Higher Education Commons^™

Combating Anti-Statistical Thinking Using Simulation-Based Methods Throughout The Undergraduate Curriculum, Nathan L. Tintle, Beth Chance, George Cobb, Soma Roy, Todd Swanson, Jill Vanderstoep

Faculty Work Comprehensive List

The use of simulation-based methods for introducing inference is growing in popularity for the Stat 101 course, due in part to increasing evidence of the methods ability to improve students’ statistical thinking. This impact comes from simulation-based methods (a) clearly presenting the overarching logic of inference, (b) strengthening ties between statistics and probability/mathematical concepts, (c) encouraging a focus on the entire research process, (d) facilitating student thinking about advanced statistical concepts, (e) allowing more time to explore, do, and talk about real research and messy data, and (f) acting as a firmer foundation on which to build statistical intuition. Thus, …

Mindsets, Attitudes, And Achievement In Undergraduate Statistics Courses, Valorie L. Zonnefeld

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The purpose of this study was to determine the effects of theories of intelligence and an intervention of incremental mindset training on students’ attitudes toward statistics and their mastery of content in an introductory statistics college course. The sample was 547 undergraduate students at a small, faith-based, liberal arts college in the Midwest.

A pretest-posttest design was used for the three instruments implemented. The Comprehensive Assessment of Outcomes in a first Statistics course (CAOS) assessed students’ statistical literacy. The Student Attitudes Towards Statistics – 36© (SATS©) assessed six components of students’ attitudes toward statistics including affect, cognitive competence, difficulty, effort, …

Challenging The State Of The Art In Post-Introductory Statistics: Preparation, Concepts, And Pedagogy, Nathan L. Tintle, Beth Chance, George Cobb, Allan Rossman, Soma Roy, Todd Swanson, Jill Vanderstoep

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The demands for a statistically literate society are increasing, and the introductory statistics course ("Stat 101") remains the primary venue for learning statistics for the majority of high school and undergraduate students. After three decades of very fruitful activity in the areas of pedagogy and assessment, but with comparatively little pressure for rethinking the content of this course, the statistics education community has recently turned its attention to use of randomization-based methods to illustrate core concepts of statistical inference. This new focus not only presents an opportunity to address documented shortcomings in the standard Stat 101 course (for example, improving …