College professors are going back to paper exams and handwritten essays to fight students using ChatGPT
College professors are going back to paper exams and handwritten essays to fight students using ChatGPT
The growing number of students using the AI program ChatGPT as a shortcut in their coursework has led some college professors to reconsider their lesson plans for the upcoming fall semester.
College professors are going back to paper exams and handwritten essays to fight students using ChatGPT::The growing number of students using the AI program ChatGPT as a shortcut in their coursework has led some college professors to reconsider their lesson plans for the upcoming fall semester.
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Prof here - take a look at it from our side.
Our job is to evaluate YOUR ability; and AI is a great way to mask poor ability. We have no way to determine if you did the work, or if an AI did, and if called into a court to certify your expertise we could not do so beyond a reasonable doubt.
I am not arguing exams are perfect mind, but I'd rather doubt a few student's inability (maybe it was just a bad exam for them) than always doubt their ability (is any of this their own work).
Case in point, ALL students on my course with low (<60%) attendance this year scored 70s and 80s on the coursework and 10s and 20s in the OPEN BOOK exam. I doubt those 70s and 80s are real reflections of the ability of the students, but do suggest they can obfuscate AI work well.
Here's a somewhat tangential counter, which I think some of the other replies are trying to touch on ... why, exactly, continue valuing our ability to do something a computer can so easily do for us (to some extent obviously)?
In a world where something like AI can come up and change the landscape in a matter of a year or two ... how much value is left in the idea of assessing people's value through exams (and to be clear, I'm saying this as someone who's done very well in exams in the past)?
This isn't to say that knowing things is bad or making sure people meet standards is bad etc. But rather, to question whether exams are fit for purpose as means of measuring what matters in a world where what's relevant, valuable or even accurate can change pretty quickly compared to the timelines of ones life or education. Not long ago we were told that we won't have calculators with us everywhere, and now we could have calculators embedded in our ears if wanted to. Analogously, learning and examination is probably being premised on the notion that we won't be able to look things up all the time ... when, as current AI, amongst other things, suggests, that won't be true either.
An exam assessment structure naturally leans toward memorisation and being drilled in a relatively narrow band of problem solving techniques,1 which are, IME, often crammed prior to the exam and often forgotten quite severely pretty soon afterward. So even presuming that things that students know during the exam are valuable, it is questionable whether the measurement of value provided by the exam is actually valuable. And once the value of that information is brought into question ... you have to ask ... what are we doing here?
Which isn't to say that there's no value created in doing coursework and cramming for exams. Instead, given that a computer can now so easily augment our ability to do this assessment, you have to ask what education is for and whether it can become something better than what it is given what are supposed to be the generally lofty goals of education.
In reality, I suspect (as many others do) that the core value of the assessment system is to simply provide a filter. It's not so much what you're being assessed on as much as your ability to pass the assessment that matters, in order to filter for a base level of ability for whatever professional activity the degree will lead to. Maybe there are better ways of doing this that aren't so masked by other somewhat disingenuous goals?
Beyond that there's a raft of things the education system could emphasise more than exam based assessment. Long form problem solving and learning. Understanding things or concepts as deeply as possible and creatively exploring the problem space and its applications. Actually learn the actual scientific method in practice. Core and deep concepts, both in theory and application, rather than specific facts. Breadth over depth, in general. Actual civics and knowledge required to be a functioning member of the electorate.
All of which are hard to assess, of course, which is really the main point of pushing back against your comment ... maybe we're approaching the point where the cost-benefit equation for practicable assessment is being tipped.
- In my experience, the best means of preparing for exams, as is universally advised, is to take previous or practice exams ... which I think tells you pretty clearly what kind of task an exam actually is ... a practiced routine in something that narrowly ranges between regurgitation and pretty short-form, practiced and shallow problem solving.
Ah the calculator fallacy; hello my old friend.
So, a calculator is a great shortcut, but it's useless for most mathematics (i.e. proof!). A lot of people assume that having a calculator means they do not need to learn mathematics - a lot of people are dead wrong!
