Double loop learning
A way of problem solving, which questions also existing assumptions in order to create new insights
Adaptive learning uses knowledge based on existing assumptions and is often based on what happened in the past. In contrast, Double-loop learning (also called ‘Generative learning’) goes a step further and questions existing assumptions in order to create new insights. Single-loop (or adaptive) learning has been compared to a thermostat that controls temperature to a fixed setting and double-loop learning to a thermostat that could ask why it were set on that particular temperature. In the nuclear industry, these learning concepts are particularly pertinent in root cause analysis, appreciative inquiry, and other performance improvement initiatives. Double-loop learning requires more introspection by participants, as they must be willing to probe their own thoughts, actions, and attitudes rather than just seeking something or someone else to ‘blame’ for problems. The use of such a process is essential for an organization to adopt a learning culture.