Hi Dav, Sarah!

Thanks so much for these incredibly interesting resources. This made me
realise again how important it is to take context into consideration when
developing courses. I think there's a lot here that may be useful, but I
also realise that a very small percentage of South African learners have
the kind of exposure that is for example spoken about in the AI4K12
materials. Still very interesting.

I specifically found this resource relevant and potentially of interest to
people who are teaching the Carpentries Spreadsheet lesson to complete data
novices - https://databasic.io/en/culture/paper-spreadsheet. I might even
try this in our upcoming Data Carpentry workshop in two weeks' time.

A related question - does anyone know of intro to data science materials
for teachers? I expect these will focus a lot on explaining why it is
important to learn (and teach) data science concepts and skills. From the
materials that was posted here, I immediately realised that teachers may be
more of a stumbling block than the kids' lack of prior exposure. Not to
criticise teachers, but they are already way over-worked and under-payed...

Thanks,

Anelda

On Wed, Mar 6, 2019 at 5:23 PM Dav Clark <[email protected]> wrote:

> The bootstrap community also has done a ton of work on computing-focused
> education, including aligning modules with math standards, etc. (US based,
> AFAIK, but probably easy to adapt) They've gotten great empirical results.
> They are very friendly. You can find them on the web here:
>
> https://www.bootstrapworld.org/
>
> There are social media links there and they're quite responsive.
>
> There's also a more data journalism angle, for example the Data
> Storytelling Studio / Data Murals out of https://datatherapy.org/, and
> also some of the projects at the Emerson Engagement Lab:
> https://elab.emerson.edu/projects
>
> FWIW, my sense is that the carpentries materials will be less effective
> than targeted curricula for high school, but also it's probably dependent
> on the teacher. As always in education, you do what you can.
>
> I'm actually quite interested in this topic, so happy to brainstorm more
> or even contribute (though I'm fairly constrained right now in terms of
> free time).
>
> Best,
> D
>
> On Wed, Mar 6, 2019 at 9:54 AM Sarah Brown <[email protected]> wrote:
>
>> Hi Anelda,
>>
>> There's a group of academics and K-12 teachers working on Artificial
>> Intelligence curricula for Kindergarten-high school learners. They have a
>> lot of resources: AI4K12.org.  I attended an event in the fall where they
>> had k-12 techers summarize what students at each age tend to know and be
>> able to learn.  The materials for high schoolers are available from this
>> page:
>> https://github.com/touretzkyds/ai4k12/wiki/2018-Fall-Symposium-Materials
>> .
>>
>> *Sarah M Brown, PhD*
>> sarahmbrown.org
>> Data Sciences Postdoctoral Research Associate
>> Brown University
>>
>>
>> On Wed, Mar 6, 2019 at 3:53 AM Anelda van der Walt <
>> [email protected]> wrote:
>>
>>> Dear community,
>>>
>>> Colleagues of mine (copied here) have received funding from the SA
>>> government to run an introduction to data science course for high school
>>> learners (16 & 17 years old). We had some preliminary discussions about
>>> content, but I have no experience with that age group  - what they know and
>>> don't know and how applicable the Carpentries materials might be to them.
>>>
>>> They specifically want to focus on Python.
>>>
>>> The course will run in July and they'll also host a datathon in
>>> December, where the learners will have an opportunity to participate in a
>>> competition to show off their skills. This means there is an opportunity to
>>> continue working with the learners between July and December, but taking
>>> their school work into consideration.
>>>
>>> Does anybody have a curriculum that have been taught to that age group
>>> that could help them think through their own curriculum? Any advice,
>>> resources, pointers would be greatly appreciated.
>>>
>>> Thanks as always!
>>>
>>> Anelda
>>>
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