Online Program Home
My Program

Abstract Details

Activity Number: 558
Type: Contributed
Date/Time: Wednesday, August 3, 2016 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistical Education
Abstract #319368
Title: Lexical Ambiguity in Statistics: The Development of High-Impact, Little-Time Activities to Help Students Better Understand the Meaning of Parameter
Author(s): Neal Rogness* and Jennifer Kaplan and Diane Fisher
Companies: Grand Valley State University and University of Georgia and University of Louisiana at Lafayette
Keywords: Lexical ; Ambiguity ; Statistics ; Education ; Parameter

Researchers have long-noted that language poses a barrier for introductory-level students studying STEM disciplines. For instance, many words used in statistics, such as random, average, normal, and parameter, have everyday meanings which differ from their discipline usage, which can lead to lexical ambiguity. The main suggestion in the literature for addressing lexical ambiguity in the classroom is to exploit the ambiguities of the target words. To do this, instructors should contrast the statistical meanings with everyday meanings used by students outside the classroom. An NSF-funded project is focusing on ways to help students better understand how certain words are used within statistics through a variety of activities designed to have High Impact on student learning while requiring Little Time to implement (or having the HILT attribute). Six volunteer instructors participating in the study have been developing HILT activities for target words of interest. For this presentation, we will share the HILT activities created to exploit the lexical ambiguities associated with parameter and findings related to their effectiveness.

Authors who are presenting talks have a * after their name.

Back to the full JSM 2016 program

Copyright © American Statistical Association