Causal mapping refers to the use of directed node and link graphs -- similar to concept maps in some ways -- to represent a set of causal relationships within a system. For example, the causal map shown below reflects two sixth grade girls representation of the factors that contribute to the health of a stream.
Causal mapping is more structured than concept mapping, in that links can only mean one thing (a causal relation). This has the advantage, in the context in which we use causal mapping, of allowing students to develop a shared representation for causality. This in turn allows students to quickly examine and critique each others causal maps, and pursue discussions -- with peers and with the teacher -- about what factors should be included and how different causal chains should be represented.
The Rationale Behind the Feature (Specific Design Principle):
Causal mapping uses a representation that is similar that those used by dynamic modeling environments like STELLA and Model-It. These tools allow the user to design and test causal models and offer fine control over the specific mathematical nature of the causal relationship. The causal mapping tool does not support the ability to test ones causal map by running it over time (as do these other tools). It focuses solely on providing a expressive representation that students, with minimal training, can use to explore the behavior of causal systems.
Context of Use:
The primary use of causal mapping has been within the Web-based Science Inquiry Environment (WISE). We have developed several WISE projects that include causal mapping as a means to make sense of a set of causal relationships.
Several WISE investigation-based curricula have employed the causal mapper. Teachers and students report the utility of the tool.