Feedback from Lawrence Berkeley National Lab

This post originally appeared on the Software Carpentry website.

Katy Huff, Justin Kitzes, and I wrapped up our LBL workshop yesterday. We had ~25 participants with a broad range of backgrounds and levels of experience. Here's our traditional table of good/bad feedback:

Good Bad
can use python better don't know how to apply git to work
covered lots of material covered too much material
can use git better now group felt too large for number of helpers
covered from basics to advanced programming felt unprepared for git instruction
helpers were knowledgeable and nice couldn't run VM, add system reqs
motivated version control well python level was too easy
started with basics, had good help need well defined goals for exercises
got exposed to a lot group people by experience
all the material is available on GitHub would have liked a more detailed description of course
learned enough to get started didn't get any emails on the waitlist
have hope getting info ahead of time
good overview for later whole thing too fast
format - work through code live topics jumped around
testing cases maybe too language (Python) dependent, no objects
self-consistent complete package burnt out at end of first day (fast)
inspirational 9-4:30 draining, more breaks between topics
great intro to vocabulary, how programmers think didn't expect to program at end, was right
gained confidence from seeing experts switch morning git with afternoon python on 2nd day
seeing github, advice on resources not clear that mac users needed to install software ahead, why certain steps
had to do exercises, version control in beginner class some hard to follow along, relies on previous success with commands
instructors :-D, with real-world experience more relevant examples to audience, day to day data/problems
demo writing, troubleshooting, testing very valuable what was xcode for?
falling behind in python - 2 tiered exercises
documentation needs comments
is there help for release management?
advanced math?
third day - integrative exercise, case study - start to finish
follow up project, final suggested homework assignment

The good news is that they liked our material and they liked us (and seemed to think we knew what we were talking about). The bad news is a lot of them had a hard time keeping up and a couple complained it was too slow. These are typical complaints of our shotgun approach to teaching to a random sampling of scientists. We'd like to do more discipline specific bootcamps where we can tailor things better. Another typical complaint was they they aren't sure how to apply what they've learned to their research. We're still working on that one.

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