Corpus Use in Language Learning: A Meta‐Analysis. Issue 2 (15th February 2017)

• Record Type: Journal Article
• Authors: Boulton, Alex; Cobb, Tom
• Is Part Of: Language learning. Volume 67:Issue 2(2017)
• Page Start: 348
• Page End: 393
• Publication Date: 2017-02-15
• Subjects: corpus‐based language learning -- data‐driven learning -- DDL -- meta‐analysis -- research synthesis; Language and languages -- Periodicals; Language and languages -- Study and teaching -- Periodicals; Linguistics; 407
• DOI: 10.1111/lang.12224
• Languages: English
• ISSNs: 0023-8333

Abstract

Abstract: This study applied systematic meta‐analytic procedures to summarize findings from experimental and quasi‐experimental investigations into the effectiveness of using the tools and techniques of corpus linguistics for second language learning or use, here referred to as data‐driven learning (DDL). Analysis of 64 separate studies representing 88 unique samples reporting sufficient data indicated that DDL approaches result in large overall effects for both control/experimental group comparisons ( d = 0.95) and for pre/posttest designs ( d = 1.50). Further investigation of moderator variables revealed that small effect sizes were generally tied to small sample sizes. Research has barely begun in some key areas, and durability/transfer of learning through delayed posttesting remains an area in need of further investigation. Although DDL research demonstrably improved over the period investigated, further changes in practice and reporting are recommended. Open Practices: This article has been awarded Open Materials and Open Data badges. All materials and data are publicly accessible via the Open Science Framework athttps://osf.io/jkktw . Learn more about the Open Practices badges from the Center for Open Science:https://osf.io/tvyxz/wiki .