Predicting Mathematics Performance: A Structural Equation Model

Abstract

The relationships among personality and socialization factors that may contribute to mathematics performance were investigated using structural equation modeling. Five nested models were examined: a full model, a mediational model, a model eliminating the mediator, a regression model, and a model combining the significant paths from other models. Preliminary analyses (i.e., MANOVAS, follow-up univariate ANOVAS) revealed that men reported significantly higher math self-efficacy than women. Evaluation of the structural models identified the full model as the best representation of the data. This model examined the relationships among gender, gender schema, math anxiety, math self-efficacy, math attitude, math experience, math socialization, cognitive mediation, and math performance. Its hypothesis that direct paths from independent constructs to math performance would not be significant and that the direct paths to and from general ability would be crucial was supported. The full model accounted for 57% of the variance in math performance and 30% of the variance in general ability. These results suggest that the relationships among these variables function through the mediation of general ability. Interviews conducted with a small sub-set of the college-aged participants emphasized the role of elementary through high school teachers. This research clarifies conflicting findings concerning the predictors of math performance; specifically refuting the often made claim that men are inherently better at math; suggesting that teachers' and parents' attitudes about children's math abilities may contribute to the development of strong math self-efficacy and a lessening of math anxiety, particularly pointing to the need for teachers to express equal math expectations for both boys and girls.