IMPACT OF NEURAL NETWORKS ON ADAPTATION TO LEARNERS' EDUCATIONAL NEEDS AND THE IMPROVEMENT OF TEACHING METHODS

Shaira Haitbayeva, Karine Barmuta, Sergey Ignatyev, Alla Ignatyeva, Andrey Baksheev, Nikolay Gubachev

Abstract


Objective: This article explores the dynamic technological development of modern society with a focus on the application of neural networks in education.

Methods: Utilizing an integrated research approach that combines descriptive and comparative analytical methods, this study examines the role and potential of neural networks in enhancing the adaptability and effectiveness of higher education. A review of existing scientific literature provides a comprehensive overview of current trends.

Results: The study concludes that neural networks hold significant potential to revolutionize both teaching and learning processes. Education systems thus need to rapidly adapt to technological advancements and modify current educational practices to shape the future of teaching.

Conclusion: The article highlights the modern tools for applying neural networks in education and outlines their potential to significantly influence the education of future generations. It discusses how neural networks can transform educational processes into more accessible, flexible, and efficient experiences, although it also acknowledges the challenges and ethical concerns of integrating these technologies into higher education settings.


Keywords


Neural networks in education; Educational technology. Adaptive learning; Future of education; Educational innovation

References


Abdullaev, I., Prodanova, N., Bhaskar, K.A., Lydia, E.L., Kadry, S., & Kim, J. (2023). Task offloading and resource allocation in IoT based mobile edge computing using deep learning. Computers, Materials & Continua, 76(2), 1463-1477. https://doi.org/10.32604/cmc.2023.038417

Abdullayev, I., Akhmetshin, E., Nayanov, E., Otcheskiy, I., & Lyubanenko, A. (2024a). Possibilities of using online network communities in the educational process to develop professional skills in students. Revista Conrado, 20(98), 395-401.

Abdullayev, I., Osadchy, E., Shcherbakova, N., Kosorukova, I. (2025). An innovative approach to financial distress prediction using relative weighted neutrosophic valued distances. International Journal of Neutrosophic Science, 25(1), 370-381. https://doi.org/10.54216/IJNS.250133

Abdullayev, I.S., Akhmetshin, E.M., Krasnovskiy, E.E., Tuguz, N.S., & Mashentseva, G. (2024b). Soliton solutions to the DS and generalized DS system via an analytical method. Computational Methods for Differential Equations. https://doi.org/10.22034/cmde.2024.60337.2576

Aitimov, B.Z., Seriev, B.A., & Kopbasarova, G.K. (2015). Interaction of non-profit organizations with government bodies in the fight against corruption as a basis for citizens' economic rights protection. Actual Problems of Economics, 167(5), 95-102.

Akhmetshin, E. (2023). Enhancing advanced mathematical proficiency in economics students through software integration. Multidisciplinary Science Journal, 5, e2023064. https://doi.org/10.31893/multiscience.2023064

Auyelbek, M., Ybyraimzhanov, K., Andasbayev, E., Abdykerimova, E., & Turkmenbayev, A. (2022). Analysis of studies in the literature on educational robotics. Journal of Turkish Education, 19(4), 1267-1290.

Babaskin, D., Masharipov, F., Savinkova, O., Shustikova, N., & Volkova, N. (2024). Functional state of team sports athletes in the annual training cycle. Retos, 54, 106-113. http://dx.doi.org/10.47197/retos.v54.99620

Bakunova, O.M., Kalitenia, I.L., Bakunov, A.M., Paluiko, A.F., Antonov, E.D., & Grechko, I.S. (2018). Ispolzovanie neironnykh setei v obrazovanii [The use of neural networks in education]. Web of Scholar, 1(1(19)), 8-10.

Bobkov, V.N., Simonova, M.V., Loktyuhina, N.V., & Shichkin, I.A. (2020). Peculiarities of unstable employment in the era of a digital economy from data of social media of Russia. In S. Ashmarina, A. Mesquita, & M. Vochozka (Eds.), Digital transformation of the economy: Challenges, trends and new opportunities (pp. 235-243). Cham: Springer. https://doi.org/10.1007/978-3-030-11367-4_22

Bosov, A.V. (2022). Primenenie samoorganizuiushchikhsia neironnykh setei k protsessu formirovaniia individualnoi traektorii obucheniia [Application of self-organizing neural networks to the process of forming an individual learning path]. Informatics and Applications, 16(3), 7-15. https://doi.org/10.14357/19922264220302

Chumaceiro Hernández, A.C., Hernández García De Vela, J., Velazco Hernández, J., Lagusev, Y., & Rogozhina, A. (2022). The impact of sustainable development and social responsibility on quality education. Journal of Environmental Management and Tourism, 13(1), 51-62. https://doi.org/10.14505/jemt.v13.1(57).05

Filatova, O.N., Bulaeva, M.N., & Gushchin, A.V. (2022). Primenenie neirosetei v professionalnom obrazovanii [Application of neural networks in vocational education]. Problemy sovremennogo pedagogicheskogo obrazovaniya, 77-3, 243-245.

