Double loop learning

From Wikipedia, the free encyclopedia
Jump to: navigation, search

Double-loop learning (DLL) (coined by Chris Argyris) is the modification or rejection of a goal in the light of experience. DLL recognises that the way a problem is defined and solved and can be a source of the problem.[1]

"Single-loop learning" is the repeated attempt at the same problem, with no variation of method and without ever questioning the goal.

See also[edit]


External sources[edit]