The emergence of learner corpus research (LCR) has bridged the gap between theoretical Second Language Acquisition (SLA) and practical classroom pedagogy. This article explores the systematic methodology of compiling learner corpora, emphasizing the transition from raw data collection to pedagogical application. By integrating the specific research of Radjabova (2018–2024) alongside international standards set by Sinclair, Granger, and Hunston, the study outlines the critical role of design criteria, metadata, and error annotation. Special attention is given to the utility of written and spoken corpora in academic writing and assessment. The findings suggest that locally compiled corpora offer unique diagnostic insights that generic textbooks cannot provide, ultimately fostering a more data-driven and learner-centered educational environment.
| Mualliflar | Radjabova , Gulnoza Giyosiddinovna |
|---|---|
| Jurnal | Lingvospektr |
| Nashr sanasi | 2026-06-23 |
| Jild | 4 |
| Son | 1 |
| Betlar | 255-262 |
| Til | Ingliz |
Learner Corpora, Corpus Linguistics, Academic Writing, Pedagogy, Interlanguage, Error Annotation, SLA, Data-Driven Learning
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