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Home Archive 2026 Year Issue №4 Opportunities of generative artificial intelligence for developing learners' critical thinking
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Opportunities of generative artificial intelligence for developing learners' critical thinking

Chervonnyy M.A., Abakumova N.N.

DOI: 10.23951/2307-6127-2026-4-181-194

Information About Author:

Chervonnyy M.A., Doctor of Pedagogical Sciences, Associate Professor, Tomsk State Pedagogical University (ul. Kiyevskaya, 60, Tomsk, Russian Federation, 634061). E-mail: mach@tspu.ru; ORCID ID: https://orcid.org/0000-0002-4459-5726; SPIN-code: 4196-1264; WoS Researcher ID AAF-2512-2019; Scopus Author ID: 57204964813. Abakumova N.N., Candidate of Pedagogical Sciences, Associate Professor, Tomsk State Pedagogical University (ul. Kiyevskaya, 60, Tomsk, Russian Federation, 634061). E-mail: niv_tomsk@mail.ru; ORCID ID: https://orcid.org/0000-0003-3221-0400; SPIN-code: 2932-8741; WoS Researcher ID: ABF-4712-2020; Scopus Author ID: 55622952900.

In the context of the digital transformation of general education, fostering critical thinking in learners has become a key meta-subject task as reflected in the Federal State Educational Standards. The integration of Generative Artificial Intelligence (GAI) into the educational process creates both new opportunities for developing students’ cognitive abilities and significant risks of reducing their cognitive autonomy and criticality. The aim of this article is to provide a theoretical justification and systematisation of ways to use GAI for the purposeful development of students’ critical thinking. The methodological framework is based on system-activity, competence-based, and cognitive-constructivist approaches. An analysis of Russian and international scientific literature (over 45 sources), employing methods of systematisation, typologisation, comparative analysis, and pedagogical modelling, revealed that critical thinking is not an isolated cognitive phenomenon but is closely interconnected with divergent, engineering, systems, creative, reflective, analytical, algorithmic thinking, and design thinking. Two main groups of GAI application methods were identified and classified: instrumental-technological (dialogue simulators, Socratic chatbots, argumentation visualisation platforms, intelligent tutoring systems, prompt engineering training tools) and pedagogical strategies (problem-based dialogue with AI, metacognitive scaffolding, AI literacy development, AI-based flipped classroom, project-based learning with algorithmisation elements). The discussion substantiates that the sign of GAI’s impact on critical thinking is determined not so much by the technology itself but by the pedagogical context of its use, with AI acting as a “cognitive mediator” that prompts students to verify, challenge, and refine their own conclusions. Based on the analysis, a structural-functional model for fostering critical thinking through GAI is proposed, comprising target, content, instrumental, procedural, evaluation, and result blocks. The practical significance of the model lies in its use as an operationalised tool for designing educational processes aimed at developing meta-subject outcomes. Further research perspectives include the development of diagnostic instruments to assess the impact of different configurations of interaction with GAI on the dynamics of critical thinking, as well as longitudinal studies of the delayed effects of such interaction.

Keywords: generative artificial intelligence, critical thinking, school education, divergent thinking, engineering thinking, AI in education, educational platforms, chatbot, digital didactics

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Issue: 4, 2026

Series of issue: Issue 4

Rubric: REVIEWS

Pages: 181 — 194

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2026 Pedagogical Review

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