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In this article, we explore the ability of demographic and attitudinal variables to predict student scores on the Quantitative Reasoning for College Science (QuaRCS) Assessment. Variables measured by the assessment include: students' academic choices and plans, attitudes and perceptions regarding mathematics, self-reported effort level, and basic demographics such as age, race/ethnicity, gender and disability status. As in previously published numeracy studies, we find significant score deviations according to gender, race/ethnicity, and disability status; however, the effect size of these correlations pale in comparison to the effect size of affective/attitudinal variables on QuaRCS score. A large number of variables with significant effects on QuaRCS score make the data well-suited to dimension reduction, and Factor Analyses reveal that a majority of affective variables can be collapsed into three underlying factors, which we call numerical self-efficacy, numerical relevancy and academic maturity. These three composite variables alone account for 32.4% of the variance in QuaRCS score. Two additional affective variables - self-reported effort and calculator usage – add 15.9% to the regression model. Together, these five variables account for nearly half of the variance in QuaRCS score. In contrast, academic and basic demographic variables, account for only 0.3% and 0.1% of the remainder, respectively. Furthermore, most demographic variables (including race and gender) do not have a significant effect on the regression model once affective variables have been accounted for.\u

numeracy

The Quantitative Reasoning for College Science (QuaRCS) Assessment 2: Demographic, Academic and Attitudinal Variables as Predictors of Quantitative Ability