Paroemiological Units In Cognitive And Linguocultural Research
Keywords:
AI-assisted learning, linguoculturology, culturally marked vocabularyAbstract
The article discusses how AI-assisted tools can be integrated into linguocultural vocabulary instruction in Uzbek universities without replacing linguistic evidence or teacher judgment. It is argued that culturally marked Russian vocabulary (realia, cultural keywords, precedent-related units, and pragmatically sensitive expressions) requires learning environments where students can observe authentic usage patterns, interpret cultural scripts, and rehearse genre-appropriate choices. The paper proposes an instructional model that combines corpus-informed noticing with AI-supported practice: micro-corpora provide empirical contexts and collocational profiles, while AI-based dialogic simulation supports scenario rehearsal for politeness, stance, and institutional communication. The article outlines design principles for pedagogical control, including transparency of evidence, constraint-based prompting, teacher validation, and ethical safeguards (privacy, bias awareness, and academic integrity). The conclusion emphasizes that AI is most effective when positioned as a structured practice layer built on corpus evidence and pragmatics-focused rubrics, leading to measurable gains in reading interpretation, register control, and communicative appropriateness
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