Methodology for developing the Russian communicative competence of Uzbek-speaking students using generative artificial intelligence

Rakhmonov, Azizkhon Bositkhonovich

Lingvospektr · 2026-yil

Annotatsiya

The article substantiates a methodology for developing the Russian communicative competence of Uzbek-speaking students using generative artificial intelligence. The study is relevant due to the contradiction between the high linguodidactic potential of large language models and the lack of methodological solutions addressing Uzbek and Russian typological differences and cross-linguistic interference. The theoretical framework integrates competence-based, communicative and contrastive approaches, the technological pedagogical content knowledge model and formative assessment. Russian and international research on generative artificial intelligence in language teaching is analysed, revealing a shortage of studies on Turkic-speaking learners and criterion-referenced assessment. The methodology is implemented through a four-stage cycle comprising diagnostic, generative interactive, reflective corrective and assessment stages, governed by the principles of teacher expert control, transparency and academic integrity. It provides contrastive feedback that explains errors through comparison with the learners’ native language system. Diagnostics, assessment and evaluation are differentiated, and the use of analytic rubrics and performance-based assessment is justified. Experimental teaching shows statistically significant growth in the interactive and pragmatic components of communicative competence and fewer interference errors in the experimental group. The limitations of the methodology, critical verification of machine-generated text as a transferable skill and the changing professional role of the teacher are discussed. The findings apply to teaching Russian at Uzbek universities and teacher development.

Maqola ma’lumotlari
MualliflarRakhmonov, Azizkhon Bositkhonovich
JurnalLingvospektr
NashriyotЎзбекистон давлат жаҳон тиллари университети, “Modern Scientific Research” MChJ
ISSN3060-4958
Nashr sanasi2026-10-04
Jild9
Son1
Betlar333-342
TilIngliz
DOI10.5281/zenodo.23134069
Indeksga qo‘shilgan2026-10-04

Kalit so‘zlar

Communicative competence, Russian as a foreign language, Uzbek-speaking students, generative artificial intelligence, large language models, cross-linguistic interference, contrastive approach, formative assessment, rubrics, performance-based assessment, transferable skills, academic integrity

Iqtibos keltirish

APARakhmonov, Azizkhon Bositkhonovich (2026). Methodology for developing the Russian communicative competence of Uzbek-speaking students using generative artificial intelligence. Lingvospektr, 9(1), 333-342. https://doi.org/10.5281/zenodo.23134069
GOST (OAK)Rakhmonov, Azizkhon Bositkhonovich Methodology for developing the Russian communicative competence of Uzbek-speaking students using generative artificial intelligence // Lingvospektr. – 2026. – T. 9, № 1. – P. 333-342. – DOI: 10.5281/zenodo.23134069.
MLARakhmonov, Azizkhon Bositkhonovich. “Methodology for developing the Russian communicative competence of Uzbek-speaking students using generative artificial intelligence.” Lingvospektr, 9(1), 333-342, 2026. https://doi.org/10.5281/zenodo.23134069
ChicagoRakhmonov, Azizkhon Bositkhonovich. “Methodology for developing the Russian communicative competence of Uzbek-speaking students using generative artificial intelligence.” Lingvospektr, 9(1), 333-342 (2026). https://doi.org/10.5281/zenodo.23134069
HarvardRakhmonov, Azizkhon Bositkhonovich (2026) ‘Methodology for developing the Russian communicative competence of Uzbek-speaking students using generative artificial intelligence’, Lingvospektr, 9(1), 333-342. https://doi.org/10.5281/zenodo.23134069
BibTeX
@article{rakhmonovazizkhonbositkhonovich2026,
  title = {Methodology for developing the Russian communicative competence of Uzbek-speaking students using generative artificial intelligence},
  author = {Rakhmonov, Azizkhon Bositkhonovich},
  journal = {Lingvospektr},
  year = {2026},
  volume = {9},
  number = {1},
  pages = {333-342},
  doi = {10.5281/zenodo.23134069},
  url = {https://doi.org/10.5281/zenodo.23134069}
}

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