What are the metacognitive costs of young children’s overconfidence?

Children typically hold very optimistic views of their own skills but so far, only a few studies have investigated possible correlates of the ability to predict performance accurately. Therefore, this study examined the role of individual differences in performance estimation accuracy as a global metacognitive index for different monitoring and control skills (item-level judgments of learning [JOLs] and confidence judgments [CJs]), metacognitive control processes (allocation of study time and control of answers), and executive functions (cognitive flexibility, inhibition, working memory) in 6-year-olds (N=93). The three groups of under estimators, realists and over estimators differed significantly in their monitoring and control abilities: the under estimators outperformed the over estimators by showing a higher discrimination in CJs between correct and incorrect recognition. Also, the under estimators scored higher on the adequate control of incorrectly recognized items. Regarding the interplay of monitoring and control processes, under estimators spent more time studying items with low JOLs, and relied more systematically on their monitoring when controlling their recognition compared to over estimators. At the same time, the three groups did not differ significantly from each other in their executive functions. Overall, results indicate that differences in performance estimation accuracy are systematically related to other global and item-level metacognitive monitoring and control abilities in children as young as six years of age, while no meaningful association between performance estimation accuracy and executive functions was found

The microbiome beyond the horizon of ecological and evolutionary theory

The ecological and evolutionary study of community formation, diversity, and stability is rooted in general theory and reinforced by decades of system-specific empirical work. Deploying these ideas to study the assembly, complexity, and dynamics of microbial communities living in and on eukaryotes has proved seductive, but challenging. The success of this research endeavour depends on our capacity to observe and characterize the distributions, abundances, and functional traits of microbiota, representing an array of technical and analytical challenges. Furthermore, a number of unique characteristics of microbial species, such as horizontal gene transfer, the production of public goods, toxin and antibiotic production, rapid evolution, and feedbacks between the microbiome and its host, are not easily accommodated by current ecological and evolutionary theory. Here we highlight potential pitfalls in the application of existing theoretical tools without careful consideration of the unique complexities of the microbiome, focusing particularly on the issue of human health, and anchoring our discussion in existing empirical evidence