USING CORPUS OF CONTEMPORARY AMERICAN ENGLISH [COCA] TO ENHANCE WRITING COMPETENCE OF B2 LEVEL STUDENTS

Radjabova, Gulnoza

Ўзбекистонда хорижий тиллар (электрон илмий­методик журнал) · 2025-yil

Annotatsiya

The rapid development of computers and Internet technologies has significantly transformed education, especially methods of teaching foreign languages. Modern language pedagogy increasingly incorporates digital tools that enhance learner autonomy and improve the quality of instruction. Among these innovative tools, corpus technologies stand out as an effective resource for developing language competence. The article examines the evolution of corpus linguistics as a scientific field and analyses its pedagogical potential in teaching foreign languages. The novelty of the study lies in its systematic integration of corpus-based tools such as concordances, corpus statistics, and text-analysis applications into a structured set of exercises for improving writing competence. The purpose of the research is to evaluate the effectiveness of corpus technologies in fostering communicative competence, particularly academic writing skills of B2-level learners. The experiment was conducted among third-year students of Uzbekistan State World Languages University and employed both quantitative and qualitative data collection methods. The results demonstrate that corpus-informed instruction contributes to increased lexical awareness, improved accuracy, and deeper understanding of semantic prosody. Furthermore, the assignments designed on the basis of the Corpus of Contemporary American English (COCA) can also be used by students independently as mini-research projects. Overall, the study confirms that corpus technologies provide rich, authentic data and significantly enhance the writing competence of language learners.

Maqola ma’lumotlari
MualliflarRadjabova, Gulnoza
JurnalЎзбекистонда хорижий тиллар (электрон илмий­методик журнал)
Nashr sanasi2025-12-20
Jild65
Son6
Betlar110-124
TilIngliz
DOI10.36078/1767689405

Kalit so‘zlar

corpus linguistics, corpus technology, concordance, semantic prosody, lexical density

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