ushbu maqolada rus tilini chet tili sifatida (RFL) o'rganayotgan xalqaro talabalarda kommunikativ kompetensiyani rivojlantirish jarayoniga sun'iy intellekt (SI) texnologiyalari va raqamli ta'lim muhitini integratsiyalashning ilmiy va metodologik zarurligi asoslanadi. Raqamli transformatsiyaning kognitiv, lingvodidaktik va sotsiomadaniy muammolarini tahlil qilish asosida original ilmiy va metodologik asos taklif qilingan - Kommunikativ kompetensiyani shakllantirishning adaptiv-kontekstual modeli (ACM-CC). Model diagnostik AI skriningi, immersiv-vaziyat amaliyoti va gibrid refleksiv teskari aloqa o'rtasidagi o'zaro ta'sirni amalga oshiradi. Argumentatsiya adaptiv o'rganish, neyrolingvistika va RFL metodologiyasi bo'yicha zamonaviy tadqiqotlar ma'lumotlari bilan qo'llab-quvvatlanadi. Modelni ta'lim dasturlarida qo'llash bo'yicha tavsiyalar ishlab chiqilgan va qo'shimcha empirik tekshirishni talab qiladigan cheklovlar aniqlangan.
this article substantiates the scientific and methodological necessity of integrating Artificial Intelligence (AI) technologies and digital educational environments into the process of developing communicative competence in international students studying Russian as a Foreign Language (RFL). Based on an analysis of the cognitive, linguodidactic, and sociocultural challenges of digital transformation, an original scientific and methodological framework is proposed – the Adaptive-Contextual Model of Communicative Competence Formation (ACM-CC). The model operationalizes the interaction between diagnostic AI screening, immersive-situational practice, and hybrid reflective feedback. The argumentation is supported by data from contemporary research in adaptive learning, neurolinguistics, and RFL methodology. Recommendations for implementing the model in educational programs are formulated, and limitations requiring further empirical verification are identified.
ResearcherUz