The older I get the more I realize “moderation in everything” is the key to success and happiness. Moderation in the sense of using or consuming something to only a certain degree.
In this case, education, the answer is in the middle. It’s exploring and utilizing new tools while ensuring the base foundation of education. It’s really simple.
Apply “moderation” to nearly any facet of your life and it’s probably the correct choice. Want to consume alcohol? Moderate consumption. Enjoy TikTok or other video entertainment? Moderation. Work? Don’t destroy yourself, moderate extreme effort.
This isn’t to say don’t follow passions or pursue things to a moderate extreme, just don’t ever let it consume you.
same. the older I get, the more I appreciate the "middle of the world" attitude in classical Chinese teachings. there's no single approach that's always / universally right. so it's wise to avoid going to the extreme in any direction
I don’t know about moderation but optimization is the mother of all evil. All extremists are actually optimization agents. Let one run for too long and you greatly loose on everything.
So I don’t think that we should meet a middle ground necessarily but wary of people that are trying to maxxx something.
There’s no middle ground, just that the serial killers and the people who insist that all human life is sacred are both destructive assuming that the sacred lifers take it to the extreme(i.e. try to force all resources and politics into saving all life whatever it takes).
No I'm arguing against the false fairness in moderation in anything. It's just not correct. (Though I do sense a sort of cognitive fent fold in certain heavy AI-users, so maybe I should)
Not really, at least not without restructuring the educational system completely.
AI really isn't a skill that needs to be taught, like adults didn't need to take a semester in AI-usage, so why should children need such a thing? Besides, it interferes with how we teach, which is done by having students write things in their own words (which is just "that which I can't explain, I don't understand", instrumentalized). It's not the essay that is the point, it's probably kinda shit, but the point is the fact that you are writing it. If AI does that work for them, then they simply don't learn. It's largely the same reason we don't let children use calculators when they're learning basic arithmetic. Calculators exist, and are useful, but they're awful in a teaching environment.
If we can use AI as an expert teacher with infinite time for each child, that does theoretically have promise (per bloom 2sigma). But it's also quite far away with what we've got right now.
We'll put aside where AI usage is a skill that needs to be taught (which I think there is definitely room for teaching people how to use it effectively as a tool) since that isn't what the discussion is about.
The article's talking about the use of AI learning rather than learning how to use AI.
> If AI does that work for them, then they simply don't learn.
I agree, and I think the original commenter would agree too given that this doesn't sounds like moderation.
The no-ai end is "you write the whole essay yourself" the all-in end is "you give the ai and idea and have it write the essay". The moderation approach is somewhere in-between and it could very well be "you write the essay and ask the AI to proofread and coach you through it".
> It's largely the same reason we don't let children use calculators when they're learning basic arithmetic. Calculators exist, and are useful, but they're awful in a teaching environment.
Yes, having the ai act as a calculator when you need to learn and prove you can do it is a bad use of it. Having the Ai double check your work to catch errors, point out when you make the same mistake over and over, or ask it to walk you through another example are all productive uses.
No you kinda need to actually write the thing yourself. It's the struggle of writing that is the entire point, going through that is what teaches you the material.
Any time you reach for AI to make it easier, you're missing out on understanding and retention. If you cannot express the thing in your own words, then you do not understand it.
Just as you don't learn anything by copying someone else's homework, or expanding on someone else's summary (like if that worked, that's how we'd be doing already, holy crap would it accelerate teaching), the same doesn't work when AI is involved.
Again, it's not the essay that is the point, it's the work that goes into writing it. You need to hand it in so that the teacher understand where to put in more effort, but if it wasn't for that need, they'd probably have you throw it away after writing it. Because of this, AI even for finishing touches makes it harder for the teacher to assess your level, and the polish it brings doesn't actually help you learn.
> You need to hand it in so that the teacher understand where to put in more effort, but if it wasn't for that need, they'd probably have you throw it away after writing it.
