If you remove the mention of AI from this post, the authors process and setup of the notice to students is absolutely mental. The intentions might be good, but damn if this isn’t a comically inept way to set up a kafkaesque nightmare rather than a place for actual learning. The defensive attitude doesn’t help either. Just the sheer energy that went into all the steps mentioned here, not invested in any even superficial attempt to perhaps adapt. That isn’t to “give into AI” or cheating, but if 50% of students break your rules, more rules and litigation about the rules are not the next step to take.
My comment explicitly did not focus in the use of LLMs and in fact much of the post doesn’t. Leading with the depressing “work alone” slide, it focused on similarity, not AI use. Between students, ruling even “inadvertent” exposure as the same punishable (and literally literally undeniable!) offence. There’s millions of ways to structure a class for learning, this myopic focus is not one of them. Ironically the setup ignores the very basics of human collaboration. AI merely amplifies extremes, it’s a factor but neither the cause nor culprit here.
The title includes “retrospective” but the learning and changes following such a process are absent.
> Leading with the depressing “work alone” slide
working in a team is valuable. but that value is proportional to the teammates chosen. teammates who have worked alone and can think through their decisions are more valuable, thus it is this way.
>AI merely amplifies extremes, it’s a factor but neither the cause nor culprit here.
you may have missed this part: ~As discussed in the paper, we have also run the tool against earlier semesters with very compelling and interesting results. In particular, the indicators that we use are virtually nonexistent prior to 2024 and their presence increases rapidly over the following years.~
So it stands to reason that LLM's are in fact, the culprit here.
All these analogies are kind of tortured as they ignore the elephant in the room. The students want to be there to get their job getting paper. They aren’t there to learn.
If society offered some reward for lifting the weight while not enforcing how, forklifts would absolutely be used to lift weights.
The job-getting paper ceases to be meaningful if it no longer verifies competence. If it merely verifies the ability to prompt an LLM then nobody will pay a premium for people have it, and then nobody will pay to obtain one.
summarity · · focus · HN ↗
altruios · · focus · HN ↗
That some 50% are using the LLMs rather than spend effort learning is not a cause to remove the ban of LLMs in the classroom.
90% of the power of an LLM is being yourself competent enough to judge its outputs. Besides, do we really need more humans coding like LLMs?
summarity · · focus · HN ↗
The title includes “retrospective” but the learning and changes following such a process are absent.
altruios · · focus · HN ↗
working in a team is valuable. but that value is proportional to the teammates chosen. teammates who have worked alone and can think through their decisions are more valuable, thus it is this way.
>AI merely amplifies extremes, it’s a factor but neither the cause nor culprit here.
you may have missed this part: ~As discussed in the paper, we have also run the tool against earlier semesters with very compelling and interesting results. In particular, the indicators that we use are virtually nonexistent prior to 2024 and their presence increases rapidly over the following years.~
So it stands to reason that LLM's are in fact, the culprit here.
MattGaiser · · focus · HN ↗
If society offered some reward for lifting the weight while not enforcing how, forklifts would absolutely be used to lift weights.
altruios · · focus · HN ↗
AndrewDucker · · focus · HN ↗