the security situation in the Ukrainian education system under the intensive implementation of Artificial Intelligence (AI) technologies and identification of promising scenarios for the post-war reconstruction of Ukraine, using the example of rural education.

Methodology. The scientific research was based on general scientific methods, supplemented by a comprehensive econometric analysis of the main indicators of educational security in Ukraine. Optimisation and integral evaluation methods were also used, which do not require the involvement of experts from various fields of educational activity. The key tool in the integrated multi-factor evaluation method is the module of intelligent economic-mathematical modeling and forecasting of optimistic, realistic, and pessimistic scenarios for the implementation of digital initiatives for the post-war recovery of the educational system of Ukraine, which is implemented through the method of principles, the “t-criterion” in the calculation of scalar thresholds based on IBM SPSS Modeler, AI-Prophet, Cloud Pak for Data, and R-Studio AI.

Findings. The work highlights the key factors influencing the level of security of the Ukrainian rural education system and defines the corresponding integrated index of educational security, which in further research can play a key role in strengthening the economic security of the national economy in the era of post-war reconstruction of the country and the formation of a new digital economy in Ukraine. Based on the obtained integrated assessment of the security of the educational system, the authors have identified probable trajectories for the transformation of educational processes in the context of the use of AI technologies. Key scenarios for the improvement of tactical and strategic management tools in the education sector are proposed in order to accelerate the processes of high-quality digital transformation aimed at the post-war recovery of Ukraine.

Originality. Based on the developed innovative digital platform “Central European Network for Sustainable and Innovative Economy”, an open source program IIS-GPT 3 was created, which, unlike the existing analogues, integrates new algorithms for the use of AI technology for forecasting key security indicators based on SPSS and AI-Prophet. This made it possible to carry out an independent integral assessment, modelling and forecasting of the transformation of the processes of strengthening the educational security of Ukraine in the context of post-war reconstruction.

Practical value. The conducted research proves the relevance of the modern national educational policy of digitization and indicates the potential benefits, challenges, and risks, particularly regarding the implementation of a digital environment with AI elements “Dream”, which can become a game changer in Ukrainian education. The research materials form a scientific basis for further systematic analysis of the key post-war imperatives of educational security in Ukraine.

Keywords: educational security of Ukraine, artificial intelligence (AI), digital transformation, digitalization, post-war reconstruction

References.

1. Lee, V., Pope, D., Miles, S., & Zarate, R. (2024). Cheating in the age of generative AI: A high school survey study of cheating behaviors before and after the release of ChatGPT. Computers and Education: Artificial Intelligence, 7, 1-10, 100253. https://doi.org/10.1016/j.caeai.2024.100253.

2. Alfredo, R., Echeverria, V., Jin, Y., & Yan, L. (2024). Human-centred learning analytics and AI in education: a systematic literature review. Computers and Education: Artificial Intelligence, 6, 100215. https://doi.org/10.1016/j.caeai.2024.100215.

3. Dyvan, K., Srinivasa, S., Suri, G., Agarwal, S., & Ram, P. (2023). Creating educational content based on artificial intelligence and expanding the learning path to increase student engagement. Computers and Education: Artificial Intelligence, 4, 100-110. https://doi.org/10.1016/j.caeai.2022.100110.

4. Weissman, S., Ayalon, M., & Leikin, R. (2023). Unravelling Tutors’ Conceptions of Teaching Mathematics in Virtual School Using a Goal-Action Model. International Journal of Science and Mathematics Education, 21, 1521-1543. https://doi.org/10.1007/s10763-022-10300-7.

5. Vizcaíno-Verdú, A., & Abidin, C. (2023). TeachTok: Teachers of TikTok, micro-celebrification, and fun learning communities. Teaching and Teacher Education, 123, 103978. https://doi.org/10.1016/j.tate.2022.103978.

6. Beege, M., Schroeder, L., Heidig, S., Rey, G., & Schneider, S. (2023). The instructor presence effect and its moderators in instructional video: A series of meta-analyses. Educational Research Review, 41, 100564. https://doi.org/10.1016/j.edurev.2023.100564.