I am not sure how your literature classes went, but all of my essays were graded and feedback was provided to me specifically so I can get better. Perhaps my previously reply was too long winded, but feedback on your essay on how to improve it is the exact use case I gave as an example.
Sure, let's say you used AI to correct your mistakes before you submitted it, now you can't get that feedback, and again, you're missing out on learning.
Why would I be missing out on learning? If I want to improve my writing, why does it matter that if it’s Word, ChatGPT, or a teaching telling me that my spelling is wrong? Or that I keep making comma splice errors? Or that I have run on sentences?
Your teacher needs to understand your level to provide you with further instruction that is suitable for your level. If you show them what ChatGPT wrote, then they're working completely blind, and the education is equivalent to watching a series of youtube lectures.
Not that it's impossible to learn a subject that way, it just requires extremely self-motivated students.
At this point that's like saying Microsoft Excel isn't a skill that needs to be taught.
None of this stuff is easy to use, or obvious. If you want to get meaningful results out of it and avoid the many, many traps then there is an absolute ton you need to learn.
In the context of this conversation, the skill that needs to be learned is how to use AI to learn effectively. That gets into pedagogy and personal learning styles and self-discipline and all sorts of other extremely gnarly areas.
Isn't the industry's idea that 'prompt engineering' is over and anyone can use this stuff effectively?
There seems to be a literal trap where people are too trusting of the LLM and take its word on code or whatever is being offered instead of reading it themselves.
In the context of the classroom this means teaching discernment more than ever.
I don't like the conflation of terms, but they're obviously referring to LLMs, which are designed to use natural language prompts. And the integration of LLMs into Excel means that to some degree Excel doesn't need to be taught anymore.
Well let's say that is true, and we do teach a class of kids how to use AI, how much of that will still be applicable by the time they enter the work force?
The bits about learning to communicate in clear and unambiguous way, having a skeptical ear and knowing when to double-check information that is being presented to them, and understanding how to use tools in a way that enhance their own learning should ideally last a lifetime.
Sure. Fentanyl should neither be completely banned from the nation nor easily obtained OTC by anyone. We should keep it available for things like epidurals.
Truisms fail when you get to the edge cases. This is well known and you aren't pointing out some massive flaw in their reasoning when it comes comes to classroom AI use.
They weren't responding directly to classroom AI use, they were responding to the parent comment making a general claim about moderation - which included moderation of using Tiktok. My immediate thought was "Tiktok is like meth", would you advocate for moderation of meth?
So I agree with the comment. It was appropriately placed and a valid point. Moderation is key for many things, but there are exceptions. Things that are highly addictive and corrosive may be a good category for exceptions. Things that are clearly bad (e.g. murder) are exceptions.
When someone says "life is as simple as x" and the someon else says "hold on its not that simple, what about this exception" that latter rebuttal is valid and constructive.
>"Tiktok is like meth", would you advocate for moderation of meth?
This is an absurd statement. If someone is trying to talk about the middle cases, redirecting the conversation to the edge in order to dismiss their general comment is not appropriate.
'Edge cases exist' is not a lesson most people here need to hear.
I'm not even sure it's demonstrable that all things are good in moderation. There is a very large class of things that simply aren't good in moderation.
This leaves it generously a thought teminating cliche devoid of meaning, certainly nothing you should be making decisions off.
This just isn't a good generalization though. It would be easier to enumerate the few things it does apply to than the manifold that it doesn't.
It fails in every direction, not just stepping on legos and murder. It's in no way better to be moderately happy or healthy than extremely happy or healthy.
I'm not who you asked, but here are what good generalizations are to me:
1) days contain more photons than nights
2) water boils at 100 degrees Celsius
3) eating excessive sugar will lead to obesity
They seem like good generalizations because they are true most of the time from the perspective of the speaker and listener, even thought there may be some exceptions, they are materially more rare:
1) except in multi-solar systems, where this can get complicated
2) except when under pressures different than approximately sea level atmosphere
3) except when ___ I'm not sure but I bet there is some medical exception, maybe excessive exercise?
