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This is a session of Topic 8: Research in statistics education


(Monday 14th, 10:55-12:25)

Research on developing students’ reasoning using simulation methods for introductory statistical inference: Session I


Organizers


Abstract

In his landmark paper in 2007 (TISE), George Cobb argued for a 21st century approach to teaching introductory statistics. He advocated for the use of randomization and simulation methods for instruction in statistical inference, rather than the traditional formula-based approach (using methods such as the t-test and ANOVA).

Since that time, extensive research has been undertaken to develop, implement, and formally evaluate these computational approaches to teaching statistics. In addition, there has been a slow but steady incorporation of randomization and bootstrap methods topics into textbooks at the introductory level.

This session features speakers who have been instrumental in leading research to assess the impact of simulation methods on students’ statistical reasoning. They will describe and summarize the state of the art of research related to the use of simulation methods in the introductory statistics curriculum. A primary focus will be on the impact of simulation methods on students’ statistical reasoning, as well as discussion of barriers and aspects that require additional study.


Papers

PaperTitlePresenter / Co-author(s)
8A1Students’ visual reasoning and the randomization testStephanie Budgett (New Zealand)
Chris Wild (New Zealand)
8A2Designing and implementing an alternative teaching concept within a continuous professional development course for German secondary school teachersJanina Oesterhaus (Germany)
Rolf Biehler (Germany)
8A3Quantitative evidence for the use of simulation and randomization in the introductory statistics courseNathan Tintle (United States)
Todd Swanson (United States)
Jill VanderStoep (United States)
Soma Roy (United States)
Allan Rossman (United States)
George Cobb (United States)
Ally Rogers (United States)
Beth Chance (United States)