Link to paper: link.springer.com/article/10.1...

💡The takeaway? Don’t match teaching to fixed “styles”. Let's focus on helping students be adaptive and find learning strategies which work best for their task, learning stage, and context.

Not only this, among other confounders, there are unclear definitions of learning style (e.g. "Is it really a learning style to like to work in pairs, in the afternoon, when it is warm, and while snacking?"), an over-reliance of self-reports, and commercial hype.

Just because a student’s self-identified “style” correlates with achievement doesn’t mean matching instruction to that style improves outcomes. Correlation doesn't equal causation.

One of the big problems: confusing the matching hypothesis with "correlates of learning styles" i.e. is there a correlation between a learning style and an academic outcome?

The authors concluded that the evidence for the matching hypothesis is poor, with an effect size of d=0.04, which is small and negligible.

The main claim of the learning styles myth, a.k.a. the "matching hypothesis", is that matching teaching to learning styles (visual, auditory, kinesthetic, and read/write) is more efficient and effective than teaching and learning with a less compatible style.

For a deeper dive, read my full write-up here: garyliang.substack.com/p/ai-tutorin...

Key questions remain: How do long-term learning outcomes hold up? And how will these results translate across different student demographics and subjects?

However, it’s not just about good prompt engineering. Effective AI tutors need to embody pedagogical best practices to make a meaningful impact.

These findings closely align with what we’re seeing at Bloom AI. Our AI tutors have shown similar results, demonstrating that when used correctly, AI can significantly enhance the learning experience.

The results? Students using an AI tutor learned twice as much in less time compared to those in an active-learning class. They also reported higher levels of engagement and motivation!

Gregory Kestin, Kelly Miller, Anna Klales, Timothy Milbourne, and Gregorio Ponti conducted a randomized controlled trial (RCT) in an introductory physics course.