Bad generalizations will have many many exceptions such that the generalizations is materially lossy and even dangerous (e.g. "everything in moderation" -> murder in moderation, meth in moderation, punching grandmas in the face in moderation, etc.)
> murder in moderation, meth in moderation, punching grandmas in the face in moderation
I know these are your extreme examples but this is literally how society functions in each one.
Meth in moderation = prescription stimulants for ADHD or narcolepsy.
Murder in moderation = war, capital punishment.
Punching grandmas in the face in moderation = arrests of shoplifters or intoxicated grandmas apparently require physical restraint, lots of possible examples of violence for purported good on youtube.
Each of your hard lines are things that literally happen daily around the world, in moderation.
I mean, it worked reasonably well for my father while he was as recovering from his knee replacement. Fentanyl patches that gave a precise time-released dose.
I don't know what that means. Building muscle involves incredibly complicated biological processes, there's nothing "simple" about it. In the parent comment the "simple" advice is also fallacious.
I found this article frustrating. In my experience, the students who participate in the “co-creation of a contract” would likely also have done their best to comply with Professor induced rules. The challenge is the 10-20% who, stressed and overworked, will be just as likely to ignore this contract as any other. I would have liked to understand how the situation is changed compared to no rules at all…
As an educator, I found that the institution was often powerless to prevent or detect cheating, because many, many applicants are highly motivated by perverse incentives.
Many students attend because it's a "piece of paper" that's mandatory for their career aspirations. They'll never get hired without the college cred, and so they need to grab it by any means necessary. It's often not their own money they're spending: it's a federal grant, a loan, or mommy and daddy pining to give the same or better opportunity to the next generation. So family pressure to achieve is often immense, and overwhelming to a child being shoved through this system.
Other students, they already have a job and/or family, striving to get ahead and be upwardly mobile according to the American Dream, and so they simply don't have time for actual study or homework, but they paid tuition and purchased books, and these consumers need their product that they already invested in.
Perverse incentives abound in higher education, and without removing those or reforming the system, you'll never, ever stop or slow down the cheating, which is pervasive and rampant, believe you me.
After some debate, we drew a line separating mechanical churning from actual thinking. Automating repetitive tasks or literature searches was acceptable.
Was there any possibility of this not being the case? Rules which are not enforceable do not exist. If it's any part of the process you can't check, students are going to do it in the easiest way possible.
My job is to teach students how to get stronger. Instead of forcing them to stack and rerack their own weights, and instead of using the existing university policy against plagiarism, or the existing social contract. I made them sign an additional set of rules where they promise to only use the magic weight lift button when stacking or reracking. I feel that this middle ground is superior: I'd rather sacrifice the subtle exercise benefits of moving relatively light weight in weird ways; that extremely important toward helping prevent injuries, instead of actually dealing with the desire of students (human nature) to get out of the effort that goes into learning.
I have no idea how accurate, or useful that analogy is, but personal intuition tells me it's really close. I also don't envy teachers. I used to teach, so I do understand the position they feel that they are required to adapt into. However, I prefer CS programs that don't encourage people to tolerate non-determinism, or otherwise unpredictable outputs. They're the source of some of the most intractable bugs, one i doubt the next generation of students will be able to troubleshoot correctly if they never learn to solve beginner level bugs without LLM assistance.
Instruction needs to shift to accommodate AI rather than preventing it from being used to complete assignments and tests.
Assignments and tests were always lossy, and over time more cheating crept in.
Instruction should shift to benchmarking productive output, strategic thinking and group collaboration. Similar to labs where you are tested on completing an experiment or a project with artifacts. Or an MBA program with quarterly group objectives. A major part of the group effort is dealing with collaboration and overcoming obstacles like laggards.
Hopefully people will realize how poor testing is for preparing students for the real world. the ultimate goal is preparing the students for a productive life, most commonly in commercial enterprise, but even academic pursuits require collaboration, productivity and other characteristics that were not well assessed by traditional testing and homework.
