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Systematic review and meta-analysis of educational approaches to reduce cognitive biases among students

Nature Human Behaviour volume 9, pages 2510–2538 (2025)Cite this article

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Abstract

Resistance to cognitive biases is a crucial element of rationality that influences judgement and decision-making. Here we synthesized the effects of debiasing training in educational settings. Our systematic review found 54 randomized controlled trials consisting of 383 effect sizes and 10,941 participants. Our meta-analysis of educational interventions showed a small, yet significant, improvement in reducing the likelihood of committing biases compared with control conditions (g = 0.26, 95% confidence interval 0.14 to 0.39), 160 effects from 41 studies, P < 0.001). Most studies focused on reducing the likelihood of committing biases (for example, confirmation bias) using cognitive strategies. Some biases seemed difficult to overcome (for example, representativeness heuristic), and questions remain about the depth and transferability of learning beyond classroom settings. All studies had unclear or high risk of bias and there was some risk of publication bias. While evidence suggests that educational interventions can reduce bias on targeted tasks, more research is needed to determine whether these improvements translate to meaningful changes in real-world decision-making and to identify which paedagogical approaches are most effective for reducing the influence of cognitive biases.

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Fig. 1: PRISMA flow diagram for study selection.
Fig. 2: Forest plot of pooled results for educational intervention effects on cognitive bias.
Fig. 3: Plot of overall moderation analyses.
Fig. 4: Risk of bias summary for included studies.
Fig. 5: Sensitivity analysis by risk of bias criteria.
Fig. 6: Funnel plot for publication bias assessment.

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Data availability

The data supporting the findings of this systematic review and meta-analysis are openly available via the OSF repository at https://osf.io/7x5z6. This repository contains the complete dataset extracted from the included studies, including effect sizes, moderator variables and risk of bias assessments. The minimum dataset necessary to interpret, verify and extend the research includes the coded effect sizes from each study, sample sizes and moderator variables used in our analyses. All data are provided in accessible formats.

Code availability

The R code used to conduct all analyses and generate the figures in this systematic review and meta-analysis is available via the same OSF repository at https://osf.io/7x5z6. The code includes all scripts used for data preparation, meta-analytic models, moderation analyses, sensitivity analyses and visualization. All analyses were conducted using R (version 4.4.1) with the metafor, meta and ggplot2 packages. The repository includes documented code with comments and a README file to facilitate reproducibility of all results presented in this Article.

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Acknowledgements

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Authors and Affiliations

  1. School of Psychology, The University of Queensland, Brisbane, Queensland, Australia

    Ghassani Swaryandini, Jessica Graham, Shantell Griffith, Jason Tangen, Alexander Saeri & Michael Noetel

  2. Frente Animal, Porto, Portugal

    Vasco Grilo

  3. MoMiLab Research Unit, IMT School for Advanced Studies, Lucca, Italy

    Federica Ruzzante

  4. ILR School, Cornell University, Ithaca, NY, USA

    Xingruo Zhang

  5. Department of Psychology, Chinese University of Hong Kong, Hong Kong, China

    Siu Kit Yeung

  6. School of Psychology and Vision Sciences, University of Leicester, Leicester, UK

    Marta Mangiarulo

  7. Institute for Positive Psychology and Education, Australian Catholic University, Sydney, New South Wales, Australia

    Geetanjali Basarkod & Philip Parker

  8. Institute for Learning Sciences and Teacher Education, Australian Catholic University, Brisbane, Queensland, Australia

    Clarence Ng

  9. Massachusetts Institute of Technology, Cambridge, MA, USA

    Emily Grundy & Peter Slattery

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  1. Ghassani Swaryandini
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Contributions

Conceptualization by G.S., M.N., P.P., C.N., G.B., A.S., E.G. and P.S. Methodology by G.S., M.N., J.G., S.G., V.G., F.R., M.M., S.K.Y. and X.Z. Analysis by G.S. and M.N. Writing—original draft preparation by G.S. and M.N. Writing—review and editing by G.S., M.N., J.T., P.P., C.N., G.B., V.G., F.R., M.M., S.K.Y. and X.Z. Supervision by M.N., P.P., C.N., G.B. and J.T.

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Correspondence to Michael Noetel.

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Swaryandini, G., Graham, J., Griffith, S. et al. Systematic review and meta-analysis of educational approaches to reduce cognitive biases among students. Nat Hum Behav 9, 2510–2538 (2025). https://doi.org/10.1038/s41562-025-02253-y

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