One of the best – and yet perhaps most confusing – ways to look at the current state of today’s students is to look at the Canadian version of the National College Health Assessment (NCHA) survey, which is done every three years. I want to take you through a quick comparison of the 2013 and 2019 surveys (each of which were taken by tens of thousands of Canadian students, so it’s a good sample), because I think there is a
Canada is – to put it mildly – flat-out terrible at releasing student aid data. How many loans are issued? How many grants? In what amounts? These rather basic facts are unknowable from the public record. The government of Canada publishes statistics on the Canada Student Loans Program, which is good except that a) that’s only about 40% of the system and b) the most recent publication is from – and I wish I were kidding about this – 2016-17.
Yesterday, I looked at some reasons why WIL works. Today, I would like to talk about how we might answer larger questions about the extent to which WIL works (or, more accurately, what the impacts of individual aspects of WIL experiences look like). The case for WIL “working” in terms of labour market outcomes largely rests on data for co-op placements, and then kind of assuming that WIL is “co-op lite” (which is sort of true, sometimes). C.D. Howe Institute’s
All models are wrong, but some models are useful. This phrase, usually attributed to the statistician George Box, is especially apt when it comes to labour market forecasts. There is an obsession among policymakers about “getting better data” and “getting good labour market projections,” which can in turn (to some extent) drive planning for skills training and post-secondary education. And it is definitely a phrase that comes to mind when describing the new, bold labour market projection system described in
As you all know, a reasonable chunk of my work involves making international comparisons. This is far from simple in higher education because basic units of analysis differ enormously from one country to another. Whether you are counting students (do doctoral students count, when in some countries they are classified as employees? How do you equivalize student numbers for part-time status, which exists only in some countries?), or staff (how do you equivalize by rank? Do teaching-only staff count? What
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