> > 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 >>> >>> >>> >>> >>> >>> >>> >>> >>> >>> >>> >>> ------------------------------ >>> >>> Founded in 1821, Heriot-Watt is a leader in ideas and solutions. With >>> campuses and students across the entire globe we span the world, delivering >>> innovation and educational excellence in business, engineering, design and >>> the physical, social and life sciences. This email is generated from the >>> Heriot-Watt University Group, which includes: >>> >>> 1. Heriot-Watt University, a Scottish charity registered under >>> number SC000278 >>> 2. Heriot- Watt Services Limited (Oriam), Scotland's national >>> performance centre for sport. Heriot-Watt Services Limited is a private >>> limited company registered is Scotland with registered number SC271030 >>> and >>> registered office at Research & Enterprise Services Heriot-Watt >>> University, >>> Riccarton, Edinburgh, EH14 4AS. >>> >>> The contents (including any attachments) are confidential. 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