Serendipity

Computer Science, as an undergraduate degree, is in trouble. Enrollments have dropped steadily throughout this decade: for example at U of T, our enrollment is about half what it was at the peak. The same is true across the whole of North America. There is some encouraging news: enrollments picked up a little this year (after a serious recruitment drive, ours is up about 20% from it’s nadir, while across the US it’s up 6.2%). But it’s way to early to assume they will climb back up to where they were. Oh, and percentage of women students in CS now averages 12% – the lowest ever.

What happened? One explanation is career expectations. In the 80’s, its was common wisdom that a career in computers was an excellent move, for anyone showing an aptitude for maths. In the 90’s, with the birth of the web, computer science even became cool for a while, and enrollments grew dramatically, with a steady improvement in gender balance too. Then came the dotcom boom and bust, and suddenly a computer science degree was no longer a sure bet. I’m told by our high school liaison team that parents of high school students haven’t got the message that the computer industry is short of graduates to recruit (although with the current recession that’s changing again anyway).

A more likely explanation is perceived relevance. In the 80’s, with the birth of the PC, and in the 90’s with the growth of the web, computer science seemed like the heart of an exciting revolution. But now computers are ubiquitous, they’re no longer particularly interesting. Kids take them for granted, and a only a few über-geeks are truly interested in what’s inside the box. But computer science departments continue to draw boundaries around computer science and its subfields in a way that just encourages the fragmentation of knowledge that is so endemic of modern universities.

Which is why an experiment at Georgia Tech is particularly interesting. The College of Computing at Georgia Tech has managed to buck the enrollment trend, with enrollment numbers holding steady throughout this decade. The explanation appears to be a radical re-design of their undergraduate degree, into a set of eight threads. For a detailed explanation, there’s a white paper, but the basic aim is to get students to take more ownership of their degree programs (as opposed to waiting to be spoonfed), and to re-describe computer science in terms that make sense to the rest of the world (computer scientists often forget the the field is impenetrable to the outsider). The eight threads are: Modeling and simulation; Devices (embedded in the physical world); Theory; Information internetworks; Intelligence; Media (use of computers for more creative expression); People (human-centred design); and Platforms (computer architectures, etc). Students pick any two threads, and the program is designed so that any combination covers most of what you would expect to see in a traditional CS degree.

At first sight, it seems this is just a re-labeling effort, with the traditional subfields of CS (e.g. OS, networks, DB, HCI, AI, etc) mapping on to individual threads. But actually, it’s far more interesting than that. The threads are designed to re-contextualize knowledge. Instead of students picking from a buffet of CS courses, each thread is designed so that students see how the knowledge and skills they are developing can be applied in interesting ways. Most importantly, the threads cross many traditional disciplinary boundaries, weaving a diverse set of courses into a coherent theme, showing the students how their developing CS skills combine in intellectually stimulating ways, and preparing them for the connected thinking needed for inter-disciplinary problem solving.

For example the People thread brings in psychology and sociology, examining the role of computers in the human activity systems that give them purpose. It explore the perceptual and cognitive abilities of people as well as design practices for practical socio-technical systems. The Modeling and Simluation thread explores how computational tools are used in a wide variety of sciences to help understand the world. Following this thread will require consideration of epistemology of scientific knowledge, as well as mastery of the technical machinery by which we create models and simulations, and the underlying mathematics. The thread includes in a big dose of both continuous and discrete math, data mining, and high performance computing. Just imagine what graduates of these two threads would be able to do for our research on SE and the climate crisis! The other thing I hope it will do is to help students to know their own strengths and passions, and be able to communicate effectively with others.

The good news is that our department decided this week to explore our own version of threads. Our aims is to learn from the experience at Georgia Tech and avoid some of the problems they have experienced (for example, by allowing every possible combination of 8 threads, it appears they have created too many constraints on timetabling and provisioning individual courses). I’ll blog this initiative as it unfolds.