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The influence of parental beliefs and behaviors on children's math confidence and performance is well documented, but few studies examine these associations over time, or in large samples of Latino/a families. This study used longitudinal data from 247 (114 sons and 133 daughters) mother-child dyads to examine whether maternal math gender stereotypes and math involvement predict changes in the mothers' behavior or changes in the child's perceived math competence. Maternal math gender stereotypes when children were in fifth grade predicted decreases in mothers' involvement in their daughter's math homework from fifth to sixth grade. Greater maternal math involvement in fifth grade predicted increases in sons' and daughters' perceptions of math ability from fifth to sixth grades.

Data collected from partners in a dyadic instructional setting are, by definition, not statistically independent. As a consequence, conventional parametric statistical analyses of change and influence carry considerable risk of bias. In this article, we illustrate a strategy to overcome this obstacle: the longitudinal actor-partner interdependence model (APIM). Participants included 60 girls and 100 boys enrolled in public middle schools, who ranged in age from 10 to 14 at the outset. Students worked in pairs assigned by teachers. At the beginning and end of the instructional period, students completed surveys rating the degree to which the partner was a friend, confidence in one's own computing skills, and computer programming knowledge. APIM analyses revealed partner influence over the acquisition of computer programming skills among friends but not nonfriends. Students with higher initial levels of confidence in their own computing skills were more apt to be influenced by friends. This association was especially strong when confident partners were paired with friends who knew relatively more about computer programming.