USING ARTIFICIAL INTELLIGENCE TOOLS IN LEARNING RUSSIAN AS A FOREIGN LANGUAGE IN CHINESE UNIVERSITIES

Abstract

The article reveals a problem of the systematic use of large language models (LLM) in the study of Russian as a foreign language in Chinese universities in conditions of a shortage of educational resources and high demand for Russian language specialists. The study aims to provide an empirical basis for theoretical research and practical application of AI, in particular LLM, in teaching Russian as a foreign language in Chinese universities. The work uses three key research methods to fulfill the research objectives: the method of analyzing theoretical sources to identify the essence of LLM and their potential in learning a foreign language, including Russian; content analysis to determine the state mandate of the Ministry of Education of China for the use of AI tools in higher language education, as well as the most effective use cases of LLM in Russian language lessons; the questionnaire survey method for assessing ten key changes in the use of LLM in Russian language learning by Chinese Russian students (AI penetration into students’ educational activities, student preferences, main use cases, motivation for choosing LLM, error correction opportunities, accuracy of LLM translation, learning effect of LLM application, trust in LLM, risk of dependence on LLM, the risk of misinformation when using LLM). The research findings can be considered on two levels: theoretical and practical. The theoretical significance of the study consists in the author’s elaborated conceptualization of LLM for teaching Russian to Chinese university students, as well as in the identified challenges and prospects for the development of LLM in the context of Russian language learning by Chinese learners. The practical significance of the research is provided by the author’s recommendations on the use of LLM in learning Russian at four levels: for Chinese students of Russian studies, teachers at Chinese universities, developers of AI tools and administrative bodies in the education system. The developed recommendations can be used in the activities of Chinese universities focused on teaching Russian, as well as in the development of AI tools for educational purposes.