In terms of exams being about memory, I run mine open book (i.e. students can take pre-prepped notes in). Did you know, some students still cram and forget right after the exams? Do you know, they forget even faster for courseworks?
Your argument is a good one, but let's take it further - let's rebuild education towards an employer centric training system, focusing on the use of digital tools alone. It works well, productivity skyrockets, for a few years, but the humanities die out, pure mathematics (which helped create AI) dies off, so does theoretical physics/chemistry/biology. Suddenly, innovation slows down, and you end up with stagnation.
Rather than moving us forward, such a system would lock us into place and likely create out of date workers.
At the end of the day, AI is a great tool, but so is a hammer and (like AI today), it was a good tool for solving many of the problems of its time. However, I wouldn't want to only learn how to use a hammer, otherwise how would I be replying to you right now?!?
So ... I honestly think this is a problematic reply ... I think you're being defensive (and consequently maybe illogical), and, honestly, that would be the red flag I'd look for to indicate that there's something rotten in academia. Otherwise, there might be a bit of a disconnect here ... thoughts:
- The
calculatorwas in reference to arithmetic and other basic operations and calculations using them ... not higher level (or actual) mathematics. I think that was pretty clear and I don't think there's any "fallacy" here, like at all. - The
value of learning (actual) mathematicsis pretty obvious I'd say ... and was pretty much stated in my post about alternatives to emphasise. On which, getting back to my essential point ... how would one best learn and be assessed on their ability to construct proofs in mathematics? Are timed open book exams (and studying in preparation for them) really the best we've got!? Still forgetting with open book exams... seems like an obvious outcome as the in-exam materials de-emphasise memory ... they probably never knew the things you claim they forget in the first place. Why, because the exam only requires the students to be able to regurgitate in the exam, which is the essential problem, and for which in-exam materials are a perfect assistant. Really not sure what the relevance of this point is.Forgetting after coursework... how do you know this (genuinely curious)? Even so, course work isn't the great opposite to exams. Under the time crunch of university, they are also often crammed, just not in an examination hall. The alternative forms of education/assessment I'm talking about are much more long-form and exploration and depth focused. The most I've ever remembered from a single semester subject came from when I was allowed to pursue a single project for the whole subject. Also, I didn't mention ordinary general coursework in my post, as, again, it's pretty much the same paradigm of education as exams, just done at home for the most part.Rebuilding education toward employer centric training system... I ... ummm ... never suggested this ... I suggested the opposite ... only things that were far more "academic" than this and were never geared toward "productivity". This is a pretty bad staw man argument for a professor to be making, especially given that it seems constructed to conclude that the academy and higher learning are essential for the future success of the economy (which I don't disagree with or even question in my post).- You speak about AI a lot. Maybe your whole reply was solely to the whole calculator point I made. This, I think, misses the broader point, which most of my post was dedicated to. That is, this isn't about us now needing to use AI in education (I personally don't buy that at all for probably much of the same reason you'd push back on it). Instead, it's about what it means about our education system that AI can kinda do the thing we're using to assess ourselves ... on which I say, it tells us that the value of assessment system we take pretty seriously ought to be questioned, especially, as I think we both agree on, given the many incredibly valuable things education has to offer the individual and society at large. In my case, I go further and say that the assessment system is and has already detracted from these potential offerings, and that it does not bode well for modern western society that it seems to be leaning into the assessment system rather than expanding its scope.
OK Mr Socrates how else would you assess whether a student has learned something?
Ha ... well if I had answers I probably wouldn't be here! But seriously, I do think this is a tough topic with lots of tangled threads linked to how our society functions. I'm not sure there are any easy "fixes", I don't think anyone who thinks that can really be trusted, and it may very well turn out that I'm completely wrong and there is not "better way", as something flawed and problematic may just turn out to be what humanity needs.
A pretty minor example based on the whole thing of returning to paper exams. What happens when you start forcing students to be judged on their ability to do something, alone, where they know very well that they can do better with an AI assistant? Like at a psychological and cultural level? I don't know, I'm not sure my generation (Xennial) or earlier ever had that. Even with calculators and arithmetic, it was always about laziness or dealing with big numbers that were impossible for (normal humans), or ensuring accuracy. It may not be the case that AI is at that level yet for many exams and students (I really don't know), but it might be or might be soon. However valuable it is to force students to learn to do the task without the AI, there's gotta be some broad cultural effect in just ignoring the super useful machine.
