Data Modeling

This project aimed to change the way students -- and teachers -- think about math and science and was part of a larger endeavor by Peabody College to "reform the schooling of mathematics and science," said co-investigator and Professor of Science Education Rich Lehrer. This innovative project focused on learning rather than performance as the standard by which educational methods are judged.

"The goal is to support teachers who can look at how kids are thinking and adapt instruction accordingly," said Lehrer. At the new math and science-focused Rose Park Magnet Middle School in Nashville, investigators used model-based reasoning to help teachers design a learning environment that was more in tune with "real world" math and science. These are not always familiar concepts to teachers, Lehrer said, and a key of the project was to "introduce ideas in a way they'll find fruitful."

At the heart of the investigation was the relationship between statistics (math) and biology (science). The discipline of statistics developed from a need to model natural systems using mathematical descriptions -- for example, measuring variation in organisms over time -- so it seemed only natural to reunite the two fields for an examination of how statistical reasoning develops. "We know, for example," said Lehrer, "that if you look at plants and take a measure of something like height, you'll find a lot of variation. There's a structure to that variation," and that's where statistics comes in. "If you take a group of plants, or of people," he continued, "and ask, what would happen if I grew them again? What would that look like? -- mathematical structures help you predict nature."

At the University of Massachusetts Amherst, we created new capabilities with TinkerPlots that help students develop statistical reasoning and learn new ways of representing data that don't exist except in a computer world. These tools aided investigators and teachers in developing lesson plans throughout the course of the three-year project. While development would be ongoing, teachers began introducing statistical concepts to students in fall 2004.

Assessment played a vital role in the project, though not in the traditional fashion: Evaluations of students' learning would serve as instructional tools for teachers. "If you're going to assess a kid," said Lehrer, "the assessment ought to inform instruction -- tell you how a kid is thinking about a set of problems so you know what the next step is." Researchers from the University of California-Berkeley helped develop techniques to assess students' learning. One of the most innovative aspects of the project involved not educational design or assessment, but the collaboration between investigators. Rather than dividing research into separate segments for each investigator to research independently and then combine at the conclusion of the project, all team members participated in multiple aspects of the investigation. "It's unusual to collaborate in this way," said Lehrer, but the result -- cohesive research that produces more comprehensive results -- may someday make it the standard.

This project is supported in part by a grant from the National Science Foundation (REC-0337675). Opinions expressed here are those of the project staff and do not necessarily reflect the views of the Foundation.