Sun protection factor (SPF) in 5 minutes from jonathan rees on Vimeo.

I am near through reading Derek Bok’s ‘Higher Education in America’. Coupled with the day job, it is hardly surprising I spend much of my waking time thinking about Higher Education. One of the things I read into Bok’s book is the way that the professional schools have been a safe bet for smart students. It is not that all is good in the professional schools, but that the world has treated them and their graduates relatively well, by comparison with sciences and the humanities (I will try and flesh these statements out another time, but one of the reasons why people should worry about the lack of interest in STEM, is that careers in science are not attractive to so many bright people).

I have just come across a nice article by Tressie McMillan Cottom that summarises some of the issues, for those who graduate out with the professional schools. The content is not too unusual if you are interested in these matters, but it is a well written piece, that summarises a lot of thinking about what has, and what might happen. Here is a quote: (that I picked up on Audrey Watters’ site)

“The current narrative from the private sector and elite opinion-makers is that higher education is failing Americans. College is overpriced and due for disruption. Graduates are not prepared for their jobs, and rigid class schedules make it hard for workers to retrain for twenty-first-century jobs. But just thirty short years ago, the wage premium for college graduates was being touted as the saving grace of higher education. How could college have gone so wrong so fast?”

Bok’s book includes chapters on the three main professional schools: medicine, law and business. The similarities and differences between them are interesting. But law, he makes clear, has perhaps seen the most radical change as a profession, and in what value law students get from Higher Education. By comparison, there have been less change in US medical education. The same factors are however at work, and the rate of change will accelerate, I think. In the UK, change has been less, but the same forces are at work. All the changes that have affected much of the middle class, are going to sweep through medicine. An obvious statement perhaps, but I am not really certain how much our UK students see this coming. Timescale? Always the most difficult question.

Two items in the THE caught my eye. The first reporting on old data said:

 Hepi found that in medicine and dentistry, for example, students at the hardest-working university put in an average of 49.8 hours a week, compared with 32.7 hours at the university with the lowest workloads (the figures include timetabled and private study).

The figures for some other disciplines were as follows:

business and administration, 39.2 and 15.9 hours; history and philosophy, 44.6 and 19.3 hours; and biological sciences, 46.3 and 20.2 hours.

Not certain what I believe. But then a few pages on, in an article on Birbeck College, University of London, we read:

Part-time degrees over three years are also attractive because those doing the courses are eligible for maintenance loans, worth up to £7,751 a year in London next year, unlike traditional part-time students, Professor Latchman said.
….
But how can a student complete a degree over three years on a part-time basis, sometimes while holding down a full-time job, when others are full time over the same period?
Professor Latchman believes Birkbeck’s three-year cohort are sacrificing socialising. “Part of the experience of going to university is maturing and having a good time – that is what our students are losing,” he said. Birkbeck has also put many more lectures online to intensify the study experience, he added. Nonetheless, are there enough hours in the day for the three-year students to take classes and remain in full-time work?

There is a lot to think about here—if you have the time of course. In medicine we also have a rather bizarre way of using time as some sort of measure of learning, or even of what is to be learned. So, in university X the students do so many weeks of a particular clinical discipline, whereas in university Y, the allocations can be wildly different. Ironically, much as we talk about competency, knowledge is measured in ‘allocated weeks’, irrespective of the amount of content to be acquired or the type of teaching provided. Or of course what sort of exposure is most appropriate. As they say, TIJABP, but maybe if I could skip the day job, I could think it through a little more.

Teaching in higher education is about to go through as major a revolution as one can imagine. This is not going to be easy; indeed it could get brutal.

 

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Colleges typically want, in addition to a share of parents’ incomes, about 5 percent of the value of their assets, plus 20 to 25 percent of the students’ (Penn settles for just 5 percent of student assets). But there are differences in how colleges define assets. Cornell, Stanford, Columbia and Duke, for example, take into account home equity. Harvard and Princeton do not, and neither does the federal formula. New Yorkers might fare better with one of the elite private colleges, nearly all of which consider regional variations in cost of living. High medical expenses and kids in prep school? A few top schools, like Princeton, discount for both. The federal government and state colleges do not.

 

NYT

I was lucky enough in 2001 to hear the Greek computer scientist Christos H. Papadimitriou  talk at the Informatics Jamboree here in Edinburgh. It was soon after when I had discovered Herb Simon, and when I was trying to think hard about diagnosis, learning and clinical skills. I remember little of the content of the lecture, except that part of it was given over to thinking about  the size of the internet. What I have never forgotten however was the sense of intellectual playfulness that he demonstrated, and also an informality of style that was exhillerating.  There is a lesson here: be careful how you measure what  success in lecturing means. He has authored some works of fiction (better still, lets call them works of imagination, because they are both fiction and non-fiction) including Turing (A novel about computation), and with Apostolos Doxiadis, Logicomix.