Fiore, U. (2019). Neural networks in the educational sector: Challenges and opportunities. Balkan Region Conference on Engineering and Business Education, 1(1), 332-337.

Hernández García de Velazco, J.J. (2022). Sociedades del conocimiento y ciencia abierta en la nueva normalidad. Jurídicas CUC, 18(1), 1-4.

Ilin, I.G. (2024). Personal data in artificial intelligence systems: Natural language processing technology. Journal of Digital Technologies and Law, 2(1), 123-140. https://doi.org/10.21202/jdtl.2024.7

Ilyushin, Y., & Martirosyan, A. (2024). The development of the soderberg electrolyzer electromagnetic field's state monitoring system. Scientific Reports, 14, 3501. https://doi.org/10.1038/s41598-024-52002-w

Kasatkina, T.I. (2021). Matematicheskoe modelirovanie obrazovatelnogo portala vuza na osnove tekhnologii neironnykh setei [Mathematical modeling of the university educational portal based on neural network technology]. Modeling, Optimization and Information Technology, 9(4), 1-12.

Kazachenok, V.V. (2019). Primenenie neironnykh setei dlia avtomatizatsii individualizirovannogo obucheniia [The usage of neural networks for the automization of individualized learning]. In M.V. Noskov (Ed.), Informatizatsiia obrazovaniia i metodika elektronnogo obucheniia: Proceedings of the III International scientific conference (Part 3, pp. 244-250). Krasnoyarsk: Siberian Federal University.

Kazachenok, V.V. (2020). Primenenie neironnykh setei v obuchenii [Application of neural networks in training]. Informatics and Education, 2, 41-47. https://doi.org/10.32517/0234-0453-2020-35-2-41-47

Khabibullin, I.R., Azovtseva, O.V., & Gareev, A.D. (2023). Aktualnost ispolzovaniia neirosetei v obrazovatelnykh tseliakh [The relevance of applying neural networks for educational purposes]. Young Scientist, 13(460), 176-178.

Koriakova, K.A., & Sudakova, O.V. (2023). Neiroseti kak novye instrumenty v obrazovanii [Neural networks as a new instrument in education]. Informatsionnyye tekhnologii v obrazovanii, 6, 180-186.

Kozlova, O.A., & Protasova, A.A. (2021). Ispolzovanie neironnykh setei v distantsionnykh obrazovatelnykh tekhnologiiakh dlia identifikatsii obuchaiushchikhsia [The use of neural networks in distance education technologies for the identification of students]. Open Education, 25(3), 26-35. https://doi.org/10.21686/1818-4243-2021-3-26-35

Kravtsova, A.G. (2023). Chatgpt-3: Perspektivy ispolzovaniia v obuchenii inostrannomu iazyku [CHATGPT-3: Perspectives of application to foreign language teaching]. Mir nauki, kultury, obrazovaniya, 3(100), 33-35. https://doi.org/10.24412/1991-5497-2023-3100-33-35

Kurbanova, Z.S., & Ismailova, N.P. (2023). Neiroseti v kontekste tsifrovizatsii obrazovaniia i nauki [Neural networks in the context of digitalization of education and science]. Mir nauki, kultury, obrazovaniya, 3(100), 309-311. https://doi.org/10.24412/1991-5497-2023-3100-309-311

Luo, Q., & Yang, J. (2022). The artificial intelligence and neural network in teaching. Computational Intelligence and Neuroscience, 2022, 1778562. https://doi.org/10.1155/2022/1778562

Matvienko, E., Zolkin, A., Suchkov, D., Shichkin, I., & Pomazanov, V. (2022). Applying of smart, robotic systems and big data processing in agro-industrial complex. IOP Conference Series: Earth and Environmental Science, 981, 032002. https://doi.org/10.1088/1755-1315/981/3/032002

Mitsel, A.A., Poguda, A.A., Semenov, K.A., & Utesheva, A.E. (2013). Metody testirovaniia znanii na osnove primeneniia apparata neironnoi seti [Testing methods of knowledge on the basis of neural network]. Open Education, 2(97), 34-41.

Novichkov, V.B., Ilyichyova, I.V., & Potapov, D.A. (2022). Principles of constructing the content of general secondary education. Anthropological Didactics and Upbringing, 5(4), 10-26.

