Students playing computer games generate large quantities of rich, interesting, highly variable data that mostly evaporates into the ether when the game ends. What if in a classroom setting, data from games students played remained accessible to them for analysis? In software and curriculum materials being developed by the Data Games project at UMass Amherst and KCP Technologies, data generated by students playing computer games form the raw material for mathematics classroom activities. Students play a short video game, analyze the game data, conjecture improved strategies, and test their strategies in another round of the game.
The twenty video games are embedded in TinkerPlots and Fathom, two data analysis learning environments widely used in grades 5-8 and 8-14 respectively. The game data appear in graphs in real time, allowing several cycles of strategy improvement in a short time. The games are designed so that these cycles improve understanding of specific data modeling and/or mathematics concepts. Lessons will be embedded in LessonLink from Key Curriculum Press to facilitate their integration into standard curricula. The three-year project expands research in students' understanding of data modeling and their ability to learn mathematical content embedded in data-rich contexts.
A teaching experiment methodology is used to investigate four research questions: (1) To what extent do students view the data as the result of a production process and does this conception have the same sort of affordances as repeated-measures contexts for interpreting data in terms of signals and noise? (2) How do students view data, especially when they encounter data that do not fit into rows and columns? What data structures are appropriate to introduce in middle school? High school? (3) How do students' understandings, interpretations, and interactions with data change as a function of size of the data set? (4) To what extent do the mechanisms the project builds for web-enabled collaboration and data sharing enhance classroom activities? Data, including video, student work, and student interviews, are collected from after-school Data Game clubs and middle and high school mathematics classrooms. Data are analyzed using a grounded theory approach.