I'm not sure it's possible to force someone to learn who doesn't want to. From what I can tell, the article is basically saying that giving the students some form of agency and trust is a better way to motivate them to take it seriously than being a strict top-down disciplinarian. This fits with my experience (both from when I was a student and in my interactions with younger people as an adult), and I would expect that most people who have seriously evaluated this strategy would come to the same conclusion. It's not perfect, as some students may try to take advantage of things or will still phone it in, but the same thing happens with every other way of trying to engage with them.
My experience has been the complete opposite, a bit of pressure goes a long way. There are many people who need to know X or Y and just dont have the maturity or innate motivation to do it properly. This comes from the experience of a Dutch school system so perhaps its different in other countries.
A variety of performance assessments more similar to commercial pursuits.
Group projects with tangible artifacts, including finished prototypes that meet objectives. More emphasis on group projects. If AI accelerates productive development like with software, move the objectives up the ladder in complexity, or expectations.
Peer assessments and performance reviews like employment . This also helps prepare students for adult life.
If the subject matter is merchandisable, have the students operate an enterprise. My local high school has the students operate a food cart for example, and it opens to the public one weekend a month, otherwise open to students. Students are responsible for inventory, marketing, accounting, maintenance , customer service etc.
More verbal challenges . These can be operated by AI with human supervision while being recorded, with spot checks from supervisors.
Every diagnostic has a precision / recall curve and some fall through the cracks. But you have to shift your approach when old testing no longer becomes viable. Better that than to revert to the stone age of informatics.
This argument has been beaten to death before AI: Ever since calculators were able to do math, students have been wondering why they need to learn how to do all of this math manually when they could get the same answer from a calculator.
The reasons become more obvious only when you get deeper into a field where the math gets too complex to get a simple answer out of a calculator. If you never learned the basic concepts, you can’t progress to the more difficult topics because you don’t have a good understanding of the foundation.
That’s why changing goals to only look at the output doesn’t work for educating kids. Now that they can have ChatGPT answer every question they might see on a middle school or even high school exam, you could conceivably get all the way through high school graduation never having learned a single thing other than how to copy and paste between the assignment and ChatGPT.
Then what happens in the real world when that student needs to learn something new? It’s obvious: They’re going to try to put the problem into ChatGPT and then give you the result back. They don’t have any foundational tools to do anything else. They haven’t even learned how to learn because there was always an easy way out. Why would anyone hire a person who can only act as an interface to ChatGPT? They won’t. They’ll use ChatGPT themselves.
My unpopular opinion is that some times hard work, memorization, doing work manually, and yes, even testing, are necessary to build up an education and thinking foundation. I don’t believe it can all be replaced by ideas about challenging students to get results and then ignoring how they arrive at the result. I’ve worked with kids enough to know that they are more resourceful about finding lazy ways to pass a test than you could ever imagine.
What is your opinion on using an LLM to provide immediate feedback/grading at scale such that students have to muster their own answers but can check them quickly, compressing the feedback loop and allowing for more iterations?
Students still have to muster their own answers, but the LLM is used to minimize the confusion or uncertainty about the quality of the answer and the time to wait for that clarity.
My understanding is decades of research long before AI has shown the benefit of timely constructive feedback on the learning process. Why aren't all educators tripping over themselves to use LLMs to maximize access to timely constructive feedback?
One interpretation of your comment is "LLM chat bots don't" or more specifically "ChatGPT doesn't", but I feel like this is a straw man and not intellectually honest answer to my question.
The real crux is not grounded in chat bots default behavior but the technology's capability: "Can LLMs provide access to timely constructive feedback in specific educational contexts?". The answer to this question is definitely yes. If you think the answer is no, then my guess is you haven't made an honest effort to try, or you just want the answer to be no and aren't interested in the truth.
Analogies with calculators have a big problem. The calculator has no intelligence of its own. A model does. (Yes, it does. You have to be either delusional or willfully ignorant to argue otherwise at this point. Take a calculator to the IMO and see how far you get.)
