The method of computer-simulated scenarios has recently been introduced to study how people solve complex problems. This article describes a special approach to constructing such microworlds by means of linear structural equation systems. The subjects' task is to first identify in a knowledge application phase the causal structure of a hitherto unknown system. In a later knowledge application phase they try to control this system with respect to a given goal state. Verbalizable knowledge that was acquired on the task is assessed both my means of causal diagrams as well as by the degree of successful control performance. Five experiments on special attributes of such systems illustrate the approach. The experiments investigated effects of active interventions versus observation only, effects of different degrees of Eigendynamik, the influence of different degrees of side effects, the role of prior knowledge, the amount of controllability and number of variables to be controlled. These factors have considerable effects on identification of the system structure and control of its states, these being two central indicators of complex problem solving. Three topics are identified as main goals for future research: (1) separation of different sources of variance (person, system, situation); (2) research on reliability and validity of performance indicators; (3) development of measures for an operators' heuristic and strategic knowledge
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