Thanks Hao!

Best Regards,
Federica Gazzelloni


On Tue, 18 Mar 2025 at 17:30, Hao Ye <[email protected]> wrote:

> I’m curious if others have tried similar methods or have insights on
>> striking the right balance between leveraging AI tools and preserving
>> hands-on learning opportunities.
>
>
> Hi Federica,
>
> If you hadn't seen it already, there was this thread that Lex started in
> the slack last year on this topic - I think there are quite a few links to
> examples
> https://carpentries.slack.com/archives/C03LE48AY/p1713166328175869
>
> Best,
> --
> Hao Ye
> (he/him/his)
> [email protected]
>
>
> On Tue, Mar 18, 2025 at 12:13 PM Federica Gazzelloni <
> [email protected]> wrote:
>
>> Hi all,
>>
>> This thread continues to highlight such important insights. I wanted to
>> add another perspective, building on what’s been said.
>>
>> A key distinction I often emphasize in my own teaching is the
>> relationship between effort and comprehension. It’s true that AI tools can
>> make the process of problem-solving more efficient, but it’s also critical
>> to ensure that learners are actively engaging with the concepts, rather
>> than passively accepting solutions.
>>
>> One possible approach is introducing structured exercises that leverage
>> AI as a learning companion. For instance:
>>
>> Students can use AI tools to draft initial code.
>>
>> They then analyze and critique the AI's output—identifying potential
>> errors, inefficiencies, or areas for improvement.
>>
>> Finally, they optimize the code manually, applying their own knowledge to
>> refine and debug.
>>
>> This strategy shifts the focus from simply generating output to
>> understanding the "why" and "how" behind it. It also aligns with the
>> growing need to teach "meta-skills" for interacting with AI: evaluating its
>> reliability, fine-tuning its outputs, and balancing automation with human
>> creativity.
>>
>> Hao's analogy with meal kits is particularly apt here—AI can provide the
>> "ingredients" or the base recipe, but students still need to understand how
>> to "cook," adapting the process to suit their specific needs or goals. This
>> fosters a deeper understanding of the coding principles and encourages
>> critical thinking.
>>
>> I’m curious if others have tried similar methods or have insights on
>> striking the right balance between leveraging AI tools and preserving
>> hands-on learning opportunities.
>>
>> Best,
>> Federica
>>
>>
>> On Tue, Mar 18, 2025 at 4:58 PM Hao Ye <[email protected]> wrote:
>>
>>> If we only care about the end result (e.g. a function that computes
>>>> something) and not the means to the end (e.g. how you compute something),
>>>> it may be fine to teach an AI heavy methodology. We, as teachers, first
>>>> have to decide what we want a student to learn before deciding the means to
>>>> get them to that objective. We still teach mathematics to students even
>>>> though we've been able to answer most all math questions through the
>>>> college level with Wolfram Alpha for 15 years now and many things can be
>>>> done on a calculator for 50 years now.
>>>
>>>
>>> I am strongly in agreement with the distinction here between learning
>>> programming vs. learning *some* set of skills whose end product is a
>>> correct program.
>>>
>>> And because I like my cooking analogies, I'll add in an additional
>>> metaphor of learning to cook vs. following the instructions in a meal kit.
>>>
>>> I am also reminded about the pedagogical literature findings that people
>>> are bad at evaluating how much they've learned; and one of the common
>>> estimators people use (that is biased) is how *easy* the learning was
>>> (e.g. passively listening to a lecture vs. active learning).
