J. Intell., Volume 5, Issue 2 (June 2017) – 17 articles

Although recent developmental studies exploring the predictive power of intelligence and working memory (WM) for educational achievement in children have provided evidence for the importance of both variables, findings concerning the relative impact of IQ and WM on achievement have been inconsistent. Whereas IQ has been identified as the major predictor variable in a few studies, results from several other developmental investigations suggest that WM may be the stronger predictor of academic achievement. In the present study, data from the Munich Longitudinal Study on the Genesis of Individual Competencies (LOGIC) were used to explore this issue further. The secondary data analysis included data from about 200 participants whose IQ and WM was first assessed at the age of six and repeatedly measured until the ages of 18 and 23. Measures of reading, spelling, and math were also repeatedly assessed for this age range. Both regression analyses based on observed variables and latent variable structural equation modeling (SEM) were carried out to explore whether the predictive power of IQ and WM would differ as a function of time point of measurement (i.e., early vs. late assessment). As a main result of various regression analyses, IQ and WM turned out to be reliable predictors of academic achievement, both in early and later developmental stages, when previous domain knowledge was not included as additional predictor. The latter variable accounted for most of the variance in more comprehensive regression models, reducing the impact of both IQ and WM considerably. Findings from SEM analyses basically confirmed this outcome, indicating IQ impacts on educational achievement in the early phase, and illustrating the strong additional impact of previous domain knowledge on achievement at later stages of development. Full article

The aim of this paper is to provide a parsimonious account of developmental and individual differences in intelligence (measured as g). The paper proposes a Differential–Developmental Model (DDM), which focuses on factors common to intelligence and cognitive development (e.g., mental speed and attention lapses). It also proposes a complementary method based on Jensen’s box, a chronometric device. The device systematically varies task complexity, and separates two components of mental speed that differentially predict intelligence and cognitive development (reaction time and movement time). The paper reviews key assumptions of DDM, preliminary findings relevant to DDM, and future research on DDM. Full article

In common with most, if not all, papers in this special issue, I will argue that understanding the nature of developmental change and individual differences in intelligence requires a theory of the mechanisms underlying both factors. Insofar as these mechanisms constitute part of the fundamental architecture of cognition, this is also an exercise in unifying the discipline and research on intelligence in both children and adults. However, I argue that a variety of data support a theory suggesting that developmental change is the province of mechanisms commonly regarded as components of executive functioning or cognitive control, whereas individual differences are constrained by the speed of information processing. Perhaps paradoxically, this leads to the conclusion that Binet’s fundamental insight—that children’s increasing ability to solve problems of increasing difficulty could generate a single scale of intelligence—is wrong. Compounding the paradox, this means that mental age and IQ are not simply two different ways of expressing the same thing, but are related to two different dimensions of g itself. Full article

Integration/differentiation of mental processes is major mechanism of development. Developmental theories ascribe intellectual development to it. In psychometric theory, Spearman’s law of diminishing returns postulates that increasing g allows increasing differentiation of cognitive abilities, because increased mental power allows variable investment in domain-specific learning. Empirical evidence has been inconsistent so far, with some studies supporting and others contradicting this mechanism. This state of affairs is due to a developmental phenomenon: Both differentiation and strengthening of relations between specific processes and g may happen but these changes are phase-specific and ability-specific, depending upon the developmental priorities in the formation of g in each phase. We present eight studies covering the age span from 4 to 85 years in support of this phenomenon. Using new powerful modeling methods we showed that differentiation and binding of mental processes in g occurs in cycles. Specific processes intertwine with g at the beginning of cycles when they are integrated into it; when well established, these processes may vary with increasing g, reflecting its higher flexibility. Representational knowledge, inductive inference and awareness of it, and grasp of logical constraints framing inference are the major markers of g, first intertwining with in their respective cycles and differentiating later during the periods of 2–6, 7–11, and 11–20 years, respectively. The implications of these findings for an overarching cognitive developmental/differential theory of human mind are discussed. Full article

