With the announcement of the amount of funding awarded to UK Higher Education institutions from HEFCE, the government funding body, several people posted me links to the data wondering what I might do with it. I saw this as a good opportunity to do something I’ve been meaning to do for ages, specifically have another look at how to provide a view of a range of HE related datasets around particular institutions. So for example, if you ever wondered whether or not there is a relationship between the drop out rate from a university and a surveyed average teaching score, you should be able to look it up:

Since its launch, one of the more actively maintained areas of the Guardian datastore has been the education area. A quick skim over HE related data turns up at least the following:

• University funding, (March 2010) (data);
• University Pay (March 2010) (data);
• University Guide (student survey) (2009/10) (data);
• UNiversity drop-out rate s (June 2009) (data);
• University building repair (February 2010) (data).

In a follow on post, I’ll show how to pull this data together, but for now, let’s look at some of the possibilities of pulling data in from these separate sheets around an HEI. As a proof of concept, I grabbed the following data and popped it into Many Eyes Wikified:

(I need to add provenance info to the wiki, but didn’t in this instance because I don’t want the data to be referenced or trusted… I still need to check everything is working properly… (so I guess I should have used dummy HEI names… hmm…)

The data is pulled from four separate sheets and aggregated around HEI name. The “Percentage no longer in HE” comes from the datastore Dropout spreadsheet, the “Total staff earning ..” etc column is from the Pay spreadsheet, the “Average Teaching” to “Student to Staff Ratio” columns come from the 2009-10 university tables spreadsheet, and the “Teaching funding” to “Funding change” columns from the most recent (2010-11) funding spreadsheet.

I’ve posted a couple of interactive visualisations on to Many Eyes WIkified so you can have a play with the numbers (but don’t trust them or quote them unless you fact check them first…;-)

The first is a Scatter Chart, which gives us three dimensions to play with – x, y, and dot size.

So for example, in the chart shown above, we see that lower teaching scores seem to correlate with higher drop out rates. In the chart below, we seed how teaching scores relate to the expenditure per student and the student staff ratio (and how expenditure per student and student staff ratio relate to each other):

Is satisfaction rewarded with funding, or is funding to improve matters?

The other chart type I produced is a bar chart. These are less interesting, but heavily used…

I assume that university strategy and planning units worry over this sort of combined data all the time (but I’m not sure how they: obtain it, combine it, represent it, report it, use it? Maybe if an HE planner is reading they could post a comment or two to describe what data they use, how they use it and what they use it for…?;-) Anyway, it’s getting close to a stage now where the rest of us can play along too…;-)