Tuesday, March 8th, 20112:00 pm – 2:30 pm ET
Presented by: Cliff Konold, Director, Scientific Reasoning Research Institute, University of Massachusetts Amherst
Generally in learning statistical inference, students reason backwards from data to the (usually invisible) process that produced them. I will demonstrate an alternative approach in which students begin at the process end, designing their own "data factories." Based on their output, students modify their factories such that, for example, a collection of cats produced by a cat factory has features that look more like real cats. This work is part of the NSF-funded "Model Chance" project. In this project, we have been adding probability modeling to the existing data-visualization capabilities of TinkerPlots and, using that environment, exploring how data and chance might be better integrated in our instruction beginning in the middle school.