Findings of studies on the unique effects of reasoning and working memory regarding complex problem solving are inconsistent. To find out if these inconsistencies are due to a lack of symmetry between the studies, we reconsidered the findings of three published studies on this issue, which resulted in conflicting conclusions regarding the inter-relations between reasoning, working memory, and complex problem solving. This was achieved by analysing so far unpublished problem solving data from the study of Bühner, Krumm, Ziegler, and Plücken (2006) (N= 124). One of the three published studies indicated unique effects of working memory and reasoning on complex problem solving using aggregated scores, a second study found no unique contribution of working memory using only figural scores, and a third study reported a unique influence only for reasoning using only numerical scores. Our data featured an evaluation of differences across content facets and levels of aggregation of the working memory scores. Path models showed that the results of the first study could not be replicated using content aggregated scores; the results of the second study could be replicated if only figural scores were used, and the results of the third study could be obtained by using only numerical scores. For verbal content, none of the published results could be replicated. This leads to the assumption that not only symmetry is an issue when correlating non-symmetrical data, but that content also has to be taken into account when comparing different studies on the same topic. Full article

Working memory capacity (WMC) and reasoning abilities—as assessed by figural matrices tests—are substantially correlated. It is controversially discussed whether this correlation is only caused by controlled attention or also by storage capacity. This study aims at investigating storage of partial solutions as a possible mechanism by which storage capacity may contribute to solving figural matrices tests. For this purpose, we analyzed how an experimental manipulation of storage demands changes the pattern of correlations between WMC and performance in a matrix task. We manipulated the storage demands by applying two test formats: one providing the externalization of partial solutions and one without the possibility of externalization. Storage capacity was assessed by different types of change detection tasks. We found substantial correlations between storage capacity and matrices test performance, but they were of comparable size for both test formats. We take this as evidence that the necessity to store partial solutions is not the limiting factor which causes the association between storage capacity and matrices test. It is discussed how this approach can be used to investigate alternative mechanisms by that storage may influence performance in matrices tests. Full article

Business owners are faced with complex problems and are required to make decisions on a daily basis. The purpose of this study was to investigate complex problem solving (CPS) between experts and novices and to explore the competing theories of expert-rigidity versus expert-adaptability, as part of exploring which theory better explains crystallized intelligence. Participants were 140 business owners, business management undergraduate students and psychology students. Each participant managed a highly complex simulated chocolate company. Decisions and systems data were automatically saved in log files. Results revealed that small business owners performed best, followed by business students and then psychology students. A process analysis revealed that experts compared to novices spent more time initially exploring the complex situation. Experts were found to have greater flexibility in their decisions, having made the most personnel and advertising changes in response to situational demands. Adaptability and flexibility were predictive of performance, with results supporting the adaptability/flexibility theory of expertise. This study shows the influence of expertise on complex problem solving and the importance of flexibility when solving dynamic business problems. Complex business simulations are not only useful tools for research, but could also be used as tools in training programs teaching decision making and problem solving strategies. Full article

Evidence suggests that cytokines may be one of the major factors influencing cognitive development in those with autism spectrum disorder (ASD). To shed light on the neural and cognitive mechanisms of ASD, we investigated the association between peripheral cytokine levels and cognitive profiles in children with ASD. The serum levels of 10 cytokines (granulocyte macrophage colony-stimulating factor, interferon (IFN)-γ, interleukin (IL)-1β, IL-2, IL-4, IL-5, IL-6, IL-8, IL-10, and tumor necrosis factor-α) were examined in 14 children with ASD using the Human Ultrasensitive Cytokine Magnetic 10-Plex Panel for the Luminex platform. The Wechsler Intelligence Scale for Children (WISC) was administered to each subject, and the relationships between WISC scores and serum levels of the cytokines were examined. The full-scale intelligence quotient (IQ) was significantly negatively correlated with the levels of IL-6 (Spearman’s rank, p < 0.0001, false discovery rate q < 0.01). The levels of IL-6 and IFN-γ showed significant negative correlations with the verbal comprehension index (p < 0.001, q < 0.01) and working memory index (p < 0.01, q < 0.05), respectively. No other cytokines were significantly correlated with full-scale IQ or with any of the subscale scores of the WISC. The present results suggest negative correlations of IL-6 and IFN-γ levels with cognitive development of children with ASD. Our preliminary findings add to the evidence that cytokines may play a role in the neural development in ASD. Full article

