UDC378

Likhacheva O.N.¹ (Krasnodar, Russian Federation) – olga-lihacheva@rambler.ru; Tymchuk E.V.² (Krasnodar, Russian Federation) – elena-timchuk@mail.ru; Pasevich D.K.¹ (Krasnodar, Russian Federation) – daniil-pas@mail.ru; Golyshev V.V.¹ (Krasnodar, Russian Federation) – vlad-ff@mail.ru

¹IMSIT Academy

²Kuban State Technological University

Abstract. The rapid penetration of artificial intelligence technologies into everyday life and professional activity marks the beginning of a new era in the history of human cognition. While previous technological revolutions—such as the invention of writing, printing, and the internet—primarily expanded access to information and its distribution channels, modern artificial intelligence, particularly through generative models, actively intervenes in the very process of producing, processing, and, most importantly, comprehending information. Central to this profound transformation is linguistic thinking—that higher mental function that inextricably links language, consciousness, and cognition, determining how we formulate ideas, construct arguments, and perceive the world. The impact of artificial intelligence on this fundamental process is multifaceted and deeply ambivalent, opening up both unprecedented opportunities and posing serious challenges for the future of human intelligence. The relevance of this study lies in identifying the positive and negative aspects of artificial intelligence in the context of the development of linguistic thinking in modern pedagogical processes. The research focuses on the impact of artificial intelligence on linguistic thinking in modern pedagogical contexts. The scientific novelty of this work lies in the development of recommendations for leveraging the positive impact of artificial intelligence on the linguistic thinking of modern learners. The practical significance of this work lies in the potential for incorporating research findings into the modern pedagogical process.

Keywords: artificial intelligence, development, cognition, linguistic thinking, algorithm, cognitive profile, educational content.

References:

1. Kosacheva A.O. Students’ motivation for learning and professional development.  The World of Science, Culture, Education, 2022, no. 5 (96), pp. 235–238. (In Russian). (In Russian). DOI: 10.24412/1991-5497-2022-596-235-238
2. Malakhova O.N., Mosina L.S. Developing academic motivation in higher education: research emphases. Studia Humanitatis, 2022, no. 1, pp. 11. (In Russian). DOI: 10.24412/2308-8079-2022-1-11
3. Likhacheva O.N., Koroleva Yu.V., Tymchuk E.V. Regional component as one of the aspects of the modern educational process at a university: the example of a foreign language. The World of Science, Culture, and Education, 2019, no. 1 (74), pp. 95-97(In Russian). URL: https://elibrary.ru/izycgg
4. Belyakova Yu.G. Students’ motivation for studying at a university. Scientific Works of the Moscow Humanitarian University, 2025, no. 3, pp. 22-26. (In Russian). URL: https://www.elibrary.ru/skozmw
5. Veremchuk A.S. On student motivation as a necessary condition for improving the quality of education.  Scientific Review. Pedagogical Sciences, 2020, no. 2, pp. 34-38. (In Russian). DOI: 10.17513/srps.2284
6. Yusupov V.Z. Comparative analysis of empirical studies of university students’ academic motivation. Knowledge. Understanding. Skill, 2022, no. 1, pp. 226-236. (In Russian). URL: https://www.elibrary.ru/dqdngu
7. Gurnikovskaya R.Yu. et al. On the experience of implementing the basic principles of digital didactics based on the electronic information and educational environment of higher educational institutions. Education Management: Theory and Practice, 2023, vol. 13, no. 10-2, pp. 95-124. (In Russian). DOI: 10.25726/i2321-1735-7310-c
8. Bosov A.V. Application of self-organizing neural networks to the process of forming an individual learning trajectory. Computer Science and its Applications, 2022, vol. 16, no. 3, pp. 7–15. (In Russian). URL: https://www.elibrary.ru/jvzxbi
9. Likhacheva O.N. Independent work as an effective means of developing and improving students’ foreign language communicative competence in a non-linguistic university. Proc. “The III International scientific and practical conference”. Krasnodar, Kuban State Technological University Publ., 2018. pp. 541-549. (In Russian). URL: https://elibrary.ru/xnsytb
10. Zhdanova O.V. Understanding the pedagogical and socio-cultural heritage of a region in the context of modern educational problems. CITISE, 2023, no. 4, pp. 88-95. (In Russian). URL:  https://elibrary.ru/xwcdzs
11. Alhumaid K., Naqbi S., Elsori D. The adoption of artificial intelligence applications in education. International Journal of Data and Network Science. 2023. Vol. 7, no. 1. pp. 457–466. DOI:10.5267/j.ijdns.2022.8.013
12. Garda-Martmez I., Fernandez-Batanero J.M., Fernandez-Cerero J. Analyzing the impact of artificial intelligence and computational sciences on student performance: Systematic review and meta-analysis. Journal of New Approaches in Educational Research, 2023, vol. 12, no. 1, pp. 171–197. DOI: 10.7821/naer.2023.1.1240
13. Uzwyshyn R.J. From open science and datasets to AI and discovery. Trends & Issues in Library Technology. 2023. January. pp. 26–38.
14. Okewu E., Adewole P., Misra S. et al. Artificial neural networks for educational data mining in higher education: A systematic literature review. Applied Artificial Intelligence, 2021, vol. 35, no. 13, pp. 983–1021. DOI: 10.1080/08839514.2021.1922847
15. Chen X., Zou D., Xie H. et al. Two decades of artificial intelligence in education. Educational Technology & Society, 2022, vol. 25, no. 1, pp. 28–47. URL: https://www.elibrary.ru/mjthfm
16. Perrotta C., Selwyn N. Deep learning goes to school: Toward a relational understanding of AI in education. Learning, Media and Technology, 2020, vol. 45, no. 3. pp. 251–269. DOI: 10.1080/17439884.2020.1686017
17. Yilmaz R., Karakus T. Artificial intelligence-based educational applications: A systematic review of the literature. Journal of Educational Technology & Society, 2020, vol. 23, no. 3, pp. 1–15.

For citation:  Likhacheva O.N., Tymchuk E.V., Pasevich D.K., Golyshev V.V. To the question of artificial intelligence influence on language thinking in a modern pedagogical process. CITISE, 2025, no. 4, pp. 365-374.