Score gains (Flynn Effect) on g-loaded tests : No g

Score gains on g-loaded tests : No g. Jan te Nijenhuis, Annelies E.M. van Vianen, Henk van der Flier, 2007.

IQ scores provide the best general predictor of success in education, job training, and work. However, there are many ways in which IQ scores can be increased, for instance by means of retesting or participation in learning potential training programs. What is the nature of these score gains? Jensen … argued that the effects of cognitive interventions on abilities can be explained in terms of Carroll’s three-stratum hierarchical factor model. We tested his hypothesis using test–retest data from various Dutch, British, and American IQ test batteries combined into a meta-analysis and learning potential data from South Africa using Raven’s Progressive Matrices. The meta-analysis of 64 test–retest studies using IQ batteries (total N=26,990) yielded a correlation between g loadings and score gains of −1.00, meaning there is no g saturation in score gains. The learning potential study showed that: (1) the correlation between score gains and the g loadedness of item scores is −.39, (2) the g loadedness of item scores decreases after a mediated intervention training, and (3) low-g participants increased their scores more than high-g participants. So, our results support Jensen’s hypothesis. The generalizability of test scores resides predominantly in the g component, while the test-specific ability component and the narrow ability component are virtually non-generalizable. As the score gains are not related to g, the generalizable g component decreases and, as it is not unlikely that the training itself is not g-loaded, it is easy to understand why the score gains did not generalize to scores on other cognitive tests and to g-loaded external criteria.

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