The concept of intelligence encompasses the mental abilities necessary to survival and advancement in any environmental context. Attempts to grasp this multifaceted concept through a relatively simple operationalization have fostered the notion that individual differences in intelligence can often be expressed by a single score. This predominant position has contributed to expect intelligence profiles to remain substantially stable over the course of ontogenetic development and, more generally, across the life-span. These tendencies, however, are biased by the still limited number of empirical reports taking a developmental perspective on intelligence. Viewing intelligence as a dynamic concept, indeed, implies the need to identify full developmental trajectories, to assess how genes, brain, cognition, and environment interact with each other. In the present paper, we describe how a neuroconstructivist approach better explains why intelligence can rise or fall over development, as a result of a fluctuating interaction between the developing system itself and the environmental factors involved at different times across ontogenesis. Full article

Working memory (WM) includes short-term storage and executive processing of information. WM has been suggested to be one of the key concepts to explain individual differences in fluid intelligence (Gf). However, only a few studies have investigated the association of the two different aspects of WM in relation to Gf. Furthermore, even fewer studies have included children. Therefore, we first investigated the inter-relations between the WM aspects (verbal and visual-spatial storage, verbal and visual-spatial executive processing). Second, we explored the relation between a general WM factor and Gf. Third, we analyzed the relations between the different WM aspects and Gf while we controlled for common variance among all WM tasks. Nine- to 11-year olds had to solve simple and complex span tasks. Correlations and structural equation modeling techniques were used to examine these relations. Most inter-relations among simple and complex spans were found to be substantial and positive. The general WM factor was related to Gf. Furthermore, after controlling for common variance among all WM tasks, individual differences in verbal storage, visual-spatial storage and verbal processing still uniquely related to Gf. Visual-spatial processing, however, was not related to Gf. Results are discussed in terms of underlying mechanisms. Full article

Cronbach’s (1957) famous division of scientific psychology into two disciplines is still apparent for the fields of cognition (general mechanisms) and intelligence (dimensionality of individual differences). The welcome integration of the two fields requires the construction of mechanistic models of cognition and cognitive development that explain key phenomena in individual differences research. In this paper, we argue that network modeling is a promising approach to integrate the processes of cognitive development and (developing) intelligence into one unified theory. Network models are defined mathematically, describe mechanisms on the level of the individual, and are able to explain positive correlations among intelligence subtest scores—the empirical basis for the well-known g-factor—as well as more complex factorial structures. Links between network modeling, factor modeling, and item response theory allow for a common metric, encompassing both discrete and continuous characteristics, for cognitive development and intelligence. Full article

In this paper we discuss how the lack of a common framework in Complex Problem Solving (CPS) creates a major hindrance to a productive integration of findings and insights gained in its 40+-year history of research. We propose a framework that anchors complexity within the tri-dimensional variable space of Person, Task and Situation. Complexity is determined by the number of information cues that need to be processed in parallel. What constitutes an information cue is dependent on the kind of task, the system or CPS scenario used and the task environment (i.e., situation) in which the task is performed. Difficulty is conceptualised as a person’s subjective reflection of complexity. Using an existing data set of N = 294 university students’ problem solving performances, we test the assumption derived from this framework that particular system features such as numbers of variables (NoV) or numbers of relationships (NoR) are inappropriate indicators of complexity. We do so by contrasting control performance across four systems that differ in these attributes. Results suggest that for controlling systems (task) with semantically neutral embedment (situation), the maximum number of dependencies any of the output variables has is a promising indicator of this task’s complexity. Full article

