Jill Vanderstoep – Hope College

To be completely honest, I didn’t choose to teach with simulation-based methods. Nathan Tintle made a curricular change, and I followed. To this day, I am so glad I did because the changes have been the most refreshing and fun changes I have made in my Statistics classes over the twenty plus years I have been teaching.

[pullquote]I am so glad I did because the changes have been the most refreshing and fun changes I have made in my Statistics classes over the twenty plus years I have been teaching.[/pullquote] Continue reading →

The CATALST group – University of Minnesota

JOAN GARFIELD

Inspired by George Cobb’s plenary address at the first USCOTS in 2005, we began to explore ways to turn his ideas into an actual curriculum. We decided to explore the use of models and modeling in the course, and, funded by a NSF grant, developed the CATALST curriculum. [pullquote] Our guiding principle was to teach students to really cook, rather than follow recipes.[/pullquote] Our goal was to develop a course that focused on randomization methods and random sampling, taking away the traditional focus on the two-sample t-test. The CATALST course went through many iterations and had input from a team of great collaborators, including courageous graduate students who taught early versions of this radically different course. Our guiding principle was to teach students to really cook, rather than follow recipes. The cooking method uses randomization and repeated sampling methods to make statistical inferences. Even though there were many challenges, we feel that we developed a course that engages students and stimulates them to think, build and test models, and understand the core ideas of statistical inference. Continue reading →

Josh Tabor, Canyon del Oro High School

Short answer: I teach with simulation-based methods because I believe they make it easier for students to understand the logic of inference and see statistics as a complete investigative process from asking questions to drawing conclusions.

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I settled on two guiding principles that would inform the way I designed the course:

1. Emphasize that Statistics is an investigative process, not a set of isolated skills.
2. Stay focused on the logic of inference.

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Chris Malone, Winona State University

I started teaching at Winona State University in 2002.  I am fortunate to be able to teach a variety of statistics courses to students with an even wider variety of backgrounds here at Winona State.  About 10 years ago, at the advice of a senior faculty member, I started doing statistical consulting work to balance my teaching duties.  This had a remarkable impact on my teaching at that time.  Consulting continues to this day to shape my approach to teaching statistics.

[pullquote]The traditional sequence was too compartmentalized and did not allow much time for students to conduct a statistical analysis from start-to-finish.[/pullquote] Continue reading →

Dave Klanderman , Trinity Christian College

It would be accurate to say that I was a skeptic when I showed up at a week-long MAA workshop at Dordt College in June 2013.  At the urging of my departmental colleague, who is now serving as our Provost, I signed up to learn more about a new statistics textbook, a new paradigm for teaching and learning statistics, and a chance to connect with both friends and family in Sioux Center, Iowa.[pullquote]Additional sessions convinced me that this approach had merit and the comparison data using the CAOS provided the final piece of assessment evidence.[/pullquote]

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Lacey Echols, Butler University

I knew I was in trouble teaching statistics when I always thought I was doing such a great job, but the students were totally lost the last four weeks of the semester!  It didn’t matter how many times I used active learning in my classroom or the how many great lectures I thought I presented, they just did not get the concept of a hypothesis test.  [pullquote] it is wonderful to present the ideas of how to think about research questions, the proper way to write hypotheses, the meaning of a p-value, and the meaning of statistically significant within the first four days of a semester.[/pullquote] The early part of the semester with data description, probability, and experimental design had lulled them into a false sense of security.

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