The Quantitative Reasoning for College Science (QuaRCS) Assessment 2: Demographic, Academic and Attitudinal Variables as Predictors of Quantitative Ability
quantitative literacy, science literacy, assessment
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.
Follette, Katherine, Sanlyn Buxner, Erin Dokter, Donald McCarthy, Beau Vezino, Laci Brock, and Edward Prather. "The Quantitative Reasoning for College Science (QuaRCS) Assessment 2: Demographic, Academic and Attitudinal Variables as Predictors of Quantitative Ability." Numeracy 10, Iss. 1 (2017): Article 5. DOI: http://dx.doi.org/10.5038/1936-46188.8.131.52
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