What I usually tell students is that homework and projects are learning opportunities. The point isn't for them to produce a particular artifact; it's to go through the process and develop skills along the way. For instance, I do not need a program that can sort numbers... I can do that myself and there are a gazillion instances of that. However, students should do that assignment to practice learning how to code, how to debug, how to think through problems, and much more. The point isn't the sorting program... it's the process and experience.
How do you get better at say gymnastics? You do a bunch of exercises and skills, over and over.
How do you get better at say playing the guitar? You play a lot songs, over and over.
How do you get better at say writing? You write a lot, some good, some bad, over and over.
To get better at anything, you need to do the thing, a lot. You need to build intuition and muscle memory. Taking shortcuts prevents that and in the long run, hurts your learning and growth.
So viewing homeworks as just about the artifact you submit is missing the point and short-sighted. Cheating, whether using AI or not, is preventing yourself from learning and developing mastery and understanding.
I want to start off by saying that I agree there are aspects of the process which are important and should be learned, but this is more to do with critical thinking and applicable skills than it has to do with the process itself.
Of note, this part of your reply in particular I believe is somewhat shortsighted
Cheating, whether using AI or not, is preventing yourself from learning and developing mastery and understanding.
Using AI to answer a question is not necessarily preventing yourself from learning and developing mastery and understanding. The use of AI is a skill in the same way that any ability to look up information is a skill. But blindly putting information into an AI and copy/pasting the results is very different from using AI as a resource in a similar way one might use a book or an article as a resource. A single scientific study with a finding doesn't make fact - it provides evidence for fact and must be considered in the context of other available evidence.
In addition, learning to interact with and use AI is a skill in the same way that learning to interact with and use a phone, or the internet, or an app are all skills. With interaction layers becoming increasingly more abstract (which is normal and good), people need to have skills at each layer in order for processes to exist and for tools be useful to humanity. Most modern tools require people who can operate on different levels with different levels of skill. While computers are an easy example since you are replying on some kind of electronic device which requires everything from chemists to engineers to fabrication specialists and programmers (hardware, software, operating system, etc.) to work, this is true for nearly any human made product in the modern world. Being able to drive a car is a very different skill set than being able to maintain a car, or work on a car, or fabricate parts for a car, or design parts for a car, or design the machinery that manufactures the parts for the car, and so on.
This is a particularly long winded way of pointing out something that's always been true - the idea that you should learn how to do math in your head because 'you won't always have a calculator' or that the idea that you need to understand how to do the problem in your head or how the calculator is working to understand the material is a false one and it's one that erases the complexity of modern life. Practicing the process helps you learn a specific skill in a specific context and people who make use of existing systems to bypass the need of having that skill are not better or worse - they are simply training a different skill. The means by which they bypass the process is extremely important - they could give it no thought at all or they may critically think about it and devise a process which still pays attention to the underlying process without fully understanding how to replicate it. The difference in approach is important, and in the context of learning it's important to experiment and learn critical thinking skills to make a decision of where you wish to have that additional mastery and what level of abstraction you are comfortable with and care about interacting with.
Using AI to answer a question is not necessarily preventing yourself from learning and developing mastery and understanding. The use of AI is a skill in the same way that any ability to look up information is a skill. But blindly putting information into an AI and copy/pasting the results is very different from using AI as a resource in a similar way one might use a book or an article as a resource.
I generally agree. That's why I'm no longer banning AI in my courses. I'm allowing students to use AI to explain concepts, help debug, or as a reference. As a resource or learning aid, it's fine or possibly even great for students.
However, I am not allowing students to generate solutions, because that is harmful and doesn't help with learning. They still need to do the work and go through the process, AI assisted or not.
This is a particularly long winded way of pointing out something that's always been true - the idea that you should learn how to do math in your head because 'you won't always have a calculator' or that the idea that you need to understand how to do the problem in your head or how the calculator is working to understand the material is a false one and it's one that erases the complexity of modern life. Practicing the process helps you learn a specific skill in a specific context and people who make use of existing systems to bypass the need of having that skill are not better or worse - they are simply training a different skill.
I disagree with your specific example here. You should learn to do math in your head because it helps develop intuition of the relationship between numbers and the various mathematical operations. Without a foundational understanding of how to do the basics manually, it becomes very difficult to tackle more complicated problems or challenges even with a calculator. Eventually, you do want to graduate to using a calculator because it is more efficient (and probably more accurate), but you will be able to use it much more effectively if you have a strong understanding numbers and how the various operations work.
