I'm on record saying that a system like this with some extra hardware (i.e. a way for the LLM to have live understanding of the student's paper notebook or handout which are being written in with a plain old pencil) combines the best of both worlds - individual tutoring with approximately zero screen time which scales linearly with the number of students. The role of the teacher or professor then becomes a manager of the student - agentic tutor pairs, a referee when the student and model disagree, etc. and most importantly still being the human teacher you can just talk to in the human education process.

I'm convinced this is the future of education - models are there, we need the classroom tech to catch up. The alternative is obvious and quantified in the paper - students just use models to do their work for them and learn nothing.

Conflicted about this study. On one hand, LLMs have been incredible for my personal learnings of new concepts.

On the other, I'm sceptical of that it'll have "strong benefits" at scale; I'd be more in favor if the wording was "some"/"moderate". I reckon self-selection plays a huge part, as mentioned in the "Limitations" section of the paper.

I'd also caution against attaching the tool to grading. That means students have to put more effort into the course, which increases the chances that they will use LLMs to save time rather than make the investment.

This is exciting because the effect size is so large. But as the author's acknowledged, selection bias is nearly impossible to control for in this non-randomized study:

> and lacks randomized controls. Self-selection is the central threat: students who complete more quizzes may be more motivated or higher-performing generally

But this is still a strong result. I'm excited to see more in this space.

Curious how this holds up across different learning styles. SD effect sizes look impressive, but I'd want to see retention data at 30/90 days before drawing conclusions.

Interesting, congrats.

Are you planning on opening access to Phosphor?

Do you have a larger study planned for the Fall? It definitely seems promising.

I'm curious how well you feel this worked because the subject was Statistics (objective grading) versus something more subjective like Civics or Literature.

PS - I'd say this qualifies for Show HN, too!

Do you

Honestly whether or not this was effective seems less important to me than the adoption numbers.

Text book reading in this course was 10-15% at baseline ... but this AI thing got 90% voluntary usage ungraded.

Even if its worse per-hour than a textbook, you're now teaching 6x as many students _something_ instead of teaching a small minority everything.

So really it just becomes an optimization problem at that point because most students are at least in the funnel/in the running to learn something.

The paper kind of proves this itself ... they tweaked the quize formats mid-semester and where able to iterate which you can't do on a textbook that nobody opens in the first place

Too bad the educational use case doesn't make any money. Good LLMs are a game changer for people motivated to learn.

Very nicely typeset.

Shocking that a well executed AI tutor improves outcomes.

Hasn't computer assisted interactive learning already been proven for years? Why does there seem to be so much skepticism about enhancing it with AI?

Is this just something like, astoundingly slow adoption or poor execution? Being held back by paper textbook makers? Teachers unions dragging their feet?

How can interactive AI driven individually paced learning _not_ be obviously dramatically more effective?