Showing papers by "Maxine Pfannkuch published in 2002"

How Faithful Is Old Faithful? Statistical Thinking: A Story of Variation and Prediction

Abstract: tatistics is a relatively new discipline. Only in the last one hundred years have common methods and common reasoning evolved that can be applied to data from many fields. In the early years, the field of statistics was influenced by the work of Ronald A. Fisher, Karl Pearson, and Jerz Neyman. They focused on developing tools and methods that primarily focused on randomization More recently, exploratory data analysis has been emphasized (Tukey 1977). As statistics continues to mature as a discipline, statistics educators are paying more attention to developing overall models of statistical thinking (Wild and Pfannkuch 1999). This shift in statistics means refocusing the emphasis in teaching from how to do statistics to how to think about statistics. In this next step in the evolution of statistics and statistics teaching, two questions arise: What is statistical thinking? and How can we develop students’ statistical thinking? The authors of this article have found that data sets from the Old Faithful geyser in Yellowstone Park furnish a rich context for introducing such important aspects of statistical thinking as the central role of variation and the importance of asking our students what they would predict. In this article, we first discuss the context of the data, next present a classroom exploration of the data, and then discuss the nature of statistical thinking as it pertains to this Old Faithful data set.

Probability With Less Pain

Abstract: Summary The teaching of probability theory has been steadily declining in introductory statistics courses as students have difficulty with handling the rules of probability. In this article, we give a data-driven approach, based on two-way tables, which helps students to become familiar with using the usual rules but without the formal structure.

Statistical thinking models

Abstract: Models for statistical modes of thinking and problem solving have been developed, and continueto be developed, by teachers and researchers. The purpose of these models range from helping tounderstand how individual students solve problems to developing instruments for educationalresearch. These models have arisen with particular perspectives and primary uses in mind. In thispaper we compare and contrast some statistical thinking models originating from statisticseducation research (Ben-Zvi & Friedlander, 1997; Jones, Thornton, Langrall, Mooney, Perry P Hoerl & Snee, 2001). Drawing upon models from both these areas we discussissues that include their development and use, how they might illuminate one another and whatwe can learn from them.

Is what you see what you get? representations, metaphors and tools in mathematics didactics

Abstract: This paper is exploratory in character. The aim is to investigate ways in which it is possible to use the theoretical concepts of representations, tools and metaphors to try to understand what learners of mathematics ‘see’ during classroom interactions (in their widest sense) and what they might get from such interactions. Through an analysis of a brief classroom episode, the suggestion is made that what learners see may not be the same as what they get. From each of several theoretical perspectives utilised in this paper, what learners ‘get’ appears to be something extra. According to our analysis, this something ‘extra’ is likely to depend on the form of technology being used and the representations and metaphors that are available to both teacher and learner.