2026, no. 5
PHILOSOPHY & SOCIOLOGY

Neural networks in university academic environment: Methodological thinking as a response to a challenge

Natalya P. Sukhanova

DOI 10.20339/am.05-26.024pp. 24–29UDC 167/168+37880 RUB

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Abstract

University education is being transformed, and neural networks currently play a key role in these changes. Algorithms capable of instantly producing texts are undermining the human monopoly on the production and dissemination of knowledge. Academics have various pedagogical approaches to neural networks, one of which can be called defensive, the other capitulatory. This article demonstrates their limitations. The idea is that neural networks can be viewed as an opportunity to redesign the educational process, whereby people learn not to compete with machines in speed, which is inherently problematic, but to surpass them in the depth of methodological analysis. Developing methodological thinking is an important task for modern higher education. The programmatic principles of this approach are traced through the prism of M.A. Rozov’s theory of social relay races. The article focuses on the content of the “Logic and Critical Thinking” course tools, which serve to develop students’ methodological reflection. The author concludes that the accelerated development of neural networks makes methodological thinking not an academic luxury, but a necessary condition for preserving human epistemological sovereignty in the digital age.

References

  1. Vorobev, R.R., Krasnov, A.S. Epistemology of intelligence: methodology of distinguishing natural and machine thinking. The Kazan Social-Humanitarian Bulletin. 2025. No. 3 (70). Pp. 46-53. https://doi.org/10.26907/2079-5912.2025.3.46-53

    DOI 10.26907/2079-5912.2025.3.46-53
  2. Zhuchkova, Yu.A. Risks of Using AI Technologies in Science and Education. Education and Science Without Borders: Social and Humanitarian Sciences. 2024. No. 22. Pp. 297–301.

  3. Kazakova, E.I., Kuzminov, Ya.I. We Should Foster a Culture of Critical Attitude toward Artificial Intelligence. Educational Studies Moscow. No. 1. Pp. 8–24. https://doi.org/10.17323/vo-2025-25882

    DOI 10.17323/vo-2025-25882
  4. Karpov, G.V. The Theory and Practice of Argumentation: We Got to the Wrong Place. Philosophy. Journal of the Higher School of Economics. 2025. Vol. 9ю No. 1. Pp. 229–257. https://doi.org/10.17323/2587-8719-2025-1-229-257

    DOI 10.17323/2587-8719-2025-1-229-257
  5. Markov, A.V. The Birth of Complexity. Evolutionary Biology Today: Unexpected Discoveries and New Questions. Moscow: Astrel: CORPUS, 2010. 527 p.

  6. Medvedev, V.A. The Problem of Conceptualization of Theoretical- Methodological Foundations of Research. Vestnik of Tomsk State University. 2010. No. 339. Pp. 49–56.

  7. Mikhaylova, E.E., Udalova, L.V. Speech Statement in the Structure of Critical Thinking: Searching for the Meaning of Evidential Judgment. Contemporary Philosophical Research. 2024. No. 4. Pp. 6–14. https://doi.org/10.18384/2949-5148-2024-4-6-14

    DOI 10.18384/2949-5148-2024-4-6-14
  8. Pugach, V.E. An attempt at dialogue with artificial intelligence: the education aspect. Education quality management: theory and practice of effective administration. 2025. No. 4. Pp. 45–53.

  9. Razumov, V.I. Cognitive Turn: Shifting the Foundations of Intellectual Culture. Ideas and Ideals. 2025. Vol. 17. No. 3-1. Pp. 155–172. https://doi.org/10.17212/2075-0862-2025-17.3.1-155-172

    DOI 10.17212/2075-0862-2025-17.3.1-155-172
  10. Rozov, M.A. Methodological Thinking and Tasks of University Education. In: Rozov, M.A. Gnoseology of Culture. Moscow: Novy Khronograf, 2015. Pp. 376–398.

  11. Sukhanova, N.P. Critical Thinking in the Context of the Expansion of Neural Networks: Narrative as an Existential Filter. Alma mater (Vestnik vysshey shkoly). 2025. No. 10. Pp. 31–36. https://doi.org/10.20339/AM.10-25.031

    DOI 10.20339/am.10-25.031
  12. Yarovova, T.V. Influence of Artificial Intelligence on Education. Pedagogical Education and Science. 2024. No. 3. Pp. 108–112. https://doi.org/10.56163/2072-2524-2024-3-108-112

    DOI 10.56163/2072-2524-2024-3-108-112