Double Loop Learning

Learning/Reflection Cycle
This model is based on a theory of Self-Regulated Learning (Zimmerman, 1990), with questions from the Service Learning literature (What? So What? Now What?), and the addition of double loop learning (Why?) for deeper thinking. This model is further discussed in Dr. Barrett's blog, including a poster on mPortfolios: Supporting Reflection in ePortfoios with Mobile Devices. Below are several diagrams and definitions of Double Loop Learning.

A Little Learning Science: What We Mean When We Talk About Reflection

Kolb's (1984) classic depiction of learning concisely describes the process of "single-loop learning," and can be considered a simplified version of the scientific method. Kolb's learning cycle begins with Experience, upon which we Reflect, then Generalize, and finally Test our generalizations, which leads to more and more informed experience. This cycle is the top circle in the figure below.

Reflection, however, is the stage at which we may venture into double-loop learning: a much less frequent but more powerful-and potentially unsettling-experience of fundamental change in our understanding. Brockbank and McGill (2007) made the case that emotional energy can be the force that opens the door to reflection which leads to double-loop learning, citing Barnett's (1997) statement that "critical energy has to have a head of steam behind it" (p. 172).

Kolb's Experiential Learning Model (1984)
Experiential and Double Loop Learning

Definition of Double Loop Learning

Double-loop learning is an educational concept and process that involves teaching people to think more deeply about their own assumptions and beliefs. It was created by Chris Argyris, a leading organizational trainer, in the mid-1980’s, and developed over the next decade into an effective tool. Double-loop learning is different than single-loop learning which involves changing methods and improving efficiency to obtain established objectives (i.e., “doing things right”). Double-loop learning concerns changing the objectives themselves (i.e., “doing the right things”).

Chris Argyris coined the terms “Double Loop Learning” and “Single Loop Learning. Single loop learning has often been compared to a thermostat in that it makes a “decision” to either turn on or off. Double loop learning is like a thermostat that asks “why” — Is this a good time to switch settings? Are there people in here? Are they in bed? Are they dressed for a colder setting? — thus it orientates itself to the present environment in order to make the wisest decision.