British education research and its quality: An analysis of Research Excellence Framework submissions.

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Title: British education research and its quality: An analysis of Research Excellence Framework submissions.
Authors: Inglis, Matthew, Foster, Colin, Lortie‐Forgues, Hugues, Stokoe, Elizabeth
Source: British Educational Research Journal. Oct2024, Vol. 50 Issue 5, p2495-2518. 24p.
Subjects: British education system, Dirichlet principle, Calculus of variations, Higher education, Continuing education
Abstract: We analysed the full text of all journal articles returned to the education subpanel of the 2021 Research Excellence Framework (REF2021). Using a latent Dirichlet allocation topic model, we identified 35 topics that collectively summarise the journal articles that research units, typically schools of education, selected for submission. We found that the topics which units wrote about in their submitted articles collectively explained a large proportion (84.1%) of the variance in the quality assessments they received from the REF's expert peer review process. Further, with the important caveat that we cannot attribute causality, we found that there were strong associations between what the subpanel perceived to be excellent research and the adoption of particular methods or approaches. Most notably, units that returned more interview‐based work typically received lower scores, and those which returned more analyses of large‐scale data and meta‐analyses typically received higher scores. Finally, we applied our 2021 model to articles submitted to the previous exercise, REF2014. We found that education research seems to have become less qualitative and more quantitative over time, and that our 2021 model could successfully predict the scores assigned by the REF2014 subpanel, suggesting a reasonable degree of between‐exercise consistency. [ABSTRACT FROM AUTHOR]
Copyright of British Educational Research Journal is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: British education research and its quality: An analysis of Research Excellence Framework submissions.
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  Data: <searchLink fieldCode="JN" term="%22British+Educational+Research+Journal%22">British Educational Research Journal</searchLink>. Oct2024, Vol. 50 Issue 5, p2495-2518. 24p.
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  Data: <searchLink fieldCode="DE" term="%22British+education+system%22">British education system</searchLink><br /><searchLink fieldCode="DE" term="%22Dirichlet+principle%22">Dirichlet principle</searchLink><br /><searchLink fieldCode="DE" term="%22Calculus+of+variations%22">Calculus of variations</searchLink><br /><searchLink fieldCode="DE" term="%22Higher+education%22">Higher education</searchLink><br /><searchLink fieldCode="DE" term="%22Continuing+education%22">Continuing education</searchLink>
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  Label: Abstract
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  Data: We analysed the full text of all journal articles returned to the education subpanel of the 2021 Research Excellence Framework (REF2021). Using a latent Dirichlet allocation topic model, we identified 35 topics that collectively summarise the journal articles that research units, typically schools of education, selected for submission. We found that the topics which units wrote about in their submitted articles collectively explained a large proportion (84.1%) of the variance in the quality assessments they received from the REF's expert peer review process. Further, with the important caveat that we cannot attribute causality, we found that there were strong associations between what the subpanel perceived to be excellent research and the adoption of particular methods or approaches. Most notably, units that returned more interview‐based work typically received lower scores, and those which returned more analyses of large‐scale data and meta‐analyses typically received higher scores. Finally, we applied our 2021 model to articles submitted to the previous exercise, REF2014. We found that education research seems to have become less qualitative and more quantitative over time, and that our 2021 model could successfully predict the scores assigned by the REF2014 subpanel, suggesting a reasonable degree of between‐exercise consistency. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of British Educational Research Journal is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1002/berj.4040
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              Text: Oct2024
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