|Standing: outgoing SIGMAA chair Andy Zieffler; seated: Robin Lock, Kari Lock Morgan, Laura Ziegler, Elizabeth Fry, Rachel Dunwell, Allan Rossman, Soma Roy|
CATALST represents a sharp break from many statistics education traditions. Elizabeth and Laura described its radical content, pedagogy, technology, and assessments as part of a panel discussion on randomization methods in the introductory course:
CATALST course materials can be downloaded from the CATALST website. Development was funded by NSF DUE-0814433, and the full project team can be viewed here.
What's so radical about CATALST? The course joins the new wave of randomization-based curricula, spurred on by statistic education luminary George Cobb: "Randomization-based inference makes a direct connection between data production and the logic of inference that deserves to be at the core of every introductory course." (from The Introductory Statistics Course: A Ptolemaic Curriculum?)
Laura and Elizabeth presented CATALST as a part of a panel discussion on randomization curricula organized by the Statistics Education SIGMAA group. This was one of U of M Senior Lecturer Andy Zieffler's final duties as the 2012 chair of the SIGMAA. Rachel Dunwell of Rhodes College started by talking about how they used to teach a traditional curriculum, and now they're doing simulations with Fathom; Allan Rossman and Soma Roy of California Polytechnic State University talked about their randomization course; and Kari Lock Morgan and Robin Lock talked about their new book and online StatKey software.
CATALST's pedagogy is also radical. The curriculum moves students through a range of activities that they work on in groups. Instructors deliver support with "just-in-time" statistics instruction that's driven by the activities. These activites are made possible by allowing students to directly model probabilities in TinkerPlots. Elizabeth and Laura's presentation discusses an activity, "Matching Dogs to Owners", where students create simulation models of a messy situation that would be difficult to solve analytically.
These radical techniques call for radical assessment that is based on the actual goals of the course. The assessments, known as GOALS and MOST and part of the e-ATLAS project for the Evaluation and Assessment of Teaching and Learning About Statistics, measure conceptual understanding rather than the procedural knowledge of how to compute t-statistics and correlations.
|Elizabeth Fry with her poster on the e-ATLAS evaluation and assessment project.|
Want to know more? U of M's Laura Ziegler and Joan Garfield wrote an article about the first activity in the course in the latest issue of Teaching Statistics! We'll be taking a closer look at this article in a forthcoming post.