Xuezhu Ren

Process-based account for the effects of perceptual attention and executive attention on fluid intelligence: An integrative approach

Perceptual attention and executive attention represent two higher-order types of attention and associate with distinctly different ways of information processing. It is hypothesized that these two types of attention implicate different cognitive processes, which are assumed to account for the differential effects of perceptual attention and executive attention on fluid intelligence. Specifically, an encoding process is assumed to be crucial in completing the tasks of perceptual attention while two executive processes, updating and shifting, are stimulated in completing the tasks of executive attention. The proposed hypothesis was tested by means of an integrative approach combining experimental manipulations and psychometric modeling. In a sample of 210 participants the encoding process has proven indispensable in completing the tasks of perceptual attention, and this process accounted for a considerable part of fluid intelligence that was assessed by two figural reasoning tests. In contrast, the two executive processes, updating and shifting, turned out to be necessary in performance according to the tasks of executive attention and these processes accounted for a larger part of the variance in fluid intelligence than that of the processes underlying perceptual attention.

Models for the Detection of Deviations from the Expected Processing Strategy in Completing the Items of Cognitive Measures

This paper presents confirmatory factor models with fixed factor loadings that enable the identification of deviations from the expected processing strategy. The instructions usually define the expected processing strategy to a considerable degree. Simplification is a deviation from instructions that is likely to occur in complex cognitive measures. Since simplification impairs the validity of the measure, its identification is important. Models representing simplicity and instruction-based processing strategies were considered in investigating the data of 345 participants obtained by a working memory measure in order to find out whether and how the use of these strategies influences model-data fit. As expected, the consideration of simplicity strategies improved the model-data fit achieved for the instruction-based strategy.

The Prediction of Students' Academic Performance With Fluid Intelligence in Giving Special Consideration to the Contribution of Learning.

The present study provides a new account of how fluid intelligence influences academic performance. In this account a complex learning component of fluid intelligence tests is proposed to play a major role in predicting academic performance. A sample of 2, 277 secondary school students completed two reasoning tests that were assumed to represent fluid intelligence and standardized math and verbal tests assessing academic performance. The fluid intelligence data were decomposed into a learning component that was associated with the position effect of intelligence items and a constant component that was independent of the position effect. Results showed that the learning component contributed significantly more to the prediction of math and verbal performance than the constant component. The link from the learning component to math performance was especially strong. These results indicated that fluid intelligence, which has so far been considered as homogeneous, could be decomposed in such a way that the resulting components showed different properties and contributed differently to the prediction of academic performance. Furthermore, the results were in line with the expectation that learning was a predictor of performance in school.