Research

In this exploratory study, we followed approximately 1000 students (Economics and Business) in their freshman year at the University of Maastricht (Netherlands). Those students attended three compulsory courses in Quantitative Methods, each having an important component of statistics. Our population of students exhibits a strong heterogeneity with respect to several aspects: attitude towards and prior knowledge of mathematics and statistics, nationality, type of prior education and the mastery of languages. To study the impact of this heterogeneity on learning introductory statistics, the development of a model of students' learning of introductory statistics was chosen as the goal of the project. In order to develop a relational model, several surveys were taken and data sources were used with regard to the students' characteristics, learning context, students' perceptions and the approaches students took. The major contribution of this study is the broad range of different determinants of learning that is considered, which allows investigation of the interrelation between several factors influencing learning besides studying the direct impact of each factor on learning.

This paper describes a project that involves statistical researchers and software designers in a collaboration designed to accelerate progress in research on statistical thinking and the development of effective software tools for statistical education; the two tools in question are TinkerPlots and Fathom. Most of the paper is devoted to a description of teachers analyzing a dataset first without, then with technology and to a discussion of the implications of such observations for both research and software development.

This paper presents the results of a pilot study investigating the use of short stories in teaching introductory statistics to positively affect statistical anxiety and attitudes toward statistics. The Statistics Anxiety Rating Scale (STARS) and the Attitude Toward Statistics (ATS) scale were given to 17 graduate students at the beginning and end of the semester course. Results suggest a significant decline in statistical anxiety and a positive change in attitudes toward statistics courses, but no significant change in negative attitudes toward the field of statistics.

The studies we present investigate elementary students' reasoning about distributions in two contexts: (a) measurement and (b) naturally occurring variation. We first summarize an investigation in which fourth-graders measured the heights of a variety of objects and phenomena, including the school's flagpole, a pencil, and several launches of model rockets. Students noted that the measurements were distributed and that sources of error corresponded to differences in qualities of distribution, especially spread. Next, students investigated the distributions of measurements of height for rockets of different design, to learn whether and how they could be confident that rockets with rounded nose cones "really" went higher than those with pointed nose cones. We then turn to the naturally-occurring variation context, in which these same students (now fifth-graders) studied the growth of Wisconsin Fast Plants(tm), fast-growing members of the Brassica family that enable multiple cycles of classroom observation and experiment within a school year (life cycle is about 40 days). We recount how students became adept at using changing shapes of distributions to support plausible accounts of growth processes. Questions about what would be likely to happen "if we grew them again" motivated investigations of sampling, which, in turn, suggested choices of statistics to represent a sample distribution. Finally, students invented means for considering how one might know whether two different distributions of measures could reasonably be considered "really different."