Learning scientists

Built on the research. Open to collaboration.

thinkering is grounded in learning science — but we know there's far more to draw on than what we've built so far. We'd love to work with researchers to deepen the strategy library and better understand how to support real learners in practice.

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What we're built on

A starting point, not a complete picture.

These are the ideas that shaped how thinkering works — the foundation we've built from. We know there's much more to incorporate, and we want help getting it right.

Retrieval practice
The testing effect — Roediger & Karpicke (2006). The act of recalling information from memory strengthens it more than re-studying.
Spaced repetition
The spacing effect — Ebbinghaus (1885), Cepeda et al. (2006). Distributing practice over time dramatically outperforms massed practice for long-term retention.
Interleaving
The interleaving effect — Kornell & Bjork (2008). Mixing problem types or topics within a session improves discrimination and transfer, even when it feels more difficult during practice.
Elaboration
Pressley et al. (1992). Prompting learners to ask «why» builds richer semantic networks with more retrieval paths.
Self-explanation
Chi et al. (1989, 1994). Narrating your own reasoning surfaces gaps in understanding and integrates steps into a coherent mental model.
Deliberate practice
Ericsson et al. (1993). Focused effort at the edge of ability, with feedback, is the mechanism of expertise development across domains.
Metacognitive reflection
Zimmerman (2000). Learners who plan, monitor, and reflect on their own process (self-regulated learning) consistently outperform those who don't — and develop transferable learning skills.
Motivation and identity
Nasir & Cooks (2009), Dawes & Larson (2011). Developing a sense of identity within a domain — and feeling a sense of purpose and capability — produces more durable motivation than external rewards or gamification.

This list reflects what we've drawn on so far. We're actively looking to expand it — with researcher input on what's missing, what we've got wrong, and what the evidence actually says.

Collaborate

Two things we want to build together.

A high-quality strategy library
thinkering surfaces learning strategies to help people figure out how to learn what they're working on. We want that library to be accurate, well-grounded, and genuinely useful — and we need researcher expertise to get there. That means reviewing what we have, filling gaps, and thinking carefully about how strategies translate across domains.
A better understanding of how to support learners
What does it actually look like to scaffold self-directed learning well? When does AI support help, and when does it get in the way? We're genuinely curious — and we think pilot studies, close observation, and collaboration with people who study learning could help us answer those questions in ways that matter for real learners.
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