so in the end we give attention to gifted and the struggling since there's very little you can do to children who are already decent and are capable of keeping up at most they lack discipline or motivation.
so in the end we give attention to gifted and the struggling since there's very little you can do to children who are already decent and are capable of keeping up at most they lack discipline or motivation.
Gifted students especially.
Students who learn ahead don’t want to be told: “ok you have the material, so I’ll ignore you for a bit.” They want more. They want their questions answered, even if the questions aren’t part of the lesson plan.
Nobody wants to be told “we aren’t studying that today.”
You really can’t starve the rest of the class to cater to poor performers.
also there is very little excuse now with how advanced AI is getting at being able to explain subjects, it's all coming down to motivation, environment and the ability to use these tools in the first place - children struggle to use computers since we see it as a given, but to someone who didn't grow up with the incremental advancements it can seem very overwhelming.
I suspect, but can’t prove, that model trainers deliberately steer models away from creating tests and worksheets.
The reason being that when a human asks a written question: “who president of the US in 1962?” it’s very likely to be a part of a worksheet.
Novels don’t contain many questions like that, nor do non fiction. They’re mostly paragraphs. Most text is mostly paragraphs.
Naked question usually means worksheet. AIs know this, so their if you ask it a question like: “who president in 1962?” It responds which the most likely next sentence, a related question: “How was the Cuban Missile resolved?”
So there’s a huge discrepancy between the next most likely sentence based on training, and what a user likely wants. If I ask, “Who was president in 1962?” I don’t want another question, nor does anyone else.
But that’s what the training data provides.
So model trainers have to bias it away from worksheets. This isn’t hard to do, and is a normal part of model training.
I’ve personally seen this behavior in poorly parameterized or trained models. They love answering questions by assuming they are in worksheets. It’s a huge pain.
Interestingly it never happens with top-line models like ChatGPT.
Carefully hyperparameterizatiin helps, but I think you’ll have to adjust the weights too. But that likely makes it harder to make actual worksheets.
This is just a guess. But I suspect models are weighted to discount pedagogical materials because of how different they are from what the users often expect.