So there are, or at least there will be, cases where it's actually a good idea to delegate your thinking to an AI model. Students who aren't taught to acknowledge that possibility and keep it in mind are being done a disservice, just as if they were taught to treat today's limited, early-generation LLMs as a first resort.
I don’t understand the analogy you’re making, or maybe I think it’s wrong. This is the first time ive ever seen someone say you should outsource your thinking to an LLM, rather than say idea generation.
No one thinks you shouldn’t do 8 digit multiplication with a calculator, But you should understand what it’s doing under thr hood so if you say typo something you can catch when the answer is off by an order of magnitude.
But the same argument applies to AI. If you don’t understand the basics of an argument or the nature of the subject you’re investigating, you can’t tell - not even an if it’s working correctly but if it’s responding to the question you asked. If it applied the right context for your particular situation.
And I think it’s the exact same thing - whether AI is really thinking is irrelevant, students need to understand the nature of how to make arguments and validate information, before they can trust their own usage of AI.
This is the first time ive ever seen someone say you should outsource your thinking to an LLM, rather than say idea generation.
You could think of this story[1] as an example of why it's not useful to compare AI models with pocket calculators. Here, some professional mathematicians successfully farmed out part of their thought process to an AI model.
It doesn't mean they shut their own brains down, or that they are suggesting that students do so, only that they allowed for the possibility that the model might be able to see something they didn't see themselves, or make a connection that no one had considered before.
I suspect it is all futile without resurrecting the old idea of being "learned" as in learn-ed.
"Learned" didn't really mean what we mean today by being well educated or smart. You can't use AI to cheat and become "learned". AI can find the books to read but you still have to read them and understand the ideas.
There was connotation of breadth as opposed to depth with being "learned".
I think we also have to forget about "the real world". Being "learned" automatically is going to inherit dealing with "the real world" because the real world is always changing and that is exactly why breadth should be the focus going forward more than the depth of the research university model.
Of course, in a society so dominated by credentialism, credentialed people are going to hate AI because it will obviously let anyone cheat at the credential they put so much time and effort into. This doesn't need to be dressed up in some "think of the children" argument.
Claude to me is the greatest thing since sliced bread that increases my "learnedness" every single day but I also am a drop out that invested basically nothing in being a credentialed person.
This is nonsensical. Without a corpus of knowledge memorized and at your fingertips it’s next to impossible to build on it. Project work isn’t going to get you there. Creativity and new ideas happen when someone is deeply immersed in a space and can make connections.
I'm glad to see more of this approach to modernizing education. I roll my eyes seeing people argue that we should go back to pen + paper or other weird rose-colored regressive approaches to preventing AI usage. It's part of education now, it's part of work now, and learning environments that don't acknowledge that are going to be dragged kicking and screaming into a future with empty classrooms.
Both things can be true at the same time. The article mention switching to shorter reports and oral discussion but other courses may not have the luxury, especially the introductory ones.
> He didn’t try to hide that he had used AI to generate much of his assignment. Instead, he admitted his anxiety. He felt that mastering these tools was essential for his future career, yet he had no idea how—or even whether—he was allowed to use them.
I'm empathetic to the student: I'd bet a large majority of employers/careers he's researching right now are making a lot of press noise about "the importance of AI" and how "it's a necessary part of the workplace now." Can you really expect someone in his shoes to avoid it entirely?
In this case, education, the answer is in the middle. It’s exploring and utilizing new tools while ensuring the base foundation of education. It’s really simple.
Apply “moderation” to nearly any facet of your life and it’s probably the correct choice. Want to consume alcohol? Moderate consumption. Enjoy TikTok or other video entertainment? Moderation. Work? Don’t destroy yourself, moderate extreme effort.
This isn’t to say don’t follow passions or pursue things to a moderate extreme, just don’t ever let it consume you.
So I don’t think that we should meet a middle ground necessarily but wary of people that are trying to maxxx something.
Just moderate your moderation! It’s turtles all the way down
The difference between AI robbing you of learning opportunities and acting as a tutor or sounding board is what question you ask.
