Bloom's paradox is well known and proven in education.
AI is the first thing that can positively personalize education and instruction and provide support to instructors.
The authors seem of limited technical literacy to know that you can just train and focus only on textbooks, instead of their explorations using general models and the pitfalls that they have. Not knowing this key difference affects some of the points being made.
The intersection of having a take on technology needs some semblance of digital and technical literacy involved in the paper to help acknowledge or navigate it, or it become a potential blind spot.
It takes legitimate concerns and ironically explores them in average ways, much like an llm returns average text for vague or incomplete questions.
Doesn't matter. Every time some maniac invents some, we all need to scramble to adopt it. This is what _progress_ is. Is there's a new technology, we don't think about the consequences. We all just adopt it and use it so thoroughly that we cannot imagine living without it.
Calm down, what actually happens is there is a reaction to new technology and then once its been used there is a counter reaction which takes into account what works and what dosent.
Is there a previous decade you'd prefer to return too for quality of life? Why?
Calling the Alpha school "AI" or even "AI to aid learning" is a massive stretch. I've read that article and nothing in there says AI to me. Data collection and on-demand computer-based instruction, sure.
I don't disagree with your premise, but I don't think that article backs it up at all.
Imagine a tutor that stays with you as long as you need for every concept of math, instead of the class moving on without you and that compounding over years.
Rather than 1 teacher for 30 students, 1 teacher can scale to 30 students to better address Bloom's 2 sigma problem, which discovered students in a 1:2 ratio with a tutor full time ended up in the 98% of students reliably.
LLMs are capable of delivering this outright, or providing serious inroads to it for those capable and willing to do the work beyond going through the motions.
This is kind of odd.
Bloom's paradox is well known and proven in education.
AI is the first thing that can positively personalize education and instruction and provide support to instructors.
The authors seem of limited technical literacy to know that you can just train and focus only on textbooks, instead of their explorations using general models and the pitfalls that they have. Not knowing this key difference affects some of the points being made.
The intersection of having a take on technology needs some semblance of digital and technical literacy involved in the paper to help acknowledge or navigate it, or it become a potential blind spot.
It takes legitimate concerns and ironically explores them in average ways, much like an llm returns average text for vague or incomplete questions.
Doesn't matter. Every time some maniac invents some, we all need to scramble to adopt it. This is what _progress_ is. Is there's a new technology, we don't think about the consequences. We all just adopt it and use it so thoroughly that we cannot imagine living without it.
Calm down, what actually happens is there is a reaction to new technology and then once its been used there is a counter reaction which takes into account what works and what dosent.
Is there a previous decade you'd prefer to return too for quality of life? Why?
The 1990s surely
Nonsense
There will however be a gigantic gulf between kids who use AI to learn vs those who use AI to aid learning
Objective review of Alpha school in Austin:
https://www.astralcodexten.com/p/your-review-alpha-school
Calling the Alpha school "AI" or even "AI to aid learning" is a massive stretch. I've read that article and nothing in there says AI to me. Data collection and on-demand computer-based instruction, sure.
I don't disagree with your premise, but I don't think that article backs it up at all.
What is the distinction between using "AI to learn" and using "AI to aid learning?"
Imagine a tutor that stays with you as long as you need for every concept of math, instead of the class moving on without you and that compounding over years.
Rather than 1 teacher for 30 students, 1 teacher can scale to 30 students to better address Bloom's 2 sigma problem, which discovered students in a 1:2 ratio with a tutor full time ended up in the 98% of students reliably.
LLMs are capable of delivering this outright, or providing serious inroads to it for those capable and willing to do the work beyond going through the motions.
https://en.wikipedia.org/wiki/Bloom's_2_sigma_problem (1984)
I don't think this answers the question in the comment you're replying to.