Identifying a research agenda for postgraduate taught education in the UK: lessons from a machine learning facilitated systematic scoping review

Gale Macleod*, Marshall Dozier, Rosanna Alice Marvell, Gerri Matthews, Malcolm Macleod, Jing Liao

*Corresponding author for this work

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    This research aimed to describe and evaluate research on the Postgraduate Taught (PGT) sector in the UK from January 2008 to October 2019. The focus on PGT allowed a detailed analysis of an often overlooked part of the HE sector. Methodologically, the research is original in its use of an innovative machine learning approach to a systematic scoping review. The review scrutinised subject areas, topics studied and methodological approaches taken. Initial searches found 9,814 potentially relevant studies which were reduced to 693 for analysis. The machine learning approach was successful in reducing time without compromising accuracy. We conclude that this methodological approach is appropriate for similar reviews within education. Findings show a dominance of research into professional education programmes; a majority of research with PGT as the context rather than focus; a small number of comparative and large-scale studies; and substantial research categorised as ‘scholarship of teaching’. While further research is required to ascertain if the findings are transferable to other national contexts, this study provides a reproducible methodology and identifies areas for future research to examine.
    Original languageEnglish
    Number of pages18
    JournalOxford Review of Education
    Early online date30 May 2023
    Publication statusEarly online - 30 May 2023


    • Postgraduate taught
    • Master’s
    • systematic review
    • machine learning

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