PERSONALIZED ENGLISH IDIOM LEARNING THROUGH AI-SUPPORTED ADAPTIVE TASKS

Abstract

English idiomatic expressions are an important component of communicative competence, yet they remain challenging for foreign-language learners because their meanings are not always predictable from the meanings of their constituent words. Learners also differ considerably in their previous exposure to idioms, ability to interpret figurative meanings and capacity to use idiomatic expressions appropriately in context. This paper proposes a personalized approach to English idiom learning through AI-supported adaptive tasks. The framework draws on Russian phraseological theory and phraseodidactics, Uzbek research into linguocultural and technology-supported idiom instruction, and international research on second-language idiom processing and acquisition. The proposed model consists of five progressive stages: meaning recognition, contextual interpretation, controlled production, independent use and transfer. AI is conceptualized not as a replacement for the teacher but as a tool for generating differentiated tasks, adjusting scaffolding and providing context-sensitive practice according to learners' demonstrated performance. The paper argues that combining established principles of phraseological pedagogy with adaptive technology can provide a promising framework for personalized idiom instruction among first-year Philology students. The model requires subsequent empirical validation through controlled classroom research.