The exploration notebook feels like it's too long

[choldgraf]

I haven't taught it in full yet, but just going through the notebook it really feels like a lot of material to go through, and some topics that are sort of casually mentioned but that are really quite complex, and I could see the instructor getting bogged down in explanations (e.g., regex). I'd be curious how long it took some folks to teach this lecture, and to decide if it needs cutting back.

[hlapp]

@JamiesHQ had an afternoon for this lesson at the workshop at Duke, and she finished early. And I thought her pacing was not rushed by any measure.

[hlapp]

However, there were some thoughts about the lesson content as part of the debrief afterwards, for example focusing more on imparting the concepts than how the specific implementations of those concepts look in the Python language. @kcranston, @dleehr, and @tracykteal did we record that somewhere?

[choldgraf]

I think this is a great idea @hlapp ...I'm going through the material now and I agree it's a little focused on the syntax of python etc. I think you could have the same code that's there, but call out the higher-level concepts better.

[nerdcommander]

I'm interested in working on this lesson. I've taught two different derivations of it to two different classes - one with no previous python experience - and think it went well, but I had tweaked it and will need to tweak it again. We had a 2 hr class period and there was homework for the students. I'll put my adapted versions in a repo and post the link. My semester is winding down (which means my workload is ratcheting up) so it will be hard for me to do much with this for the next few weeks. Is there a deadline/time pressure?

[burkesquires]

@choldgraf Chris I agree. I have taught this with @hlapp and at the NIH a week or so ago. When I informally surveyed the NIH attendees the majority of them had programming experience, many in python. So, I do not think we need to "teach" python in these lessons. I think that the people who realize they can use reproducible science techniques are advanced enough to not need language training. Furthermore, a major advantage of the Jupyter Notebook is the ability to build workflows that incorporate many languages - python, R, bathe, perl, etc.