Increasing meta-analytic quality: A multivariate multilevel meta-analysis of note-taking through exposure to L2 input

Abstract

Meta-analytic studies of second language (L2) learning typically employ a classic approach to meta-analysis. Although the classic approach can clarify findings, a multivariate, multilevel meta-analysis (3M) approach increases transparency by accounting for (a) dependencies in the evidence presented by primary studies, (b) methodological differences confounding the effectiveness of interventions, (c) differences in research designs, and (d) enhancing the accessibility of findings by using percentages. This reproducible study (https://rnorouzian.github.io/m/p.html) employed a 3M approach and used the (M)UTOS framework to examine the effect of note-taking on learning through exposure to L2 input. Retrieving 55 effect sizes from 27 studies, the 3M approach found that there was at least a 63% likelihood for note-taking treatments to produce a meaningfully positive benefit (≥0.2 gain on the effect-size scale) on learning outcomes and revealed that the type of note-taking treatment, measurement type, input mode, and learners’ proficiency levels were particularly influential.