Abstract for: Mental model comparison: current methodic challenges and advances

This paper contributes to research on mental models of dynamic systems (MMDS). Such models are compared at the level of variables and causal links, feedback loops, and the entire model. At the level of variables and links, only direct links in the same causal direction are taken into account. We use exemplary data from a current case study to show that there are blind spots in the current methods: (1) when there are intermediate variables in between two key variables in one of the compared models or in both, the number of differences in the details of the MMDS results in an exaggerated Element Distance Ratio (EDR). And (2) when two variables are linked in the two compared model with different directions, the fact that both models posit a relationship between the variables is amalgamated with the complete absence of a relationship, which also exaggerates the EDR. The paper first demonstrates these problems and then discusses modifications to the current method and shows how they overcome the detected problems. We propose that the same modifications could be useful for mental model research in general.