Gender differences and similarities in the relations of key constructs in Eccles and colleagues' (Wigfield & Eccles, 2000) model of achievement were examined as predictors of math grades and enrollment intentions for Grade 9 boys (n = 263) and girls (n = 277). A number of gender similarities were found, particularly in the prediction of math grades. There were, however, two gender-specific paths: for girls, a direct path from competence beliefs to enrollment intentions, and for boys, a direct path from prior math grades to enrollment intentions. In addition, for boys, the path from utility value to enrollment intentions was stronger than it was for girls. These differential predictive patterns were found even though girls and boys reported similar levels of math utility and girls had lower math competence beliefs. For girls, competence beliefs were a significant predictor of both intentions and current math grades, which indicates the central role of competence beliefs.
This study examined social and personal concomitants of exceptional academic capability in the context of various educational settings. Students in Grades 5, 8, and 10 participated in the study. At each grade level, there were students in classes for the gifted (self-contained gifted), gifted students in regular classes (integrated gifted), and classmates of the integrated gifted (matched and random controls). Subjects completed self-report scales of social competence and feelings about school. Peer nominations for social competence were also obtained from children in the integrated classes. The integrated gifted children at all three grade levels had higher scores for academic self-concept than the other groups; there were no differences in social or physical selfconcept. In Grade 5 only, the integrated gifted were rated by their classmates as higher in social competence than were controls. Although there were no significant differences among groups in terms of attitude towards school, feelings toward school became less positive as age increased.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.