USING ENGLISH-UZBEK PARALLEL CORPORA IN EFL DATA-DRIVEN LEARNING

Parallel corpora create a bridge between form and meaning across languages and, when embedded in data-driven learning (DDL), enable learners to interrogate authentic evidence rather than rely on prescriptive rule lists. Building on well-established DDL principles and recent meta-analytic evidence, the article maps readily accessible English–Uzbek resources (OPUS, JW300, the Uzbek National Corpus’ parallel section) and workable tools (ParaConc, AntPConc, Sketch Engine’s parallel concordancer).