UDC 167/168+378
DOI 10.20339/AM.05-26.024
Natalya P. Sukhanova, PhD (Philosophy), Associate Professor, Department of Philosophy and Humanities, Novosibirsk State University of Economics and Management, Russia, eLibrary SPIN-code: 2647-7829, AuthorID: 599434, е-mail: konfngi@yandex.ru
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.
Keywords: education, university, neural networks, knowledge, methodological thinking, logic, learning
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