Daniel Lemire's blog

This morning, I am deeply upset. Some of you who know me will know why. No, I don’t care so much that Buch was elected, though it does puzzle me. Read through, you might find out why I’m upset.

I did my Ph.D. with the intent of getting into “industrial research”. Yes, there are different types of research. You have “pure” research where people have no idea why they do the research except that it looks nice. For example, solving for all algebra having property X is pure research. You have “applied” research which is often closely related to “pure” research except that the topic is a bit closer to “real world” concerns. For example, finding a new way to solve Navier-Stokes equations is applied research. It should be noted that “applied” research doesn’t equate with “useful in the real world” research. In fact, it could very well be that some “pure” research is more applicable in the real world. Finally, you have “industrial” research. Industrial research is meant to be useful in the real world. It is the primary purpose of such research. The excitement comes not from elegance alone, but mostly by solving real problems people have. You might say that some people working on the linux kernel are industrial researchers, at least when they innovate. A given researcher may cover all three research types, but he may switch hat depending on the project he is working on.

All types of research are equally worthy, but they are not equal in all things. For example, “pure” research might give you a lot of prestige is some universities. Pure researchers have “pure” concerns and it is often thought that only the smarter researchers can be pure researchers. Applied researcher have often an edge when it comes time to get some research funding. That’s because the applied researcher can easily justify that his work might be applicable in the real world. Finally, the industrial researcher might be looked down upon by some people: because industrial research must be tied closely to the real world, it will sometimes trade fashion or elegance for convenience or applicability. Often, “industrial” research may appear to be simpler, maybe easier. Believe me, it is not easier. On the other hand, the “industrial” researcher can really license technology or even start a company. This, in turn, may bring tremendous leverage to such a researcher. Unfortunately, these things take time, and in a university setting where tenure should be first on your mind, the industrial researcher might have a harder time. Hence, in many schools, most professors are pure or applied researchers. Fortunately, the industrial researcher has a broader choice of employment.

This is actually a very interesting topic. Many questions may come to mind… For example, is there any such thing as industrial research in mathematics? You bet! See SIAM.

Now, that you see what I mean by an industrial researcher, you might understand that one of his strength is when dealing with companies. He is able to understand the concerns of their engineers and his research accounted for many of these concerns already. However, for him, it is crucial that people do not get in the way between him and a company. He needs, he wants technology transfert.

That’s why I’m upset today: I feel someone pushed me aside and got in the way. People are always eager to take someone else’s work and then ignore this person when money is involved and the author is not being difficult. I hope this will get fixed, but either way, I’ve been reminded that the industrial researcher must keep a very close eye and much control on the technology transfert process. And not be nice.

Here’s a report released in 2001 on the state of doctoral education. It looks like a serious study and the conclusion is scary:

What we learned may not be entirely surprising because our findings confirm many of the concerns that have been raised in the last 10 years. However, our data provide detailed, confirmatory evidence of particular tension points. We found that:

• The training doctoral students receive is not what they want, nor does it prepare them for the jobs they take.
• Many students do not clearly understand what doctoral study entails, how the process works and how to navigate it effectively.

Seb sent me this extract of a book. The extract is called So, you want to do a Ph.D.? As usual with this sort of book, it is delightful.

Here’s a fun quote:

One thing which is seldom mentioned is what happens to you after you finish the PhD. A classic story is as follows. A student focuses clearly, submits the thesis and starts looking for a lecturing job, only to discover that they need two years of lecturing experience and preferably a journal publication as well if they are to be appointable for a job in a good department in their field. If they had known this two years previously, they could have started doing some part-time lecturing and submitted a paper or two to a journal.

I haven’t read the entire book, of course, and I’m somewhat worried that the book might not be sufficiently focused on why one does a Ph.D. and might be a tad too cynical. Learning the rules is very nice and very important, and I wished I had learned them when it was time. However, there is also the issue of figuring out whether these rules make sense, and knowing when to break them. Well, I guess that learning the rules to begin with is a very good start.

Sharleen talks about how evil junior faculty can be in their approach with grad students:

(…) in academia, (…), there are limited options, and a poor grad student may have to work with the asshole who has naive, unethical, or objectionable approaches to working with grad students. Now, we could simply say, the ones who survive are the ones who deserve to get jobs/get the PhD. We could point out that the market is much tougher. But if we respond this way, we’re not critiquing the culture of academia (a culture which, if I may point out, is largely responsible for the other problems that we all bitch about); we’re justifying it.

I’m unsure why she points at junior faculty as the source of the problem. She’s probably got some personal experience going.

However, I agree with her criticism of the tough love approach to supervising graduate students. I don’t think it can be justified from a pedagogical point of view, it is not justified from a management point of view, and so, indeed, it might be some kind of power trip.

On the other hand, I disagree with her implication that there are no choices. In most cases, the graduate student can go with another supervisor. It might costly, but it is almost always an option. Or else, you can simply go out there and find a job and be happy.

