Claims

Corpus-based DDL shows large effects on L2 learning outcomes in meta-analytic evidence

Claim · All claims
Evidence · 1 study · review r2 · q3 · i3 large
Currency · newest study 2019 · not yet checked against its sources · not reviewed by a person

Subclaims

Reading the evidence codes

q is the design tier, i the impact, n the sample, and the kind with its r the rigour judged within that kind: what each code means.

This claim: no standardized effect is recorded in observations/ for it yet, so no benchmark reading is possible.

q3 i3 A meta-analysis of corpus use in language learning found large overall effects for control/experimental group comparisons (d = 0.95) and for pre/posttest designs (d = 1.50). → Rasikawati 2019

Evidence

Rasikawati 2019

Ira Rasikawati (2019). Corpus-Based Data-Driven Learning to Augment L2 Students’ Vocabulary Repertoire. International Dialogues on Education, 6(2), 83-98. https://eric.ed.gov/?id=EJ1245249

q3 · i3 · review · r2

The article reports the Boulton & Cobb (2017) meta-analysis, the first on corpus use in language learning, drawing on 64 meta-analyzable studies with over 3,000 participants. It found "large overall effects for control/experimental group comparisons" with d = 0.95 and d = 1.50 for pre/post designs.

"The result of 64 meta -analyzable studies from a pool of 205 studies showed large overall effects for control/experimental group comparisons ( d = 0.95) and for pre/posttest designs ( d = 1.50)"

Discussion

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generated by process:wiki-ingest on 2026-11-03
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