7. Samusevych, Y., Novikov, V., Artyukhov, A., & Vasylieva, T. (2021). Convergence trends in the “economy ‒ education ‒ digitalization ‒ national security” chain. Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu, (6), 177-183. https://doi.org/10.33271/nvngu/2021-6/177.

8. Zhivko, Z., & Kuharska, L. (2019). Education in the country’s national security system. Academic notes of the University “STEP”, 2(54), 206-211. https://doi.org/10.31732/2663-2209-2019-53-205-211.

9. Panfilov, O., & Savchenko, O. (2021). Education as a factor to support the National security of the state. Bulletin of Yaroslav Mudryi National Law University, 1(48), 146-156. https://doi.org/10.21564/2075-7190.48.224807.

10. Chiou, E., Schroeder, N., & Craig, S. (2020). How we trust, perceive, and learn from virtual humans: The influence of voice quality. Computers & Education, 146, 103756. https://doi.org/10.1016/j.compedu.2019.103756.

11. Karan, B., & Angadi, G. (2023). Potential Risks of Artificial Intelligence Integration into School Education: A Systematic Review. Bulletin of Science, Technology & Society, 43(3-4), 67-85. https://doi.org/10.1177/02704676231224705

12. Rossiter, A., Nortcliffe, A., Griffin, A., & Middleton, A. (2015). Using student generated audio to enhance learning. Journal of the Higher Education Academy, 4(302), 52-61. https://doi.org/10.11120/ened.2009.04020052.

13. Désiron, J., & Schneider, S. (2024). Listen closely: Prosodic signals in podcast support learning. Computers & Education, 216, 105051. https://doi.org/10.1016/j.compedu.2024.105051.

14. Alekseieva, K., Novikova, І., Zalizko, V., Bediukh, O., & Gupta, S. (2023). Prognosis Assessment of the Role of Digital Platforms in Providing the Internationalization of the Knowledge Economy. Technological Forecasting & Social Change (the article uses my forecasting methodology and algorithm, preprint for printing in 2023). IJERR, 31(1), 1-11. https://doi.org/10.52756/10.52756/ijerr. 2023.v31spl.001.

15. Hwang, G.-J., & Tu, Y.-F. (2021). Roles and Research Trends of Artificial Intelligence in Mathematics Education: A Bibliometric Mapping Analysis and Systematic Review. Mathematics, 9(584). https://doi.org/10.3390/math9060584.

16. Zhou, C., & Zhang, W. (2024). Computational Thinking (CT) towards Creative Action: Developing a Project-Based Instructional Taxonomy (PBIT) in AI Education. Education Sciences, 14, 134. https://doi.org/10.3390/educsci14020134hjjj.

17. Scutari, M., & Denis, J.-B. (2021). Bayesian Networks: With Examples in R (2 ^nd ed.). Chapman and Hall/CRC. https://doi.org/10.1201/9780429347436.

18. Methodology for calculating the level of economic security of Ukraine: order of the Ministry of Economy of Ukraine No. 60 dated 03.2.2007. Retrieved from https://zakononline.com.ua/documents/show/117663___531337.

19. Verkhovna Rada of Ukraine (n.d.). On the approval of Methodological recommendations for calculating the level of economic security of Ukraine. Ministry of Economy of Ukraine 29.10.2013, Order No. 1277. Retrieved from https://zakon.rada.gov.ua/rada/show/v1277731-13#Text.

20. Leviatan, D., & Shevchuk, I. (2023). Coconvex Approximation of Periodic Functions. Constructive Approximation, 57, 695-726. https://doi.org/10.1007/s00365-022-09597-y.

21. Statistical Yearbook of Ukraine for 2022. State Statistics Service of Ukraine (2022). Retrieved from https://ukrstat.gov.ua/druk/publicat/kat_u/2023/zb/11/year_22_u.pdf.

22. Public report of the Head of the State Education Quality Service of Ukraine for 2023. State Education Quality Service of Ukraine (2023). Retrieved from https://sqe.gov.ua/wp-content/uploads/2024/02/Zvit_Golovi_SQE_16.02.2024.pdf.

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