A multilevel Bayesian meta-analysis of the effects of translanguaging pedagogy on L2 achievement

Abstract Globalisation and the multilingual turn in applied linguistics have exposed a persistent tension between learners’ linguistic repertoires and traditional monolingual pedagogies. It is out of this tension that translanguaging pedagogy (TP) emerged as an instructional framework grounded in translanguaging theory, witnessing a burgeoning empirical literature on its classroom value. However, the empirical evidence has failed to produce a coherent account of TP’s effectiveness in L2 education, as findings have exhibited considerable heterogeneity across instructional contexts, learner populations, and outcome measures. The present study sought to reconcile these inconsistent findings through a multilevel Bayesian meta-analysis of 108 effect sizes drawn from 40 independent studies among 3,145 learners. The pooled effect size of Hedges’ g = 1.014 (standard error = 0.138, 95% credible interval [0.748, 1.291]) establishes a positive and statistically credible effect of TP on L2 achievement. Moderator analyses identified educational level and target language skills as credible sources of heterogeneity, with tertiary-level learners and speaking outcomes yielding the largest effect sizes. Target language, linguistic distance, and treatment duration did not reach the posterior probability threshold for credible inference. These findings advance the theoretical understanding of TP and furnish an empirically grounded basis for instructional decision-making in L2 education.

Authors

Institutions

Publication Details

Journal
Language Teaching
Published
2026-06-16
DOI
https://doi.org/10.1017/s0261444826101335
Primary Topic
Second Language Learning and Teaching
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A multilevel Bayesian meta-analysis of the effects of translanguaging pedagogy on L2 achievement

Lawrence Jun Zhang, Xiaoqi Wang
Language Teaching
Second Language Learning and Teaching
article

A multilevel Bayesian meta-analysis of the effects of translanguaging pedagogy on L2 achievement

Lawrence Jun Zhang, Xiaoqi Wang
article en

Abstract

Abstract Globalisation and the multilingual turn in applied linguistics have exposed a persistent tension between learners’ linguistic repertoires and traditional monolingual pedagogies. It is out of this tension that translanguaging pedagogy (TP) emerged as an instructional framework grounded in translanguaging theory, witnessing a burgeoning empirical literature on its classroom value. However, the empirical evidence has failed to produce a coherent account of TP’s effectiveness in L2 education, as findings have exhibited considerable heterogeneity across instructional contexts, learner populations, and outcome measures. The present study sought to reconcile these inconsistent findings through a multilevel Bayesian meta-analysis of 108 effect sizes drawn from 40 independent studies among 3,145 learners. The pooled effect size of Hedges’ g = 1.014 (standard error = 0.138, 95% credible interval [0.748, 1.291]) establishes a positive and statistically credible effect of TP on L2 achievement. Moderator analyses identified educational level and target language skills as credible sources of heterogeneity, with tertiary-level learners and speaking outcomes yielding the largest effect sizes. Target language, linguistic distance, and treatment duration did not reach the posterior probability threshold for credible inference. These findings advance the theoretical understanding of TP and furnish an empirically grounded basis for instructional decision-making in L2 education.

Language Teaching
University of Auckland (NZ)
Quality Education
Openalex Percentile: Top 2%
Second Language Learning and Teaching
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.