20 years ago, straight from graduating, I started work as a part-time tutor within a Department of Mathematics and Computing. Within a few years it was obvious to a naive computing person that the mathematics part of the department was in trouble. Fewer and fewer people were enrolling in the mathematics programs, but they still had a fairly large group of academics (mostly doing service teaching – i.e. stats for business undergrads). At the same time, computing was exploding in enrolments. We had too few staff and too many students. The perception was that it wasn’t fair on us, to carry them.
How the worm turns. The descendant of that department is now a combination of computing (information technology), mathematics (mostly service), and information systems (a business flavour of computing). Computing had flourished around the turn of the century with the Y2K and dot-com influences, combined with international students in Australia. But the bubble has burst and the computing disciplines now find themselves struggling with large numbers of staff and bugger all students. They are suffering the same problem as the mathematicians.
One of the reasons I got out of computing and into L&T support within the university sector a few years ago was that I could see writing on the wall. What’s worse, I was not confident that the strategies being adopted (or likely to be adopted) would do anything to turn this around. I’m still not confident.
Infancy is perpetual
As a sign of getting older, this (as with many other events) continually reminds me of the Santayana quote
Progress, far from consisting in change, depends on retentiveness. When change is absolute there remains no being to improve and no direction is set for possible improvement: and when experience is not retained, as among savages, infancy is perpetual. Those who cannot remember the past are condemned to repeat it.
Here’s how this problem was planned to be solved in the past:
- Back in the mid to late 1990s, the mathematicians (led by a new professor) redesigned/recreated a mathematics degree that would be sexy to potential students and thus create a huge influx of new enrolments.
- In the mid to late 2000s, the computing folk (led by a Dean and a professor) redesigned/recreated the computing degree so it would be sexy to potential students and thus create a huge influx of new enrolments.
A key part of that initial plan was “games programming”, the apparent saviour of the information technology discipline in Australia.
Both failed.
What do you think the solution is to the new problem? Especially for computing?
Yep, you’re right. They are going to discuss changes needed to programs that will help increase enrolments. I hear that games programming is being thrown around again as possible solution.
The commodification of knowledge
Apart from the problem of failing to learn from the past, the other fundamental problem that I see in this response is a limited and incorrect view of higher education. It’s a view that sees the product of a university to be the degree program. It’s the view that leads to the above solution. Our product is our program, people don’t like our programs, so we have to reorganise the program or create new ones. The trend to creating new programs leads to the situation where “Forensic science graduates outnumber criminals”.
It’s the focus on the product that has led university leaders to place less emphasis on the process and the people. More importantly there hasn’t been an emphasis on the alignment between process, people, and product. It’s assumed that a university can create and teach any program. Oh, there is demand for a program in Paramedic Science. Oh, then we’d better employ a few folk in Paramedic Science, crank the product creation process and offer a program in Paramedic Science and people will come.
It’s a market driven, techo-rational approach that assumes a traditional analyse, design, implement, evaluate cycle that fails to understand the full complexity of what is required and the changing nature of surrounding environment.
Alignment of process, people and product
This type of process is externally driven and led by “leaders”. It assumes that there are people who are smart enough to predict what “consumers” will want from the University. It assumes that those folk can then create and control an environment that leads to the creation of what the consumers want. After 20 years within the university sector, I question all of those assumptions.
It also ignores the centrality of the people, but then is a long running theme of Australian higher education. I’m talking here about the academics. This process assumes that the academics are interchangeable. That there isn’t a significant difference between academics. That as long as you have an academic assigned to a course the outcome will be a good one. Especially if the institution is quality assured and has a significant number of checklists to control what is done.
As but one example, I’ve been trying to think of the programs I’m familiar with and asking the question “How many of the staff teaching courses in that program, actively engage in research/practice within the area they are teaching?”. In all of the examples I can think of, the answer is very, very few.
There are many reasons for this, but a major one is that this type of process starts with the end-product, and jury rigs a connection with the people. Often very badly.
The alternatives
There’s no easy fix for this problem. The idea that a new program will change things assumes that there are easy fixes. Any truly effective solution is going to be really, really hard and require some guts and intelligence on the part of the people involved. From that foundation, I can only see two alternatives:
- “Right-size” the program; or
i.e. if you accept the status quo, then there are only every going to be X students enrolled in the program (where X may be 0) and the number of staff you have should match that. Bite the bullet and effectively and appropriately “right-size” the number of staff required.
- Re-think the problem.
This takes guts and is briefly commented on below.
Re-think the problem
It doesn’t take a genius to see that society (in the broadest possible sense), how it works, and what it expects from education is changing. This post talks about Sir Ken Robinson’s take and mentions some of the societal changes. Tomaz captures a list of the almost taken for granted changes and starts talking about the fears that prevent people from engaging with them. Both of these are mostly school-focused, but they exist within higher education. Stephen Downes talks about these and other factors more broadly.
With all of those factors (and more) influencing how and what is expected from education, then old thinking isn’t going to cut it. Especially old thinking that assumes it knows the answers. Which influences what I’d suggest as the solution.
Focus on what you do well and learn
Let’s get specific. For the computing program, my suggestion would be figure out what you are good at. Or what the academics in your program are interested in. Focus on that, build on it, tend to ignore the rest, create networks around that, and learn.
Remember, I said above that there is no easy answer. This is not a simple process. It will be ruined by simple answers such as let everyone do there own thing or let them do what they’ve always done.
Some brief expansion on only a couple of those points.
Good at
Importantly, I would define “good at” not be the number of formal qualifications held, self-reporting, or number of research grants/journal publications. I would measure “good at” by the size, diversity and quality of the network surrounding the teaching and research the academics do in the area. The number of folk that are using or following the work the person does in that area.
For example, back in the mid-1990s I taught Systems Administration. We produced some resources. Those resources were widely used across the world. People were translating them into other languages. That’s being good at something.
But the network doesn’t have to be this focused on production. One of the significant limitations of the work in Systems Administration is that we never really grew a reciprocal network with these people where we used their materials and insights as much as they used ours.
This doesn’t mean that “good at” means you are the expert in the network, but that you are actively participating in the network. That you are learning.
Learning
Learning doesn’t apply to just to what you are teaching. It also applies to how you teach and how the institution supports you in your teaching and your practice. That learning has to be used to build on what you’re doing.
Build on
Too much of what goes on institutions is historical. It doesn’t change. It doesn’t learn. The “learning” isn’t enough, practice and the organisation has to build on what is learned. It has to be continually emerging.
For example, back when we were doing the work on Systems Administration, we had requests from hundreds of people from throughout the world to do the course. They wanted to pay and they wanted to do it entirely online.
The institutional rules at the time required overseas students to pay $1200 to take the course. There was no freedom for us to charge less because we planned to offer and suppor the course in a different way. There was no way for us to build on what was being done.
Time to get back to the thesis.
