Modeling complexity and difficulty in measures of fluid intelligence

Abstract

This article applies structural equation modeling to the simultaneous study of task complexity and difficulty in measures of fluid intelligence. The interrelation between 3 tests of fluid intelligence, 2 experimental tasks, and age is examined. Each experimental task is decomposed into 4 subtasks, with the most intellectually demanding ones being measures of fluid intelligence, and the remaining 3 levels constructed to be gradually simpler. The findings suggest that the experimental manipulations produced systematic changes in 3 sets of parameters. These are: (a) the mean intercept parameters of the structural equation model—interpreted as “pure test difficulties” reflecting task‐specific demands placed on elementary cognitive processes of the “same kind” (b) factor loadings on 2 subtask‐specific narrow factors (SWAPS and TRIPLETS) that reflect demands placed on processes of “similar kinds,” that is, processes common to variations within the same experimental task; and (c) factor loadings on a fluid intelligence factor (Gf) that reflect demands placed on processes of “diverse kinds,” which are common to measures of a broad range of different cognitive tasks. The results indicate that as task requirements become more demanding, cognitive processes of the same kind, which are involved in solving the easier subtasks, are no longer critical to performance, but the demand on processes of similar and diverse kinds is increased. It is suggested that for human subjects, increase in task complexity may be associated with lapses of attention in the course of carrying out a series of interconnected steps.