Getting Personal With Big Data: Stories With Multivariable ︎Models About Global Health and Wealth

• In Event: Mathematics and Technology-Based Learning Environments

Abstract

This paper presents part of a multiyear design study that engaged prospective secondary mathematics and social studies teachers (separately) in multivariable modeling practices with big data to support learning about critical mathematical and statistical literacies. Student groups constructed models and performed big data stories about global development using an online, dynamic graphing tool (Gapminder© motion chart). A comparison of a selected case study from each iteration and interaction analysis of participants’ model construction and performances suggest that the motion chart tool supported critical data literacy perspectives and personal connections to complex models of aggregated global data. Implications for public scholarship are discussed.

Authors

• Jennifer Beth Kahn, Vanderbilt University - Peabody College

• Rogers P. Hall, Vanderbilt University