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Foreign language communicative competence of non-linguistic university graduates: Criteria, levels, and the didactic potential of artificial intelligence technologies

Aug 2026 · Informatics and Education · 0 citations · 5 references

Abstract

The digital transformation of higher education and the rapid spread of artificial intelligence (AI) technologies make it urgent to provide a scientifically grounded description of the criteria and levels of development of foreign language communicative competence (FLCC) in graduates of non-linguistic universities. The aims of the study are to identify and substantively characterise the criteria and levels of FLCC development of students of non-linguistic programmes in line with the Common European Framework of Reference for Languages (CEFR) and to reveal the didactic potential of AI technologies for its formation. The materials comprised regulatory documents (the Federal State Educational Standard 3++, the Council of Europe document “Common European Framework of Reference for Languages: Learning, Teaching, Assessment”, letter of the Ministry of Education of Russia of 04.12.2019 No. 04-1375), the results of Russian and international research, and the authors’ long-term teaching experience; the methods of analysis, synthesis, comparison, and modelling were applied. It is established that the content of FLCC is formed by three qualitatively distinct competencies — linguistic, speech, and sociocultural — regarded as criteria of its development; their components and measurable indicators are described. Three levels of FLCC development (Elementary — A1–A2, Intermediate — B1–B2, Advanced — C1–C2) are identified and mapped onto the CEFR scale; it is shown that B1–B2 are the target levels for bachelor’s and specialist programmes, and B2–C1 for master’s programmes. The didactic potential of AI technologies (adaptive platforms, conversational chatbots, generative language models) is systematised with respect to the formation of each FLCC component and the implementation of individual learning trajectories. The results make it possible to unify the content, objectives, and monitoring of foreign language training at a non-linguistic university.

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