Computational Competence for Biologists

Posted 2013-07-16 by Greg Wilson in Assessment, Education.

On July 8 and 9, I had the pleasure of taking part in a two-day workshop at SESYNC to discuss what we ought to teach biologists about computing. It was a relatively small meeting, but the participants spanned the range from computer scientists and systems engineers to bioinformaticians, field biologists, and a few odd ducks like me.

One of our group exercises was to design a proficiency exam to determine whether a biologist was computationally competent. This was inspired by the driver's license exam we've helped put together for the DiRAC supercomputing consortium, but we weren't seriously proposing such a test. Instead, we wanted to use it to focus discussion of what we all actually mean by "computational competence" when it comes to biology.

The five groups' submissions are included below. The most interesting thing for me was how discussion was dominated by data rather than computation. I was also struck by how much agreement there was between the groups, though this might have been a result of the way the question was posed. Other common themes included:

  1. Documenting process for others
  2. Reproducibility of results
  3. Knowing how to test results
  4. Managing errors
  5. Posting to places like GitHub, BitBucket, and Figshare—the concept was more important than brand—to make work sustainable even when students move on
  6. Database management—not just how to write queries, but also how to create a sensible schema

If this is what computationally skilled biologists think their peers need to know, then we need to rethink and rewrite some of our material. On the bright side, there's clearly an enthusiastic audience for what we're doing, and they clearly think we're making their lives better.


Group 1

Data

Programming

Testing

Reproducibility


Group 2


Group 3


Group 4


Group 5

Given:

do the following:

Given:

do the following:

Given:

do the following:

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