Corpus Use in Language Learning: A Meta-Analysis

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.