Repeat after me: the world is big and there are almost always options. Unless you are a slave stranded somewhere, you can almost certainly find another job, another graduate program, another project… it might be costly, it might imply extra work, but it is most often possible.

The reason why these professors are getting away with treating graduate students badly is that graduate students allow it. If they chose not to go with this “evil” supervisor, there wouldn’t be any problems any more.

That’s how the real world works. Evil employers will have trouble finding good employees. The good employees will leave for a better employer. That’s the market at work.

The day when the employees stop leaving, because they are scared or tired, the market stops working and the trouble starts.

Generally speaking, academia doesn’t have so much a culture problem as it has a market problem: too many potential candidates for some positions leading to a general degradation of the working conditions for everyone involved.

I had an off-line discussion with a collaborator about student supervision and how frustrating it can be. As a professor, you have, from time to time, to supervise students. It could be a graduate student you are supervising as part of their studies, it could be an undergraduate project, it could an assistant you’ve hired.

You know you have a bad student if the student

• cannot keep track of tasks assigned to him and be responsible for such tasks;
• lies to you about what has been done and what hasn’t been done;
• repeatedly ignores some of your phone calls or emails.

In my experience, a bad student is a drain on your resources and a professor simply has to drop such a student as soon as possible. Even if you have funding or need of a student, you are better off with no student than a bad student.

So, what about my title? The art of supervising students?

My experience has been that there is no need to be tough or strict with the students. There is nothing magical you can do: forcefully organizing many meetings with the student often won’t help. If you have a bad student (see above), cut your losses as early as possible. Otherwise, trust the student.

Here are a few rules based on my experience:

• Be clear about the tasks you expect the student to perform and the time it should take.
• Be available to the student in a personalized way: some students benefit from frequent meetings, others do not.
• Get to know and leverage the student strengths and know his weaknesses: you are better off doing some of the tasks yourself.
• Trust the student: most students have tremendous potential and will deliver greatness given a chance.

Tall, Dark, and Mysterious wrote about this student she has in her class who is actually a fairly typical student:

“I memorized how to do the problem you did in class, but then on the test you put a DIFFERENT problem, and you never showed us how to do THAT one, and it’s not fair! My method of doing math by memorizing formulas and then blindly applying them to problems that are identical to the ones I’ve seen has gotten me A’s until now, so what gives?”

Repeat after me: memorization is not learning. Learning has to be a higher level task.

I’ve written on this blog about the recent drop in enrollment for Computer Science degrees in North America: I gave an estimate of a drop by 25%. Looks like it is worse:

The number of new undergraduate majors in U.S. computer science programs has fallen 28 percent since 2000, reports the Computing Research Association, a group of more than 200 North American computer science, computer engineering and related academic departments.

The explanation would be that students do not want a Dilbertesque life:

One reason, say those in the field, is that technology jobs appear less lucrative than they did during the dot-com boom. Then, students thought a computer science degree would lead to riches and a quick retirement. Many took on the major.

Another reason might be that Business Schools are now competing with Computer Science departments for students:

Colleges have also begun to integrate computer instruction into other majors such as e-commerce programs in business schools. A computer science degree, therefore, can be unnecessary.

Through Downes’, I found an article by David Wiley’s with the provocative title How Technology Will Destroy Schools (he actually is being needlessly provocative, he means “schools as they exist now”). The gist of his argument goes as follows:

The development of (…) technology will obviate the need for certain types of instruction — like the teaching of facts. Why spend time memorizing when the same information is available just as quickly from the network as it is from your own memory? But never fear, schools! The technology will create the need for new types of instruction — in higher level information literacy skills. Perhaps this will finally force some change through the public schools.

Well, I must admit. I have a Ph.D. in mathematics and I never learned my multiplication tables. There you go. I never saw the point of learning these tables, so I didn’t. Instead, I learned a few tricks to do multiplications… like 9 times 8 is almost 10 times 8, you have to subtract 1 times 8.

Mathematics is not about learning facts. I suspect that all disciplines have a component above learning the facts. You can’t be an expert in something if you only know the facts… because I can easily input the facts into a piece of software and compete with you, but we all know that software can’t compete (yet) against human experts. I’m not very good at memorizing facts, I’ve never been good at it. In fact, I’m not good at memorizing anything and that’s why I have a PDA always with me. Yet, I’m in expert at some things.

It is the difference between real knowledge and shallow knowledge. Most of our education system is based on acquiring and testing shallow knowledge. Most but not all.

How are you going to get past shallow knowledge through technology as Wiley predicts we will? I think that blogs, games, and simulations are good examples. Yes, we can role play without technology, but it becomes so much cheaper to deploy gaming scenarios through technology (because you only have to do it once) that it might become more common place in the future.

Maybe my son Lohan, by the time he makes it to school, will have “gaming instruction” where he will enter a gaming universe to learn basic mathematics. Who knows.

I’m not holding my breath though, I think we lack the human power to do pull it off in the next 5 years.