Otherwise, my general ideas would be to emphasise longer form work (which AI is not terribly useful for). Work that requires creativity, thinking, planning, coherent understanding, human-to-human communication and collaboration. So research projects, actual practical work, debates, teaching as a form of assessment etc. In many ways, the idea of "having learned something" becomes just a baseline expectation. Exams, for instance, may still hold lots of value, but not as forms of objective assessment, but as a way of calibrating where you're up to on the basic requirements to start the real "assessment" and what you still need to work on.
Also ...
OK Mr Socrates... is maybe not the most polite way of engaging here ... comes off as somewhat aggressive TBH.
- The
let’s rebuild education towards an employer centric training system, focusing on the use of digital tools alone. It works well, productivity skyrockets, for a few years, but the humanities die out, pure mathematics (which helped create AI) dies off, so does theoretical physics/chemistry/biology. Suddenly, innovation slows down, and you end up with stagnation.
Rather than moving us forward, such a system would lock us into place and likely create out of date workers.
I found this too generalizing. Yes, most people only ever need and use productivity skills in their worklife. They do no fundamental research. Wether their education was this or that way has no effect on the advancement of science in general, because these people don't do science in their career.
Different people with different goals will do science, and for them an appropriate education makes sense. It also makes sense to have everything in between.
I don't see how it helps the humanities and other sciences to teach skills which are never used. Or how it helps to teach a practice which no one applies in practice. How is it a threat to education when someone uses a new tool intelligently, so they can pass academic education exams? How does that make them any less valuable for working in that field? Assuming the exam reflects what working in that field actually requires.
I think we can also spin an argument in the opposite direction: More automation in education frees the students to explore side ideas, to actually study the field.
"I don’t see how it helps the humanities and other sciences to teach skills which are never used." - I can offer an unusual counter here, you're assuming the knowledge will never be used, or that we should avoid teaching things that are unlikely to be used. Were this the case, the field of graph theory would have ceased to exist long before it became useful in mapping - indeed Bool's algebra would never have led to the foundations of computer science and the machines we are using today.
"How is it a threat to education when someone uses a new tool intelligently, so they can pass academic education exams?" - Allow me to offer you the choice of two doctors, one of whome passed using AI, and the other passed a more traditional assessment. Which doctor would you choose and why? Surely the latter, since they would have also passed with AI, but the one without AI might not have passed the more traditional route due to a lack of knowledge. It isn't a threat to education, it's adding further uncertainty as to the outcome of such an education (both doctors might have the same skill levels, but there is more room for doubt in the first case).
"Wether their education was this or that way has no effect on the advancement of science in general, because these people don’t do science in their career." - I strongly disagree! In an environment where knowledge for the sake of knowledge is not prised, a lie is more easy plant and nurture (take for example the antivax movement). Such people can be an active hinderence to the progress of knowledge - their misconceptions creating false leads and creating an environment that distrusts such sciences (we're predisposed to distrust what we do not understand).
you’re assuming the knowledge will never be used, or that we should avoid teaching things that are unlikely to be used.
Not exactly. What I meant to say is: Some students will never use some of the knowledge they were taught. In the age of information explosion, there is practically unlimited knowledge 'available'. What part of this knowledge should be taught to students? For each bit of knowledge, we can make your hypothetic argument: It might become useful in the future, an entire important branch of science might be built on top of it.
So this on it's own is not an argument. We need to argue why this particular skill or knowledge deserves the attention and focus to be studied. There is not enough time to teach everything. Which in turn can be used as an argument to more computer assisted learning and teaching. For example, I found ChatGPT useful to explore topics. I would not have used it to cheat in exams, but probably to prepare for them.
the choice of two doctors, one of whome passed using AI, and the other passed a more traditional assessment. Which doctor would you choose and why? Surely the latter, since they would have also passed with AI, but the one without AI might not have passed the more traditional route due to a lack of knowledge.
