The relative importance of predictors of math and science achievement: An opportunity–propensity analysis

In the present study, the authors propose a new framework that integrates literature on achievement, supports the testing of novel hypotheses, and stresses the importance of examining a large number of factors in the same study. This framework assumes that high achievement is a function of three categories of factors: (a) opportunity factors (e.g., coursework), (b) propensity factors (e.g., prerequisite skills, motivation), and (c) distal factors (e.g., SES). A secondary analysis of the National Longitudinal Educational Study (NELS:88) using hierarchical regression and structural equation modeling revealed that 58–81% of the variance in achievement was explained by family variables and specific opportunity and propensity factors. The findings are discussed in terms of their potential implications for intervention efforts.