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

Аннотация

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). Keywords: parallel corpus; English–Uzbek; data-driven learning; concordancing; collocation; translation shifts; OPUS/JW300; Sketch Engine Introduction. Data-driven learning positions learners as investigators who query concordances and infer patterns from usage. Tim Johns captured the stance crisply: “the language-learner is also, essentially, a research worker” and “the most important computing tool… is the concordancer” [1. p. 6]. In parallel settings, the same investigative loop extends across aligned translations, letting EFL learners contrast English phraseology with Uzbek renderings and observe real translation choices. Large open collections such as OPUS, now listing 747 languages and tens of billions of aligned sentence pairs, supply the raw material; classroom-friendly concordancers and clear task design supply the pedagogy. Methods and literature review. We adopt a two-stage protocol: Stage 1 is a resource audit (identify English–Uzbek sources in OPUS, JW300, and the Uzbek National Corpus; record licensing, genres, and access modes). Stage 2 is implementation: short DDL cycles where learners use a parallel concordancer (ParaConc, AntPConc, or Sketch Engine) to query English targets (e.g., take into account, according to); observe Uzbek correspondences; generalize distributional constraints, and produce micro-outputs (gap-fills, micro- translations, paraphrases). Tools were selected for parallel search, alignment inspection, and frequency/collocation support. DDL’s rationale reaches back to Johns and early classroom concordancing; recent syntheses show consistent learning gains when learners consult corpora directly. Johns’ argument for learner-as-researcher remains the governing idea, while a multilevel meta-analysis reports medium positive effects for vocabulary learning with corpus use, moderated by proficiency, training, and duration. For 172 ACADEMIC RESEARCH IN MODERN SCIENCE International scientific-online conference parallel data supply, OPUS provides the largest open ecosystem; JW300 adds wide coverage across 300+ languages, including Uzbek, with sentence-aligned articles. Results. Open repositories expose multiple English–Uzbek entry points. OPUS offers umbrella access (OpenSubtitles, Tatoeba, CCMatrix, etc.); JW300 aggregates Watchtower/“Awake!” translations across 300+ languages; the Uzbek National Corpus hosts a dedicated parallel section. Table 1. Public English–Uzbek parallel resources for EFL DDL EN–UZ License / Resource Scale signal Typical genres Citation presence access 58.85B sentence pairs Yes Open OPUS across 747 subtitles, web, (multiple downloads / opus.nlpl.eu collection languages institutional subcorpora) web query (collection- level) 300+ languages; Research use; religious/educati JW300 Yes 109M paper with aclanthology.org onal expository sentences links overall Uzbek National developing; Yes Web interface mixed; curated uzbekcorpus.uz Corpus – institutional Parallel Parallel concordancers differ in depth of alignment control and analytics. Table 2. Parallel concordance tools and pedagogical affordances Tool Key functions for EFL outcomes it parallel DDL supports ParaConc KWIC in two panes; noticing translation alignment utilities; options; form–function collocate spans; regex mapping; contrastive collocation AntPConc Freeware; UTF-8; simple low-barrier DDL tasks; parallel search for quick verification of beginners equivalents Sketch Engine (Parallel Alignment view; pattern generalization; concordance) lemma/POS display; lexico-grammatical frequency and filters; profiling across user corpora languages 173 ACADEMIC RESEARCH IN MODERN SCIENCE International scientific-online conference We operationalized three repeatable templates for English–Uzbek DDL sessions—each built around a parallel query plus a constrained output. Meta- analytic results indicate medium gains for vocabulary learning with corpus consultation, with stronger effects for in-depth knowledge dimensions and when training/time are adequate. Representative figures reported: posttest Hedges’ g ≈ 0.74; delayed g ≈ 0.64. Discussion. Parallel concordances externalize contrasts that textbooks often flatten. Observing how according to disperses into ga ko‘ra plus case marking, or how light-verb constructions map onto Uzbek verbal morphology, encourages hypothesis formation grounded in real usage, aligning with the original DDL principle of learner inquiry. For entry-level courses, AntPConc reduces friction; for advanced cohorts