AI really isn't a skill that needs to be taught, like adults didn't need to take a semester in AI-usage, so why should children need such a thing? Besides, it interferes with how we teach, which is done by having students write things in their own words (which is just "that which I can't explain, I don't understand", instrumentalized). It's not the essay that is the point, it's probably kinda shit, but the point is the fact that you are writing it. If AI does that work for them, then they simply don't learn. It's largely the same reason we don't let children use calculators when they're learning basic arithmetic. Calculators exist, and are useful, but they're awful in a teaching environment.
If we can use AI as an expert teacher with infinite time for each child, that does theoretically have promise (per bloom 2sigma). But it's also quite far away with what we've got right now.
The article's talking about the use of AI learning rather than learning how to use AI.
> If AI does that work for them, then they simply don't learn.
I agree, and I think the original commenter would agree too given that this doesn't sounds like moderation.
The no-ai end is "you write the whole essay yourself" the all-in end is "you give the ai and idea and have it write the essay". The moderation approach is somewhere in-between and it could very well be "you write the essay and ask the AI to proofread and coach you through it".
> It's largely the same reason we don't let children use calculators when they're learning basic arithmetic. Calculators exist, and are useful, but they're awful in a teaching environment.
Yes, having the ai act as a calculator when you need to learn and prove you can do it is a bad use of it. Having the Ai double check your work to catch errors, point out when you make the same mistake over and over, or ask it to walk you through another example are all productive uses.
Any time you reach for AI to make it easier, you're missing out on understanding and retention. If you cannot express the thing in your own words, then you do not understand it.
Just as you don't learn anything by copying someone else's homework, or expanding on someone else's summary (like if that worked, that's how we'd be doing already, holy crap would it accelerate teaching), the same doesn't work when AI is involved.
Again, it's not the essay that is the point, it's the work that goes into writing it. You need to hand it in so that the teacher understand where to put in more effort, but if it wasn't for that need, they'd probably have you throw it away after writing it. Because of this, AI even for finishing touches makes it harder for the teacher to assess your level, and the polish it brings doesn't actually help you learn.
I am not sure how your literature classes went, but all of my essays were graded and feedback was provided to me specifically so I can get better. Perhaps my previously reply was too long winded, but feedback on your essay on how to improve it is the exact use case I gave as an example.
Not that it's impossible to learn a subject that way, it just requires extremely self-motivated students.
At this point that's like saying Microsoft Excel isn't a skill that needs to be taught.
None of this stuff is easy to use, or obvious. If you want to get meaningful results out of it and avoid the many, many traps then there is an absolute ton you need to learn.
In the context of this conversation, the skill that needs to be learned is how to use AI to learn effectively. That gets into pedagogy and personal learning styles and self-discipline and all sorts of other extremely gnarly areas.
There seems to be a literal trap where people are too trusting of the LLM and take its word on code or whatever is being offered instead of reading it themselves.
In the context of the classroom this means teaching discernment more than ever.
Moderation in fentanyl.
So I agree with the comment. It was appropriately placed and a valid point. Moderation is key for many things, but there are exceptions. Things that are highly addictive and corrosive may be a good category for exceptions. Things that are clearly bad (e.g. murder) are exceptions.
When someone says "life is as simple as x" and the someon else says "hold on its not that simple, what about this exception" that latter rebuttal is valid and constructive.
This is an absurd statement. If someone is trying to talk about the middle cases, redirecting the conversation to the edge in order to dismiss their general comment is not appropriate.
'Edge cases exist' is not a lesson most people here need to hear.
This leaves it generously a thought teminating cliche devoid of meaning, certainly nothing you should be making decisions off.
It fails in every direction, not just stepping on legos and murder. It's in no way better to be moderately happy or healthy than extremely happy or healthy.
1) days contain more photons than nights
2) water boils at 100 degrees Celsius
3) eating excessive sugar will lead to obesity
They seem like good generalizations because they are true most of the time from the perspective of the speaker and listener, even thought there may be some exceptions, they are materially more rare:
1) except in multi-solar systems, where this can get complicated
2) except when under pressures different than approximately sea level atmosphere
3) except when ___ I'm not sure but I bet there is some medical exception, maybe excessive exercise?
