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.

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Creativity commonly refers to the ability to generate ideas, solutions, or insights that are novel yet feasible. The ability to generate creative ideas appears to develop and change from childhood to adulthood. Prior research, although inconsistent, generally indicates that adults perform better than adolescents on the alternative uses task (AUT), a commonly used index of creative ideation. The focus of this study was whether performance could be improved by practicing alternative uses generation. We examined the effectiveness of creative ideation training in adolescents (13–16 years, N = 71) and adults (23–30 years, N = 61). Participants followed one of three types of training, each comprising eight 20-min practice sessions within 2 week time: (1) alternative uses generation (experimental condition: creative ideation); (2) object characteristic generation (control condition: general ideation); (3) rule-switching (control condition: rule-switching). Progression in fluency, flexibility, originality of creative ideation was compared between age-groups and training conditions. Participants improved in creative ideation and cognitive flexibility, but not in general ideation. Participants in all three training conditions became better in fluency and originality on the AUT. With regard to originality, adolescents benefitted more from training than adults, although this was not specific for the creative ideation training condition. These results are interpreted in relation to (a) the different underlying processes targeted in the three conditions and (b) developmental differences in brain plasticity with increased sensitivity to training in adolescents. In sum, the results show that improvement can be made in creative ideation and supports the hypothesis that adolescence is a developmental stage of increased flexibility optimized for learning and explorative behavior.

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Cronbach's (1957) famous division of scientific psychology into two disciplines is still actual 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.

Working memory and inductive reasoning ability each appear related to children's achievement in math and reading. Dynamic measures of reasoning, based on an assessment procedure including feedback, may provide additional predictive value. The aim of this study was to investigate whether working memory and dynamic measures of analogical reasoning are unique predictors of children's concurrent and subsequent reading and math achievement. School children (N = 188, M = 7.1 years, SD = 11 months) were administered a dynamic test of analogical reasoning comprising a pretesttraining-posttest design. Pretest performance measures static reasoning ability, whereas posttest performance and feedback-needs during training are considered dynamic measures. Verbal and visuo-spatial working memories were assessed prior to dynamic testing. Performance on national reading and math achievement tests were gathered at two time points within one school year. A multilevel mixed-effects model indicated that verbal (but not visuo-spatial) working memory and dynamic reasoning measures formed unique predictors of concurrent and subsequent achievement in math and reading. Verbal working memory efficiency and performance on a dynamic test of analogical reasoning were both positively related to math and reading achievement in children in kindergarten, first grade and second grade. Dynamic assessment, in addition to working memory assessment, may be useful for educational psychologists when attempting to gauge children's future school performance.

This study investigates why children who are good at one math skill also perform well on other math tasks and seeks a solution by comparing two influential theories of general intelligence. The g-factor theory (g for 'general intelligence') implies a general math ability that steers all math-related development. In contrast, mutualism theory states that different math skills co-develop, positively influencing each others growth. We examined this with a large longitudinal data set (N ≈ 12.000) that tracked the development of basic (counting ↔ addition) and more advanced (multiplication ↔ division) math skills for a full school year. We used bivariate latent change score models to investigate whether g-factor or mutualism theory provides a better explanation of their co-development. We found that basic and more advanced math skills become more strongly related over time and that co-development is mutually beneficial. Both results support mutualism theory, a dynamic network perspective of cognitive development, where, in this case, growth in a particular math domain positively influences that of other math skills. Our results perhaps reveal the tip of the iceberg when it comes to the intricacies of co-developing math abilities. We discuss the implications of mutualism theory for understanding the dynamics of learning mathematics.

Prior research suggests that adolescence is a time of enhanced sensitivity for practice and learning. In this study we tested the neural correlates of divergent thinking training in 15- to 16-year-old adolescents relative to an age-matched active control group. All participants performed an alternative uses task, a valid measure to test divergent thinking, while functional magnetic resonance imaging (fMRI) images were acquired before and after a training program. In between the 2 scanning sessions the experimental group completed 2 weeks of divergent thinking training (8 sessions) and the control group completed 2 weeks of rule switching training (8 session). A Group × Time interaction demonstrated stable divergent thinking performance for the experimental group, whereas in the control group performance declined. Generating alternative uses (experimental task condition) relative to generating ordinary characteristics of objects (control task condition) was associated with increased activation in the supramarginal gyrus (SMG), angular gyrus (AG), and middle temporal gyrus (MTG). Test-retest analyses showed that within-individuals-activation in these regions was stable over time in both groups. Changes in alternative uses fluency over time, however, were positively associated with changes in superior lateral PFC activation over time. Together, the results indicate that core brain regions for creativity (SMG, AG, and MTG) are consistently recruited in adolescence, and that changes in performance are associated with changes in activation in lateral PFC. (PsycINFO Database Record