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In this study, we aimed to explore the relationships between intuitive abilities, intelligence (explicit cognitive ability) and personality. We found that intuition is not homogenous and there are three types of intuitive ability: Coherence & Insight, Implicit Learning and Subjective Intuitive Abilities that showed different patterns of relationships with explicit cognitive ability and personality. Coherence & Insight was predicted by intelligence and Openness to Aesthetics. Implicit Learning was weakly predicted by explicit cognitive ability. Subjective Intuitive Abilities was predicted only by Openness subscales: Fantasy, Action and Ideas. We demonstrated that intuition is not a unitary psychological construct but rather a complex cognitive conglomerate that incorporates diverse processes and mechanisms and these intuitive abilities are largely independent from psychometric intelligence.

We examined the degree to which the conventional notion of g associated with IQ tests and general cognitive ability tests (COG-g) relate to the general ability that underlies tests of reading, math, and writing achievement (ACH-g). Two large, nationally representative data sets and two independent individually-administered set of test batteries were analyzed using confirmatory factor analysis procedures: (a) the Kaufman-II sample (N = 2520), organized into six age groups between 4–5 and 16–19 years, tested on both the Kaufman Assessment Battery for Children-2nd ed. (KABC-II) and the Kaufman Test of Educational Achievement-2nd ed. (KTEA-II) Comprehensive Form; and (b) the WJ III sample (N = 4969), organized into four age groups between 5–6 and 14–19 years, tested on both the Cognitive and Achievement batteries of the Woodcock–Johnson-3rd ed. (WJ III). Second-order latent factor models were used to model the test scores. Multi-group confirmatory factor analysis was used to investigate factor loading invariance across the age groups. In general, invariance was tenable, which allowed for valid comparisons of second-order COG-g and ACH-g factor variance/covariances and correlations across age. Although COG-g and ACH-g were not isomorphic, they correlated substantially, with an overall mean correlation coefficient of .83, and with the correlations generally increasing with age (ranging from .77 to .94). The nature of the relation between COG-g and ACH-g was explored and the best measures of COG-g were examined.

The existence of general-purpose cognitive mechanisms related to intelligence, which appear to facilitate all forms of problem solving, conflicts with the strong modularity view of the mind espoused by some evolutionary psychologists. The current study assessed the contribution of general intelligence (g) to explaining variation in contextualized deductive reasoning. One hundred and twelve participants solved 70 contextualized reasoning problems in a computerized version of the Wason Card Selection Task that recorded both accuracy and reaction time. Consistent with prior research, in the sample as a whole, precautionary and social exchange reasoning problems were solved more frequently and more quickly than reasoning problems about arbitrary rules. At the individual-differences level of analysis, however, performance on all reasoning tests was significantly correlated and loaded on a single deductive-reasoning accuracy factor. Further, this factor was significantly correlated with g. There was no relation, however, between g and the speed of arriving at the correct answer for any form of deductive reasoning. We discuss the implications of these findings for evolutionary psychology, intelligence, and reasoning.

Recent evidence suggests the existence of multiple cognitive mechanisms that support the general cognitive ability factor (g). Working memory and processing speed are the two best established candidate mechanisms. Relatively little attention has been given to the possibility that associative learning is an additional mechanism contributing to g. The present study tested the hypothesis that associative learning ability, as assessed by psychometrically sound associative learning tasks, would predict variance in g above and beyond the variance predicted by working memory capacity and processing speed. This hypothesis was confirmed in a sample of 169 adolescents, using structural equation modeling. Associative learning, working memory, and processing speed all contributed significant unique variance to g, indicating not only that multiple elementary cognitive processes underlie intelligence, but also the novel finding that associative learning is one such process.

Sex differences in spatial ability are well documented, but poorly understood. In order to see whether working memory is an important factor in these differences, 50 males and 50 females performed tests of three-dimensional mental rotation and spatial visualization, along with tests of spatial and verbal working memory. Substantial differences were found on all spatial ability and spatial working memory tests (that included both a spatial and verbal processing component). No significant differences were found in spatial short-term memory or verbal working memory. In addition, spatial working memory completely mediated the relationship between sex and spatial ability, but there was also a direct effect of sex on the unique variance in three-dimensional rotation ability, and this effect was not mediated by spatial working memory. Results are discussed in the context of research on working memory and intelligence in general, and sex differences in spatial ability more specifically.

► Intelligence research has been of several kinds, three of which are (a) finding new correlates of g and (b) understanding better the nature of g, (c) expanding our conceptions of intelligence beyond g. ► In the Cambridge Handbook of Intelligence, authors who have devoted more of their careers to (b) and (c) than to (a) were relatively more cited. ► We suggest that this is because it is already established that g correlates with an extremely broad range of human behavior. ► We suggest therefore that future research may tilt more toward (b) and (c) than toward (a) simply because (a) already has been so well established.