Bad generalizations will have many many exceptions such that the generalizations is materially lossy and even dangerous (e.g. "everything in moderation" -> murder in moderation, meth in moderation, punching grandmas in the face in moderation, etc.)
I know these are your extreme examples but this is literally how society functions in each one.
Meth in moderation = prescription stimulants for ADHD or narcolepsy.
Murder in moderation = war, capital punishment.
Punching grandmas in the face in moderation = arrests of shoplifters or intoxicated grandmas apparently require physical restraint, lots of possible examples of violence for purported good on youtube.
Each of your hard lines are things that literally happen daily around the world, in moderation.
But yeah, what's moderation and what's excessive is subjective.
https://en.wikipedia.org/wiki/Argument_to_moderation
https://www.logicallyfallacious.com/logicalfallacies/Argumen...
What I've found as I get older is that when someone says "It’s really simple," that's a good sign it isn't.
Many students attend because it's a "piece of paper" that's mandatory for their career aspirations. They'll never get hired without the college cred, and so they need to grab it by any means necessary. It's often not their own money they're spending: it's a federal grant, a loan, or mommy and daddy pining to give the same or better opportunity to the next generation. So family pressure to achieve is often immense, and overwhelming to a child being shoved through this system.
Other students, they already have a job and/or family, striving to get ahead and be upwardly mobile according to the American Dream, and so they simply don't have time for actual study or homework, but they paid tuition and purchased books, and these consumers need their product that they already invested in.
Perverse incentives abound in higher education, and without removing those or reforming the system, you'll never, ever stop or slow down the cheating, which is pervasive and rampant, believe you me.
Was there any possibility of this not being the case? Rules which are not enforceable do not exist. If it's any part of the process you can't check, students are going to do it in the easiest way possible.
I have no idea how accurate, or useful that analogy is, but personal intuition tells me it's really close. I also don't envy teachers. I used to teach, so I do understand the position they feel that they are required to adapt into. However, I prefer CS programs that don't encourage people to tolerate non-determinism, or otherwise unpredictable outputs. They're the source of some of the most intractable bugs, one i doubt the next generation of students will be able to troubleshoot correctly if they never learn to solve beginner level bugs without LLM assistance.
Assignments and tests were always lossy, and over time more cheating crept in.
Instruction should shift to benchmarking productive output, strategic thinking and group collaboration. Similar to labs where you are tested on completing an experiment or a project with artifacts. Or an MBA program with quarterly group objectives. A major part of the group effort is dealing with collaboration and overcoming obstacles like laggards.
Hopefully people will realize how poor testing is for preparing students for the real world. the ultimate goal is preparing the students for a productive life, most commonly in commercial enterprise, but even academic pursuits require collaboration, productivity and other characteristics that were not well assessed by traditional testing and homework.
Group projects with tangible artifacts, including finished prototypes that meet objectives. More emphasis on group projects. If AI accelerates productive development like with software, move the objectives up the ladder in complexity, or expectations.
Peer assessments and performance reviews like employment . This also helps prepare students for adult life.
If the subject matter is merchandisable, have the students operate an enterprise. My local high school has the students operate a food cart for example, and it opens to the public one weekend a month, otherwise open to students. Students are responsible for inventory, marketing, accounting, maintenance , customer service etc.
More verbal challenges . These can be operated by AI with human supervision while being recorded, with spot checks from supervisors.
Every diagnostic has a precision / recall curve and some fall through the cracks. But you have to shift your approach when old testing no longer becomes viable. Better that than to revert to the stone age of informatics.
The reasons become more obvious only when you get deeper into a field where the math gets too complex to get a simple answer out of a calculator. If you never learned the basic concepts, you can’t progress to the more difficult topics because you don’t have a good understanding of the foundation.