Research on intelligence, mainly based on correlational and factor-analytical work, research on cognitive development, and research in cognitive psychology are not to be opposed as has traditionally been the case, but are pursuing the same goal, that is, understand how the human being adapts to his/her own, complex environment. Each tradition of research has been focusing on one source of variation, namely situational differences for cognitive psychology, individual differences for psychometrics, and age differences for developmental psychology, while usually neglecting the two other sources of variation. The present paper compares those trends of research with respect to the constructs of fluid intelligence, working memory, processing speed, inhibition, and executive schemes. Two studies are very briefly presented to support the suggestion that tasks issued from these three traditions are very similar, if not identical, and that theoretical issues are also similar. We conclude in arguing that a unified vision is possible, provided one is (a) interested in the underlying processes and not only in the experimental variations of conditions; (b) willing to adopt a multidimensional view according to which few general mechanisms are at work, such as working memory or processing capacity, inhibition, and executive schemes; and (c) granting a fundamental role to individual differences. Full article

A frequently reported finding is that general mental ability (GMA) is the best single psychological predictor of job performance. Furthermore, specific abilities often add little incremental validity beyond GMA, suggesting that they are not useful for predicting job performance criteria once general intelligence is accounted for. We review these findings and their historical background, along with different approaches to studying the relative influence of g and narrower abilities. Then, we discuss several recent studies that used relative importance analysis to study this relative influence and that found that specific abilities are equally good, and sometimes better, predictors of work performance than GMA. We conclude by discussing the implications of these findings and sketching future areas for research. Full article

The effects of aging on response time were examined in a paper-based lexical-decision experiment with younger (age 18–36) and older (age 64–75) adults, applying Ratcliff’s diffusion model. Using digital pens allowed the paper-based assessment of response times for single items. Age differences previously reported by Ratcliff and colleagues in computer-based experiments were partly replicated: older adults responded more conservatively than younger adults and showed a slowing of their nondecision components of RT by 53 ms. The rates of evidence accumulation (drift rate) showed no age-related differences. Participants with a higher score in a vocabulary test also had higher drift rates. The experiment demonstrates the possibility to use formal processing models with paper-based tests. Full article

The current study investigated a longitudinal data set of 4790 adults examining a set of socio-demographic and psychological factors that influence adult financial well-being. Parental social status (at birth), childhood intelligence and self-esteem (at age 10), locus of control (at age 16), psychological distress (age 30), educational qualifications (age 34), current occupation, weekly net income, house ownership status, and number of rooms (all measured at age 38 years) were examined. Structural Equation Modelling showed that childhood intelligence, locus of control, education and occupation were all independent predictors of adult financial well-being for both men and women. Parental social status and psychological distress were also significant predictors of the outcome variable for men, but not for women. Whereas for women, in comparison to men, the effects of current occupation and childhood intelligence on the outcome variable appeared to be stronger. The strongest predictor of adult financial well-being was current occupational prestige, followed by educational achievement. The gender deferential of financial well-being indicators and its implications are discussed. Full article

Collaborative problem solving (ColPS) proficiency was developed as a new assessment for the Programme for International Student Assessment (PISA) in the 2015 international evaluation of student skills and knowledge. The assessment framework defined by the PISA ColPS 2015 expert group crossed three major collaboration processes with four problem solving processes that were adopted from the PISA 2012 individual problem solving assessment to form a matrix of 12 specific skills. The three major collaboration processes are (1) establishing and maintaining shared understanding; (2) taking appropriate action; and (3) establishing and maintaining team organization. The four problem solving processes are exploring and understanding the problem, representing and formulating the problem, planning and executing strategies, and monitoring and reflecting on the problem-solving activities. This article discusses how the problem-solving dimension was integrated with the collaboration dimension. We also discuss how computer agents were involved in the PISA ColPS 2015 assessment in order to ensure a satisfactory assessment of collaborative problem solving. Examples of the use of agents to assess ColPS are provided in the context of a released PISA item and a project conducted in Taiwan. Full article