Student perceptions of AI coding assistants in learning

> Automatic creation of an initial billboard: Upon starting the program, a predefined list of movies currently showing must be automatically generated, including their details (title, genre, duration, and showtimes).

I would say that these results might be relevant for a university CS program setting, but I would make the distinction between this and actually learning to program.

The context of this task is definitely a very contrived "Let's learn OOP" assignment that, for example, just tires to cram in class inheritance without really justifying it's use in the software that's being built. It's a lazy kind of curriculum building that doesn't actually tell the students about OOP.

In that sense it's no wonder that AI is not that helpful in the context of the assignment and learning.

I wouldn't chalk this up to "AI doesn't help you learn". I would put this in the category of, in an overly academic assignment with contrived goals, AI doesn't help the student accomplish the goals of the course. That conclusion could be equally applied to French literature 102.

And that's very different from whether or not an AI coding assistant can help you learn to code or not. (I'm actually not sure if it can, but I think this study doesn't say anything new).

The sad reality is that this is probably not a solvable problem. AI will improve more rapidly than the education system can adapt. Within a few years it won't make sense for people to learn how to write actual code, and it won't be clear until then which skills are actually useful to learn.

My recommendation would be to encourage students to ask the LLM to quiz and tutor them, but ultimately I think most students will learn a lot less than say 5 years ago while the top 5% or so will learn a lot more

This sounds like one of the "Ironies of Automation" as Lisain Bainbridge pointed out several years ago.

The more prevalent automation is, the worse humans do when that automation is taken away. This will be true for learning now .

Ultimately the education system is stuck in a bind. Companies want AI-native workers, students want to work with AI, parents want their kids to be employable. Even if the system wants to ensure that students are taught how to learn and not just a specific curriculum, their stakeholders have to be on board.

I think we're shifting to a world where not only will elite status markers like working at places like McKinsey and Google be more valuable but also interview processes will be significantly lengthened because companies will be doing assessments themselves and not trusting credentials from an education system that's suffering from great inflation and automation

I have access to so many videos and even video games that teach me exactly how to perform as a world class athlete.

If I don’t exercise, will I ever become one?

I am not a student and I wonder often whether we fill in memorization for the idea of learning, as though it’s somehow more valuable to be able to write valid syntax from memory on a blank file than it is to know and practice the broader strokes of abstractions, operators, readability and core concepts which make up good software craftsmanship.

Sometimes I’m doing something in a new to me language, using an LLM to give me a head start on structure and to ask questions about conventions and syntax, and wondering to myself how much I’m missing had I started just by reading the first half of a book on the language. I think I probably would take a lot longer to do anything useful, but I’d probably also have a deeper understanding of what I know and don’t know. But then, I can just as easily discover those fundamental concepts to a language via the right prompt. So am I learning? Am I somehow fooling myself? How?

Interesting to see quotes but note N=20 and the methodology doesn’t seem all that rigorous. I didn’t see anything that wasn’t exactly what you would expect to hear.

I wonder when will there be something more rigorous on what works clearing house https://ies.ed.gov/ncee/WWC/Search/Products?searchTerm=AI&&&...

I am actually hoping someone there studies such interventions the way they did with CMU's intelligent tutor — which if I recall correctly did not have net strong evidence in its favors as far as educational outcomes per the reports in WWC — given the fall in grade level scores in math and reading since 2015/16 across multiple grades in middle school. It is vital to know if any of these things help kids succeed.

Crazy idea but: what if we built an AI pair programmer that actually pair programmed? That is, sometimes it was the driver and you navigated, pretty much as it is today, but sometimes you drive and it navigates.

I surmise that would help people learn to code better.

Knowledge not earned is not gained.

It is notable that so many publications try to salvage "AI" ("need for new pedagogical approaches that integrate AI effectively") rather than ditch "AI" completely.

The world worked perfectly before 2023, there is no need to outsource information retrieval or thinking.

> Our findings reveal that students perceived AI tools as helpful for grasping code concepts and boosting their confidence during the initial development phase. However, a noticeable difficulty emerged when students were asked to work unaided, pointing to potential overreliance and gaps in foundational knowledge transfer.

This is basically what would be expected. However n=20 is too small. This needs to be replicated with x10 the n.

> Our findings reveal that students perceived AI tools as helpful for grasping code concepts and boosting their confidence during the initial development phase. However, a noticeable difficulty emerged when students were asked to work un-aided, pointing to potential over reliance and gaps in foundational knowledge transfer.

As someone studying CS/ML this is dead on but I don't think the side-effects of this are discussed enough. Frankly, cheating has never been more incentivized and it's breaking the higher education system (at least that's my experience, things might be different at the top tier schools).

Just about every STEM class I've taken has had some kind of curve. Sometimes individual assignments are curved, sometimes the final grade, sometimes the curve isn't a curve but some sort of extra credit. Ideally it should be feasible to score 100% in a class but I think this actually takes a shocking amount of resources. In reality, professors have research or jobs to attend to and same with the students. Ideally there are sections and office hours and the professor is deeply conscious of giving out assignments that faithfully represent what students might be tested on. But often this isn't the case. The school can only afford two hours of TA time a week, the professors have obligations to research and work, the students have the same. And so historically the curve has been there to make up for the discrepancy between ideals and reality. It's there to make sure that great students get the grades that they deserve.

LLMs have turned the curve on its head.

When cheating was hard the curve was largely successful. The great students got great grades, the good students got good grades, those that were struggling usually managed a C+/B-, and those that were checked out or not putting in the time failed. The folks who cheated tended to be the struggling students but, because cheating wasn't that effective, maybe they went from a failing grade to just passing the class. A classic example is sneaking identities into a calculus test. Sure it helps if you don't know the identities but not knowing the identities is a great sign that you didn't practice enough. Without that practice they still tend to do poorly on the test.

But now cheating is easy and, I think it should change the way we look at grades. This semester, not one of my classes is curved because there is always someone who gets a 100%. Coincidentally, that person is never who you would expect. The students who attend every class, ask questions, go to office hours, and do their assignments without LLMs tend to score in B+/A- range on tests and quizzes. The folks who set the curve on those assignments tend to only show up for tests and quizzes and then sit in the far back corners when they do. Just about every test I take now, there's a mad competition for those back desks. Some classes people just dispense with the desk and take a chair to the back of the room.

Every one of the great students I know is murdering themselves to try to stay in the B+/A- range.

A common refrain when people talk about this is "cheaters only cheat themselves" and while I think has historically been mostly true, I think it's bullshit now. Cheating is just too easy, the folks who care are losing the arms race. My most impressive peers are struggling to get past the first round of interviews. Meanwhile, the folks who don't show up to class and casually get perfect scores are also getting perfect scores on the online assessments. Almost all the competent people I know are getting squeezed out of the pipeline before they can compete on level-footing.

We've created a system that massively incentivizes cheating and then invented the ultimate cheating tool. A 4.0 and a good score on an online assessment used to be a great signal that someone was competent. I think these next few years, until universities and hiring teams adapt to LLMs, we're going to start seeing perfect scores as a red flag.