Developing statistical modelers and thinkers in an introductory, tertiary-level statistics course
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While models are an important concept in statistics, few introductory statistics courses at the tertiary level put models at the core of the curriculum. This paper reports on a radically different approach to teaching statistics at the tertiary level, one that uses models and simulation as the organizing theme of the course. The focus on modeling and simulation—along with inference—was facilitated by having students use TinkerPlots™ software for all modeling and analysis. Results from a 3-month teaching experiment suggest that a course focused on modeling and simulation through randomization and resampling methods in which students learn to think using a powerful and conceptual modeling tool can foster ways of thinking statistically. Furthermore, such an approach seems to help students develop experiences with and appreciation for the science and practice of statistics.
KeywordsStatistics education Modeling Simulation Random
The authors gratefully acknowledge the support of the National Science Foundation for the CATALST project. (Collaborative Research: The CATALST Project, Change Agents for Teaching and Learning Statistics, DUE-0814433). They also appreciate the contributions of their CATALST collaborators Beth Chance, George Cobb, John Holcomb and Allan Rossman. The advice given by Cliff Konold, Richard Lesh, Tamara Moore, and Rob Gould was extremely valuable. The work and dedication of graduate students Rebekah Isaak, Laura Le and Laura Ziegler, and of Dr. Herle McGowan at North Carolina State University, was a major contribution to this project. Lastly, the authors thank Anelise Sabbag for her copy-editing on this paper.
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