Tag Archives: teaching

A proposal for restructuring tenure

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An Op-Ed from the NY Times (warning: paywall) suggests creating research and teaching tenure tracks and hire people for one or the other. This is an interesting proposal, and while the author Adam Grant marshals empirical evidence showing that the two skills are largely uncorrelated, as well as research on designing incentives, it seems that the social and economic barriers to implementing such a scheme are quite high.

Firstly, the economic. Grant-funded research faculty bring in big bucks (sometimes more modest bucks for pen-and-paper types) to the university. They overheads (55% at Rutgers, I think) on those grants help keep the university afloat, especially at places which don’t have huge endowments. Research in technology areas can also generate patents, startups, and other vehicles that bring money to the university coffers. This is an incentive for the university to push the research agenda first. Grant funding may be drying up, but it’s still a big money maker.

On the social barriers, it’s simply true in the US that as a society we don’t value teaching very highly. Sure, we complain about the quality of education and its price and so on, but the taxpayers and politicians are not willing to put their money where their mouth is. We see this in the low pay for K-12 teachers and the rise of the $5k-per-class adjunct at the university level. If a university finds that it’s doing well on research but poorly on teaching, the solution-on-the-cheap is to hire more adjuncts.

Of course, the proposal also represents a change, and institutionalized professionals hate change. For what it’s worth, I think it’s a good idea to have more tenure-track teaching positions. However, forcing a choice — research or teaching — is a terrible idea. I do like research, but part of the reason I want to be at a university is to engage with students through the classroom. I may not be the best teacher now, but I want to get better. A better, and more feasible, short-term solution would be to create more opportunities and support for teacher development within the university. This would strengthen the correlation between research and teaching success.

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Toolkit revisited

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I joined TTI Chicago almost a year ago, and it’s been an interesting time here. Since my background is a bit different from most of the other folks here, I have many moments of “academic cognitive dissonance” as it were — but more on that later. Madhur Tulsiani is going to offer a toolkit course in the spring focusing on mathematical tools for CS theory — I wanted to revisit a topic from a few years ago, namely what an EE-systems/theory “toolkit” would look like. I think a similar course / seminar would be really handy (even for self-study), but the topics we came up with before seem a little dated now. It seems like the topics fall under a few categories

  • advanced stochastic processes : stochastic approximation
  • mathematical economics : game theory, auctions, mechanism design
  • advanced probability : concentration of measure, random graphs
  • optimization : stochastic control, dynamic programming, convex optimization
  • mathematical statistics : asymptotic statistics, minimax theory

Roy’s observation is that these topics are already covered in graduate syllabi is still apt. But I still think that knowing a smattering of these topics is still important for general literacy and critical reading of papers. In reading a new paper I first situate the techniques within the context of things I know about — if I have to absorb the author’s cursory description of the general method as well as its application to the problem at hand, I get bogged down in the former and find the latter mystifying.

Actually, I think what would be great is to make tutorials on the topics and gather them together. I know that people who make research tutorials spend a lot of time on them and there’s some reluctance to gather them together, but these topics are not bleeding edge and could be part of a course. It’s sort of like Connexions, but perhaps a little less wiki-like and more lecture-notes like. What would be the best way to do that?

As an aside, Madhur is also thinking of doing a more focused course later which would cover coding and information theory for (theoretical) computer scientists. I’ve thought a fair bit about such a course focused on machine learning — focusing a bit more on statistical issues like redundancy and Sanov’s theorem instead of Gaussian channels. But how could one do an information theory course without \frac{1}{2} \log( 1 + \mathsf{SNR} )?

What’s the point of an X department?

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Over at Crooked Timber there’s a discussion on eliminating some majors to save money, particularly if they don’t have many graduates.

The issue made it to Leiter because several of the Philosophy departments in those institutions fall into the low-major category. But is producing Philosophy majors the point of having a Philosophy department? In Our Underachieving Colleges (CT review still on its way: DD to blame if I never get round to it) Derek Bok claims that the standard assumptions within most departments in research universities is that the undergraduate curriculum is for attracting and then teaching majors, and, further, that our attention to the majors should be shaped by the aim of preparing them well for graduate school. This means that the curriculum is designed for a tiny minority of the students who take classes, and even many of them, probably, would be better off doing something other than going to graduate school (that’s me, not Bok, saying the last bit).

Philosophy departments should take heed of Samidh’s observation that philosophers are good entrepreneurs and point out that they may produce the next big alumni donor!

I wonder the degree to which Bok’s claim is true in mathematics, science, and engineering. I think it’s probably true that the average biology major or electrical engineer is being prepared for work at a company. Even senior electives are useful in this sense, especially if they are project-oriented. However, it’s probably the case that if you major in math and do not plan to go to graduate school, then your senior seminar in commutative algebra is pretty much useless for the work you’ll do later. But is the average math major at a public university being prepared for (some) graduate program? Is math in this sense closer to the humanities programs mentioned above?

In electrical engineering, it’s to go work in a company (or for the government) designing/building stuff, and those specialized classes are geared for that. On average, I think undergraduate programs in engineering in the US don’t emphasize going on to graduate study. An exception is the profit-turning one-year masters programs that have become popular in recent years. Designing a program to prepare people primarily for graduate school or designing a program to prepare people primarily for the workforce misses the point of college.

The story you hear is that a classical liberal arts education in the US is supposed to teach you to think critically and be an active and thoughtful member of society. So what does that mean for engineers? In a sense, design choices are a form of critical analysis within the context of engineering, but I think that kind of perspective can be construed more broadly. We’re so keen on formulating notions of optimality or engineering tradeoffs that we don’t also consider the societal aspects of the things that we design. It would be nice to get upper-division engineering classes that talk about where technology is headed, where society is headed, and how those interact on a more technical level. This kind of thinking is good preparation for work and for research. I think there are some classes like that out there, but they’re more or an anomaly than the norm, and they’re not really required. But it would be valuable for the students, regardless of where they go.