Though amateur higher education statisticians are addicted to it, there is virtually no statistic less useful than the student-staff ratio. There are basically two reasons why this is the case.

The first is that not all students are alike. Some are full-time, some are part-time. This problem is reasonably easy to solve by creating a method for calculating full-time equivalency. But for this, the number of credit-hours students take must be transparent. The second is that not all professors are alike. This is a bigger issue, because it takes in two possible issues.

The first is that the definition of a “professor” is more fluid than most people realize. Everyone can agree to including full-time tenured or tenure-track professors. But what about adjuncts? Chargés de cours? Clinicians in teaching hospitals? Emeritus professors? When outside agencies come knocking for statistics from universities, universities will supply figures that depend on their use. If they want to emphasize how underfunded they are, they will use the smallest possible number; if they want to emphasize how great the student-professor ratio is, they will include all of the above. The number of professors on hand can shift considerably in the context of a single data request.

There’s a solution to this of course – schools can simply report many different categories of professors and allow users to use whichever combination of them they choose. Ontario universities, for instance, report about a half-dozen such figures to government for precisely this reason. But that only solves part of the problem. Because, just as not all students are in class for the same amount of time, not all profs spend the same amount of time in class, either.

The reason anybody cares about staff-student ratio is that it’s a proxy for class size. But if you have two universities with identical ratios, but at university A the expected course load is 4/4 and at university B its 2/2, you’re going to have radically different class sizes. Just counting bodies isn’t enough: you need to count hours in the class.

Here’s what institutions ought to do. They ought to publish the number of credit hours taken by students. And they ought to publish the number of class hours that each of the various types of professors (tenure-track, adjunct, etc.) has. If they could do this at the faculty level, so much the better. Then, by dividing the two sets of numbers, you’d get an actual average class size. Which, again, is what people actually care about.

Making this data available would vastly improve our understanding of classroom conditions. And at most institutions, it should not require any extra data collection – everything required should already be “in the system.”

So, to all our IR readers: how about it?

Yesterday, I promised to show you some of the data on our alternative measure of class size (see here for more details). Some preliminaries, though:

Our measure of “average number of classmates” may be a bit crude (it depends on student estimates of class sizes), but it is robust. Institutional averages bounce around by a few percent each year, but long-term averages – which at most institutions involve between two and four thousand observations – are pretty stable. To avoid complicating things, what I present here are six-year institutional means.

Obviously, class size is correlated with institutional size (i.e., smaller universities have smaller classes); but the data shows an enormous amount of variation around the mean. Take a look at the highest- and lowest-scoring U-15 schools: even among supposedly similar universities (research-intensive universities with medical schools), one can get vastly different average class sizes. Since they’re the same type of institution, these differences can’t be accounted for by different mixes of faculties – they must be straight-up reflections of differences in the way undergraduate education is managed.

Smallest and Largest Class Sizes Among U-15 Schools

Perhaps more intriguing are the results for the next tier of institutions – comprehensive institutions with substantial student populations but without medical schools. At the lower end, these schools have substantially smaller “average numbers of classmates,” but at the top end, at universities like Brock and Guelph, the numbers are indistinguishable from those at top research universities.

Smallest and Largest Class Sizes Among Comprehensive Schools

Finally, here’s smallest and largest class sizes among the smaller universities.

Smallest and Largest Class Sizes Among Small Undergraduate Schools

Notice how the institutions with the highest numbers on each of those graphs are from Ontario? That’s not a coincidence. Only three Ontario universities (Ryerson, Lakehead and Laurentian) have averages under 100; outside the province, only seven (Dalhousie, McGill, Manitoba, Calgary, Alberta, SFU and UBC) have averages over 100. Clearly, when you combine the lowest per-student funding in the country with the highest professors’ salaries in the country, something has to give somewhere: that something, apparently, is class size.

Small classes aren’t everything, of course; after all, Western manages to get stellar satisfaction ratings despite having some of the country’s largest classes. But this data does suggest that the Ontario student experience is significantly different than that in the rest of the country – and it’s not commensurate with the tuition they’re paying.