>>>
>>> Best,
>>> --
>>> Hao Ye
>>> (he/him/his)
>>> [email protected]
>>>
>>>
>>> On Tue, Mar 18, 2025 at 7:31 AM Jason Moore <[email protected]>
>>> wrote:
>>>
>>>> I think you have to carefully evaluate what the learning objectives are
>>>> before deciding on AI or not or how much AI, etc. Take the analogy of
>>>> learning an ancient way of making bowls by hand with wood versus learning
>>>> how operate a manufacturing plant's bowl making machine. For the latter,
>>>> you may not even need to know what a carving knife is or how the blade
>>>> interacts with wood. In computer science, we have similar analogies tied to
>>>> learning to code in assembly versus python. I can engineer a solution with
>>>> either language and get something that does the same thing but I need
>>>> different knowledge and understanding to succeed with each language. Of
>>>> course we can teach students "how to code" using AI but they learn
>>>> different things and the focus may mostly be on the product. If we only
>>>> care about the end result (e.g. a function that computes something) and not
>>>> the means to the end (e.g. how you compute something), it may be fine to
>>>> teach an AI heavy methodology. We, as teachers, first have to decide what
>>>> we want a student to learn before deciding the means to get them to that
>>>> objective. We still teach mathematics to students even though we've been
>>>> able to answer most all math questions through the college level with
>>>> Wolfram Alpha for 15 years now and many things can be done on a calculator
>>>> for 50 years now. If we want a student to know how every line in a program
>>>> works, then they probably need to think about and write every line of that
>>>> code. I listened to a recent podcast, the name is escaping me, where the
>>>> caster lamented on students using AI to get the product, a written essay,
>>>> but not learning how to write. Do we really want to stop teaching people
>>>> how to write because a computer can write things?
>>>>
>>>> Jason
>>>> moorepants.info
>>>> +01 530-601-9791
>>>>
>>>>
>>>> On Tue, Mar 18, 2025 at 11:25 AM Paola Di Maio <[email protected]>
>>>> wrote:
>>>>
>>>>> Simon, and Toby whose sentiment is echoed-
>>>>>
>>>>> thanks for the discussion points
>>>>>
>>>>> In my personal experience, it is important to use the new tools
>>>>> responsibly and intelligently.
>>>>> if they can help us learn faster and better. Because there is too much
>>>>> to learn, esp for younger generations
>>>>> There is a race going on, and machines can give us some edge
>>>>>
>>>>> I feel that my mission is how to teach how to use AI responsibly* and
>>>>> critically*
>>>>>
>>>>> which in fact is true of any technology, starting from evaluating
>>>>> critically search results of any query
>>>>>
>>>>> So rather than saying do not use AI code generators, I d say
>>>>>
>>>>> a) continue to learn how to code, but use that knowledge
>>>>> to write good prompts for the code generators and
>>>>> b) learn how to evaluate debug, proof, test, implement, integrate,
>>>>> test. evaluate, optimise  code
>>>>> *shameless self promotion: I teach a course on responsible use of AI
>>>>> if anyone is interested/able to collaborate with me on offering it
>>>>>
>>>>> By all means we must continue to learn and teach how to code - bur we
>>>>> do not have to do the work ourselves
>>>>> we become supervisors, system integrators etc
>>>>>
>>>>> How to use code generators to produce the code we want/need and how to
>>>>> evaluate the qualify of ai generated code?
>>>>> how to evaluate the output of any technology mediated process,really,
>>>>> is what I think we help learners with
>>>>>
>>>>> I attach three relevant short posts in PDF from my feed
>>>>> *disclaimer A*I supported, let me know if you spot terrible wrongs*
>>>>>
>>>>> for general interest/discussion and it would be great to connect over
>>>>> our shared experiences
>>>>> of using AI tor teaching/learning
>>>>>
>>>>> PDM
>>>>>
>>>>> On Mon, Mar 17, 2025 at 5:26 PM Waldman, Simon via discuss <
>>>>> [email protected]> wrote:
>>>>>
>>>>>> I think the reasoning behind the “don’t use AI when you’re learning”
>>>>>> comment is that there is a risk that people simply use code that they are
>>>>>> given without thinking about it, and therefore don’t build a mental model
>>>>>> of what is going on, don’t learn, and hence are unable to spot mistakes 
>>>>>> by
>>>>>> the AI or build more advanced things.
>>>>>>
>>>>>>
>>>>>>
>>>>>> In a sense, I think it’s best to think of AI coding assistance as a
>>>>>> more advanced version of “look it up on StackOverflow”. We have all come
>>>>>> across plenty of people who have done all their coding by copy-pasting
>>>>>> snippets from StackOverflow without fully understanding them – as well as
>>>>>> people who have laid the groundwork by learning what they are doing 
>>>>>> first,
>>>>>> and **then** looked things up to much better effect. I think this is
>>>>>> especially important for a first language – when one is learning
>>>>>> programming as well as a particular syntax.