Good point, but it depends on context. You assume the traditional doc would have passed with AI, but that is questionable. These are complex tools with often counterintuitive behaviour. They need to be studied and approached critically to be used well. For example, the traditional doc might not have spotted the AI hallucinating, because she wasn't aware of that possibility.
Further, it depends on their work environment. Do they treat patients with, or without AI? If the doc is integrated in a team of both human and artificial colleagues, I certainly would prefer the doc who practiced these working conditions, who proved in exams they can deliver the expected results this way.
In an environment where knowledge for the sake of knowledge is not prised
I feel we left these lands in Europe when diplomas were abandoned for the bachelor/master system, 20 years ago. Academic education is streamlined, tailored to the needs of the industry. You can take a scientific route, but most students don't. The academica which you describe as if it was threatened by something new might exist, but it lives along a more functional academia where people learn things to apply them in our current reality.
It's quite a hot take to paint things like the antivax movement on academic education. For example, I question wether the people proposing and falling for these 'ideas' are academics in the first place.
Personally, I like learning knowledge for the sake of knowledge. But I need time and freedom to do so. When I was studying computer science with an overloaded schedule, my interest in toying with ideas and diving into backgrounds was extremely limited. I also was expected to finish in an unreasonably short amount of time. If I could have sped up some of the more tedious parts of the studies with the help of AI, this could have freed up resources and interest for the sake of knowledge.
I think a central point you're overlooking is that we have to be able to assess people along the way. Once you get to a certain point in your education you should be able to solve problems that an AI can't. However, before you get there, we need some way to assess you in solving problems that an AI currently can. That doesn't mean that what you are assessed on is obsolete. We are testing to see if you have acquired the prerequisites for learning to do the things an AI can't do.
- AI isn’t as important to this conversation as I seem to have implied. The issue is us, ie humans, and what value we can and should seek from our education. What AI can or can’t do, IMO, only affects vocational aspects in terms of what sorts of things people are going to do “on the job”, and, the broad point I was making in the previous post, which is that AI being able to do well at something we use for assessment is an opportunity or prompt to reassess the value of that form of assessment.
- Whether AI can do something or not, I call into question the value of exams as a form of assessment, not assessment itself. There are plenty of other things that could be used for assessment or grading someone’s understanding and achievement.
- The real bottom line on this is cost and that we’re a metric driven society. Exams are cheap to run and provide clean numbers. Any more substantial form of assessment, however much they better target more valuable skills or understanding, would be harder to run. But again, I call into question how valuable all of what we’re doing actually is compared to what we could be doing, however more expensive and whether we should really try to focus more on what we humans are good at (and even enjoy).
Here's a somewhat tangential counter, which I think some of the other replies are trying to touch on ... why, exactly, continue valuing our ability to do something a computer can so easily do for us (to some extent obviously)?
My theory prof said there would be paper exams next year. Because it's theory. You need to be able to read an academic paper and know what theoretical basis the authors had for their hypothesis. I'm in liberal arts/humanities. Yes we still exist, and we are the ones that AI can't replace. If the whole idea is that it pulls from information that's already available, and a researcher's job is to develop new theories and ideas and do survey or interview research, then we need humans for that. If I'm trying to become a professor/researcher, using AI to write my theory papers is not doing me or my future students any favors. Ststistical research on the other hand, they already use programs for that and use existing data, so idk. But even then, any AI statistical analysis should be testing a new hypothesis that humans came up with, or a new angle on an existing one.
So idk how this would affect engineering or tech majors. But for students trying to be psychologists, anthropologists, social workers, professors, then using it for written exams just isn't going to do them any favors.
I also used to be a humanities person. The exam based assessments were IMO the worst. All the subjects assessed without any exams were by far the best. This was before AI BTW.
If you’re studying theoretical humanities type stuff, why can’t your subjects be assessed without exams? That is, by longer form research projects or essays?
As they are talking about writing essays, I would argue the importance of being able to do it lies in being able to analyze a book/article/whatever, make an argument, and defend it. Being able to read and think critically about the subject would also be very important.
