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Why fight against it? Because some of these students will be going into jobs that are life-or-death levels of importance and won't know how to do what they're hired to do.
There's nothing wrong with using a large language model to check your essay for errors and clumsy phrasing. There's a lot wrong with trying to make it do your homework for you. If you graduate with a degree indicating you know your field, and you don't actually know your field, you and everyone you work with are going to have a bad time.
It's almost like we shouldn't value the importance of just passing the exam/ writing the paper and revamp our entire approach to teaching
A theoretically correct but practically useless sentiment.
Yup. Although "avoid relying on writing and especially subjective long-form writing" is much more practicable.
Ditto. A license just means you can pass a test. It doesn’t say anything more than that. That’s why you’re always advised to get 2nd opinions.
This is what I have been hoping LLMs would provoke since the beginning.
Testing understanding via asking students to parrot textbooks with changed wording was always a shitty method, and one that de-incentivizes deep learning:
It allows for teachers that do not understand their field beyond a superficial level to teach, and to evaluate. What happens when a student given the test question "Give an intuitive description of an orbit in your own words" answers by describing orbital mechanics in a relative frame instead of a global frame, when the textbook only mentions global frame? They demonstrate understanding beyond the material which is excellent but all they do is risk being marked down by a teacher who can't see the connection.
A student who only memorized the words and has the ability to rearrange them a bit, gets full marks no risk.
Maybe we can get back to workplaces training their employees for the job they want them to do rather than putting the entire cost of training on 18 year oldish high school graduates for a job market that might not even be great (or exist) once they graduate post-secondary.
Realistically, any job that you hire someone with a degree for will require training - the question is how much they'll understand and at what level the training needs to start.
If ChatGPT can consistently do the needed activities without raising eyebrows, it's kind of a redundant job anyway. If they're posing problems that have little to do with the job, it's a shit course.
That's an odd thing to say. For one thing, there are plenty of physical activities that one could get a reasonable description of from ChatGPT, but if you can't actually do them or understand the steps, you're gonna have a bad time.
Example: I've never seen any evidence that ChatGPT can properly clean and sterilize beakers in an autoclave for a chemical engineering laboratory, even if it can describe the process. If you turned in homework cribbed from ChatGPT and don't actually know how to do it, your future lab partners aren't going to be happy that you passed your course by letting ChatGPT do all the work on paper.
There's also the issue that ChatGPT is frequently wrong. The whole point here is that these cheaters are getting caught because their papers have all the hallmarks of having been written by a large language model, and don't show any comprehension of the study material by the student.
And finally, if you're cheating to get a degree in a field you don't actually want to know anything about... Why?
Well then make the students clean and sterilise beakers. It only kills assignments in written form with limited supervision, the way I assume calculators and traditional algorithms changed a bunch of things before my time. Lots of professors and educators in general are making exactly that kind of change.
That means more lab time, it's true, but it's not the first time universities have had to expand their facilities. And at the other end think of all the savings on teaching writing.
It's kind of unrelated, but money and prestige, probably. Caring about knowing for it's own sake is depressingly rare.