J. Intell., Volume 6, Issue 4 (December 2018) – 10 articles

We present three studies which investigated the relations between cognition and personality from 7 to 20 years of age. All three studies showed that general cognitive ability and the general factor of personality are significantly related throughout this age span. This relation was expressed in several ways across studies. The first investigated developmental relations between three reasoning domains (inductive, deductive, and scientific) and Eysenck’s four personality dimensions in a longitudinal-sequential design where 260 participants received the cognitive tests three times, and the personality test two times, covering the span from 9 to 16 years. It was found that initial social likeability significantly shapes developmental momentum in cognition and vice versa, especially in the 9- to 11-year period. The second study involved 438 participants from 7 to 17 years, tested twice on attention control, working memory, reasoning in different domains, and once by a Big Five Factors inventory. Extending the findings of the first, this study showed that progression in reasoning is affected negatively by conscientiousness and positively by openness, on top of attention control and working memory influences. The third study tested the relations between reasoning in several domains, the ability to evaluate one’s own cognitive performance, self-representation about the reasoning, the Big Five, and several aspects of emotional intelligence, from 9 to 20 years of age (N = 247). Network, hierarchical network, and structural equation modeling showed that cognition and personality are mediated by the ability of self-knowing. Emotional intelligence was not an autonomous dimension. All dimensions except emotional intelligence influenced academic performance. A developmental model for mind-personality relations is proposed. Full article

Research integrating cognitive abilities and personality has focused on the role of personality traits. We propose a theory on the role of intraindividual variability of personality states (hereafter state variability) on perspective taking, in particular, the ability to infer other peoples’ mental states. First, we review the relevant research on personality psychology and social cognition. Second, we propose two complementary routes by which state variability relates to anchoring and adjustment in perspective taking. The first route, termed ego-dispersion, suggests that an increased state variability decreases egocentric bias, which reduces anchoring. The second route, termed perspective-pooling, suggests that an increased state variability facilitates efficient adjustment. We also discuss how our theory can be investigated empirically. The theory is rooted in an ecological interpretation of personality and social cognition, and flags new ways for integrating these fields of research. Full article

Personality and intelligence have a long history in applied psychology, with research dating back more than 100 years. In line, early developments in industrial-organizational psychology were largely founded on the predictive power of personality and intelligence measures vis-à-vis career-related outcomes. However, despite a wealth of evidence in support of their utility, the concepts, theories, and measures of personality and intelligence are still widely underutilized in organizations, even when these express a commitment to making data-driven decisions about employees and leaders. This paper discusses the value of personality and intelligence to understand individual differences in career potential, and how to increase the adoption of theories and tools for evaluating personality and intelligence in real-world organizational contexts. Although personality and intelligence are distinct constructs, the assessment of career potential is incomplete without both. Full article

Previous research has shown that psychometrically assessed cognitive abilities are predictive of achievements in science, technology, engineering and mathematics (STEM) even in highly selected samples. Spatial ability, in particular, has been found to be crucial for success in STEM, though its role relative to other abilities has been shown mostly when assessed years before entering higher STEM education. Furthermore, the role of spatial ability for mathematics in higher STEM education has been markedly understudied, although math is central across STEM domains. We investigated whether ability differences among students who entered higher STEM education were predictive of achievements during the first undergraduate year. We assessed 317 undergraduate students in Switzerland (150 from mechanical engineering and 167 from math-physics) on multiple measures of spatial, verbal and numerical abilities. In a structural equation model, we estimated the effects of latent ability factors on students’ achievements on a range of first year courses. Although ability-test scores were mostly at the upper scale range, differential effects on achievements were found: spatial ability accounted for achievements in an engineering design course beyond numerical, verbal and general reasoning abilities, but not for math and physics achievements. Math and physics achievements were best predicted by numerical, verbal and general reasoning abilities. Broadly, the results provide evidence for the predictive power of individual differences in cognitive abilities even within highly competent groups. More specifically, the results suggest that spatial ability’s role in advanced STEM learning, at least in math-intensive subjects, is less critical than numerical and verbal reasoning abilities. Full article

Research suggests that the relation of mental speed with working memory capacity (WMC) depends on complexity and scoring methods of speed tasks and the type of task used to assess capacity limits in working memory. In the present study, we included conventional binding/updating measures of WMC as well as rapid serial visual presentation paradigms. The latter allowed for a computation of the attentional blink (AB) effect that was argued to measure capacity limitations at the encoding stage of working memory. Mental speed was assessed with a set of tasks and scored by diverse methods, including response time (RT) based scores, as well as ex-Gaussian and diffusion model parameterization. Relations of latent factors were investigated using structure equation modeling techniques. RT-based scores of mental speed yielded substantial correlations with WMC but only weak relations with the AB effect, while WMC and the AB magnitude were independent. The strength of the speed-WMC relation was shown to depend on task type. Additionally, the increase in predictive validity across RT quantiles changed across task types, suggesting that the worst performance rule (WPR) depends on task characteristics. In contrast to the latter, relations of speed with the AB effect did not change across RT quantiles. Relations of the model parameters were consistently found for the ex-Gaussian tau parameter and the diffusion model drift rate. However, depending on task type, other parameters showed plausible relations as well. The finding that characteristics of mental speed tasks determined the overall strength of relations with WMC, the occurrence of a WPR effect, and the specific pattern of relations of model parameters, implies that mental speed tasks are not exchangeable measurement tools. In spite of reflecting a general factor of mental speed, different speed tasks possess different requirements, supporting the notion of mental speed as a hierarchical construct. Full article

An article’s keywords are distinct because they represent what authors feel are the most important words in their papers. Combined, they can even shed light on which research topics in a field are popular (or less so). Here we conducted bibliometric keyword analyses of articles published in the journal, Intelligence (2000–2016). The article set comprised 916 keyword-containing papers. First, we analyzed frequencies to determine which keywords were most/least popular. Second, we analyzed Web of Science (WOS) citation counts for the articles listing each keyword and we ran regression analyses to examine the effect of keyword categories on citation counts. Third, we looked at how citation counts varied across time. For the frequency analysis, “g factor”, “psychometrics/statistics”, and “education” emerged as the keywords with the highest counts. Conversely, the WOS citation analysis showed that papers with the keywords “spatial ability”, “factor analysis”, and “executive function” had the highest mean citation values. We offer tentative explanations for the discrepant results across frequencies and citations. The analysis across time revealed several keywords that increased (or decreased) in frequency over 17 years. We end by discussing how bibliometric keyword analysis can detect research trends in the field, both now and in the past. Full article

The overwhelming majority of the research on the historical impact of IQ in special education has focused on children with cognitive disorders. Far less is known about its role for students with emotional concerns, including Emotional Disturbance (ED). To address this gap, the current study examined IQ trends in ED children who were repeatedly tested on various combinations of the WISC, WISC-R, and WISC-III using a geographically diverse, longitudinal database of special education evaluation records. Findings on test/re-test data revealed that ED children experienced IQ trends that were consistent with previous research on the Flynn effect in the general population. Unlike findings associated with test/re-test data for children diagnosed with cognitive disorders, however, ED re-diagnoses were unaffected by these trends. Specifically, ED children’s declining IQ scores when retested on newer norms did not result in changes in their ED diagnosis. The implications of this unexpected finding are discussed within the broader context of intelligence testing and special education policies. Full article