Literature Index

This paper describes some preliminary results from a classroom teaching experiment at the college level, in which students were guided through activities to reveal and develop their notions of variability. Starting with their intuitions about variability, students were asked to speculate about the distributions of different variables, focusing on the informal ideas of whether they expected the variables to have larger or smaller variability. The class activities then guided students from their intuitions about variability as meaning "lots of different values" and overall range, to a dual understanding of variability as both range and clustering in the middle. A final goal of the teaching experiment was to help students make the transition from their initial ideas of variability to the ideas that variability has many dimensions, that formal measures (e.g., range, interquartile range, and standard deviation) all measure different aspects of variability, and that these measures are more useful or appropriate (e.g., to use in comparing groups) depending on the characteristics of the data. The use of assessment items to evaluate student learning will also be described.

Comments on statistical articles in the popular press by first-year economics students studying statistics in Australia and South=East Asia are analyzed. Three common weakness are described - lack of appreciation of journalistic style, disregarding statistical variation, and incorrect percentage statements. Differences between the groups are described and implications for teaching such courses are discussed.

We conducted two design experiments aimed at engaging sixth graders (11 years old) in statistical reasoning about center and variation. We examine in particular students' informal notion of a "modal clump." Using Peirce's concept of diagrammatic reasoning, we analyze the interplay of 1) making plots with TinkerPlots - a computer data analysis tool, 2) experimenting with those plots, and 3) developing a language to talk about features of the data sets as represented in the plots by reflecting on judgments. More generally, we draw on Brandom's recent work in philosophy to argue that an "inferential" view should be privileged over a "referential" view of teaching and learning statistics.

We examined the attitudes of about 2200 students enrolled in 101 sections of post-secondary introductory statistics service courses located across the United States. Using the Survey of Attitudes Toward Statistics-36, we assessed students’ attitudes when they entered and left their courses, as well as changes in attitudes across their courses. Results showed that, on average, students entered these courses with neutral (Affect, Difficulty), positive (Cognitive Competence, Value, Interest), and very positive (Effort) attitudes. Their attitudes either stayed about the same (Affect, Cognitive Competence, Difficulty) or decreased (Value, Interest, Effort). These results help us understand the current impact of introductory statistics instruction in U.S. institutions.