PODCAST: Transfers, ONS, climate change, brexit

This week on the podcast there are new figures from the Office for Students on student transfer to understand, as well as some striking survey data out from the ONS.

News and analysis of higher education from our leading team of wonks.


This week on the podcast there are new figures from the Office for Students on student transfer to understand.

There’s also some striking survey data out from the ONS, a new paper on universities and climate change from HEPI, and the small issue of Brexit and its impact on higher education.

With Claire Taylor, Deputy Vice-Chancellor at Wrexham Glyndwr University, Johnny Rich, Chief Executive of the Engineering Professors’ Council and presented by Jim Dickinson, Wonkhe’s Associate Editor.

Items this week


This weeks’ question is very much a preview for a piece that should be out pretty soon – I’ve been looking at old unistats data to try and understand (well, understand in more detail than the OfS Key Performance Measure) how the subject areas offered as courses have changed over the past two years.

I’ve data on the number of courses that are no longer offered, and the number of new courses offered, by detailed subject area. The question I am asking you is basically whether the sector subject mix is shifting or if it is basically a steady state – will old courses in a subject being likely to be replaced by new ones in the same subject.

So – number of courses lost in two years, versus number of new courses – by subject. Does it correlate?

And the answer is – very surprisingly – yes, r squared is 0.68 and thus we have a strong correlation. However, here we reach the limits of linear correlation as an analytical tool – there are some wild outliers, and the answer belies the fact that the sector shrank by 2,300 courses where a subject is given over that period. Sport science and business are growth areas, whereas history is key among the shrinkages. Data is from two iterations of unistats data (January 2019 and October 2020), and where the data doesn’t exist I’ve not plotted it.

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