Sure, rote memorization isn't great, but neither is having to look something up every single time you ever need it because you forgot. There are also many industries in which people do need a large information base as close recall. Learning to do that much later in life sounds very difficult. I'm not saying people should memorize everything, but not having very many facts about that world around you at basic recall doesn't sound good either.
Learning to do that much later in life sounds very difficult
That's an interesting point I probably take for granted.
Nonetheless, exercising memory is probably something that could be done in a more direct fashion, and therefore probably better, without that concern affecting the way we approach all other forms of education.
It's an interesting point.. I do agree memorisation is (and always has been) used as more of a substitute for actual skills. It's always been a bugbear of mine that people aren't taught to problem solve, just regurgitate facts, when facts are literally at our fingertips 24/7.
Yea, it isn’t even a new problem. The exam was questionable before AI.
In my experience, the best means of preparing for exams, as is universally advised, is to take previous or practice exams … which I think tells you pretty clearly what kind of task an exam actually is … a practiced routine in something that narrowly ranges between regurgitation and pretty short-form, practiced and shallow problem solving.
You are getting some flak, but imho you are right. The only thing an exam really tests is how well you do in exams. Of course, educators dont want to hear that. But if you take a deep dive into (scientific) literature on the topic, the question "What are we actually measuring here?" is raised rightfully so.
Getting flak on social media, through downvotes, can often (though not always!) be a good thing ... means you're touching a nerve or something.
On this point, I don't think I've got any particularly valuable or novel insights, or even any good solutions ... I'm mostly looking for a decent conversation around this issue. Unfortunately, I suspect, when you get everyone to work hard on something and give them prestigious certifications for succeeding at that something, and then do this for generations, it can be pretty hard to convince people to not assign some of their self-worth to the quality/value/meaning of that something and to then dismiss it as less valuable than previously thought. Possibly a factor in this conversation, which I say with empathy.
Any links to some literature?
Used only papers in german so far, sadly.
Here is something I found interesting in english:
Testing the test: Are exams measuring understanding? Brian K. Sato, Cynthia F. C. Hill, S. Lo Biochemistry and Molecular Biology Education
in general: elicit.org
really good site.
Hadn't heard of that
elicitcite ... thanks! How have you found it? It makes sense that it exists already, but I hadn't really thought about it (haven't looked up papers recently but may soon).Also thanks for the paper!!
Have found it relatively early after it was created, using it for getting a quick overview over papers when writing my own. It is sooo good for that.
Yea cool. Thanks for this!
In my experience, they love to give exams where it doesn't matter what notes you bring, you're on the same level whether you write down only the essential equations, or you copy down the whole textbook.
Sorry but it was never about OUR abilility in the firts place.
In my country exams are old, outdated and often way to hard. In my country all classes are outdated and way to hard. It often feels that we are stucked in the middle of the 20th century.
You have no change when you have a disability. When you have kids, parents to take care of. Or hell: you have to work, cause you can't effort university otherwise.
So i can totaly understand why students feel the need to use AI to survive that torture. I don't feel sorry for an outdated university system.
When it is about OUR abilility, then create a System that is for students and their needs.
Is AI going to go away?
In the real world, will those students be working from a textbook, or from a browser with some form of AI accessible in a few years?
What exactly is being measured and evaluated? Or has the world changed, and existing infrastructure is struggling to cling to the status quo?
Were those years of students being forced to learn cursive in the age of the computer a useful application of their time? Or math classes where a calculator wasn't allowed?
I can hardly think just how useful a programming class where you need to write it on a blank page of paper with a pen and no linters might be, then.
Maybe the focus on where and how knowledge is applied needs to be revisited in light of a changing landscape.
For example, how much more practically useful might test questions be that provide a hallucinated wrong answer from ChatGPT and then task the students to identify what was wrong? Or provide them a cross discipline question that expects ChatGPT usage yet would remain challenging because of the scope or nuance?
I get that it's difficult to adjust to something that's changed everything in the field within months.
