Using GbCC to understand Segregation in a Graduate Level Systemic Reform in STEM Education Course

On Wednesday, October 25th, Dr. Anothony Petrosino invited doctoral student Jason Harron to speak with his graduate course on Systemic Reform about issues related to the historic segregation and recent gentrification of Austin, TX. Framed through the lens of complex behaviors in systems (Jacobson, Kapur, & Reimann, 2016), the lesson focused on how behaviors of individual agents in a system can lead to complex emergent results. Based on the Schelling-Model of Racial Segregation (1971), the class was invited to explore segregation as an emergent phenomenon using GbCC. By adjusting a variable called “happiness”, circles and squares move around a map until they are surrounded by a user-defined minimum percentage of same colored neighbors. Students are able to adjust the minimum percentage and run the model multiple times in order to test different hypotheses about how the preference for similarity may result in different segregation patterns. Using the gallery feature of GbCC, students are able to share their outcome with the rest of the class.

Much like NetLogo, GbCC is an authorable environment, meaning that code can be modified and recompiled. By leveraging this feature, we use the segregation model as our introduction to programming. Students are shown how to modify a single line of code that determines the colors of the circles and squares in the model. As members of the Systemic Reform class played with variables, some discovered that they could add more than two colors, while one student changed the colors to black and orange and kept running the model to see if a UT Austin longhorns logo would emerge through segregation. 

The lesson then turned to Austin Revealed: A Tale of Two Cities ( and History of Austin’s racial divide in maps ( to provide a localized context for how segregation has historically taken place in Austin, TX. Through reading about the history of Austin and view maps, students learn that the neighborhood of Hyde Park was originally developed for whites only, that in the 1930s the Home Owners Loan Corporation labeled African-American and Latino/a neighborhoods as "hazardous", and that over the past three decades the African-American population of East Austin has become increasingly displaced by white residents. This investigation led to conversations based on three questions:

  1. How are these maps of Austin relate to deliberate segregation? (i.e., de jure) 
  2. How are these maps of Austin relate to circumstantial segregation? (i.e., de facto)
  3. Why is understanding this history relevant in conversations about systemic education reform?

Following this discussion, we investigated the Racial Dot Map ( to take a look at how segregation takes place in Austin and metropolitan and rural areas throughout the United States. For example, students in the class discovered that the graduate housing in the city of Austin was immediately recognizable due the overrepresentation of dots representing Asian students, Other students looked at their home city or towns, with one student commenting that their rural experience was represented almost completely by white dots.

Returning to the GbCC model, the discussion on segregation culminated with three additional questions:

  1. What does this agent-based model do well? Not so well?
  2. Does this segregation model fairly represent the how segregation takes place in Austin? Why or why not?
  3. How can modeling be used to better understand the challenges in systemic education reform?

This lesson provided an introduction to how GbCC can be used in a classroom to model and facilitate discussion about social issues in an immediate and localized context. Students were left with the challenge to think about how models and simulations can be used as a tool better address systemic education reform.