Double Loop Learning

Double loop learning is a learning process that goes beyond surface level goals, techniques, and responses to target the  assumptions and values underlying the system.

The idea is to enable solutions to problems that are complex and ill-structured. Argyris and Schön, who developed and elaborated the double loop theory, describe different types of learning as follows:

When the error detected and corrected permits the organization to carry on its present policies or achieve its presents objectives, then that error-and-correction process is single-loop learning. Single-loop learning is like a thermostat that learns when it is too hot or too cold and turns the heat on or off. The thermostat can perform this task because it can receive information (the temperature of the room) and take corrective action. Double-looplearning occurs when error is detected and corrected in ways that involve the modification of an organization’s underlying norms, policies and objectives.

Double-Loop Learning vs. Single Loop Learning


If we continue the example of the thermostat above, a double loop thermostat would ask why before altering the temperature–are there people here to enjoy the heat? Are the people dressed appropriately? Could we open or close a window instead? The double loop thermometer takes into account its current environment and situation when making decisions.

To learn more about this learning tool,visit Instructional Design’s Double Loop Learning page.