Toward Assessing Understanding of Prerequisite Knowledge of Sampling Distributions

• Activity Number: 40
• Type: Contributed
• Date/Time: Sunday, August 1, 2010 : 2:00 PM to 3:50 PM
• Sponsor: Section on Statistical Education
• Author(s): Dale E. Berger and Tisha L. Hooks*+ and Michael Posner and Michelle Sisto
• Companies: Claremont Graduate University and Winona State University and Villanova University and International University of Monaco

Abstract

Statistical inference is typically the primary learning objective in an introductory statistics course. Sampling distributions play a vital role in understanding inference, yet students often do not achieve understanding of this topic. As recognized by Chance, delMas & Garfield (2004), students also sometimes fail to comprehend important prerequisite concepts, which may hinder their ability to understand sampling distributions. Based on their work, we examine three categories of prerequisite knowledge: sampling, variability, and distributional thinking. In this talk, we (1) review literature on sampling distributions, (2) discuss the development of an assessment tool to provide instructors with quick feedback, and (3) present results from a pilot study investigating the relationship between comprehension of sampling distributions and mastery of the prerequisite knowledge components.