Games, Data, and Habits of Mind

Abstract

This paper describes three simple, data-producing computer games and the means by which students are expected to analyze the data to produce a model with which they can improve their game-playing strategy. The first game is an in-out machine with linear models. In the second game students must perceive an underlying conditional probability model. And in the third game students invent ways of scoring. Lessons learned from classroom field tests of activities based on these games are described. The activities belong to the family of model eliciting activities in that they are open ended, allow for multiple problem-solving methods, and result in a model whose utility can be evaluated objectively. Habits of mind for working with data are discussed in the context of each game: Graph data and look for patterns; turn patterns into models; use models to help solve problems; automate time-consuming processes; be critical of models; and use formulas with weights to develop ratings.