J. Intell., Volume 5, Issue 3 (September 2017) – 5 articles

A cross-lagged panel analysis of Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV) intelligence test scores and reading and math achievement test scores of 337 students twice assessed for special education eligibility across a test-retest interval of 2.85 years was conducted. General intelligence (g) was loaded by the four WISC-IV factor index scores whereas reading and math were composite scores. After confirming measurement invariance, it was found that g, reading, and math were stable across time and synchronously correlated. The cross-lagged paths from g at time 1 to reading and math at time 2 (0.26 and 0.39, respectively) were both significantly greater than zero whereas the paths from reading and math at time 1 to g at time 2 (0.03 and 0.23, respectively) were not statistically significant. Given this pattern of relationships and extant research on the correlates of general intelligence, it was tentatively inferred that general intelligence was the temporal precursor to reading and math achievement. Full article

This special issue aimed to contribute to the unification of two disciplines focusing on cognition and intelligence: the psychology of cognitive development and the psychology of intelligence. The general principles of the organization and development of human intelligence are discussed first. Each paper is then summarized and discussed vis-à-vis these general principles. The implications for major theories of cognitive development and intelligence are briefly discussed. Full article

In two studies, we examined the convergent and discriminant validation of a new assessment of scientific reasoning that could be used for graduate admissions in psychology, educational psychology, human development, and in the psychological sciences more generally. The full assessment ultimately consisted of tests of generating hypotheses, generating experiments, drawing conclusions, serving as a reviewer of a scientific article, and serving as an editor of a scientific journal. The tests had generally good convergent-discriminant validity. Certain socially defined ethnic/racial group differences were observed. Full article

Complex problem solving (CPS) has emerged over the past several decades as an important construct in education and in the workforce. We examine the relationship between CPS and general fluid ability (Gf) both conceptually and empirically. A review of definitions of the two factors, prototypical tasks, and the information processing analyses of performance on those tasks suggest considerable conceptual overlap. We review three definitions of CPS: a general definition emerging from the human problem solving literature; a more specialized definition from the “German School” emphasizing performance in many-variable microworlds, with high domain-knowledge requirements; and a third definition based on performance in Minimal Complex Systems (MCS), with fewer variables and reduced knowledge requirements. We find a correlation of 0.86 between expert ratings of the importance of CPS and Gf across 691 occupations in the O*NET database. We find evidence that employers value both Gf and CPS skills, but CPS skills more highly, even after controlling for the importance of domain knowledge. We suggest that this may be due to CPS requiring not just cognitive ability but additionally skill in applying that ability in domains. We suggest that a fruitful future direction is to explore the importance of domain knowledge in CPS. Full article

The factor structure of mental abilities has most often been depicted using a higher-order model. Under this model, general mental ability (g) is placed at the top of a pyramid, with “loading” arrows going from it to the other factors of intelligence, which in turn go to subtest scores. In contrast, under the bifactor model (also known as the nested factors/direct hierarchical model), each subtest score has its own direct loading on g; the non-g factors (e.g., the broad abilities) do not mediate the relationships of the subtest scores with g. Here we summarized past research that compared the fit of higher-order and bifactor models using confirmatory factor analysis (CFA). We also analyzed additional archival datasets to compare the fit of the two models. Using a total database consisting of 31 test batteries, 58 datasets, and 1,712,509 test takers, we found stronger support for a bifactor model of g than for the traditional higher-order model. Across 166 comparisons, the bifactor model had median increases of 0.076 for the Comparative Fit Index (CFI), 0.083 for the Tucker-Lewis Index (TLI), and 0.078 for the Normed Fit Index (NFI) and decreases of 0.028 for the root mean square error of approximation (RMSEA) and 1343 for the Akaike Information Criterion (AIC). Consequently, researchers should consider using bifactor models when conducting CFAs. The bifactor model also makes the unique contributions of g and the broad abilities to subtest scores more salient to test users. Full article