Interesting results, no? Anyone who wants to work with us on improving our methodology, let us know. We’re all ears.

It may sound silly, but calculating and comparing average class sizes across institutions is very hard to do. Here’s why.

Back when institutions actually paid attention to Maclean’s, the class size questions were the easiest to “massage,” because there was no common definition of what constituted a class. Do course sections count? What about instrument practice classes in music faculties? Many universities gamed the system by including these for the purposes of calculating “average class size” but excluding them when it came to calculating “percentage of classes taught by tenured faculty.”

Playing with numerators and denominators was good for yuks, but not so good in terms of coming up with reliable comparators. Which, of course, was the point. Bluntly, any time you’re counting on institutions to give you accurate data for comparison and some institutions know they won’t come out well in such a comparison, the likelihood increases that said institutions will try to game the data. Way it goes.

But even if the input data were clean, the traditional measure of “average class size” – total student credit hours divided by the number of “classes” (however defined) – leaves much to be desired. Imagine a school with only two classes: one with five hundred students and the other with ten. The “average class size” of this institution using the traditional definition is 255. But this is a vast distortion of reality since 98% of students only experience a class of 500. Matching tiny classes with huge ones can bring the average way down without actually altering the experience of the vast majority of students. In short, the traditional way of measuring class-size can be skewed lower just by adding a few small classes – and it provides significant leeway for institutions to monkey with the data inputs.

But there is there an alternative. Instead of measuring “average class size” (credit hours divided by classes), why not measure “average number of classmates per class”? We’ve been doing it for six years now with the Globe and Mail: asking over 30,000 students each year about each of their classes and specifically asking them how many classmates they have. Using that measure, our fictional two-class university would have a score of 490, which I would argue is probably a better reflection of most students’ experience than the more traditional measure.

It’s a bit crude, to be sure, but the resulting institutional averages are pretty stable over time, which suggests it’s a robust measure. And, crucially, it’s a measure that can’t be gamed. As we’ll see tomorrow when we look at some of the data, the results shed some very interesting light on institutional priorities.

Till then.

Here’s an important question. Why do we care about how many classes a professor teaches?

Virtually every university collective agreement has some kind of minimum or average or desirable teaching load – 2+3, 2+2, etc. It doesn’t really matter since so many professors are buying their way out of these anyway and going down to one class a term. Regardless, though, the unit of analysis here is the course.

This makes absolutely no sense. Universities don’t get paid based on how many courses they teach. They get paid by how many students they teach. And the term “course” isn’t exactly homogenous. It includes tutorials, small seminars, regular classrooms and enormous 500-student affairs. And the price professors pay to get out of teaching a class is more or less the same no matter how many students are enrolled in it.

Let me suggest the following: let’s get rid of course-based workloads and adopt student-number workloads instead. Why not say that every professor has to teach a minimum of 160 student half-courses (e.g., one half course of 160 students or 4 half courses of 40 students each) per year? And, equally, that when professors want to get out of a course, the payment to do so must be proportional to the number of student half-courses being abandoned.

The benefits of this go far beyond standardizing workloads. It would prevent proliferations of small niche courses and send signals to deans and department heads about when to stop hiring (no department head will want to hire if it cannibalizes student numbers that existing professors need to hit in order to get paid). And it would put a cap on the number of students being taught by sessionals.

In fact, just looking at Statistics Canada’s FTE numbers in the CAUT Almanac, assuming that every full-time students takes five courses per term, it seems that there are a little over 8.7 million half-courses being delivered at Canadian universities. If every institution adopted the 160 student rule, then the country’s 38,300 full-time academic staff would be able to teach a minimum of 6.1 million half-courses – or very nearly three-quarters of the total.

Think about it: adopting a minimum student standard has benefits for workload standardization, cost control and decreasing reliance on sessionals. With tighter budgets on the way in most of Canada, it’s an idea whose time might be now.