Function-based modelling as a pedagogical technology for developing discourse competence of foreign students in Russian language classes

Abstract

The study aims to substantiate the need to bridge the gap between formal proficiency in Russian as a foreign language at level B2 (TORFL-2) and students’ ability to produce coherent, logical, and contextually appropriate discourses in academic and professional settings. The timeliness of addressing this issue is due to the lack of integral, diagnostic, and reproducible technologies in the practice of teaching Russian as a foreign language (RFL) aimed at forming discourse competence based on the real communicative needs of advanced-level learners. The aim of the study is to present and justify functional modelling as an effective pedagogical technology for forming discursive competence in foreign students at level B2. To achieve this aim, the following tasks have been solved: the place of discourse competence within the structure of foreign language communicative competence has been clarified; the technology of functional modelling has been developed and theoretically substantiated; a five-stage algorithm for forming discourse competence has been introduced; a modular system of tasks based on the functional-stylistic principle has been designed. The methodological foundation of the study comprises the concept of communicative competence by M. Canale and M. Swain, the provisions of the Common European Framework of Reference for Languages (CEFR), and the key principles of pedagogical technology by V.P. Bespalko. The research employs methods of theoretical analysis and pedagogical modelling of the RFL teaching process. The novelty of the study lies in the development of functional-based modelling technology that meets the criteria of systematicity, diagnosticity, and reproducibility; the principle of functionality ensures a progression from communicative intention to the selection of linguistic means. As a result, the content of discourse competence for level B2 has been specified, including analytical-interpretive, productive-genre, interactive-strategic, metalinguistic, and regulatory components; a structural-content model with a five-stage algorithm has been developed; a modular system of tasks based on styles of the Russian language has been created; and a diagnostic toolkit has been proposed.