Higher Education Strategy Associates

Category Archives: class size

November 24

Class Size, Teaching Loads, and that Curious CUDO Data Redux

You may recall that last week I posted some curious data from CUDO, which suggested that the ratio of undergraduate “classes” (we’re not entirely sure what this means) to full-time professors in Ontario was an amazingly-low 2.4 to 1.  Three quick follow-ups to that piece.

1.  In the previous post, I offered space on the blog to anyone involved with CUDO who could clear up the mystery of why undergraduate teaching loads appeared to be so low.  No one has taken me up this offer.  Poor show, but it’s not too late; I hereby repeat the offer in the hope that someone will step forward with something convincing.

2.  I had a couple of people – both in Arts faculties at different medium-sized non-U15 Ontario universities – try to explain the 2.4 number as follows: teaching loads *are* in fact 4 courses per year (2/2), they said.  It’s just that once you count sabbaticals, maternity leaves, high enrolment (profs sometimes get a reduced load if one of their classes is particularly large), leaves for administrative duty, and “buyouts” (i.e. a prof pays to have a sessional teach the class so he/she can do research), you come down to around 2.5.

This is sort of fascinating.  I mean, if this were generally true, it essentially means that universities are managing their staff on the assumption that 35-40% of staff resources are theoretically available for teaching.  Now, obviously all industries overstaff to some extent: sickleaves and maternity happen everywhere.  But 40%?  That sounds extremely high.  It does not speak particularly well of an institution that gets its money primarily for the purpose of teaching.  Again, it would be useful if someone in an institution could confirm/deny, but it’s a heck of a stat.

3.  Turns out there’s actually a way to check this, because at least one university – give it up for Carleton, everyone – actually makes statistics about sessional professors public!  Like, on their website, for everyone to seeMirabile dictu.

Anyways, what Carleton says is that in 2014-15, 1,397 “course sections” were taught by contract or retired faculty, which translates into 756.3 “credits”.  At the same time, the university says it has 850 academic staff (actually, 878, but I’m excluding the librarians here).  Assuming they are all meant to teach 2/2, this would be 3,400 “classes” per year.  Now, it’s not entirely clear to me whether the definition of “classes” is closer to “credits” or “course sections”; I kind of think it is somewhere in between.  If it’s the former, then contract/retired faculty are teaching 22.2% of all undergraduate classes; if it’s the latter, then it’s 41.1%.  That’s a wide range, but probably about right.  And since Carleton is a pretty typical Canadian university, my guess is these numbers roughly hold throughout the system.

However, what this doesn’t tell you is what percentage of credit hours are taught by sessionals – if the undergraduate classes taught by these academics are larger, on average, than those taught by full-timers, then the proportion will be even higher than this.  I’ve had numerous conversations with people in a position to know who indicate that in many Ontario Arts faculties, the percentage of undergraduate credit hours taught by sessional faculty is roughly 50%. Elsewhere, of course, mileage may vary, but my guess is that with the possible exception of the Atlantic, this is the case pretty much everywhere.

I could be wrong, of course.  As with my CUDO offer, anyone who wants to step forward with actual data to show how I am wrong is welcome to take over the blog for a couple of days to present the evidence.

November 17

Curious Data on Teaching Loads in Ontario

Back in 2006, university Presidents got so mad at Maclean’s that they stopped providing data to the publication.  Recognizing that this might create the impression that they had something to hide, they developed something called “Common University Dataset Ontario” (CUDO) to provide the public with a number of important quantitative descriptors of each university.  In theory, this data is of better quality and more reliable than the stuff they used to give Maclean’s.

One of the data elements in CUDO has to do with teaching and class size.  There’s a table for each university, which shows the distribution of class sizes in each “year” (1st, 2nd, 3rd, 4th): below 30, 31-60, 61-90, 91-150, 151-250, and over 250.  The table is done twice, once including just “classes”, and another with slightly different cut-points that include “subsections”, as well (things like laboratories and course sections).  I was picking through this data when I realised it could be used to take a crude look at teaching loads because the same CUDO data also provides a handy number of full-time professors at each institution.  Basically, instead of looking at the distribution of classes, all you have to do is add up the actual number of undergraduate classes offered, divide it by the number of professors, and you get the number of courses per professor.  That’s not a teaching load per se, because many courses are taught by sessionals, and hell will freeze over before institutions release data on that subject. Thus, any “courses per professor” data that can be derived from this exercise is going to overstate the amount of undergradaute teaching being done by full-time profs.