That’s why changing goals to only look at the output doesn’t work for educating kids. Now that they can have ChatGPT answer every question they might see on a middle school or even high school exam, you could conceivably get all the way through high school graduation never having learned a single thing other than how to copy and paste between the assignment and ChatGPT.
Then what happens in the real world when that student needs to learn something new? It’s obvious: They’re going to try to put the problem into ChatGPT and then give you the result back. They don’t have any foundational tools to do anything else. They haven’t even learned how to learn because there was always an easy way out. Why would anyone hire a person who can only act as an interface to ChatGPT? They won’t. They’ll use ChatGPT themselves.
My unpopular opinion is that some times hard work, memorization, doing work manually, and yes, even testing, are necessary to build up an education and thinking foundation. I don’t believe it can all be replaced by ideas about challenging students to get results and then ignoring how they arrive at the result. I’ve worked with kids enough to know that they are more resourceful about finding lazy ways to pass a test than you could ever imagine.
Students still have to muster their own answers, but the LLM is used to minimize the confusion or uncertainty about the quality of the answer and the time to wait for that clarity.
My understanding is decades of research long before AI has shown the benefit of timely constructive feedback on the learning process. Why aren't all educators tripping over themselves to use LLMs to maximize access to timely constructive feedback?
The real crux is not grounded in chat bots default behavior but the technology's capability: "Can LLMs provide access to timely constructive feedback in specific educational contexts?". The answer to this question is definitely yes. If you think the answer is no, then my guess is you haven't made an honest effort to try, or you just want the answer to be no and aren't interested in the truth.
So there are, or at least there will be, cases where it's actually a good idea to delegate your thinking to an AI model. Students who aren't taught to acknowledge that possibility and keep it in mind are being done a disservice, just as if they were taught to treat today's limited, early-generation LLMs as a first resort.
No one thinks you shouldn’t do 8 digit multiplication with a calculator, But you should understand what it’s doing under thr hood so if you say typo something you can catch when the answer is off by an order of magnitude.
But the same argument applies to AI. If you don’t understand the basics of an argument or the nature of the subject you’re investigating, you can’t tell - not even an if it’s working correctly but if it’s responding to the question you asked. If it applied the right context for your particular situation.
And I think it’s the exact same thing - whether AI is really thinking is irrelevant, students need to understand the nature of how to make arguments and validate information, before they can trust their own usage of AI.
You could think of this story[1] as an example of why it's not useful to compare AI models with pocket calculators. Here, some professional mathematicians successfully farmed out part of their thought process to an AI model.
It doesn't mean they shut their own brains down, or that they are suggesting that students do so, only that they allowed for the possibility that the model might be able to see something they didn't see themselves, or make a connection that no one had considered before.
1: https://www.scientificamerican.com/article/ai-just-solved-an...
It doesn't not mean that either.
"Learned" didn't really mean what we mean today by being well educated or smart. You can't use AI to cheat and become "learned". AI can find the books to read but you still have to read them and understand the ideas.
There was connotation of breadth as opposed to depth with being "learned".
I think we also have to forget about "the real world". Being "learned" automatically is going to inherit dealing with "the real world" because the real world is always changing and that is exactly why breadth should be the focus going forward more than the depth of the research university model.
Of course, in a society so dominated by credentialism, credentialed people are going to hate AI because it will obviously let anyone cheat at the credential they put so much time and effort into. This doesn't need to be dressed up in some "think of the children" argument.
Claude to me is the greatest thing since sliced bread that increases my "learnedness" every single day but I also am a drop out that invested basically nothing in being a credentialed person.
Uh, by also avoiding it entirely?
> He didn’t try to hide that he had used AI to generate much of his assignment. Instead, he admitted his anxiety. He felt that mastering these tools was essential for his future career, yet he had no idea how—or even whether—he was allowed to use them.
I'm empathetic to the student: I'd bet a large majority of employers/careers he's researching right now are making a lot of press noise about "the importance of AI" and how "it's a necessary part of the workplace now." Can you really expect someone in his shoes to avoid it entirely?
...because I'm that I'm writing this article be a AI himself...