Relationships between Prediction Accuracy, Metacognitive Reflection, and Performance in Introductory Genetics Students.

Cognitive scientists have previously shown that students' perceptions of their learning and performance on assessments often do not match reality. This process of self-assessing performance is a component of metacognition, which also includes the practice of thinking about one's knowledge and identifying and implementing strategies to improve understanding. We used a mixed-methods approach to investigate the relationship between students' perceptions of their performance through grade predictions, their metacognitive reflections after receiving their grades, and their actual performance during a semester-long introductory genetics course. We found that, as a group, students do not display better predictive accuracy nor more metacognitive reflections over the semester. However, those who shift from overpredicting to matching or underpredicting also show improved performance. Higher performers are overall more likely to answer reflection questions than lower-performing peers. Although high-performing students are usually more metacognitive in their reflections, an increase in a student's frequency of metacognitive responses over time does not necessarily predict a grade increase. We illustrate several example trends in student reflections and suggest possible next steps for helping students implement better metacognitive regulation.

A global evolutionary and metabolic analysis of human obesity gene risk variants.

It is generally accepted that the selection of gene variants during human evolution optimized energy metabolism that now interacts with our obesogenic environment to increase the prevalence of obesity. The purpose of this study was to perform a global evolutionary and metabolic analysis of human obesity gene risk variants (110 human obesity genes with 127 nearest gene risk variants) identified using genome-wide association studies (GWAS) to enhance our knowledge of early and late genotypes. As a result of determining the mean frequency of these obesity gene risk variants in 13 available populations from around the world our results provide evidence for the early selection of ancestral risk variants (defined as selection before migration from Africa) and late selection of derived risk variants (defined as selection after migration from Africa). Our results also provide novel information for association of these obesity genes or encoded proteins with diverse metabolic pathways and other human diseases. The overall results indicate a significant differential evolutionary pattern for the selection of obesity gene ancestral and derived risk variants proposed to optimize energy metabolism in varying global environments and complex association with metabolic pathways and other human diseases. These results are consistent with obesity genes that encode proteins possessing a fundamental role in maintaining energy metabolism and survival during the course of human evolution.