Development of Lexical-Collocational Competence of English Philology Students through Corpus-Informed and AI-Mediated Instruction

Abstract

This study investigates the development of lexical-collocational competence among English philology students through a corpus-based and artificial intelligence-supported instructional approach. The object of the research is students’ language performance, while the subject is the formation of their ability to combine lexical units appropriately in academic writing. The relevance of the study is determined by persistent difficulties in mastering collocations in multilingual educational contexts and the influence of interlingual interference. At the same time, rapid advances in digital technologies create new opportunities for improving language instruction. The study is grounded in usage-based and lexical approaches and employs a quasi-experimental design involving 180 students. Traditional instruction was compared with an integrated model incorporating corpus analysis, contrastive techniques, and automated feedback. Statistical analysis, including ANCOVA, confirmed the effectiveness of the proposed methodology. The novelty of the research lies in the development of an integrated model combining corpus resources and artificial intelligence to enhance collocational competence.