>>>>>>
>>>>>>
>>>>>>
>>>>>> That’s my 2p; clearly “don’t use AI” is not enforceable and won’t be
>>>>>> adhered to by many, but it’s important that we explain the reason that 
>>>>>> that
>>>>>> advice is given (and maybe consider moderating it to “limit use of AI” or
>>>>>> similar) so that hopefully most learners will bear it in mind.
>>>>>>
>>>>>>
>>>>>>
>>>>>> --
>>>>>>
>>>>>> Dr Simon Waldman / [email protected]
>>>>>>
>>>>>> Assistant Professor of Energy Technologies, Heriot-Watt University
>>>>>>
>>>>>> Programme lead for MSc Renewable & Sustainable Energy Transition
>>>>>>
>>>>>>
>>>>>>
>>>>>> *From:* Paola Di Maio <[email protected]>
>>>>>> *Sent:* 16 March 2025 22:46
>>>>>> *To:* discuss <[email protected]>
>>>>>> *Subject:* Re: [cp-discuss] Re: Feedback Request: Lesson Updates on
>>>>>> Generative AI
>>>>>>
>>>>>>
>>>>>>
>>>>>>
>>>>>> ******************************************************************
>>>>>> *Caution: This email originated from a sender outside Heriot-Watt
>>>>>> University. Do not follow links or open attachments if you doubt the
>>>>>> authenticity of the sender or the content. *
>>>>>> * *****************************************************************
>>>>>>
>>>>>>
>>>>>>
>>>>>> Thank you Toby and all for the discussion
>>>>>>
>>>>>> it is an important one, at many levels
>>>>>>
>>>>>>
>>>>>>
>>>>>> I have always detested coding, comparing it to unnecessary
>>>>>> bricklaying  vs me being interested in information architectures
>>>>>>
>>>>>>
>>>>>>
>>>>>> When AI generated code became available I felt relief, the finally
>>>>>> humanity has found a way of avoiding coding by hand
>>>>>>
>>>>>>
>>>>>>
>>>>>> My question is: is the AI generated code as good as, better or worse
>>>>>> than humanly written code?
>>>>>>
>>>>>> Having the code written up already means learners must learn how to
>>>>>> implement it and run it correctly
>>>>>>
>>>>>>
>>>>>>
>>>>>> can it be used to learn/teach about coding more productively - ie
>>>>>> engaging learners to Implement debug, test, maniupate, evaluate the ai
>>>>>> generated output
>>>>>>
>>>>>> and how to correct it and improve it, rather than putting their
>>>>>> effort into writing
>>>>>>
>>>>>>
>>>>>>
>>>>>>  AI generated code could allow learners to move straight into the
>>>>>> next level of coding, that is implementation
>>>>>>
>>>>>> Thorough understanding of how the syntax and logic of the program
>>>>>> should still be required, but the human intelligence
>>>>>>
>>>>>> so rare and precious can be spared the tedious task of actually
>>>>>> writing it
>>>>>>
>>>>>>
>>>>>>
>>>>>>
>>>>>>
>>>>>> On Mon, Mar 17, 2025 at 6:21 AM Paul Harrison via discuss <
>>>>>> [email protected]> wrote:
>>>>>>
>>>>>> Hi Toby,
>>>>>>
>>>>>> I'm following this ongoing discussion with interest. Great to see
>>>>>> this being added to Carpentries material.
>>>>>>
>>>>>> We recommend that you avoid getting help from generative AI while you
>>>>>> learn to code
>>>>>>
>>>>>>
>>>>>>
>>>>>> I was a bit surprised by this negative conclusion. My feeling would
>>>>>> be that it isn't reasonable to expect people not to use these tools while
>>>>>> learning, and therefore they need to know how to use them safely. And 
>>>>>> they
>>>>>> do seem quite good at explaining code or suggesting different approaches.
>>>>>>
>>>>>>
>>>>>>
>>>>>> Here's a slide I used in a recent workshop, although I'm far from
>>>>>> 100% happy with it.
>>>>>>
>>>>>>
>>>>>> https://monashdatafluency.github.io/r-progtidy/slides/introduction.html#11
>>>>>>
>>>>>>
>>>>>>
>>>>>>
>>>>>>
>>>>>>
>>>>>>
>>>>>>
>>>>>>
>>>>>>
>>>>>>
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