Aside from causing me to look up it’s origins, this term is the cause of a lot of higher education activity right now. Put bluntly, more than ever we need to minimise attrition and keep our students. Putting the softer aspects of that to one side this implies we must be able to measure attrition and of course to measure something we need to have a definition.
That last bit is where somehow things seem to get complicated which of course makes reporting using BI a bit difficult. You would think that the formula for measuring attrition or retention or completion was simple, widely known and certainly consistently applied, at least within Australia and New Zealand, if not internationally.
The reality seems to be quite different. Ask your colleagues for a definition of any or all of these and I suspect they’ll give you a range of responses.
Stepping back and considering where attrition fits in the overal student administration lifecycle helps and in the spirit of Glasnost I offer you the following very simple and universally applicable context (straight off the DEEWR website here).
the attrition rate plus the retention rate plus the completion rate for a given student population in a given year will equal 100 percent
As you can tell from the title of this post, I’m hinting that there is more to this subject than perhaps initially meets the eye. I will explore each of these three elements in more detail soon with the intention of putting some transparency around the whole topic, in the meantime here’s the high-level scene setting definition of them.
- Retention is all about students who continue their studies the following year
- Completion relates to those students who complete their studies at an institution
- Attrition is a measure of students who do not continue or complete their studies at the same institution the following year
I’ve actually found it extremely difficult to find a current, authoritative published source on any of this information. The only definitions I could find on DEEWR web pages relate to 1999-2002 data and it is not clear if the formula has changed since then. Next step for me is to talk to our Planning department and find out their take on it all.
Rob, I wondered where your working DEEWR definition of retention/attrition/completion includes students enrolling in a different course at the same institution. Cheers, Michael
Hi Michael, thanks for the comment. As I currently understand it, a student studying for a different award in the same institution the following year would still be classed as being retained. Of course if we’re trying to show the breakdown of the overall institutional retention by award then that poses a problem for us - do we show attrition in the original award or not?
It would be especially useful to know whether attrition is occurring in established courses or in new products that haven’t yet settled down.
It’s fairly usual for a university to have a committee or sub-committee of its academic board that approves new courses and units. In evaluating a proposal on behalf of the board the committee is supposed to look at the ‘viability’ of the course or unit. This often involves guesswork because the people who make the proposal often have very little reliable information. The result is that a lot of what gets approved has little justification other than wishful thinking: sure, there’ll be 50 EFTSL in the first year (or was that students - the proponent of one course I saw approved didn’t really know!).
How many of these bets pay off over five years?
Well, it’s OK to be wise after the event (better than not) but much more advantageous to be well-informed before. Enter, BI.
It is no easy task to relate financial data to courses and units but it’s getting better. For the moment let’s just treat enrolments as proxies for dollars and ignore different fees and Commonwealth contributions and different delivery costs.
Why is this especially important for studying attrition? Well new courses and units are sometimes rather experimental. The problem for students is that the experiment is on them.
It’s true that after all the computer modelling and wind-tunnel testing some brave soul sits in the pilot’s seat and takes a new aircraft off the ground for the first time. The big difference between this and new courses and units is that the first flight test doesn’t put any customers at risk.
If we had some measures of admissions to new courses and enrolments in new units as time series over several years the people who propose the new products would be in a better position to predict viability.
It’s a bad outcome for everyone concerned when something like a new course doesn’t work well but there are a few students in it and both they and the university have a, say, three or four year commitment.