Okewu, E., Adewole, P., Misra, S., Maskeliunas, R., & Damasevicius, R. (2021). Artificial neural networks for educational data mining in higher education: A systematic literature review. Applied Artificial Intelligence, 35(13), 983-1021. http://dx.doi.org/10.1080/08839514.2021.1922847

Onufrieva, T.A., & Sukhova, A.S. (2020). Primenenie neironnykh setei v razrabotke elektronnykh obuchaiushchikh resursov [Application of neural networks in the development of e-learning resources]. South-Siberian Scientific Bulletin, 6(34), 194-197.

Podzorova, M.I. (2022). Neironnaia set kak odno iz perspektivnykh napravlenii iskusstvennogo intellekta [Neural network as one of the promising directions of artificial intelligence]. Modern European Researches, 1(3), 169-176.

Polegoshko, K.R. (2023). Ispolzovanie chat-bota GPT v pedagogike: Preimushchestva, osobennosti i riski [Using GPT Chat bot in pedagogy: Advantages, features and risks]. Bulletin of Perm State Humanitarian and Pedagogical University, 19, 128-133.

Polovchenko, K. (2024). Interactive methodology for teaching legal disciplines: Theory and practice. Revista Juridica, 1(77), 117-140.

Kozlova, O.A., & Protasova, A.A. (2021). Ispolzovanie neironnykh setei v distantsionnykh obrazovatelnykh tekhnologiiakh dlia identifikatsii obuchaiushchikhsia [The use of neural networks in distance education technologies for the identification of students]. Open Education, 25(3), 26-35. https://doi.org/10.21686/1818-4243-2021-3-26-35

Kravtsova, A.G. (2023). Chatgpt-3: Perspektivy ispolzovaniia v obuchenii inostrannomu iazyku [CHATGPT-3: Perspectives of application to foreign language teaching]. Mir nauki, kultury, obrazovaniya, 3(100), 33-35. https://doi.org/10.24412/1991-5497-2023-3100-33-35

Kurbanova, Z.S., & Ismailova, N.P. (2023). Neiroseti v kontekste tsifrovizatsii obrazovaniia i nauki [Neural networks in the context of digitalization of education and science]. Mir nauki, kultury, obrazovaniya, 3(100), 309-311. https://doi.org/10.24412/1991-5497-2023-3100-309-311

Luo, Q., & Yang, J. (2022). The artificial intelligence and neural network in teaching. Computational Intelligence and Neuroscience, 2022, 1778562. https://doi.org/10.1155/2022/1778562

Matvienko, E., Zolkin, A., Suchkov, D., Shichkin, I., & Pomazanov, V. (2022). Applying of smart, robotic systems and big data processing in agro-industrial complex. IOP Conference Series: Earth and Environmental Science, 981, 032002. https://doi.org/10.1088/1755-1315/981/3/032002

Mitsel, A.A., Poguda, A.A., Semenov, K.A., & Utesheva, A.E. (2013). Metody testirovaniia znanii na osnove primeneniia apparata neironnoi seti [Testing methods of knowledge on the basis of neural network]. Open Education, 2(97), 34-41.

Novichkov, V.B., Ilyichyova, I.V., & Potapov, D.A. (2022). Principles of constructing the content of general secondary education. Anthropological Didactics and Upbringing, 5(4), 10-26.

Okewu, E., Adewole, P., Misra, S., Maskeliunas, R., & Damasevicius, R. (2021). Artificial neural networks for educational data mining in higher education: A systematic literature review. Applied Artificial Intelligence, 35(13), 983-1021. http://dx.doi.org/10.1080/08839514.2021.1922847

Onufrieva, T.A., & Sukhova, A.S. (2020). Primenenie neironnykh setei v razrabotke elektronnykh obuchaiushchikh resursov [Application of neural networks in the development of e-learning resources]. South-Siberian Scientific Bulletin, 6(34), 194-197.

Podzorova, M.I. (2022). Neironnaia set kak odno iz perspektivnykh napravlenii iskusstvennogo intellekta [Neural network as one of the promising directions of artificial intelligence]. Modern European Researches, 1(3), 169-176.

Polegoshko, K.R. (2023). Ispolzovanie chat-bota GPT v pedagogike: Preimushchestva, osobennosti i riski [Using GPT Chat bot in pedagogy: Advantages, features and risks]. Bulletin of Perm State Humanitarian and Pedagogical University, 19, 128-133.

Polovchenko, K. (2024). Interactive methodology for teaching legal disciplines: Theory and practice. Revista Juridica, 1(77), 117-140.




DOI: http://dx.doi.org/10.21902/Revrima.v2i44.7350

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