Your overall point about how a tool is used being important is true and I agree that if used wisely, AI or any other tool can be a good thing. That said, from my experience, I find that many students will take the easy way out and do as you noted at the top: "blindly putting information into an AI and copy/pasting the results".
Sure. If you do enough basic math, you start to see things like how 2/8 can be simplified to 1/4 or you recognize that 10 is not a perfect square root or how you could reorder some operations to make things easier (sorry, examples from my kids). Little things like that where you don't even think about it... it becomes second nature to you and that makes you a lot faster because you are not worrying about those basic ideas or mechanics. Instead, you can think about more complicated things such as which formulas to apply or the process to compute something.
As another example, since I teach computer science, a lot of novice students struggle with basic programming language syntax... How exactly do you declare a variable? What order do things go? How does a for loop work? Do you need a semicolon or parentheses, etc. If you do enough programming, however, these things become second nature and you stop thinking about it. You just seemily, intuitively, know these things and do them naturally without thinking, even though when you first started, it was really complicated and daunting and you probably spent a lot of time constructing a single line of code.
Once you develop a foundation however, you don't need to worry about these low-level things. Instead you worry about high-level issues such as how to organize larger pieces of code into functions or how to I utilize different paradigums, etc.
This is why a basketball player, for instance, will shoot thousands of shots in practice or why a piano player will play a piece over and over for many hours. It's so they don't have to think about the low-level mechanics. It becomes muscle memory and it's just natural to them.
Okay I understand what you are saying now, but I believe that you are conflating two ideas here.
The first idea is about learning the concepts, and not just the specifics. There's a difference between memorizing a specific chemical reaction and understanding types of chemical reactions and using that to deduce what a specific chemical reaction would be given two substances. I would not call that intuition, however, as it's a matter of learning larger patterns, rules, or processes.
The second idea is about making things happen faster and less consciously. In essence, this is pattern recognition, but in practice it's a bit more complicated. Playing a piece over and over or shooting a basketball over and over is a rather unique process in that it involves muscle memory (or more accurately it involves specific areas of the brain devoted to motor cortex activation patterns working in sync with sensory systems such as proprioception). Knowing how to declare a variable or the order of operations, on the other hand, is pattern recognition within the context of a specific language or programming languages in general (as a reflection of currently circulating/used programming languages). I would consider both of these (muscle memory and pattern recognition) as aligned with the idea of intuition as you've defined it.
Rote learning is not necessary to understand concepts, but the amount of repetition needed to remember an idea after x period of time is going vary from person to person and how long after you expect someone to remember something. Pattern recognition and muscle memory, however, typically require a higher amount of repetition to sink in, but will also vary depending on person and time between learning and recall.
I get where you're coming from on most points and agree overall. However, you're not taking into consideration what secondary schooling looks like before students arrive.
I was told by multiple English teachers (including the head of the department) that I was a math student and should never attempt to write because I saw through the regurgitation assignments, didn't agree with teacher assessments of what Dickens "was trying to do" and had zero interest in confirming their biases.
I also didn't pursue page design and getting onto my high school paper because the only F I got there was from the advisor who was exceptionally clear that I was not welcome to attempt committing journalism after mocking up yearbook pages and being very unhappy with the results in Aldus PageMaker; there was no support system in place. (Also, our yearbook was shit on every level.)
That said, I can still write a ternary line of code where it makes sense sted an if-else block.
College coursework on the whole is a waste of time reinventing wheels. I don't need to spend a couple of weeks working up to "Hello, world!" in C and as such left CS as a major my first quarter at uni.
For the most part, I've been very lucky with teachers and professors. When I started taking college classes in high school and escaped the absurdity of recitation being "thinking for myself," I learned to love writing because my prof, a Catholic deacon, wanted thesis defense, not what he'd said in lecture. If I was 180 off of his viewpoint but could cite sources, that was an A.
But teachers do this shit every day, year after year, and we blindly say they're doing important work even as they discourage people from finding their path and voice, because god forbid a 16-year-old challenges someone in their 50s.
Right, what I was trying to say is that 10 itself is not a perfect square. You cannot take the square root of 10 and get an integer (ie. 1, 4, 9, 16, 25, etc.).
I was told by multiple English teachers (including the head of the department) that I was a math student and should never attempt to write because I saw through the regurgitation assignments, didn't agree with teacher assessments of what Dickens "was trying to do" and had zero interest in confirming their biases.
I think that is unfortunate and probably inappropriate. I try to avoid classifying students as particular types and generally try to encourage them whenever possible to pursue whatever their interests are (even if I disagree or don't have the same interest myself).
