Double loop learning is a concept developed by organizational theorist Chris Argyris that describes a deeper, more transformative way of learning from experience.
Single loop vs. double loop:
In single loop learning, when something goes wrong, you adjust your actions or strategies while keeping your underlying goals and assumptions intact. It’s like a thermostat that detects when a room is too cold and turns up the heat—it fixes the immediate problem without questioning whether the temperature setting itself is appropriate.
In double loop learning, you go further by questioning and potentially changing the underlying assumptions, beliefs, and mental models that guide your actions. You ask not just “How do we fix this?” but “Why did we think this was the right approach in the first place?” and “Should we rethink our goals or assumptions?”