A quick summary of two studies that came out this week which everyone should know about.
Programme for International Student Assessment (PISA)
On Tuesday, the results for the 2015 PISA tests were released. PISA is, of course, that multi-country assessment of 15 year-olds in math, science and reading which takes place every three years and is managed by the Organization for Economic Co-operation and Development (OECD). PISA is not a test of curriculum knowledge (in an international context that would be really tough); what it is instead is a test of how well individuals’ knowledge of reading, math and science can be applied to real-world challenges. So the outcomes of the test can best be thought of as some sort of measure of cognitive ability in various domains.
In addition to taking the tests, students also answer questions about themselves, their study habits and their family background. Schools also provide information about the kinds of resources they have and what kind of curriculum structure they use, there is an awful lot of background information about each student who takes the test, and that permits some pretty interesting and detailed cross-national examination in the determinants of this cognitive ability. And from this kind of analysis, the good folks at OECD have determined that government policy is best focused in four areas.
But heck, nobody wants to hear about that; what everybody wants to know is “where did we rank”? And the answer is: pretty high. The short version is here and the long version here, but here are the headlines: Out of the 72 countries where students took the test, Canada came 2nd in Reading, 7th in Science and 10th in Math. If you break things down to the sub-jurisdictional level (Canada vastly oversamples compared to other countries so that it can get results at a provincial level), BC comes first in the world for reading (Singapore second, Alberta third, Quebec fourth and Ontario fifth). In Science, Alberta and British Columbia come second and third in the world (behind only Singapore which as a country came top in every category). In Math, the story is not quite as good, but Quebec still cracks the top three.
CMEC also has a publication out which goes into more depth at the provincial level (available here). The short story is our four big provinces do well across the board but the little ones less so (in some cases much less so). Worth a glance if comparing provinces rather than countries is your thing.
One final little nugget from the report: the survey taken by students asks if the students see themselves heading towards a Science-based career in the future. In Canada, 34% said yes, the second highest of any country in the survey (after the US). I’d like to think this will put to rest all the snarky remarks about how kids aren’t sufficiently STEM-geared these days (<cough> Ken Coates <cough>), but I’m not holding my breath.
Statscan Report on Youth Employment
Statistics Canada’s put out some interesting data youth employment by Rene Morisette on Monday. It’s one of those half-full/half-empty stories: the youth unemployment rate is back down to 13% where it was in 1976 (and hence lower than it has been for most of the intervening 40 years), but the percentage of youth working full-time has dropped. The tricky part of this analysis – not really covered by the paper – is that the comparison in both time periods excludes students. That makes for a tricky comparison because there are proportionately about 3 times as many students as there were 40 years ago. To put that another way, there are a lot fewer bright kids – that is, the kind likely to get and keep jobs – not in school now than in 1976. So it’s not quite an apples-to-apples comparison and it’s hard to know what having more young people in school actually does to the employment rate.
Aside from data on employment rates, the report (actually a condensation of some speaking notes and graphs from a presentation made earlier this year) also includes a mishmash of other related data, from differing recent youth employment trends in oil provinces vs. non-oil provinces (short version: they’re really different) to gender differences in graduate wage premiums (bigger for women than men, which may explain participation rate differences), to trends in overall graduate wage premiums. Intriguingly, these rose through the 80s and 90s but are now declining back to 1980 levels, though whether that is due to an increase in the supply of educated labour or reflects broader changes in the labour market such as the “Great Reversal” in the demand for cognitive skills that UBC’s David Green and others have described is a bit of a mystery.
But don’t take my word for it: have a skim through the report (available here). Well worth a few minutes of your time.
I found the provincial data interesting with a few surprises. I’d next like to see within province data analysed to sort out regional variations (especially in the biggest provinces) as well as to see the differences between urban and rural areas, or large versus small urban centres. Does this type of analysis exist?