But it's quite likely a fair bit of how education has been done for the past 20 years in the digital age (itself a gradual transition to the Internet existing) needs major reworking to adapt to changes rather than simply oppose them, putting academia in a bubble further and further detached from real world feasibility.
If you're going to take a class to learn how to do X, but never actually learn how to do X because you're letting a machine do all the work, why even take the class?
In the real world, even if you're using all the newest, cutting edge stuff, you still need to understand the concepts behind what you're doing. You still have to know what to put into the tool and that what you get out is something that works.
If the tool, AI, whatever, is smart enough to accomplish the task without you actually knowing anything, what the hell are you useful for?
But that's actually most of the works we have nowadays. IA is replacing repetitive works such as magazine writers or script writers
Writers are repetitive work????
Well, it seems they will be replaced, at least certain writers. https://www.npr.org/2023/05/20/1177366800/striking-movie-and-tv-writers-worry-that-they-will-be-replaced-by-ai Also, callcenters https://www.bbc.com/news/business-65906521 And junior programmers. The problem here it's not my opinion, those already happen so its not debatable.
And junior programmers
...no. Juniors are hard enough to mentor to write sensible code in the first place adding AI to that is only making things worse.
The long-term impacts on AI past what's already happening (and having an actual positive impact on the products and companies, that is, discount that Hollywood scriptwriting stuff) will be in industrial automation and logistics/transportation. Production lines that can QC on their own as well as a whole army of truck and taxi drivers. AI systems will augment fields such as medicine, but not replace actual doctors. Think providing alternative diagnosis possibilities and recommending suitable tests to be sure kind of stuff, combatting routine tunnel vision by, precisely, being less adaptive than human doctors.
I understand that they'll be replaced, or at least the producers want thant, but I don't think that's because of repetitive work, more like they need a lot of them.
As an anecdotal though, I once saw someone simply forwarding (ie. copy and pasting) their exam questions to ChatGPT. His answers are just ChatGPT responses, but paraphrased to make it look less GPT-ish. I am not even sure whether he understood the question itself.
In this case, the only skill that is tested... is English paraphrasing.
I'll field this because it does raise some good points:
It all boils down to how much you trust what is essentially matrix multiplication, trained on the internet, with some very arbitrarily chosen initial conditions. Early on when AI started cropping up in the news, I tested the validity of answers given:
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For topics aimed at 10--18 year olds, it does pretty well. It's answers are generic, and it makes mistakes every now and then.
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For 1st--3rd year degree, it really starts to make dangerous errors, but it's a good tool to summarise materials from textbooks.
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Masters+, it spews (very convincing) bollocks most of the time.
Recognising the mistakes in (1) requires checking it against the course notes, something most students manage. Recognising the mistakes in (2) is often something a stronger student can manage, but not a weaker one. As for (3), you are going to need to be an expert to recognise the mistakes (it literally misinterpreted my own work at me at one point).
The irony is, education in its current format is already working with AI, it's teaching people how to correct the errors given. Theming assessment around an AI is a great idea, until you have to create one (the very fact it is moving fast means that everything you teach about it ends up out of date by the time a student needs it for work).
However, I do agree that education as a whole needs overhauling. How to do this: maybe fund it a bit better so we're able to hire folks to help develop better courses - at the moment every "great course" you've ever taken was paid for in blood (i.e. 50 hour weeks teaching/marking/prepping/meeting arbitrary research requirement).
On the other hand, what if the problem is simply one that's no longer important for most people? Isn't technological advancement supposed to introduce abstraction that people can develop on?
The point is the students can't get to the higher level concepts if they're just regurgitating from what chatgpt says.
If you never learn how to do the basics without ChatGPT, it's a big jump to figure out the advanced topics where ChatGPT no longer helps you
(1) seems to be a legitimate problem. (2) is just filtering the stronger students from the weaker ones with extra steps. (3) isn't an issue unless a professor teaching graduate classes can't tell BS from truth in their own field. If that's the case, I'd call the professor's lack of knowledge a larger issue than the student's.
You may not know this, but "Masters" is about uncovering knowledge nobody had before, not even the professor. That's where peer reviews and shit like LK-99 happen.
