Fluid intelligence as a predictor of learning: a longitudinal multilevel approach applied to math

Abstract

The association between fluid intelligence and inter-individual differences was investigated using multilevel growth curve modeling applied to data measuring intra-individual improvement on math achievement tests. A sample of 166 students (88 boys and 78 girls), ranging in age from 11 to 14 (M = 12.3, SD = 0.64), was tested. These individuals took four math achievement tests, which were vertically equated via Item Response Theory, at the beginning and end of the seventh and eighth grade. The cognitive abilities studied were Numerical Reasoning, Abstract Reasoning, Verbal Reasoning, and Spatial Reasoning (as measured by the Differential Reasoning Test). The general cognitive factor was significantly associated with the parameters of initial level (intercept) and rate of change (slope). A high level of intelligence was associated with higher initial scores, as well as a steeper rise in math scores across the two years.