For some reason I came across one of his books again, and looked him up on the web. Here on this page was a lovely description of a course he is teaching at Berkeley:

Purpose:  Classics are written by people, often in their twenties, who take a good look at their field, are deeply dissatisfied with an important aspect of the state of affairs, put in a lot of time and intellectual effort into fixing it, and write their new ideas with self-conscious clarity.  I want all Berkeley graduate students to read them.

 

Now, within these few sentences is so much of what science and much of intellectual life is about; and the problems that face the organisation of modern science. Pithy statements, belong both to those who study algorithms (as Christos does), and the poets. But the thought that interests me is that many ‘classics’ within medicine, are not of this sort. If I pull Shelley and Crissey’s Classics in Clinical Dermatology off my shelf, we see something different. This difference tells us a lot about one difference between science and the practice of medicine, but exposure to the classics needs to be common to both.

Terrific article by Harold Thimbleby on IT and safe healthcare, and how they often do not work together. We don’t assess IT well, and forget how it can distort clinical care in ways that are often not apparent. Managers like it because it so often offers to cut costs, but some of the ways it does this is by lowering the standards of clinical care. The consumers of healthcare it seems  are not so much the patients, but the hospital finance officers.

Anyway, the teaching point, is the power of an example, and more so, of a demonstration. At one time science specialised in demonstrations because they have the power to overcome prejudice and outright scepticism in a way that little else will. They may be harder to do in modern  medicine, but software (ironically) offers enormous opportunities for doing this, and promoting deep learning.
The example —and demonstration— that stopped me in my tracks was:

“I live in Wales, and I am interested in what proportion of the world’s population is welsh. I therefore use a calculator to find out 3, 063, 500÷6, 973, 738, 433, which is the population of Wales divided by the population of the world (being numbers I got off the web so they must be right). Remember that you use a calculator because you do not know what the right answer is. Here, I obtain the following results (ignoring least significant digits):
Casio HS-8V 0.04 .
Apple iPhone portrait 0.004 . . .
Apple iPhone landscape 0.0004
If you didn’t know what the right answer is, you still don’t! These are all market-leading products, yet none of these calculators reports an error — only the last is correct. Whatever is going on inside the Apple iPhone, it could clearly report an error since it provides two different answers even if it doesn’t know is right!

The first electronic calculators appeared in the 1960s. We are no longer constrained by technology, and we’ve had some fifty years to get their designs right; it is hard to understand why calculators used in healthcare are not dependable.”

Well, both he and I are Welsh, but I still didn’t believe him. So, out with the iPhone and….he is right. Eppur si muove (to borrow from Galileo) . Do you use your iPhone for clinical calculations?

So Harvard Business school is dipping its toes in the online world. A quote from the Economist:

The FAQ for the CORe programme, meanwhile, warns potential students that “professors will not have direct real-time interactions with students”, that getting the certificate hinges on taking a final exam at a testing centre, and that it is possible to fail.

 

So, the usual business model then….

Nice turn of phrase in a Nature book review by Nathaniel Comfort, of ‘Gene Jockeys: Life Science and the Rise of Biotech Enterprise,’ by Nicolas Rasmussen. I haven’t read the book but the review contains a telling phrase:

Molecular biology still has its idealists, but their ponytails are greying. Today’s graduate students want training in economics, marketing and management, even MBAs. You can now go into biology for the money.

I have mainly researched in two domains; molecular biology and molecular genetics; and for a shorter period of time (and still, to a limited degree) in using computers to help us learn and practise. Comfort draws some parallels and contrasts, between these two domains of science and engineering, writing:

The contrasts between computing and biotech are as interesting as the continuities. Unlike the nerds of Silicon Valley, who started up their companies in garages, the bio-geeks started theirs in well-stocked, mainly government-funded university labs. But, as in IT, the dream became having your little company bought by one of the big corporations. By the 1990s, both industries had become less freewheeling and curiosity-driven, and more privatized and gold-directed.

One of the differences is brought out in a quote from Stewart Brand:

“I think that hackers–dedicated, innovative, irreverent computer programmers–are the most interesting and effective body of intellectuals since the framers of the US constitution. … No other group that I know of has set out to liberate a technology and succeeded. They not only did so against the active disinterest of corporate America, their success forced corporate America to adopt their style in the end….. The quietest of all the ‘60s subcultures has emerged as the most innovative and powerful”.

Molecular biology never had this widespread culture of hacking for long—it became institutionalised all too early in its history. In the long term, the hackers will have —I hope — more influence on medicine, and most of all on how we teach and learn medicine. It is still easier to set up a software business than a hardware business. If the barriers to entry are lower, we will see more novelty. I like to think the best is yet to come.

Let’s Scramble, Not Flip, the Classroom

 

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