The Problem of the 12 Hats

I can’t think of any other profession that requires quite the diversity of skills as a scientific academic. By the time you’re a tenure track professor, you are expected to be proficient in a dozen skill sets, each of which is sufficient for a profession in of itself [1]:

  1. researcher and expert
  2. statistician
  3. grant writer
  4. non-fiction writer
  5. public speaker
  6. diplomat
  7. visionary
  8. classroom teacher
  9. mentor and trainer
  10. accountant
  11. office manager
  12. recruiter

Note that I say proficient and not excellent. You need to be proficient in most of the core 12, but you need to be excellent in at least a handful of these 12 to make it to the tenure track in the first place. But how is one supposed to learn all these skills? As I pointed out, excellence in just one or two of these would qualify you for a (probably higher paid) job in industry. And yet, academics are supposed to master the whole suite.

In theory, that’s what graduate school (and postdoc positions) are all about: learning these skill sets – the things that will make you an excellent professor. But graduate school (and postdoc positions) are typically very skewed in the skills they teach. Here’s my rough break-down of typical training [2]:

  1. researcher and expert: classroom training, apprenticeship, trial-and-error
  2. statistician: classroom training, apprenticeship, trial-and-error
  3. grant writer: apprenticeship, trial-and-error
  4. non-fiction writer: apprenticeship, observation of others, trial-and-error
  5. public speaker: observation of others, trial-and-error
  6. diplomat: observation of others, trial-and-error
  7. visionary: trial-and-error
  8. classroom teacher: observation of others
  9. mentor and trainer: observation of others
  10. accountant: none
  11. office manager: none
  12. recruiter: none

And this leads to the 12 Hats Problem: namely, that academics are expected to be proficient-to-excellent in an impossibly wide range of skills. They’re expected to wear 12 big hats. And yet, it’s unachievable for one person to have mastered all those skills by early-to-mid career, and I don’t know anyone at any career stage who is excellent in all of them.

I think the most prominent tension is between the skills that are considered the skills of a scientist and the so-called soft skills that are the skills of a teacher. These days, a professor is typically expected to be quite good in both. R1 universities stress the former and primarily undergraduate institutions stress the latter. But I’ll argue that it makes a lot more sense to allow academics to specialize much more than they currently do.

For starters, classes on teaching are almost never required by graduate programs – and they’re often not even offered. Teaching is an acquired skill. Science pedagogy is an entire area of research. For many (most?) newly minted assistant professors, the first year’s teaching learning curve is brutal. Taking people who are excellent in a wide range of science-based skills and hiring them to perform a job for which they are novices is ludicrous. But somehow we think it’s normal.

I think there are many benefits for universities to start to hire people for narrower job responsibilities. Science might be more efficiently done if research scientists had lighter teaching loads. Students would almost surely benefit from having instructors for whom teaching isn’t a secondary job. Science teachers might feel more fulfilled, as they could justify spending more time on learning, pedagogy, and classroom prep. I’ll even go so far as to suggest that specializing would help with diversifying science. For those whose time and energy must be split between professional and non-professional endeavors – be they dependent care-giving, management of personal health conditions, or diversity advocacy – wearing only a half-dozen professional hats increases the feasibility of juggling academic and non-academic duties.

I’ve seen this begin to happen at the University of Minnesota. For the many general biology courses, the university is hiring Teaching Professors. These positions are tenure track and teaching heavy. Like at many liberal arts colleges, there is the expectation of some research during the summer. But in the case of Minnesota’s Teaching Professors, the research is expected to be pedagogical rather than domain-oriented.

I think this is great, but we could go even further. Do great teachers of general biology really need to have PhDs? I don’t think so. Why not create paths that combine a Master’s level research project with a teaching certificate? These would be professionals who have a good command of science knowledge, who understand research, who have connections to the research community, but who also understand pedagogy and are focused on teaching. We need both things, of course: scientists who are professional undergraduate-level teachers AND good-quality positions (i.e. permanent with benefits) offered by Universities. I think everyone would benefit.

I’ll end by saying that I’ve really only talked in depth about separating two major academic hats. I think there’s a lot to be gained by even further specialization. I expect that established academics will balk at the idea. After all, it’s (sometimes) fun to have so many hats, and change is always hard. But in academia, we know that subpar mentoring is a problem. Science outreach is a problem. The lack of tech transfer within academic science is a problem. And these problems all stem from the expectation that professors be experts in too many domains. To solve them, professors may need to doff some of their many hats.


[1] ^ And there are additional skill sets for which an academic might also show proficiency: editor, fundraiser, publicist, mathematician, computer programmer, construction engineer… You can probably think of more. I list the 12 core skills above that I think are generally required of everyone.

[2] ^ Definitions: classroom training = actual classes on skill set; apprenticeship = significant one-on-one training with an established academic; observation of others = witnessing others performing the skill set or the results of that performance of the skill set; trial-and-error = the chance to practice the skill set during grad school/postdoc years

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