INTEGRATING ARTIFICIAL INTELLIGENCE INTO RUSSIAN LANGUAGE TEACHING: A METHODOLOGICAL FRAMEWORK FOR NON-NATIVE LEARNERS AT HIGHER EDUCATION LEVEL

Abstract

The integration of artificial intelligence (AI) technologies into foreign language education represents one of the most dynamic and consequential developments in contemporary applied linguistics. This article presents a methodological framework for the systematic incorporation of AI tools—including intelligent chatbots, neural network-based text generators, corpus technologies, and adaptive learning platforms—into the teaching of Russian as a foreign and second language (RFL/RSL) at the university level. Drawing on a mixed-methods study conducted over two academic semesters with undergraduate students at Jizzakh State Pedagogical University (Uzbekistan), the research examines the pedagogical potential and practical limitations of AI-assisted language instruction across four core competency areas: lexical-grammatical acquisition, communicative competence, reading comprehension, and writing skills. The results demonstrate that a balanced integration of AI tools with traditional communicative approaches produces statistically significant improvements in grammatical accuracy (p < 0.01) and learner motivation, while also revealing important challenges related to academic integrity, cultural-contextual gaps in AI-generated content, and the preservation of authentic human communicative practice. The article proposes a three-tier methodological model—diagnostic, instructional, and evaluative—adapted specifically for the Central Asian educational context, and provides concrete recommendations for curriculum designers and practitioners working with A1–B2 level learners.