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Using English-uzbek Parallel Corpora in Efl Data-driven Learning

Year: 2025

Type: article

Abstract: 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).

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.16938817

Author: Amonova, Makhbuba

Language: English

Topic: Second Language Acquisition and Learning

Subfield: Developmental and Educational Psychology

Field: Psychology

Domain: Social Sciences

SDG: Quality education

Open Access status: green

OpenAlex ID: W7077467786

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