It really isn't. You don't start doing properly original research until a year or two into a PhD. At best a masters project is going to be doing something like taking an existing model and applying it to an adjacent topic to the one it was designed for.
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Case in point, ALL students on my course with low (<60%) attendance this year scored 70s and 80s on the coursework and 10s and 20s in the OPEN BOOK exam. I doubt those 70s and 80s are real reflections of the ability of the students
I get that this is a quick post on social media and only an antidote, but that is interesting. What do you think the connection is? AI, anxiety, or something else?
That sounds like AI. If you do your homework then even sitting in a regular exam you should score better than 20%. This exam being open book, it sounds like they were unfamiliar with the textbook and could not find answers fast enough.
It's a tough one because I cannot say with 100% certainty that AI is the issue. Anxiety is definitely a possibility in some cases, but not all; perhaps thinking time might be a factor, or even just good old copying and then running the work through a paraphraser. The large amount of absenses also means it was hard to benchmark those students based on class assessment (yes, we are always tracking how you are doing in class, not tp judge you, but just in case you need some extra help!).
However, AI is a strong contender since the "open book" part didn't include the textbook, it allowed the students to take a booklet into the exams with their own notes (including fully worked examples). They scored low because they didn't understand their own notes, and after reviewing the notes they brought in (all word perfect), it was clear they did not understand the subject.
Oh an open notes test. Man i never use my notes on those. I try not to use the book on open tests.
Curious to know your take on why you avoid using the notes - a couple of my students clearly did this in the final and insights onto why would be welcome!
its hard to read my own hand writing. So I would just remember most of the stuff
Not the previous poster. I taught an introduction to programming unit for a few semesters. The unit was almost entirely portfolio based ie all done in class or at home.
The unit had two litmus tests under exam like conditions, on paper in class. We're talking the week 10 test had complexity equal to week 5 or 6. Approximately 15-20% of the cohort failed this test, which if they were up to date with class work effectively proved they cheated. They'd be submitting course work of little 2d games then on paper be unable to "with a loop, print all the odd numbers from 1 to 20"
Graduated a year ago, just before this AI craze was a thing.
I feel there's a social shift when it comes to education these days. It's mostly: "do 500 - 1,000 word essay to get 1.5% of your grade". The education doesn't matter anymore, the grades do; if you pick something up along the way, great! But it isn't that much of a priority.
I think it partially comes from colleges squeezing students of their funds, and indifferent professors who just assign busywork for the sake of it. There are a lot of uncaring professors that just throw tons of work at students, turning them back to the textbook whenever they ask questions.
However, I don't doubt a good chunk of students use AI on their work to just get it out of the way. That really sucks and I feel bad for the professors that actually care and put effort into their classes. But, I also feel the majority does it in response to the monotonous grind that a lot of other professors give them.
We have no way to determine if you did the work, or if an AI did, and if called into a court to certify your expertise we could not do so beyond a reasonable doubt.
Could you ever though, when giving them work they had to do not in your physical presence? People had their friends, parents or ghostwriters do the work for them all the time. You should know that.
This is not an AI problem, AI "just" made it far more widespread and easier to access.
"Sometimes" would be my answer. I caught students who colluded during online exams, and even managed to spot students pasting directly from an online search. Those were painful conversations, but I offered them resits and they were all honest and passed with some extra classes.
With AI, detection is impossible at the moment.
I recently finished my degree, and exam-heavy courses were the bane of my existence. I could sit down with the homework, work out every problem completely with everything documented, and then sit to an exam and suddenly it's "what's a fluid? What's energy? Is this a pencil?"
The worst example was a course with three exams worth 30% of the grade, attendance 5% and homework 5%. I had to take the course twice; 100% on HW each time, but barely scraped by with a 70.4% after exams on the second attempt. Courses like that took years off my life in stress. :(
If you don't mind me asking - what kind of degree was it, and what format were the exams?
Student here - How does that cursive longhand thing go again?
"Avoid at all costs because we hate marking it even more than you hate writing it"?
An in person exam can be done in a locked down IT lab, and this leads to a better marking experience, and I suspect a better exam experience!