Types of Causal Maps

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Mohammed, Klimoski and Rentsch (2000) have recently looked at four techniques for

measuring mental models: Pathfinder Associative Networks, Multidimensional Scaling,

Interactively Elicited Causal Maps and Text Based Causal Maps. The Pathfinder

Associative Network (PAN) is a technique intended to produce a network structure in

which the map nodes are the concepts and the linkages are the relatedness of the

concepts (Schvaneveldt, 1990). Multidimensional Scaling (MDS) is a set of models that

represents proximity data spatially (Carroll & Arabie, 1980, found in Mohammed et al.,

2000). MDS uses geometric distance to identify the underlying dimensions of cognitive

structure (Mohammed, et al., 2000). See Table 1 for a comparative summary of these

methods.

Prior to creating revealed causal maps, a data source is selected and narratives are

gathered. Although Mohammed et al. (2000) sees Interactively Elicited Causal Maps and

Text Based Causal Maps as different techniques for measuring mental models, I see them

as variants of the same technique. I argue that they are two data collection methods under

the causal mapping technique. Data collection (elicitation of maps) can be accomplished

in one of two ways: interviews (interactively elicited causal maps) or through archival

texts such as annual reports (text-based causal maps). Interactively elicited causal maps

(IECM) are developed from direct interaction with the participants to collect the data.

Text-based causal maps (TBCM) are developed from documents or transcripts created

for another purpose. The causal mapping data collection methods (IECM and TBCM) are

detailed below.