Fluid ability, crystallized ability, and performance across multiple domains: a meta-analysis

Cognitive ability is one of the most frequently investigated individual differences in management and psychology. Countless studies have demonstrated that tests measuring cognitive ability or intelligence predict a number of important real-world outcomes such as academic performance, vocational training performance, and job performance. Although the relationship between intelligence and real-world performance is well established, there is a lack of consensus among scholars with regard to how intelligence should be conceptualized and measured. Of the more traditional theories of intelligence, two perspectives are particularly dominant: the Cattell-Horn model of fluid and crystallized intelligence and the theory of General Cognitive Ability (GCA or g). Fluid ability (Gf) represents novel or abstract problem solving capability and is believed to have a physiological basis. In contrast, crystallized ability (Gc) is associated with learned or acculturated knowledge. Drawing on recent research in neuroscience, as well as research on past performance, the nature of work, and expert performance, I argue that compared to measures of fluid ability, crystallized ability measures should more strongly predict real-world criteria in the classroom as well as the workplace. This idea was meta-analytically examined using a large, diverse set of over 400 primary studies spanning the past 100 years. With regard to academic performance, measures of fluid ability were found to positively predict learning (as measured by grades). However, as hypothesized, crystallized ability measures were found to be superior predictors of academic performance compared to their fluid ability counterparts. This finding was true for both high school and college students. Likewise, similar patterns of results were observed with regard to both training performance and job performance. Again, crystallized ability measures were found to be better predictors of performance than fluid measures. This finding was consistent at the overall level of analysis as well as for medium complexity jobs. These findings have important implications for both intelligence theory and selection practice.

Contemporary intelligence theory has placed great emphasis on the role of fluid ability, and some researchers have argued that Gf and g are essentially the same construct. However, the results of this study, which are based on criterion-related validities rather than factor-analytic evidence, demonstrate that Gc measures are superior predictors in comparison to Gf measures. This is contrary to what one would expect if Gf and g were indeed the same construct. Rather, the findings of this study are more consistent with General Cognitive Ability theory, which predicts that Gc indicators will be the best predictors of future learning and performance. Given that Gc measures demonstrate higher criterion-related validities than Gf measures, Gc measures are likely to be preferred for selection purposes. Further, Gf scores are known to decline with age while Gc scores remain relatively stable over the lifespan. Thus, when used for selection purposes, Gf tests may underpredict the performance of older workers. In contrast, research has shown that Gc measures are predictively unbiased. Additional implications for theory and practice are discussed, along with study limitations and opportunities for future research.