Research
LocoLab’s research explores how local AI can support education, what small language models can actually do on consumer hardware, and how students interact with AI systems. Each paper is its own repository — published papers become public with links to the full text.
Active
Section titled “Active”These projects have scaffolded repositories and are under active development.
| Paper | Description | Status |
|---|---|---|
| Cognitive Strategy Transfer | Framework for understanding how cognitive strategies transfer across AI-assisted learning contexts (4-paper series) | In progress |
| DSR AI Education Simulation | Design science research on AI-powered education simulations | In progress |
| Keep Asking — Study 1: Does the Nudge Work? | Using frontier models, test whether a conversational nudge shifts students from passive delegation to active conversation and improves task outcomes | In progress |
| Keep Asking — Study 2: Does Conversation Compensate for Model Quality? | Test whether nudged students using a weak local model can match un-nudged students using a frontier model — reframing AI equity as a habits problem | Planned (pending Study 1) |
Planned
Section titled “Planned”Early-stage ideas with initial notes. Not yet under active development.
| Paper | Description |
|---|---|
| Context Length Effects on Small Language Models | How context window size affects small language model performance on consumer hardware |
| Perceived Intelligence vs Token Rate | Relationship between perceived AI intelligence and token generation speed |
Published
Section titled “Published”No papers published yet — check back soon.