'Tis the season when graduate applications are being decided as well as the job interview process starting again, and just in time for the new year, your regularly scheduled inflammatory article entitled, "Can't Get Tenure? Then Get a Real Job" up at Bloomberg. The point of the article seems to be that the tenure model follows the age-old "tournament model" of employment, with a very few plum positions at the top, and lots of people scrambling for them -- and, along the way, essentially turning themselves into free labor for existing tenured professors, as well as (in most cases) unemployable dried out husks by their early 30's -- and that's bad. The only solution suggested seems to be to cut Ph.D. production, and there are no incentives to make that happen. (I can only encourage you to avoid reading the comments, where somehow this becomes a political issue, with "liberals" being to blame for... seemingly everything, I guess, but this in particular.)
I'm always happy to admit that computer science seems to be a special case; industry takes many of our PhDs. However, without trying to dissect the article -- which is field agnostic -- I think it's healthy for computer science to regularly look at itself, and determine whether it's doing the right things. Here's my take on what those are, at the individual (faculty) level:
1) Be honest with undergraduates. If you're a professor talking to an undergrad thinking about grad school, you should point out that you're the success story, not the average story. Point them to the Taulbee survey or other figures. Have them work out the math on potential opportunity costs. Whether you're positive or negative on them going to graduate school is up to you, of course, but either way you should be giving clear, factual information as well as advice.
2) Be honest with your graduate students. If they aren't performing, let them know they need to get better (or move on). (It's painful, but better for them in the long run.) Be sure the latest "time-to-academic-job" timeline is on their radar -- how many years of postdocs is becoming the norm? Make sure they know what skills they need to work on besides research skills -- speaking, writing, organizing, managing.
3) Controversial(?): encourage breadth for your students. It seems to me that since I was a student there's much more pressure to go deep -- to show in your PhD that you are the expert on your research area, even if that research area becomes narrow. The message seem to be don't waste time on classes, projects, or learning that fall outside your clear research path. I'm torn in advising the other direction, because I think the way the academic field is progressing, that can be a promising short-term approach if the goal is to get a tenure-track position. But I don't think it's good for developing a long-term career, and I don't think it's the right approach for the significant number of students who end up doing something else. [I'm aware I'm very biased on this issue.]
At the field level, I think there are big questions, and I'm not sure how they get answered.
1) Are we encouraging too much depth over breadth in our training? (See 3 above.) Is this what we want?
2) Are we OK with what seems to be a lengthening pipeline, with postdocs becoming more common (in some areas, but not all, standard) on the academic career path?
3) Do we have any sense of goals for how many graduate students go on to careers in industry, entrepreneurship, teaching (e.g., teaching university positions as opposed to research university positions), etc.? If so, do we want to do more to help prepare students for these types of work, which may not mirror exactly what we as professors do? How do we measure success for our graduate students, and how do we tell if we're doing a good job preparing students overall?
Plenty to think about for the new year.
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3 comments:
Your three points seem, to me, unassailable. Of course be honest with undergrads about grad school success chances. Of course be honest in feedback to grad students. And of course, of course, encourage breadth! A good student can acquire depth on personal steam at any point. But breadth, if missed during grad school, is incredibly hard to acquire later on. And it is *extremely useful* later on as well. If believing this is being biased, I'm glad to join you there!
At least in CS/CE, I think there might be advantages to increasing the role of the post-doc and hopefully decreasing the time to PhD.
It will always feel uncomfortable to cut things out of a program, but if the PhD isn't the "last chance" to prepare students for professorship, it may be easier to focus on technical research and communication skills, as well as to increase breadth. (I would cut the formal monograph thesis; it's just not a useful form of technical communication.)
A shorter PhD would allow students who continue in industry, government, or entrepreneurship to enter their careers earlier in life with great R&D skills: this might even make the PhD more attractive.
At the same time, a more coherent model for post-doc would let a limited subset of students to go on to prepare for academic position, with little loss of total time and greater (statistical) probability of success. This would also be a good opportunity for students to evaluate (and be evaluated for) that option.
Also, I think that more separation between PhD-training and post-doc training would help students to learn whether they like/have aptitude for academic profession itself. Better to discover hatred of grant-smithing, student-wrangling, and administrivia during a post-doc...
Obviously, the community would need to show some discipline to emphasize aspect of post-doc as academic training position and also not to develop the habit of extended post-dockery (as in some fields).
That may not be reasonable expectation...
"encourage breadth for your students"
For students interested in teaching at liberal arts colleges, I would say this is especially important. Most liberal arts CS departments will only have a few faculty, so you'll need to teach a huge range of classes. We seem to be getting lots of applicants who only have expertise in their exact research areas.
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