On the relationship between psychometric intelligence and decision making in dynamic systems

The relationship between psychometric intelligence and performance in dynamic decision making systems (microworlds) was investigated. A theoretical analysis of the mental processes that underlie performance in intelligence tests and microworlds suggested that at least some weak positive correlations should be expected. The failure of earlier empirical investigations to find such positive relationships has been a central concern during the design and analysis of the empirical studies reported here, A number of hypotheses about the close to zero correlations that were found in earlier studies including (1) the different demands hypothesis, (2) the low reliability hypothesis, (3) the task novelty hypothesis, and (4) the complexity continuum hypothesis have been considered. Using a traditional intelligence test and three different microworlds it was found that reliable measures of performance in microworlds can be obtained, that psychometric intelligence is a predictor of success in microworlds, and that a significant portion of variance of performance in microworlds is common after statistical control of psychometric intelligence. It. was concluded that the different demands hypothesis ought to be revised in order to account for the similarities that exist between traditional tests and microworlds and that the low reliability hypothesis should be restricted to indicate methodological problems that were present in some earlier studies and not a property of the performance measures in microworlds. The task novelty hypothesis was not supported by the data. It is proposed (1) that the microworlds are appropriate material for the development of a new form of tests aimed at the more complex processes that we find in real life pursuits and (2) that the adaptation of microworlds to the needs of mental testing could lead to a major technological innovation in this area.