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Higher Education Strategy Associates

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?

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3 Responses to Counting Faculty, Counting Students

  1. Morning Reader says:

    And in calculating average class size, you’d be substituting one questionable indicator for another. First, because it assumes class size is an adequate stand-alone surrogate for … something – quality maybe? So class sizes of, say, 50, are a tad better than class sizes of 55. Second, because if class size does in fact matter, it’s the distribution and not the average that tells the story. Student A takes 5 classes each containing 100 students, for an average of 100. Student B takes 4 classes of 150 and one class of 10 for an average of 152. Student B loses by your math.Third, section sizes don’t address delivery method. A seminar of 5 might provide a great learning opportunity. A lecture of 5 might yield little more than a lecture of 500. What it boils down to is that it doesn’t boil down to class sizes, but to a host of factors that contribute to learning.

    • Alex Usher says:

      It would be silly to use as an output indicator, I’ll give you that. But as a rule-of-thumb way of looking at student experience and how universities deploy resources, for instance, it’s not bad. For instance, publishing credit hours taught (and avg. class size) by each type of faculty (e.g. FT vs. adjunct) might be revealing.

      Obviously, it would be better to get a look at more data about the host of factors relating to learning, but my experience is that this isn’t really something most institutions have the time/money to pursue and/or inclination to publish. If that were to change, I’d agree wholeheartedly with you. If it doesn’t, I think this is a modest improvement on what we have now.

      (I’ve also suggested some other improvements in the way we discuss student class sizes here: http://higheredstrategy.com/alternate-measures-of-class-size/ and here: http://higheredstrategy.com/fun-with-class-size-data/). I’d be curious to know your reaction to those measures, too.

  2. Pingback: What Would a Global Common Data Set Look Like? | HESA

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