This chapter focuses on understanding the use of and relationship among the features of statistics cognition: literacy, reasoning, and thinking. We argue that research on statistics cognition is fragmented, which is problematic for understanding how these constructs can be unified to support education. We then review methods of quantifying cognitions, involving studies which have attempted to categorize and parse cognitive processes. This information is then used to synthesize a new approach to understanding statistics cognition, proposing a model which makes specific predictions about the relationship of these features. The model and definitions of cognitions presented in this chapter are used as a basis of discussion cognition throughout the remainder of the book.
Nevertheless, a commitment to testing ourselves—actually seeing how well our predictions work in the real world rather than in the comfort of a statistical model—is probably the best way to accelerate the learning process. - Nate Silver, 2012, p. 292
Top2. Presenting Statistics Cognition
In order to elucidate how cognition can be measured, it is first necessary to define our terms. As previously discussed (see section 1), statistics cognition is purported to be comprised of three components: literacy, reasoning, and thinking (Ben-Zvi & Garfield, 2004; delMas, 2002). Traditionally, these concepts have been used in both scientific and colloquial manners for over 100 years. For example, Fox (1860) rigidly used the term “statistical reasoning” to refer to the ability to understand meaning behind statistical information, whereas Dewey (1891) simply used the term to refer to a skill consisting of “right and honest reasoning” (p. 309). While Dewey’s interpretation of Kenes argued that statistical reasoning should be no less important than teaching individuals how to “manage hygiene”, such conceptualizations of key terms varied drastically in their early use.