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