A model of information processing has been developed that combines concepts from the study of attention and the study of problem solving. The model is based on the idea that certain concepts drawn from recent theories of attention can be used to construct a psychologically motivated interpreter for production system simulations of problem solving. Within the model, automatic processing is explained in terms of the spread of activation between related productions and is independent of working memory. Controlled processing consists of the execution of a sequence of productions that manipulate the contents of working memory. The model has been realized as a computer program and used to simulate a variety of phenomena from the attention and performance literature. The relevant simulations are described. The model inherits the simulation capabilities of production-oriented simulations of problem solving, because it is an interpreter of productions. The model is compared to several other current models of attention and problem solving.

Several measures of the speed of information processing were related to ability factors derived from the Cattell-Horn theory of fluid and crystallized intelligence. Ninety-one college students took a battery of paper and pencil tests designed to measure four ability factors: fluid intelligence (Gf), crystallized intelligence (Gc), spatial visualization (Gv), and clerical perceptual speed (CPS). They also performed paper and pencil and computerized versions of three information processing tasks: mental rotations, letter matching, and sentence verification. Correlations among the ability measures, among the information processing measures, and between the two domains were analyzed using confirmatory factor analysis. The four ability factors were found to be largely independent in this college population. Speed of letter-matching and sentence verification were highly correlated, but neither was related to speed of mental rotation. Mental rotation speed was strongly correlated with Gv; letter matching speed was correlated with CPS; and sentence verification speed was correlated with both Gc and CPS.

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The purpose of this research was to use secondary task performance as a predictor of performance on a difficult primary task. Reaction time (RT) to secondary probes that occurred during the rehearsal period of an easy memory task were used to measure spare capacity associated with the memory task. This measure was then correlated with performance on a harder version of the same memory task. Experiments 1·4 involved a paired associate memory task. Probe RT was sensitive to the difficulty of the paired associate task, and analysis of individual differences showed that probe RT during the easy version of the task was correlated with performance on a harder version of the task. Experiment 4 also utilized a spatial memory task. Probe RT was less sensitive to the demands of the spatial memory task, and in that case, the "easy-to-hard" prediction was not successful. 10This article is concerned with performance on a dual task in which one component is designated as primary and the other as secondary. Suppose that there is something analogous to "mental energy," an attentional resource that is required for a variety of tasks (Kahneman, 1973). If two tasks are performed concurrently, with one designated as primary and the other as secondary, then the resource demands of the primary task should be fulfilled first. Therefore, secondary task performance should provide a measure of the spare capacity not required by the primary task (Kerr, 1973). Secondary task performance should decrease as the capacity demands of the primary task increase. The most common uses of secondary task measures have been to compare the demands of various stages in the execution of a primary task (e.g., Johnston, Greenberg, Fisher, & Martin, 1970;Logan, 1978;Posner & Boies, 1971) and to compare the demands of the same primary task under various conditions (e.g., Britton, Westbrook, & Holdredge, 1978;. Another use of secondary task measures has been to differentiate among individuals who vary in skill on the primary task. Those individuals who are highly skilled on the primary task should require a smaller proportion of their total resources to perform the task and should, therefore, have more spare capacity available to perform the secondary task. This use of secondary task measures has This research was supported by the Office of Naval Research through Contract N00014-77'{:.Q225 to the University of Washington, Earl Hunt, principal investigator. We would like to thank Beth Kerr for advice on design and interpretation and comments on an earlier draft. We would also like to thank Janet Davidson, Simon Farr, and Colene McKee for assistance in executing and analyzing theseexperiments. Requests for reprints should be sent to Marcy Lansman, Department of Psychology, NI-25, University of Washington, Seattle, Washington 98195.Copyright 1982 Psychonomic Society, Inc.been reported more often in the applied than in the experimental literature (e.g., Brown, 1968).The assertion that primary and secondary tasks compete for mental resources has a further implic...