I’ve recently been given a password for HEIDI. This is the system used to interrogate HESA data in detail, and for someone like me then there’s lots of things to experiment with.
By Shervinafshar (Own work) [CC-BY-SA-3.0 (http://creativecommons.org/licenses/by-sa/3.0) or GFDL (http://www.gnu.org/copyleft/fdl.html)], via Wikimedia Commons
I can already see some great uses though, to support my work:
- predicting our league table performance
- benchmarking our subject areas against comparators, in terms of size and performance
- investigating BME performance across the sector, so we can compare and benchmark
Here’s a few headlines I managed to generate in a short time, using the 2012-13 HESA student record:
(all data presented in this blog post was derived from HEIDI. Intellectual property rights in material generated by heidi rests with HESA and/or other Data Originators)
In terms of 1sts and 2(i)s, which we know is an area where we are lower than much of the sector, then we can see that the number of good degrees we awarded last year rose from 55% to 57.5%, against an average sector rise of 2.2%. This agrees with the internal data we have previously generated. Overall, 119 institutions saw a rise in the number of good degrees and 33 saw a drop. In terms of league tables then, this rise may have minimal impact (although I have used a wider range of HEIs in this analysis than the league table compilers would).
Benchmarking against comparators at subject level is another area in which we can develop more business intelligence, especially in terms of linking to portfolio performance and then to student and league table outcomes. For instance, some data for Law is shown below:
| 2012-13 | 2011-12 | 2012-13 | |
| Institution | enrolment | percentage good degrees, Law | percentage good degrees, Law |
| Birmingham City University | 962 | 52% | 52% |
| The University of Central Lancashire | 942 | 57% | 60% |
| Coventry University | 866 | 56% | 57% |
| University of Derby | 470 | 59% | 65% |
| Glynd?r University | 21 | .. | .. |
| The University of Huddersfield | 631 | 31% | 43% |
| The University of Keele | 475 | 61% | 63% |
| Liverpool John Moores University | 1,279 | 64% | 72% |
| The University of Plymouth | 735 | 52% | 54% |
| Staffordshire University | 843 | 57% | 59% |
| The University of Sunderland | 422 | 51% | 45% |
| Teesside University | 469 | 44% | 55% |
| The University of Wolverhampton | 1,178 | 41% | 34% |
Attainment of Black and Minority Ethnic students is another key area in which I work. Using HEIDI, I can extract the same data that the Equality Challenge Unit provide in their statistical reports – we can just get it more quickly this way.
For instance, I can now look at degree attainment of students by different ethnicity for us and our usual comparator universities.
It’s going to be a case of “watch this space”, as I can now develop more sophisticated datasets and visualisations. However, this doesn’t detract from the fact that having the data as just one small part of the jigsaw. The commitment to deliver our academic strategy, and its focus on attainment, means that we know where we are positioned now, we know where we should be so the hard work is in developing the right interventions to make sure that we have a portfolio of awards that delivers for us as an institution and for our individual students
.