Today we’d like to look at how students describe their best and worst academic experiences.

Now, you might think that these two things are pretty similar: one being the obverse of the other. Good profs = best experience, bad profs = worst experience, etc. But it turns out it’s not quite so simple.

Take technology and facilities, for instance. Students almost never cite great tech as being part of their best experience; they do, however, routinely describe bad tech as being a “worst experience.” They never describe a well-organized course or professor as a positive experience, but they regularly describe it as a worst experience.

When students talk about what made their experience at university so great, they tend to describe things like personal and intellectual growth and forming relationships (both with other students and professors). When they talk about worst experiences, they often talk about particular episodes or incidents. In other words, the good stuff takes months or years to build, the bad stuff is quicker and more transactional.

It’s an old rule of customer service – a positive reputation can take a long time to cultivate, but a bad reputation can be gained in a minute. Turns out it’s the same thing in higher education. It’s a lesson that we should all take to heart.

Families in Asian countries – particularly those from Confucian societies – don’t worry too much about things like affordability and student aid. Tiger mother stereotypes aside, there’s good survey evidence showing that it’s quite normal for even very poor families to put aside 20% or 30% of their income for the purpose of educating their children. In such countries, student aid is a pretty minor factor in access.

Many African countries are currently seeing a boom in higher education – and in a good number of them, it’s happening without any government student assistance programs. So how do they manage, given that fees are usually 2-3 times GDP per capita? Community resources, mainly. Everyone in a street or apartment building gets asked to contribute when one of their own go to school, and most people do manage to contribute a few dollars, knowing as they do that they will be able to count on those same neighbours when it comes time for their own children to go to school.

(This, by the way, is the kind of thing that makes development economics so heinously difficult. Try to institute a student loan scheme and the state pretty much ends up just displacing community support… meaning that the net beneficiaries aren’t students, but students’ parents’ neighbours. Sigh…)

Time used to be that some family sacrifice was expected in the West, too. But over the past twenty years, governments in Anglophone countries treated “sacrifice” like a bad word. When tuition was introduced in the U.K. in 1998, it was introduced with an income-contingent-like payment system to ensure that “parents would not have to pay a penny more.” In the United States, the main loan policy innovation of the 1990s was the creation of “unsubsidized” Stafford Loans for the upper-middle class whose kids weren’t eligible for the old subsidized variety. Moderately affluent Americans were perfectly capable of sacrificing present consumption to get their kids to school (they’d been doing it for the better part of forty years), they just preferred not to, so government obliged them by making it easier for their kids to indebt themselves instead.

The idea that our own middle classes are unable to pay more in tuition would seem nonsensical to African or Asian parents, who sacrifice far more to make sure their children get ahead. They just don’t seem to want to do so, given what’s on offer.

Why is that, exactly?

Anyway, my colleague Paul Jarvey and I were trolling through granting council data the other day (actually, just SSHRC and NSERC data; by a remarkable coincidence, CIHR’s attitude to data transparency also belongs to the Stalinist era), as part of a little internal project we have looking at the distribution of research grants. For kicks, we decided to look at the right-hand tail of the data – the real outliers who get more research grants than anyone else.

It turns out that two professors stand out above all the others in this country when it comes to sponsored research grants. Alexey Stakhanov, meet your Canadian academic equivalents: Donald Smith, a plant biologist at McGill University and Ajay Dalai, a chemical engineer from the University of Saskatchewan. Between 2006 and 2010, these two received $2.9 million in NSERC funding – but, rather more remarkably, were each the recipients of two new NSERC grants per year.

To be clear, that’s not two recurring grants lasting over six years. That’s two brand new ones, each year, for six years. Some of which were recurring. In total, Smith picked up twelve separate NSERC grants over a 6-year period, and Dalai eleven. And that’s not counting Smith’s work in the Biofuels Network Centre of Excellence or Dalai’s Canada Research Chair.

No, we haven’t the foggiest idea how either of them does it, though we’d assume that brigade-level complements of graduate students are somehow involved. Nevertheless, we’re seriously impressed. These two somehow have bottled the research productivity genie and their secrets need to be understood.

Or perhaps just poached. If you can’t beat ‘em, you could always try hiring them. All you enterprising science and engineering deans wanting to increase your granting council success rates, please form an orderly queue over here…

Anyway, Drummond released his report yesterday and it’s a doozy. Figure 1 provides a succinct overview of Drummond’s view on Ontario’s prospects.

Figure 1 – Don Drummond with a word on Ontario’s Fiscal Future

RUN!

The big highlight is that sticking to the status quo will mean a $30 billion annual provincial deficit by 2017. As a result, Drummond recommends significant reductions in government spending growth rates. Specifically, he recommends keeping health expenditure growth over the next seven years to 2.5% per year (good luck with that!), education to 1%, PSE to 1.5% and everywhere else to -2.4%.

(How did PSE get that lucky? I’m guessing that having two serving senior university officials – Dominic Giroux and Carol Stephenson – among that four task members didn’t hurt.)

