Kim Gilbert – University of Georgia
Trying something completely different can be very scary. But sometimes, you just know it’s totally worth the risk. That’s how I felt after hearing a couple of fabulous stat educators talk about using simulation-based methods for teaching the intro course. I was immediately inspired by their enthusiasm. But more importantly, I was excited to try pedagogy that they/I believed would make a genuine difference in student learning. So I jumped head first into the deep end and have enjoyed every minute.
As it turned out for me, technology helped.
Kathryn Dobeck – Lorain County Community College, Ohio
In 2012, I had a simple goal for my first sabbatical project: to revise the course materials for my Introduction to Statistics course in order to make them more accessible and relevant to my students. I had long been bothered by the presentation of statistical concepts that our textbook used, due to its overuse of flowcharts and “cookbook-style” explanations where logical justification should have been. With this approach, students were hung up on basic ideas such as arithmetic, rounding issues, and determining which formula to use, but never reached the higher orders of statistical thinking. My quintessential statistics course would convey the power of analyzing data, present motives for inferential statistical methods, and demonstrate the ubiquitous nature of the discipline. Unfortunately, at that time, the specific details of how I was going to solve these problems and realize my ideal course were yet to be determined (and hence the need for a sabbatical!).
I’d be lying if I said that changing to a simulation-based curriculum wasn’t a lot of work. It definitely was. However, the work load was manageable over the course of a year and was worth every bit of it. Now, student success rates and attitudes have improved and the course is an absolute joy to teach.
Erin Blankenship, University of Nebraska-Lincoln
For me, the hardest part about getting started was finding the right balance in my classroom – the right balance between lecture and activities; the right balance between in-class and out-of-class learning; the right balance between student accountability and student responsibility. None of this, however, really had much at all to do with the randomization-based curriculum. I had taught courses for pre-service and in-service K-12 teachers that focused on simulation-based methods . . . I knew it was effective pedagogically. The hard part came when a colleague and I decided that we would try to flip our classrooms the same semester we implemented the randomization-based curriculum. And, that too in a classroom with 2-3 times as many students as a “typical” intro class in our department.
… the right balance between lecture and activities; the right balance between in-class and out-of-class learning; the right balance between student accountability and student responsibility.
My move from the traditional curriculum to the simulation/randomization-based curriculum was confounded with the simultaneous move of inference to the beginning of the course. Not only was I going to dive in to simulation/randomization as the primary mode by which to develop student understanding of statistical significance, but I was going to try it while completely turning the traditional ordering on its head.
But moving inference to week 2 means my students immediately experience statistics as a science, and they get this experience repeatedly throughout the course, and in the end showing them what statisticians do and how statisticians think is more important than my struggle with where to put the definitions of parameter and statistic.