Friday, 3 July 2015

Employability

The release of the Employment Performance Indicators by HESA this week made interesting reading. Universities up and down the land will be celebrating or holding post mortems, more so as employability seems set to increase in prominence in the government's thinking about higher education.

It’s a large data-set making it hard to spot patterns. I thought it might be useful to look at the aggregate outcomes by type of university. That isn’t going by mission group, but looking at institutions in historical context:

  • The ancient universities – not just Oxbridge but also the Scottish ancient foundations
  • The redbrick universities – the civic foundations of the 19th and first half of 20th centuries
  • The CATs – the Colleges of Advanced Technology given university status in the 1950’s and the 1960’s
  • The plate-glass universities – the new creations of the 1960’s
  • The post 1992s - the former polytechnics which became universities en masse in 1992
  • Newer universities – those created after the 1992 transition, often from colleges of higher education or former teacher training institutions
  • Specialist institutions – arts, drama, agriculture, medical and so on

The HESA methodology changed in 2011-12, meaning that there’s only three years of comparable Employment PI data. This is how those seven categories aggregate:

Employment PI (%)
2011-12
2012-13
2013-14
Ancient
93.0
94.0
94.5
Redbrick
92.0
92.9
93.8
CAT
90.8
91.4
92.0
Plate-glass
92.3
93.2
94.4
Post 1992
89.0
91.0
92.4
Newer
91.4
92.5
93.4
Specialist
92.4
92.3
94.7

It’s all very close, but note one interesting feature: the types with the lower employment of graduates are the post-1992 universities and the former CATs. Both of these types of universities aimed, historically, to focus on programmes and skills which met the needs of business and industry.

Within the data, of course, are highs and lows in each category. And the outcomes for any institution will have lots of factors which determine the employment KPI– whether its region and the local economy or subject spread, or even very local issues about how the DeLHE survey was conducted.

Nevertheless, it’s sometimes good to take a step back from the data and see what might be going on.


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