Components of geometric analogy solution

Geometric analogy solution was investigated as a function of systematic variations in the information structure of individual items. Latency data from the verification of true and false items indicated that individuals decompose figural patterns in a way that represents a sequential determination of the various elements that need to be isolated. They also appear to identify and evaluate the transformations applied to elements in a way that represents a sequential determination of the separate or successive transformations that fully specify an item rule. Analysis and evaluation of transformations took more time than element analysis and was the primary source of errors. The combined effects of element and transformation processing violated a simple additive model and the best fitting functions suggested that nonadditive increases in solution latency and error rates were due to working memory limitations associated with the representation and manipulation of item features at high levels of rule complexity. Correlational data also indicated that these factors partially account for individual differences in performance on psychometric tests. The latency and error data for true and false items are used to develop a general theoretical system that incorporates assumptions about the form of item representation, working memory factors, and processing components and strategies in analogical reasoning tasks.