Science and Mathematics Education Commons^™

Numeracy And Social Justice: A Wide, Deep, And Longstanding Intersection, Kira Hamman, Victor Piercey, Samuel L. Tunstall

Numeracy

We discuss the connection between the numeracy and social justice movements both in historical context and in its modern incarnation. The intersection between numeracy and social justice encompasses a wide variety of disciplines and quantitative topics, but within that variety there are important commonalities. We examine the importance of sound quantitative measures for understanding social issues and the necessity of interdisciplinary collaboration in this work. Particular reference is made to the papers in the first part of the Numeracy special collection on social justice, which appear in this issue.

Connecting Numbers With Emotion: Review Of Numbers And Nerves: Information, Emotion, And Meaning In A World Of Data By Scott Slovic And Paul Slovic (2015), Samuel L. Tunstall

Numeracy

Scott Slovic and Paul Slovic (Eds.). Numbers and Nerves: Information, Emotion, and Meaning in a World of Data (Corvallis, OR: Oregon State University Press, 2015). 272 pp. ISBN 978-0-87071-776-5.

It is common to view quantitative literacy as reasoning with respect to numbers. In Numbers and Nerves, the contributors to the volume make clear that we should attend not only to how students consciously reason with numbers, but also how our innate biases influence our actions when faced with numbers. Beginning with the concepts of psychic numbing, and then psuedoinefficacy, the contributors to the volume examine how our behaviors when …

Random Number Simulations Reveal How Random Noise Affects The Measurements And Graphical Portrayals Of Self-Assessed Competency, Edward Nuhfer, Christopher Cogan, Steven Fleisher, Eric Gaze, Karl Wirth

Numeracy

Self-assessment measures of competency are blends of an authentic self-assessment signal that researchers seek to measure and random disorder or "noise" that accompanies that signal. In this study, we use random number simulations to explore how random noise affects critical aspects of self-assessment investigations: reliability, correlation, critical sample size, and the graphical representations of self-assessment data. We show that graphical conventions common in the self-assessment literature introduce artifacts that invite misinterpretation. Troublesome conventions include: (y minus x) vs. (x) scatterplots; (y minus x) vs. (x) column graphs aggregated as quantiles; line …