Comparison of normalized gain and Cohen�s d for Force Concept Inventory results in an introductory mechanics course

Abstract

At Texas State University, we have been using the Force Concept Inventory (FCI) to assess our introductory mechanics course since the Spring 2011 semester. This provides us with a large data set (N=1,626) on which to perform detailed statistical analysis of student learning. Recent research has found conflicting results in the relationships between normalized gain 〈g〉, Cohen's d, and pretest mean, which might lead to different interpretations of student learning. Specifically, in one study 〈g〉 was found to positively correlate with both pretest mean and pretest standard deviation, whereas Cohen's d did not; in another study, ANOVA showed no connection between 〈g〉 and pretest mean. We will present a comparison of 〈g〉 and Cohen’s d for our data set, and will specifically use these measures to look at performance gaps related to gender and race/ethnicity.