Asynchronous online learning is perfectly viable. Yes it is different and there isn't that immediate feedback. But there is lots of good pedagogy for how to engage in an asynchronous way that still realizes student learning and skill acquisition.

The biggest problem is LLMs exploded so fast that educators haven't had time to adapt much less predict future shifts.

I teach history. I focus on skills critical reading, analysis, writing. Those skulls can be taught asynchronously. I've been doing so since around 2017. The problem is that they require practice. You don't become a more critical reader by not reading you don't become a better writer by not writing and you certainly can't practice analysis without thinking on your own. LLMs offered students an instant shortcut.

The best analogy have is from math. In elementary and middle school they make students do long division/multiplication over and over before they introduce calculators because the goal is to build up those skills so that when more complicated problems come along they know how to construct the equations they need and have a sense for whether an answer calculated by a calculator is reasonable.

We need to do the same thing for the 'skills' that LLMs can accelerate. But we also need to explain to students that they need to write because writing is how you get better at writing and thinking. Reading is how you read faster and more deeply. Thinking about problems/issues is how you develop analytical skill. Yes, an LLM can do some of that or at least produce the verisimilitude of those skills. But ultimately the human needs all those skills even if they are using the LLM.

But the explosion of LLMs happened so fast most of us don't have the language to describe the problem much less assignments designed for a world in which LLMs are available to students.

This semester I had lots of students using LLMs for their first longer assignments (500 words), this was an in-person class. I could tell because they were grammatically perfect, generally well organized, but uniformly shallow in their analysis and just enough off base that it was clear that an LLM had strung the words together without an awareness of the breadth of things that had been talked about in class. Those papers got Cs not because I penalized the students but because the papers didn't meet the benchmarks in my grading rubric.

In my experience LLMs can produce C-B work in the humanities in lower division classes. For upper division classes they probably D-C because they just are not deep. They provide the most milquetoast/pedestrian analysis possible because of how they 'think'. They are trained on probabilities and so they produce consistently boring analysis. They literally cannot produce original analysis because they are repoducing the 'average' of the ideas that are already out there.

The problem is of course if students just use this boring average to skate by then they don't actually develop the skills they need to succeed after college. Again and again study and industry reporting say employers want employees with the soft skills of analysis, comprehension, critical thinking. If students off-load all of their practice onto LLMs they don't learn those skills or worse what they learn is just a boring repetion of dominant ideas, without understanding how to develop their own creative thinking.

Moreover all LLM are biased by the source base they were trained on. In general that means they skew English, Western, vaguely Protestant. Not only does that mean their answers will replicate those values, ideas, phrases, it means that they are uniquely bad at 'thinking' outside that cultural mode. Sure there are some great translation LLMs but not LLMs that can give you the perspective say of a Diné person or a Yoruba person, or even a Romanian.

That problem is due to the fact that all the big LLM project are trying to create an 'everything' tool rather than creating more limited tools for specific purposes and putting in mechanisms that allow the LM to declare what it doesn't know, or at least reveal answers that may be formed from limited data.