College coursework on the whole is a waste of time reinventing wheels. I don't need to spend a couple of weeks working up to "Hello, world!" in C and as such left CS as a major my first quarter at uni.
There is a reason for reinventing wheels; it is to understand why they are round and why they are so effective. To build the future, it helps to understand the past.
That said, perhaps the course was too slow for you, which is understandable... I frequently hear that about various classes (including ones I've taught).
But teachers do this shit every day, year after year, and we blindly say they're doing important work even as they discourage people from finding their path and voice, because god forbid a 16-year-old challenges someone in their 50s.
Again, I think you've had an unfortunate experience and I think it's a good thing to challenge your teachers. I certainly did when I was a student and I appreciate it now when students do that with me. I recognize that I am not perfect nor do I know everything. I make mistakes and can be wrong.
I wish you had a more supportive environment in secondary school and I have a better understanding of your perspective. Thanks for the dialogue.
If you had a supportive set of teachers, telling you that you can do anything, where's the challenge? I went back to my high school and dutifully waited for the department chair with a rehearsed, belittling speech. When Columbia says you're the best editorial writer in the country at the college level from literally the first one I wrote, teachers tend to not only back the fuck off but also to do this weird thing where they revise history and talk about the promise they saw in me.
I succeeded despite what I was told. It's possible that I was more inclined to fucking do it right. When I was doing the Aaron Sorkin thing and moving through the newsroom and telling my reporters that their girlfriends are irrelevant on election night, and indeed told one to get the fuck out, I saw the power of my role. This was 24 years ago, and we didn't have the phones we have today.
There are a lot of people who care deeply about others. Many of us go into journalism. We don't want anyone else to go through what we have. It's difficult, but one win is all one needs to feel like maybe we saved the next generation.
Sure, some people acquire the capability through repetition. But all that matters in the end is if you are capable or not.
I guess the question is how do you develop that capability if you are cheating or using a tool to do things for you? If I use GrubHub to order food or pay someone else to cook for me, does it make sense to say I can cook? After all, I am capable of acquiring cooked food even though I didn't actually do any of the work nor do I understand how to well, actually make food.
The how is relevant if you are trying to actually learn and develop skills, rather than simply getting something done.
No, the point is to get an irrelevant piece of paper that in the end doesn't actually indicate a persons capabilities.
Perhaps the piece of paper doesn't actually indicate a person's capabilities in part because enough students cheat to the point where getting a degree is meaningless. I do not object to that assessment.
Look, I'm not arguing that schooling is perfect. It's not. Far from it. All I am saying is that if your goal is to actually learn and grow in skill, development, and understanding, then there is no shortcut. You have to do the work.
I agree that the only way to get better is to do something over and over again. However, there is the more practical issue of there only being 24 hours in a day. I think students should be expected to work less over a longer period of time. I ground myself into dust in undergrad and I wish I just took an extra year of school. It was almost as bad in high school. I was waking up to go to school at 6:30 AM and then not finishing my homework until 10 PM or later.
I agree that the amount of work for many students can get quite out of hand and to be honest when I first started teaching, I was pretty guilty of having very work intensive courses.
That said, over the years, I've worked to streamline my courses to only have what I believe to be absolutely critical to learning and have added a lot of scaffolding and automated tests (for immediate results). In general, I try to have no busy work and make sure everything assignment is meaningful (as much as it can be anyway).
Additionally, because I understand that sometimes life happens, I have built-in facilities for automate extensions for assignments and even have a system for dropping certain homeworks.
This not to say that there isn't work in my classes... it's just that the work is intended to be relevant and reasonable, which most students seem to agree with these days.
I think students should be expected to work less over a longer period of time.
I think this would be a great idea. Or rather, I think it would be great to allow students to learn at different rates... some may want to go faster, some may want or need to go slower.
I think the modern course-based education system is often too rigid and not flexible enough to adequately accommodate the needs of students with different experience levels, resources, or constraints. Something like a Montessori model would be a lot better IMHO.
I'm an engineer. I use all of it. I use it whether I'm writing technically correct and accurate forensic reviews or doing math in my head (or on paper) to analyze a condition in real time or checking a complex finite element model to ensure that there are no improper assumptions or invalid boundary conditions. AI/ML is really useful for some things, and deadly for others.
Rote memorization may seem unnecessary, but a mental catalog - whether it be quotes, body parts and systems, equations of natural phenomena, or even manufactured parts and specifications - is the hallmark of someone who can work independently in a real time industry. It may not matter for some jobs, but it's make or break in others.