Abstract

AbstractThe extent to which findings in bilingualism research are contingent on specific analytic choices, experimental designs, or operationalisations, is currently unknown. Poor availability of data, analysis code, and materials has hindered the development of cumulative lines of research. In this review, we survey current practices and advocate a credibility revolution in bilingualism research through the adoption of minimum standards of transparency. Full disclosure of data and code is necessary not only to assess the reproducibility of original findings, but also to test the robustness of these findings to different analytic specifications. Similarly, full provision of experimental materials and protocols underpins assessment of both the replicability of original findings, as well as their generalisability to different contexts and samples. We illustrate the review with examples where good practice has advanced the agenda in bilingualism research and highlight resources to help researchers get started.

Highlights

  • A recent commentary on the bilingual advantage in executive function (Duñabeitia & Carreiras, 2015) optimistically concludes that veritas est temporis filia, truth is the daughter of time

  • As Duñabeita and Carreiras highlight, one precondition for progress is an unbiased publishing system in which the robustness of research is the primary criterion for publication. Another is the complete disclosure of all steps and processes underlying published outputs

  • Sharing of data and code underpins computational reproducibility, and is necessary for the verification of individual studies, and confers other benefits which we elaborate below

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Summary

Review Article

Cite this article: Bolibaugh C, Vanek N, Marsden EJ (2021). Towards a credibility revolution in bilingualism research: Open data and materials as stepping stones to more reproducible and replicable research.

Introduction
Open data and analytic code
Computational reproducibility
Analytic robustness
Research synthesis and planning
Good practice in reproducibility
Open materials and protocols
Good practice in replicability
Findings
Recommendations going forward
Full Text
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