Posted by pseudolus 1 day ago
All to say—I wish it was this easy to change the academy. But it's not.
STEM subjects are particularly hard to create good lectures for. And STEM expertise and speaking/communication skills don't always overlap either.
The non-STEM classes I learned the most in are the ones I learned the most in lecture in. The STEM classes, on the other hand, were pretty scattershot without as much correlation.
An LLM-based toolset could likely be much better than that and at least as good as bad lectures, but the guardrails are gonna need to be really really really good.
Mainly due to shortage of very good lecturers, no? I can not see a better way to cultivate the professional pride than to attend lectures of truly remarkable professors. The style, the manner, the attitude go much beyond the dry proofs. I'm an applied math major.
Does lecturing have a place in disseminating ideas? Sure. I love that scene from Oppenheimer when he attends Heisenberg's lecture, being exposed to cutting edge ideas directly from the mouth of a truly remarkable professor. Watching that gave me a better appreciation of lecturing's original purpose and historical importance. But that's very different from teaching well-understood concepts and skills.
It was subtle, but easy enough to pick up on if you were being attentive in class..
Sorry, but I must disagree. There is much more to learning process than just the material itself. We are social animals, so the emotional aspect matters to the majority of us. Highly technical fields are not an exception. The attitude of the lecturer and his reaction to the questions from the audience, sidetrack discussions -- it all counts. At least to me and the people I have known.
At the same time, lectures of those with no charisma is a real torture, no doubt about that.
It did, however, absolutely require everyone to prepare for every class. Some people complained a lot about this, which might be why this was not as popular as more common lectures.
There is a tension between: - authentic assessments (not multiple choice/ - grading resources - computer lab availability - students using AI in very discreet ways on their own laptop when taking an in-person exam
So overall you are on point, it's just really hard to do honest authentic assessment at scale right now (in person or otherwise).
I see a potential for it to get much better, or much worse... Hard to tell which way it will go right now.
Mandate N hours year of and guided group work for under 18s
Mandate N hours for becoming an SME for roles that require such
Break the pipeline from the factory era of linearly pumping out kids who are just smart enough to run the machines
Just because an idea is different doesn't mean it's good
Is that really the case though? It seems like quite a lot of cases get hushed up and swept under the rug.
1% are the absolutely brilliant minds that academia was originally created for. People that, without a doubt, leave their mark in the vast corpus of human knowledge. I consider myself fortunate for meeting and learning from them, and I thank the academia ecosystem for that.
But the remaining 99% are the maximalists, as described in the article. More papers/students/grants, then repeat. Worse enough, they're absolutely useless outside of academia, as they never did anything at all outside that bubble.
An embarrassing lot of CS professors would stumble around your average production codebase.
I think AI is just the final nail in the coffin for the latter bunch, as they have been dogs eating their own tail for decades already.
Arts faculty on the other hand seem to basically just be a popularity competition.
What got me out of academia (yup, I was a professor) was:
Do you have vast field experience and want to get into the classroom to teach how it's really done? Tough luck, you should've spent your time writing papers.
No matter how much you know or how good you are, everything is about feeding the maximalist machine, if you're an outlier, worse people with better "scores", more papers and never leaving faculty will forever beat you until they retire.
I took a good look at the publishing process. Absolutely everything about it was back-channeling to carefully select the topic, scope and reviewers of a paper to get it through the process. Goodhart's Law at its finest.
Advice given to me: "aim for a lower rank and be happy with teaching the whole thing while the old professor takes a nap in the corner".
AI or not AI, anything destroying that self-perpetuating bureaucracy is welcome.
As would be expected. The value of computer science has very little overlap with navigating a typical production code base.
As for the remaining 99%, maybe they should stop pretending they know (and giving advice) about navigating a typical production code base.
Too many educators don't actually know how to educate, and only focus on what to educate.
LLMs are offering some ways to dramatically improve how people learn (and therefore how well they learn, what they learn,etc - to rapidly accelerate and improve outcomes). However most educators, who are ignorant to the principles of how people learn, have no idea how to harness that potential. The result is in most cases students are just using AI to sabotage their own learning, because no better alternative is being offered.
It's a hard problem... But it's a shame that so few people are working constructively and pragmatically on it.
But in practice, they are overwhelmingly having the opposite effect, and if we're realistic about the structural incentives that have no practical path to being changed in higher ed, this will continue to be the case indefinitely.
It's as if electricity had the potential to save lives but everyone was just frantically electrocuting themselves.
We are hurling to a reality where the only noteworthy metric is human to human validation.
I highly doubt anything like that will be implemented though.
A review call might just end up being less work then reading a lot of slop papers.