> a Junior (in ANY subject) has the ability to LEARN so much faster with an AI research assistant
I’m not seeing this. And based on what we’re seeing at the university level, I’m not expecting to.
I’m not seeing this. And based on what we’re seeing at the university level, I’m not expecting to.
(The preliminary research so far supports this: using AI to do the hard assignments produces poor learning outcomes, but using AI as a tutor, or even just for help with the hard assignments, produces slightly better learning outcomes.)
I think what you're seeing is the effect of the incentives of the system. The system uses simplistic numbers like grades as proxies for actual learning, and these grades heavily influence students' job prospects, and so you're simply seeing Goodhart's Law in action. Given how easy current methods of skill assessment are to game with AI, my guess is the entire system has to be overhauled.
Source? The few people I’ve seen try to do this wind up with a terrible understanding of the material, with large knowledge gaps and one or two fundamental fuckups. In every case, an introductory textbook would have been better. (It would also have been harder.)
https://www.mdpi.com/2076-3417/14/10/4115 -- probably the earliest one of its kind, finds over-reliance degrades critical skills but supplementary use is mostly harmless.
https://arxiv.org/html/2601.20245v2 -- Anthropic's study, same as above except supplementary use (like clarifying concepts) can actually be beneficial.
https://scale.stanford.edu/ai/repository/ai-meets-classroom-... -- "Students who use LLMs as personal tutors by conversing about the topic and asking for explanations benefit from usage. However, learning is impaired for students who excessively rely on LLMs to solve practice exercises for them and thus do not invest sufficient own mental effort." Interestingly, they found simply disabling copy-paste on the chatbot interface resulted in better outcomes!
Beyond coding, I recently came across this new meta-study; largely positive findings (which it admits may be biased) but does highlight evidence of negative effects of over-reliance: https://www.sciencedirect.com/science/article/pii/S2666920X2...
(Multiple studies find that the outcome depends on how AI is used. Surprisingly, incorrect guidance / unreliability / hallucinations appear to be a bigger problem than over-reliance! That could also explain poor performance in some cases.)
My intuition, supported by these studies, is that as long as students are willing to do the hard cognitive work -- for which there is no substitute, really -- having LLM assistance is a boon. Which makes sense, it's comparable to having a tutor explain difficult concepts. This is why in my mind the real problem is that the incentives to use AI as a crutch are just too strong.
Are you a researcher in the pedagogical sciences? Regardless, you have to admit that the original claim has very little evidence behind it despite being testable. And also the caveat you tag onto the end is a pretty massive caveat, and from the sources you provided it seems that students which use in the way which you claim has been shown to be effective, that those students are in a minority anyway.
The analogy is unlimited typing in Gmail won’t make you a better writer or typesetter on its own.
I've seen this work well at a job when there's a feedback loop for juniors that incentivized them to learn with more scope and compensation