Understanding microworlds

Little is known about how individuals understand change in complex systems. In the natural world, for instance, the effects of change need to be understood in terms of two-way (interdependent) causal processes. Based on subject's ratings of the causal likelihood that a given change will yield a target effect and on subjects' ratings of the impact of a given change on specified populations in a microworld, White (1997, 2000) argued that individuals in fact understand change in terms of one-way causal processes and assume that causal effects decline with distance from the source of the change. An alternative view is that the ratings reflect individuals' mental simulations of change as elicited by the tasks. Experiments 1 and 2 confirm that such ratings are task dependent and that individuals make no general assumption that causal effects decrease with distance. Experiment 3 shows that when required to explain a pattern of change in the size of a population individuals can construct two-way causal explanations consistent with this mental simulation proposal.