Mathematics Teacher Educator Podcast · Joel Amidon

Episode 50: Engaging Teachers in the Combination of Statistical Investigation and Social Justice: Fairness in School Funding

·23 min·2 clips

Liza Bondurant shows how Pennsylvania school districts with more white students got extra funding, exposing systemic bias.

This episode features hosts Stephanie Casey and Liza Bondurant discussing their article on integrating statistical investigation with social justice, focusing on school funding fairness. Casey is a Mathematics Teacher Educator and Principal Investigator on the Modules Project, while Bondurant is an Associate Professor who teaches and researches statistics. Their work builds directly on a 2019 article by Julia Aguirre and colleagues about combining mathematical modeling with social justice, specifically the Flint water crisis. They adapted Aguirre's framework by replacing the mathematical modeling cycle with a statistical investigation cycle, which requires data analysis. The episode centers on a specific task analyzing Pennsylvania's school funding using a dataset comparing districts' actual funding to a proposed "fair funding formula." Pennsylvania's government only applied the new fair formula to 6% of new funding in 2015, leaving 94% distributed by an older method. The dataset includes demographic variables like median household income, poverty level, and the racial composition of student populations. The hosts describe using the Common Online Data Analysis Platform (CODAP) to visualize the data, plotting each school district as a point comparing fair formula funding versus actual funding. They added a line where Y equals X to identify districts that received more or less than the fair formula amount. Initial hypotheses that socioeconomic status would predict funding disparities were not supported by the data visualization. Instead, the analysis revealed that districts with a higher percentage of white students tended to receive more funding than the fair formula suggested, while those with fewer white students received less. This finding provided a concrete, data-driven illustration of systemic inequity. Pre-service teachers engaged with this task experienced a "light bulb" moment about using data to support advocacy arguments. The module concludes by having participants write letters to legislators based on their statistical findings, blending content learning with social action. The work aims to actualize equity standards from the Association of Mathematics Teacher Educators by integrating social justice into mathematics content courses. All curriculum materials from the Modules Project are freely available online to reduce costs for students and educators. The tone is collaborative and educational, focusing on practical application for teacher preparation. Listeners interested in curriculum development, statistics education, or social justice in STEM will find this episode valuable. Those seeking a highly theoretical discussion or critique of the methodology might find it less engaging.

As heard by us

A measured look at how statistics can make school funding feel teachable, not abstract.

This conversation treats a school-funding policy question as a practical lesson in how statistical inquiry can serve social justice. Its clearest strength is the steady return to classroom design: why Pennsylvania was chosen, how the fair funding formula was meant to account for…

Read the full review in PlayNext →

Why you'd press play

For when you want statistics, school funding, and social justice, with raw data, in one teacher-education conversation.

Read the full recommendation in PlayNext →

Listen to the show on

Apple Podcasts Spotify

Play clips from this episode More from Mathematics Teacher Educator Podcast