LCC Evidence
Methods for tracing claims to sources, preserving uncertainty, and making reproducible decisions.
Research programs
Broader than AI. Grounded in evidence.
LCC Research Lab investigates questions across evidence, learning, and artificial intelligence. Our research programs share a common scientific approach: careful experiments, reproducible measurements, and conclusions grounded in evidence.
“I couldn’t reduce it to the freshman level. That means we don’t really understand it.”
LCC Learning
Research on teaching, prerequisites, knowledge acquisition, transfer, and durable understanding.
LCC AI
Experiments with Teachers, Students, model evaluation, adapters, and knowledge-transfer mechanisms.
Our method
From Evidence to Defensible Conclusions
Every stage has a different job, and no stage is allowed to quietly substitute for another.
Read closely
Preserve what the source establishes before interpretation begins.
Separate carefully
Distinguish observations, inferences, uncertainty, and alternatives.
Ask before looking
Freeze the question and success rules before examining outcomes.
Say only enough
Make the narrow conclusion clear, including limits and failures.
Current questions
What we are trying to learn.
EVIDENCE
How can a team preserve the boundary between a source, an inference, and a scientific conclusion?
LEARNING
When does changed behavior become reusable knowledge rather than a temporary response to context?
TRANSFER
What is the smallest explicit package of facts and reasoning procedures that a small model can reliably acquire and reuse?