Dear all,

thank you for all the replies. I think this is a somewhat tricky task. I still 
believe it would be worthwhile to include a short list in every lesson repo. 
This should/would be tailored to the audience of the lesson. I also think this 
list should be curated so that (as Darya suggested) it's content is a perfect 
fit for our learners ... if this is through a quick comment for every item or 
a 5-star rating, does not matter. But I think, it's important that we provide 
a quick statement how useful one title over another is. As a matter of fact, 
we as trainers/teachers are the ones that know the landscape of 
programming/scripting, our learners still need a map!

Also, I believe that the references on software-carpentry.org should stay. I 
consider useful overviews and some/most of them even stretch across topics 
(like the titles on open-source software development etc.) The global 
references page could then also link to the lessen references if needed.

Best -
Peter

On Wednesday, December 09, 2015 11:31:07 AM Darya Vanichkina wrote:
> Thanks for pointing that out, Peter! 
> 
> I think the way the literature is as a separate page gives a nice overview
> of the links we recommend (as opposed to embedded/scattered in/throughout
> the lessons). However, I do feel that page needs to be revamped, since it
> doesn’t seem to be very novice-friendly.
> 
> How clear would it be, for example, as a workshop attendee what I would
> learn by perusing " Effective Computation in Physics: Field Guide to
> Research with Python.” if what I’m told is  "Covers everything from basic
> shell scripting through object-oriented Python to parallel computing.”
> 
> OK, so basic shell scripting is important, but wait there was also this
> thing called the bash shell is this to do with it or am I building on it or
> using the python shell?….  Object oriented?… What does that mean? Is that
> good? Useful? Does this mean I’ll be able to do some fancy visualisation of
> my data and set up a website (which is what I really want)? Parallel
> computing? Why would I want to use parallel computing as a researcher? How
> does that even work?… … Should I even read this book if I’m not in physics?
> 
> Same with " Practical Computing for Biologists. “ - is it useful for non
> biologists? How?…
> 
> 
> What I am trying to say is that the list seems good in terms of content -
> although not exhaustive, and I’m sure we could add more favourite resources
> - but the descriptions are not very accessible to someone who doesn’t
> already know at least a bit of the lingo. 
> 
> Perhaps one way to address this might be to restructure the page more as a
> series of questions:
> 
> Did you love shell scripting? 
> If you’d like to learn more, Unix and Linux: Visual QuickStart Guide
> provides a very gentle introduction, and showcases how to do X, Y and Z
> (tasks that might be tempting to a researcher) 
> 
> 
> Would you like to harness the power of relational databases? 
> Chris Fehily's SQL describes the 5% of SQL that covers 95% of real-world
> needs. [And, yes, we also think that it moves a little slowly in some
> places, but the examples are really clear - for example, we really like the
> one where X, Y and Z are done (again, tempting real world use cases).
> 
> etc …
> 
> Thoughts?
> 
> Darya


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