Digital Transformation in Russian Linguistics Education: Corpus-Based Teaching Practices and Learner Perceptions

Abstract

With the rapid advance of digital transformation and generative AI, foreign language education increasingly requires not only the ability to use and produce language, but also the ability to explore authentic language data and critically evaluate generated expressions in context. This study examines the pedagogical potential of corpora and digital language analysis tools in Russian linguistics education. Three level-specific courses were implemented, drawing on the Russian Digital Resource Platform and using the Russian National Corpus (RNC), Sketch Engine, and AntConc. Learners’ experiences and perceptions were then analyzed through a student survey. Although most learners had little prior experience with corpora, they came to view the educational value of corpora and analysis tools positively after the courses. The RNC was seen as especially useful for learning Russian syntax and lexical meaning, while hands-on work with Sketch Engine and AntConc fostered data-analysis skills and critical thinking through data collection, cleaning, and interpretation. By contrast, voluntary use of the tools and engagement with more advanced functions remained limited, and lower-proficiency learners tended to find unfamiliar vocabulary in search results more challenging. This study contributes to Russian linguistics education in Korea by designing and implementing corpus-based instruction and by examining its potential and constraints through learners’ experiences. It further suggests structuring corpus- based education as a staged process—from basic searching and usage interpretation to data construction, analysis, and research—with tasks and guidance materials tailored to learners’ proficiency levels.