Trait emotional intelligence and behavioral problems among adolescents: A cross-informant design

This study examined how self and parental ratings of trait emotional intelligence (trait EI), relate to self and parental ratings of internalizing and externalizing problems. A total of 263 adolescents between 13 and 17 years and their parents participated in the study, completing two forms of the Trait Emotional Intelligence Questionnaire (TEIQue-AF and TEIQue-360°) and the Child Behavior CheckList (CBCL-YSR and CBCL-parents’ report). Results revealed a strong correspondence between father and mother ratings, especially for externalizing problems. A doubly MANOVA, with gender as the between-subjects variable, rating source (father, mother, and adolescent) as the within-subjects variable, and the four trait EI factors as dependent variables revealed a significant effect of ratings. Both fathers and mothers attributed higher Well-being and Self-control to their children than the children attributed to themselves. The findings showed that while multisource ratings of trait EI generally converge, they are differentially predictive of external criteria.     

An effective metacognitive strategy: learning by doing and explaining with a computer‐based Cognitive Tutor

Recent studies have shown that self‐explanation is an effective metacognitive strategy, but how can it be leveraged to improve students' learning in actual classrooms? How do instructional treatments that emphasizes self‐explanation affect students' learning, as compared to other instructional treatments? We investigated whether self‐explanation can be scaffolded effectively in a classroom environment using a Cognitive Tutor, which is intelligent instructional software that supports guided learning by doing. In two classroom experiments, we found that students who explained their steps during problem‐solving practice with a Cognitive Tutor learned with greater understanding compared to students who did not explain steps. The explainers better explained their solutions steps and were more successful on transfer problems. We interpret these results as follows: By engaging in explanation, students acquired better‐integrated visual and verbal declarative knowledge and acquired less shallow procedural knowledge. The research demonstrates that the benefits of self‐explanation can be achieved in a relatively simple computer‐based approach that scales well for classroom use.