Generative Neural Networks in Education with Focus on Opportunities, Risks, and Implementation Problems

AUTHORS

Anastasia Viktorovna Petrova,Faculty of Education and Digital Pedagogy, Saint Petersburg National Research University, Saint Petersburg, Russia
Elena Mikhailovna Volkovа,Department of Information Technologies in Education, Ural State Digital University, Yekaterinburg, Russia
Dmitry Alexandrovich Sokolov,Institute of Artificial Intelligence Studies, Novosibirsk Research Center, Novosibirsk, Russia

ABSTRACT

This study examines the emerging role of generative neural networks in modern education, focusing on their pedagogical potential and the significant challenges of integrating them. Using an empirical research design, the study combines survey data, semi-structured interviews with experts, and document analysis to investigate how generative models influence the quality of educational content, teacher–student interaction, and institutional practices. The findings highlight key opportunities, including enhanced content generation, personalized learning support, greater efficiency in academic tasks, and new possibilities for creative and research-oriented instruction. At the same time, the study identifies critical risks related to content accuracy, data security, privacy, algorithmic bias, and threats to academic integrity. The results also reveal widespread gaps in institutional readiness, including insufficient policies, limited technical competence, and inadequate training for both teachers and students. Overall, the study concludes that while generative neural networks hold substantial promise for enriching learning environments, their successful implementation requires ethical oversight, regulatory frameworks, and the redesign of pedagogical approaches. Effective adoption depends not only on technological innovation but also on the development of clear institutional strategies that support responsible and meaningful use of generative AI in education.

 

KEYWORDS

Neural networks, Generative neural networks, Modern education, Innovative technologies in education