Not content to lay out general targets, the report offers a raft of specific measures designed to improve the efficiency of public services. The PSE chapter has no less than 30 recommendations, which vary significantly in quality. Some, like ditching tax credits and investing in upfront grants, are eminently sensible; others, like “rewarding teaching the way we reward research,” are things people have been saying for 20 years without much progress having been achieved. Some are weirdly trivial (extending the review period for OSAP default rates? Who cares?), and some are just flat out terrible. Specifically, the one about placing a moratorium on new Bachelor’s programs in community colleges. There’s zero justification for it, it will do nothing other than entrench a program-delivery monopoly by universities and it is completely at odds with the rest of the report’s emphasis on opening up public services.

It’s hard to tell how many of these 30 recommendations will actually become policy. Some are difficult to implement and TCU is – how to put this? – out of practice when it comes to tackling multiple tricky projects simultaneously. Others, like re-evaluating student assistance, will probably be seen as too likely to cause excess whingeing from certain (ahem) student groups to be worth the irritation.

If I had to guess, I’d say very few will be implemented any time soon. Universities and colleges will be grabbing that 1.5%, praying the health care leviathan doesn’t eat it into it, and letting bureaucratic inertia take care of the rest.

So, what else might be psychologically determined? How about choice of field of study? Two Princeton scientists, publishing on PLoS One, find the following:

From personality to neuropsychiatric disorders, individual differences in brain function are known to have a strong heritable component. Here we report that between close relatives, a variety of neuropsychiatric disorders covary strongly with intellectual interests. We surveyed an entire class of high-functioning young adults at an elite university for prospective major, familial incidence of neuropsychiatric disorders, and demographic and attitudinal questions. Students aspiring to technical majors (science/mathematics/engineering) were more likely than other students to report a sibling with an autism spectrum disorder (p = 0.037). Conversely, students interested in the humanities were more likely to report a family member with major depressive disorder (p = 8.8×10−4), bipolar disorder (p = 0.027), or substance abuse problems (p = 1.9×10−6). A combined Predisposition for Subject Matter score based on these disorders was strongly predictive of subject matter interests (p = 9.6×10−8). Our results suggest that shared genetic (and perhaps environmental) factors may both predispose for heritable neuropsychiatric disorders and influence the development of intellectual interests.

Now, some of this seems like overreach. I would treat the autism result in particular with extreme caution, given that it’s based on only 20 cases. But still, what a great case of science confirming every prejudice we have about those jerks from the other side of campus, right? We’re excited about the possibility of applying these insights to our own studies of student survey data.

On an only vaguely-related note, I wanted to share with all of you a piece which a colleague of mine has described – not without reason – as “the greatest journal article of all time.” It’s from volume 96 of the British Journal of Urology International, and it is entitled “How (not) to communicate new scientific information.” Caution: it is not entirely safe for work.

If any of you can top that one for sheer amusement value, send it in to us at info at higheredstrategy.com – we’ll publish the best.

Formal systems of education are more leery of this approach. In K-12, it is assumed that time served is more important than demonstrated skills in moving students from one level to another. Undergraduate education in North America similarly works on a time basis, with credits being defined in terms of contact hours.

The assumption, of course, is that time spent in the classroom ultimately implies skill acquisition, and hence that time-based education is just competency-based education by approximation. It’s a convenient argument for universities; essentially, it makes their function as certifiers of skills indistinguishable from their function as providers of knowledge/instruction. And by doing so, it gives them monopoly pricing power over instruction.

But what if someone could independently certify a set of knowledge and skills and say “yeah, that’s equivalent to a Bachelor’s degree”? Figuring out how to do that in a reliable way would be a genuine disruption to universities, because it would allow competing routes to credentials. Prior Learning Assessment Recognition (PLAR) – which is widespread in colleges if not universities – uses this same kind of techniques, though usually for advanced placement rather than delivering entire diplomas. So too, as a cautionary example, do many degree mills.

Western Governors University, a public, online university based in Salt Lake City, bases its degrees around “competency-units” rather than merely time-based credits, and it’s managed to convince a number of U.S. regional accreditors of the validity of such an approach. But despite the hype, WGU has its limitations. It has done very well to boost enrolment to 30,000 in under 15 years, but it’s still basically restricted to certain forms of professional certification and upgrading in business, IT, health and education – areas where external norms are easily available as reference points. Nobody has yet worked out how this would work in basic arts or sciences, where the attitude to the very notion of defined competencies verges on hatred.

That’s why things like Tuning, which documents degree-level outcomes, and AHELO, which is attempting to measure outcomes across different universities around the world, are so important. By getting people to focus on outcomes in areas where they haven’t before, they set the stage for a massive expansion of competency-based higher education.

If you’re looking for a “great disruption,” my money’s here. It’s not glamorous, and it won’t happen quickly, if at all. But unlike recently-hyped techno-solutions, it has the virtue of being both rigorous and realistic.