From Research to Repair: Leveraging QuantCrit to Transform Doctoral Training for Structural Change and Equity

• In Event: Methods Matter: New Directions in Interrogating the Social Contexts of Education

Abstract

This study examines transforming doctoral statistics training by integrating Quantitative Critical Race Theory (QuantCrit) principles through a community-engaged research project in a year-long introductory statistics course. It addresses two questions: the challenges and successes of co-constructing a QuantCrit-aligned curriculum, and how integrating QuantCrit impacts students' understanding of statistical methods in social justice contexts. Using a participatory action research model, the study documents course evolution, revealing shifts in students' perceptions from viewing statistics as objective to recognizing its biases and social justice potential. Key findings include enhanced critical evaluation skills and deeper engagement with social justice issues. Despite challenges like cognitive overload and resistance to new methods, the study underscores QuantCrit's transformative potential in reshaping statistical education for equity.

Authors

• Marguerite Shashoua, Fordham University

• Lisa Ciraldo, Fordham University

• Xiaohan Zhu, Fordham University

• Sharon Christian, Fordham University

• Keisha Shay, Fordham University

• Akane Zusho, Fordham University