This paper is from Session 8B: Research on developing students’ reasoning using simulation methods for introductory statistical inference: Session 2

which comes under Topic 8: Research in statistics education

The symbiotic, mutualistic relationship between modeling and simulation in developing students’ statistical reasoning about inference and uncertainty

Presenter

• Andrew Zieffler (University of Minnesota, United States)

Co-authors

• Ethan Brown (University of Minnesota, United States)
• Joan Garfield (University of Minnesota, United States)
• Robert C delMas (University of Minnesota, United States)

Abstract

We report preliminary results from an ongoing study of the development of tertiary students’ reasoning related to statistical inference and uncertainty during a one-semester modeling and simulation-based statistics course. Comparisons of students’ performance on assessments of statistical reasoning will be presented for both students enrolled in this course and those enrolled in courses that used conventional parametric methods of inference. Summaries of qualitative data from nine students who participated in problem-solving interviews will also be presented to illustrate the development of students' reasoning related to statistical inference and uncertainty. Analyses of the data indicate that students taking the modeling and simulation-based course demonstrate better understanding of the principles of study design and statistical inference and begin developing these understandings within the first few weeks of the course.