Below is a list of Ontario universities, arranged in ascending order of the number of undergraduate courses per full-time professor.  It also shows the number of courses per professor if all subsections are also included.  Of course, in most cases, at most institutions, subsections are not handled by full-time professors but some are; and so assuming the underlying numbers are real, a “true” measure of courses per professors would be somewhere in between the two.  And remember, these are classes per year, not per term.

Classes Per Professor, Ontario, 2013


















Yes, you’re reading that right.  According to universities’ own data, on average, professors are teaching just under two and a half classes per year, or a little over one course per semester.  At Toronto, McMaster, and Windsor, the average is less than one course per semester.  If you include subsections, the figure rises to three courses per semester, but of course as we know subsections aren’t usually led by professors.   And, let me just say this again, because we are not accounting for classes taught by sessionals, these are all overstatements of course loads.

Now these would be pretty scandalous numbers if they were measuring something real.  But I think it’s pretty clear that they are not.  Teaching loads at Nipissing are not five times higher than they are at Windsor; they are not three and a half times higher at Guelph than at Toronto.  They’re just not.  And nor is the use of sessional faculty quite so different from one institution to another as to produce these anomalies.  The only other explanation is that there is something wrong with the data.

The problem is: this is a pretty simple ratio; it’s just professors and classes.  The numbers of professors reported by each institution look about right to me, so there must be something odd about the way that most institutions – Trent, Lakehead, Guelph, and Nipissing perhaps excepted – are counting classes.  To put that another way, although it’s labelled “common data”, it probably isn’t.  Certainly, I know of at least one university where the class-size data used within the institution explicitly rejects the CUDO definitions (that is, they produce one set of figures for CUDO and another for internal use because senior management thinks the CUDO definitions are nonsense).

Basically, you have to pick an interpretation here: either teaching loads are much, much lower than we thought, or there is something seriously wrong with the CUDO data used to show class sizes.  For what it’s worth, my money is on it being more column B than column A.  But that’s scarcely better: if there is a problem with this data, what other CUDO data might be similarly problematic?  What’s the point of CUDO if the data is not in fact common?

It would be good if someone associated with the CUDO project could clear this up.  If anyone wants to try, I can give them this space for a day to offer a response.  But it had better be good, because this data is deeply, deeply weird.

June 06

Counting Faculty, Counting Students

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?

January 06

Fun with Class Size Data

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.

January 05

Alternate Measures of Class Size

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.

September 21

The Cult of Small vs. The Advantage of Big

Just some of the programs offered at Carleton

For a country as large a Canada it’s amazing what a fetish we make of smallness – with students packed into large institutions, there are economies of scale in terms of teaching and student services (admittedly, these economies are then splurged on research, but that’s a separate issue). But when it comes to attracting students, we try to hide bigness. Schools like to talk about how they “feel like” a small school, or give attention to students “as if it were” a small school.

This is a dumb idea for two reasons. First, it’s nonsense. Big schools can’t give a small school feel – they simply aren’t built to do so and it actually harms a university’s credibility and brand to pretend to be something they are not. That’s not to say big schools can’t give students a bit more of a human touch – the opposite of small administration needn’t be Borg-like administration – but raising expectations too high never does anyone any good.

Second, the attempt to play up smallness actually covers up big schools’ one enormous strength, and that is choice. Students love choice; if you look (as we do) at a lot of student surveys what becomes clear is that the most substantial critique students have of small schools is that they are, well, too small. As in, “limited.” Which isn’t something you can say about multiversities with a dozen or more faculties and 20,000 or more students.

Big means choice. Big means more options. Big means more opportunities. Big means not living for four years in a small community where everyone knows what you’re doing. One of the country’s comprehensive universities (my choices would be Ryerson, or Carleton, or perhaps Laval) needs to stand up in a strong marketing campaign and say “Proud to Be Big.” Not only would they stand out from the crowd, they’d be doing all other large-ish universities a service as well.

September 20

The 160 Student Solution

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.