Test your updated model in new situations

Design a small experiment that would confirm or disconfirm the principle you just derived.

Why it works

A generalized principle that is never tested remains a hypothesis, not knowledge. Active experimentation closes Kolb’s cycle by turning the abstract principle back into concrete action — with the explicit intent of generating new experience that tests the principle’s range. This is what makes experiential learning genuinely cumulative: each cycle refines the model rather than repeating the same observation in different clothing.

How to do it

1. Take the principle you derived and identify a situation where it would predict a specific outcome.
2. Design the simplest action that would test the prediction.
3. Execute it, then return to the reflective observation step.

Evidence

The experimental mindset — testing principles rather than assuming them — is consistent with scientific reasoning research and with research on hypothesis-testing in naturalistic learning. Klahr and Dunbar (1988) modeled scientific reasoning as a coordinated search across a hypothesis space and an experiment space, giving a concrete account of the design-a-test move this practice names. That deliberate experimentation accelerates skill development is mechanistically supported. (mechanistic)

Directly isolating "active experimentation" as a learning phase from the overall reflective cycle is methodologically difficult; the evidence is for the whole reflective practice process.

Sources

• Klahr, D., & Dunbar, K. (1988). Dual space search during scientific reasoning. Cognitive Science, 12(1), 1–48.

Common mistake

Treating the principle as confirmed on the basis of the single experience it was derived from — an induction from n=1 that will be wrong in every case where the original experience was exceptional.