I have tried both. Jupyter is fine for demonstrations of small snippets of
code that fit on a screen.  It is fantastic for e.g. pandas and plotting.
But as soon you have to scroll back and forth in the browser to relate
different part of code to each other, I get lost and so do the students.
Great for experimentation but not for the development skills we try to
teach.

Cheers
Olav

On Wed, May 10, 2017 at 9:45 PM, Eric Jankowski <
[email protected]> wrote:

> I've taught both ways and lean towards Jupyter for shorter-contact
> workshops, and lean towards CLI for longer-contact workshops and classes.
>
> Jupyter notebooks lower the cognitive load associated with CLI, text
> editors, edit-save-execute iterations, and are a lower barrier to providing
> a standardized implementation (e.g., Anaconda on learner's machines or a
> public-facing notebook server you control). With the lower load, it's
> possible to go from 0 to image processing in no time, and that time saved I
> think contributes substantially to the take-aways of our learners in short
> workshops. "Wow! I did some real data wrangling there, and I can use this
> on my work today!" I also *really* like having the code and the
> presentation of data in one place, so when I work with students now it's
> easy to fiddle with things in plots in the notebooks which significantly
> accelerates our group understanding of what our data means. (as compared to
> "plot it a different way and see you next week")
>
> My minor qualm is that the notebooks don't provide exposure to the CLI and
> the very common workflows that combine loops, pipes, python scripts, and
> other unixy tools. In the context of my semester-long courses we'll start
> with CLI, python, and git, and maybe 5 weeks in show "Here are jupyter
> notebooks, which are a really great compliment to what we've learned so
> far!".
> And in terms of keeping track of code used by, managing jupyter notebooks
> with version control can be tricky.
>
> So, the quick version: Jupyter notebooks are amazing, but in some ways
> orthogonal to the automation, reproducibility, and sharing ecosystem that
> software carpentry has been thoughtful about making self-consistent.
>
> Talk permissions granted!
>
> Best,
> Eric
>
> On Wed, May 10, 2017 at 1:03 PM, Maneesha Sane <[email protected]>
> wrote:
>
>> Hi all,
>>
>> I am giving two talks next week at Bryn Mawr's Jupyter days conference  (
>> http://jupyterday.blogs.brynmawr.edu/)
>>
>> One is running an intro to Python workshop using Jupyter and I'm piecing
>> together parts of the SWC and DC curricula to teach it.
>>
>> The other talk is a shorter talk (~20 minutes, incuding Q&A) about the
>> differences teaching Python via straight command line compared to teaching
>> from the Jupyter notebook.  When I've taught for the Carpentries, I've
>> always used Jupyter.  In other contexts, I've taught strictly from the
>> CLI.  I'm curious to know if others have taught in both ways (either for
>> the Carpentries or in other circumstances) and what you've thought of it.
>> Advantages/disadvantages?  What you like and don't like about Jupyter and
>> CLI environments?
>>
>> With your permission, I'd like to use some of your feedback in my talk.
>> I also think it would be useful for Carpentries instructors to know in
>> general, so please share any feedback to the list.
>>
>> Thanks!
>>
>>
>>
>> --
>> Maneesha Sane
>> Software Carpentry: https://software-carpentry.org/
>> Data Carpentry: http://www.datacarpentry.org/
>>
>>
>> _______________________________________________
>> Discuss mailing list
>> [email protected]
>> http://lists.software-carpentry.org/listinfo/discuss
>>
>
>
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