Critical Theory in Statistics Education
Presented at: 6 October 2022; 18:00 UTC
Webinar duration: 90 minutes
Presenter(s): Lucia Zapata-Cardona and Travis Weiland
We are in an information age where data is constantly being collected and analyzed under the guise of benefiting all. This would seem to be a time for statistics and data science education to flourish. However, many of the algorithms and processes have baked into them the same biases as those who created them. Critical theory provides a lens to interrogate systemic issues of injustice and address crises in society. Given our current state of democracies in crisis across the globe we plan to discuss ways that statistics and data science educators can and have incorporated ideas from critical theory into their work in statistics and data science education. We provide some background into critical theory and how it has been taken up in mathematics education work and then discuss how these ideas could and have been used in the context of statistics and data science education work. Our goal is also to foster dialogue over these ideas so significant time will be devoted to discussion and questions.
Lucia is at the Universidad de Antioquia, Medellin, Antioquia.
Travis is at the University of Houston, Houston, Texas