> The AI crew's fantasy is that students sitting in front a screen will be motivated because A) the adaptive technology will hit them with exactly the right material for the student and B) shiny! Arnett explains that any dreams of AI-aided motivation are doomed to failure.
> Arnett's explanation is not exactly where I expected we were headed. Human respect is scarce, he argues, because humans only have so much time and attention to parcel out, and so it's valuable. AI has infinite attention resources, can be programed to be always there and always supportive. Arnett argues that makes its feedback worthless in terms of status and respect. ...
> But I think much of what he says here is valuable and valid-- that AI faces a major hurdle in classrooms because it offers no social relationship component, little opportunity to provide students with status or respect. Will folks come up with ways to use AI tools that have those dimensions? No doubt. But the heart of Arnett's argument is an explanation of one more reason that sitting a student in front of an AI-run screen is not a viable future for education.
is there a way to use it that prevents "tell me the answer", if not that is what enough students will gravitate towards that it will be harmful to society at large. If there is an agent that only works as an infinitely patient tutor, that will under no circumstance do the work for you, then sure. Just have expereience educators dictate the way the agent works and is used, not some marketing dweeb or MBAsshole.
That's certainly one outcome. Another is having AI tell you the answer and you understanding why your answer is incorrect. This is not black and white.
If the Agent is designed for that type of interaction and not "do it for me so i don't have to know the details" then yes, but currently that is not supported so teenagers and children will absolutely use it as a "don't make me think" button
You still have to double check the Agent's grading as they still make frequent minor mistakes, that while they don't really impact coding as much or can be caught with tests, that is not the case here.
The actual question to ask is if the agent makes more mistakes than a human being. Grading homework involves reading over similar/identical answers to the same questions over and over, and it is easy for human beings to make mistakes while doing that.
(That is basically the argument for OCR in the postal system -- it does make mistakes but it makes fewer mistakes than human beings.)
Have you ever graded tests for an entire class? I did so for two years when I was a PhD student and had to work as a TA. It does not matter if you are an expert in the subject because the problem has nothing to do with expertise, it has to do with how our brains work. The worst case is when most of the class answers the question correctly, and you don't encounter a mistake until you have finished grading most of the tests -- your brain really wants to just keep repeating the same motion (e.g. writing a check mark) and even if you spot the error you might accidentally mark it correct anyway.
Really though, this is missing the point. Yes, grading tests and homework is different from sorting mail, but both are tedious tasks that involve a lot of repetitive actions -- hard for the human brain, but easy for software. Software does not get tired or distracted by other responsibilities (or non-responsibilities). We have already been using software to grade tests for a long time now, but mostly for multiple choice questions; AI will expand the scope of that.