REFERENCES

[1] UNESCO, Recommendation on the Ethics of Artificial Intelligence, UNESCO, (2021)
[2] C. K. Lo, “What is the impact of ChatGPT on education? A rapid review of the literature,” Education Sciences, vol.13, no.4, p.410, (2023) DOI:10.3390/educsci13040410(CrossRef)(Google Scholar)
[3] J. Dempere, K. Modugu, A. Hesham, and L. K. Ramasamy, “The impact of ChatGPT on higher education,” Frontiers in Education, vol.8, 1206936, (2023) DOI:10.3389/feduc.2023.1206936(CrossRef)(Google Scholar)
[4] R. H. Mogavi, C. Deng, J. Kim, P. Zhou, Y. D. Kwon, A. H. S. Metwally, A. Tlili, S. Bassanelli, A. Bucchiarone, S. Gujar, L. E. Nacke, and P. Hui, “ChatGPT in education: A blessing or a curse? A qualitative study exploring early adopters’ utilization and perceptions,” Computers in Human Behavior: Artificial Humans, vol.2, no.1, 100027, (2023) DOI:10.1016/j.chbah.2023.100027(CrossRef)(Google Scholar)
[5] M. F. Shahzad, S. Xu, and I. Javed, “ChatGPT awareness, acceptance, and adoption in higher education: the role of trust as a cornerstone,” International Journal of Educational Technology in Higher Education, vol.21, pp.46, (2024) DOI:10.1186/s41239-024-00478-x(CrossRef)(Google Scholar)
[6] S. Sok and K. Heng, “Opportunities, challenges, and strategies for using ChatGPT in higher education: A literature review,” Journal of Digital Educational Technology, vol.4, no.1, ep2401, (2024) DOI:10.30935/jdet/14027(CrossRef)(Google Scholar)
[7] P. Bitzenbauer, “ChatGPT in physics education: A pilot study on easy-to-implement activities,” Contemporary Educational Technology, vol.15, no.3, ep430, (2023) DOI:10.30935/cedtech/13176(CrossRef)(Google Scholar)
[8] A. Ateeq, M. Alzoraiki, M. Milhem, and R. A. Ateeq, “Artificial intelligence in education: Implications for academic integrity and the shift toward holistic assessment,” Frontiers in Education, vol.9, 1470979, (2024) DOI:10.3389/feduc.2024.1470979(CrossRef)(Google Scholar)
[9] A. Bethencourt-Aguilar, D. Castellanos-Nieves, J. J. Sosa-Alonso, and M. Area-Moreira, “Use of Generative Adversarial Networks (GANs) in educational technology research,” Journal of New Approaches in Educational Research, vol.12, pp.153–170, (2023) DOI:10.7821/naer.2023.1.1231(CrossRef)(Google Scholar)
[10] O. Zawacki-Richter, V. I. Marín, M. Bond, and F. Gouverneur, “Systematic review of research on artificial intelligence applications in higher education – where are the educators?” International Journal of Educational Technology in Higher Education, vol.16, pp.39, (2019) DOI:10.1186/s41239-019-0171-0(CrossRef)(Google Scholar)
[11] W. Holmes, M. Bialik, and C. Fadel, Artificial Intelligence in Education: Promises and Implications for Teaching and Learning, 1st ed., Boston, MA, USA: Center for Curriculum Redesign, (2019)
[12] Hariyanto, F. X. D. Kristianingsih, and R. Maharani, “Artificial intelligence in adaptive education: A systematic review of techniques for personalized learning,” Discover Education, vol.4, pp.458, (2025) DOI:10.1007/s44217-025-00908-6(CrossRef)(Google Scholar)
[13] D. Ali, Y. Fatemi, E. Boskabadi, M. Nikfar, J. Ugwuoke, and H. Ali, “ChatGPT in teaching and learning: A systematic review,” Education Sciences, vol.14, no.6, pp.643, (2024) DOI:10.3390/educsci14060643(CrossRef)(Google Scholar)
[14] A. Yusuf, N. Pervin, and M. Román-González, “Generative AI and the future of higher education: A threat to academic integrity or reformation? Evidence from multicultural perspectives,” International Journal of Educational Technology in Higher Education, vol.21, (2024) DOI:10.1186/s41239-024-00453-6(CrossRef)(Google Scholar)
[15] E. Kasneci, K. Sessler, S. Küchemann, M. Bannert, D. Dementieva, F. Fischer, U. Gasser, G. Groh, S. Günnemann, E. Hüllermeier, S. Krusche, G. Kutyniok, T. Michaeli, C. Nerdel, J. Pfeffer, O. Poquet, M. Sailer, A. Schmidt, T. Seidel, and G. Kasneci, “ChatGPT for good? On opportunities and challenges of large language models for education,” Learning and Individual Differences, vol.103, 102274, (2023) DOI:10.1016/j.lindif.2023.102274(CrossRef)(Google Scholar)
education,” International Journal of Educational Technology in Higher Education, vol.20, pp.43, (2023). DOI:10.1186/s41239-023-00411-8(CrossRef)(Google Scholar)

CITATION

  • APA:
    Petrova,A.V.& Volkovа,E.M.& Sokolov,D.A.(2025). Generative Neural Networks in Education with Focus on Opportunities, Risks, and Implementation Problems. Asia-Pacific Journal of Educational Management Research, 10(2), 17-26. 10.21742/AJEMR.2025.10.2.02
  • Harvard:
    Petrova,A.V., Volkovа,E.M., Sokolov,D.A.(2025). "Generative Neural Networks in Education with Focus on Opportunities, Risks, and Implementation Problems". Asia-Pacific Journal of Educational Management Research, 10(2), pp.17-26. doi:10.21742/AJEMR.2025.10.2.02
  • IEEE:
    [1] A.V.Petrova, E.M.Volkovа, D.A.Sokolov, "Generative Neural Networks in Education with Focus on Opportunities, Risks, and Implementation Problems". Asia-Pacific Journal of Educational Management Research, vol.10, no.2, pp.17-26, Dec. 2025
  • MLA:
    Petrova Anastasia Viktorovna, Volkovа Elena Mikhailovna and Sokolov Dmitry Alexandrovich. "Generative Neural Networks in Education with Focus on Opportunities, Risks, and Implementation Problems". Asia-Pacific Journal of Educational Management Research, vol.10, no.2, Dec. 2025, pp.17-26, doi:10.21742/AJEMR.2025.10.2.02

ISSUE INFO

  • Volume 10, No. 2, 2025
  • ISSN(p):2207-5380
  • ISSN(e):2207-290X
  • Published:Dec. 2025

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