Journal article
Effectiveness of EMI in higher education: a multi-level meta-analysis
- Abstract:
- This study is one of the first comprehensive multi-level meta-analyses investigating the effects of English Medium Instruction in higher education. It synthesizes a total of 41 samples, comprising a total of 8,747 participants, from 28 quantitative studies, including 23 samples on content learning (7,659 participants) and 18 on English performance (1,088 participants). A comparison of EMI students’ post-test and pre-test scores (within-group comparison) revealed that students significantly improved on measures of content knowledge (d = 1.57, p < .001) and English proficiency (d = 0.81, p < .001), although we acknowledge that this finding does not account for external factors or establish causality. A comparison of post-test performance between EMI and non-EMI groups (between-group comparison), which aimed to assess EMI's effectiveness relative to non-EMI, showed that EMI students achieved comparable outcomes in content learning (d = 0.13, p = 0.14) and significantly outperformed non-EMI students in English development (d = 0.33, p = 0.009). Moderator analyses further revealed that studies with methodological limitations, such as selection biases for within-group comparisons or unaddressed group homogeneity for between-group comparisons, often overestimate the effectiveness of EMI for content learning. Based on our findings, we offer practical implications for the implementation of EMI in higher education.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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- Files:
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(Preview, Accepted manuscript, pdf, 1.5MB, Terms of use)
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- Publisher copy:
- 10.1016/j.system.2025.103755
Authors
- Publisher:
- Elsevier
- Journal:
- System More from this journal
- Volume:
- 133
- Article number:
- 103755
- Publication date:
- 2025-06-24
- Acceptance date:
- 2025-06-19
- DOI:
- EISSN:
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1879-3282
- ISSN:
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0346-251X
- Language:
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English
- Keywords:
- Pubs id:
-
2133309
- Local pid:
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pubs:2133309
- Deposit date:
-
2025-07-24
Terms of use
- Copyright holder:
- Elsevier Ltd
- Copyright date:
- 2025
- Rights statement:
- © 2025 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
- Notes:
- The author accepted manuscript (AAM) of this paper has been made available under the University of Oxford's Open Access Publications Policy, and a CC BY public copyright licence has been applied.
- Licence:
- CC Attribution (CC BY)
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