Scores on cognitive tasks used in intelligence tests correlate positively with each other, that is, they display a positive manifold of correlations. The positive manifold is often explained by positing a dominant latent variable, the g factor, associated with a single quantitative cognitive or biological process or capacity. In this article, a new explanation of the positive manifold based on a dynamical model is proposed, in which reciprocal causation or mutualism plays a central role. It is shown that the positive manifold emerges purely by positive beneficial interactions between cognitive processes during development. A single underlying g factor plays no role in the model. The model offers explanations of important findings in intelligence research, such as the hierarchical factor structure of intelligence, the low predictability of intelligence from early childhood performance, the integration/differentiation effect, the increase in heritability of g, and the Jensen effect, and is consistent with current explanations of the Flynn effect.

How children learn from positive and negative performance feedback lies at the foundation of successful learning and is therefore of great importance for educational practice. In this study, we used functional magnetic resonance imaging (fMRI) to examine the neural developmental changes related to feedback-based learning when performing a rule search and application task. Behavioral results from three age groups (8 -9, 11-13, and 18 -25 years of age) demonstrated that, compared with adults, 8-to 9-year-old children performed disproportionally more inaccurately after receiving negative feedback relative to positive feedback. Additionally, imaging data pointed toward a qualitative difference in how children and adults use performance feedback. That is, dorsolateral prefrontal cortex and superior parietal cortex were more active after negative feedback for adults, but after positive feedback for children (8 -9 years of age). For 11-to 13-year-olds, these regions did not show differential feedback sensitivity, suggesting that the transition occurs around this age. Presupplementary motor area/anterior cingulate cortex, in contrast, was more active after negative feedback in both 11-to 13-year-olds and adults, but not 8-to 9-year-olds. Together, the current data show that cognitive control areas are differentially engaged during feedbackbased learning across development. Adults engage these regions after signals of response adjustment (i.e., negative feedback). Young children engage these regions after signals of response continuation (i.e., positive feedback). The neural activation patterns found in 11-to 13-year-olds indicate a transition around this age toward an increased influence of negative feedback on performance adjustment. This is the first developmental fMRI study to compare qualitative changes in brain activation during feedback learning across distinct stages of development.

The ability to learn from environmental cues is an important contributor to successful performance in a variety of settings, including school. Despite the progress in unraveling the neural correlates of cognitive control in childhood and adolescence, relatively little is known about how these brain regions contribute to learning. In this study, 268 participants aged 8-25 years performed a rule-learning task with performance feedback in a 3T MRI scanner. We examined the development of the frontoparietal network during feedback learning by exploring contributions of age and pubertal development. The pFC showed more activation following negative compared with positive feedback with increasing age. In contrast, our data suggested that the parietal cortex demonstrated a shift from sensitivity to positive feedback in young children to negative feedback in adolescents and adults. These findings were interpreted in terms of separable contributions of the frontoparietal network in childhood to more integrated functions in adulthood. Puberty (testosterone, estradiol, and self-report) did not explain additional variance in neural activation patterns above age, suggesting that development of the frontoparietal network occurs relatively independently from hormonal development. This study presents novel insights into the development of learning, moving beyond a simple frontoparietal immaturity hypothesis.

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The question of how learners’ motivation influences their academic achievement and vice versa has been the subject of intensive research due to its theoretical relevance and important implications for the field of education. Here, we present our understanding of how influential theories of academic motivation have conceptualized reciprocal interactions between motivation and achievement and the kinds of evidence that support this reciprocity. While the reciprocal nature of the relationship between motivation and academic achievement has been established in the literature, further insights into several features of this relationship are still lacking. We therefore present a research agenda where we identify theoretical and methodological challenges that could inspire further understanding of the reciprocal relationship between motivation and achievement as well as inform future interventions. Specifically, the research agenda includes the recommendation that future research considers (1) multiple motivation constructs, (2) behavioral mediators, (3) a network approach, (4) alignment of intervals of measurement and the short vs. long time scales of motivation constructs, (5) designs that meet the criteria for making causal, reciprocal inferences, (6) appropriate statistical models, (7) alternatives to self-reports, (8) different ways of measuring achievement, and (9) generalizability of the reciprocal relations to various developmental, ethnic, and sociocultural groups.

This study investigated the effect of evidence conflicting with preschoolers' naive theory on the patterns of their free exploratory play. The domain of shadow size was used--a relatively complex, ecologically valid domain that allows for reliable assessment of children's knowledge. Results showed that all children who observed conflicting evidence performed an unconfounded informative experiment in the beginning of their play, compared with half of the children who observed confirming evidence. Mainly, these experiments were directed at investigating a dimension that was at the core of children's initial theory. Thus, preschoolers were flexible in the type of experiments they performed, but they were less flexible in the content of their investigations.

Markov models have been used extensively in psychology of learning. Applications of hidden Markov models are rare however. This is partially due to the fact that comprehensive statistics for model selection and model assessment are lacking in the psychological literature. We present model selection and model assessment statistics that are particularly useful in applying hidden Markov models in psychology. These statistics are presented and evaluated by simulation studies for a toy example. We compare AIC, BIC and related criteria and introduce a prediction error measure for assessing goodness-of-fit. In a simulation study, two methods of fitting equality constraints are compared. In two illustrative examples with experimental data we apply selection criteria, fit models with constraints and assess goodness-of-fit. First, data from a concept identification task is analyzed. Hidden Markov models provide a flexible approach to analyzing such data when compared to other modeling methods. Second, a novel application of hidden Markov models in implicit learning is presented. Hidden Markov models are used in this context to quantify knowledge that subjects express in an implicit learning task. This method of analyzing implicit learning data provides a comprehensive approach for addressing important theoretical issues in the field.

ABSTRACT:In this paper, we introduce the Exploratory Behavior Scale (EBS), a quantitative measure of young children's interactivity. More specifically, the EBS is developed from the psychological literature on exploration and play and measures the extent to which preschoolers explore their physical environment. A practical application of the EBS in a science museum is given. The described study was directed at optimizing parent guidance to improve preschoolers' exploration of exhibits in science center NEMO. In Experiment 1, we investigated which adult coaching style resulted in the highest level of EXPLORATORY BEHAVIOR SCALE 795exploratory behavior at two exhibits. In Experiment 2, we investigated whether informing parents about an effective way of coaching influenced preschoolers' exploratory behavior at two exhibits. The results of the study demonstrate the added value of the EBS in visitor behavior research: compared to existing global measures of visitor interactivity; the EBS adds information about the quality of the hands-on behavior. Compared to existing detailed measures of visitor interactivity, the EBS has the advantage of being applicable in different museum settings and enabling comparisons between exhibits or exhibitions. In addition, the EBS allows for quantification of unanticipated behavior.C 2010 Wiley Periodicals, Inc. Sci Ed 94: 794 -809, 2010