Ladder of Inference
The Ladder of Inference is a framework developed by organizational learning professor Chris Argyris. It examines the mental process that moves us from the data we observe to the beliefs and conclusions we adopt about the world around us. Our beliefs are largely self-generated and untested. We come to conclusions based on our experiences and what we observe in the world around us, yet we are largely oblivious to this process, thinking instead that we are merely seeing reality.
The ladder of inference:
Provides a framework to help students examine their reasoning and accessing the reasoning of others.
- Offers students a way to explicitly visualize their (otherwise implicit) thinking process in any situation.
- Helps students understand specific reasons why and how they have come to different conclusions than others who disagree with them, and access concrete value in the opposing views.
Causal modelling is a tool that helps us visually depict the causal links among states and factors within a complex system. Like mind-mapping, causal modelling provides a framework for making explicit the causal relationships we associate with a particular outcome. Causal models assist us to make clearer our thinking with respect to relationships and interactions in a given situation. These models help us to explain our thinking to others, our thinking about complex systems, and provides us with a guide to test our assumptions to enrich our understanding of a particular phenomenon.
Good causal models:
- Help us make implicit assumptions explicit, so we can explore and test them.
- Are rich enough to take multiple factors into account.
- Are clear enough to make the underlying thinking understandable to others.
- Say something specific and meaningful about how the world works.
- Can explain a phenomenon, predict an outcome, or generate new ideas