METAPHORICAL COMPETENCE IN LINGUISTIC EDUCATION: A COGNITIVE–CORPUS APPROACH USING AI TECHNOLOGIES

Abstract

The development of metaphorical competence has become an essential objective in the professional training of future linguists, as metaphor plays a crucial role in conceptualization, meaning construction, and discourse interpretation. This paper examines the theoretical and applied foundations of forming metaphorical competence in linguistic education through the use of AI-oriented corpus technologies. Drawing on cognitive metaphor theory and corpus-based approaches, the study conceptualizes metaphorical competence as an integrative component of linguistic, cognitive, and cultural proficiency.

Alongside the theoretical analysis, the paper presents a pilot practical implementation conducted with first-year undergraduate students majoring in Foreign Philology. The applied component focuses on integrating AI-supported corpus tools into regular language instruction without modifying the official curriculum content. Students engaged in guided corpus-based tasks aimed at identifying, interpreting, and contextualizing metaphorical expressions across authentic language data. AI-oriented tools were employed to facilitate metaphor detection, pattern recognition, and semantic comparison.

The findings of the pilot implementation indicate that AI-assisted corpus work enhances students’ metaphor awareness, interpretative accuracy, and reflective engagement with metaphorical language. The study argues that even at the early stages of linguistic education, AI-oriented corpus technologies can serve as an effective pedagogical resource for developing metaphorical competence. The paper concludes by outlining methodological implications and directions for further large-scale empirical research.