Using Computer Science to Model Inclusion and Diversity in STEM Content Area

Troy's Athletic Club- Little League Team (circa 1961)

Explaining segregation is more difficult than one might imagine due to the deeply rooted inequities based on historical policies and practices that have carved and shaped this city. The ability for all learners to understand the legal (“de jure”) and social (“de facto”)  process of segregation is imperative for uncovering misconceptions and addressing narratives about equitable participation in society. To address this need, Dr. Anthony Petrosino leads the Group-based Cloud Computing (GbCC) for STEM Education project, which works to develop curricula using cognitive tools to help all learners understand complex problems like segregation.

GbCC is a collaborative agent-based modeling program based on NetLogo (Wilensky, 1997). These agent-based models allow students to engage in simulations that explore how actions and interactions of autonomous agents have an effect on the system as a whole. This platform empowers students to take agency in their own learning by controlling variables, making changes to code, and sharing changes with classmates anonymously. GbCC addresses diversity and inclusion in the classroom by providing a platform that allows all students to participate in real-time modeling of scientific content.

Using the GbCC segregation model, students have investigated how small changes in simple variables, such as wanting neighbors similar to yourself, can result in emergent segregation of society. Dr. Sepehr Vakil and doctoral student Jason Harron have used this tool to discuss complex social challenges associated with the gentrification of East Austin with pre-service STEM teachers in the UTeach course, Classroom Interactions. Pre-service teachers were able to learn about redlining - the legal process of denying services based on geographic location - and modify the NetLogo code to alter the functioning of the model.

Since the environment is authorable, GbCC provides students with a low-threshold to begin exploring with little or no programming background knowledge. As students advance in their programming skills, the platform continues to provide room for growth (high-ceilings) allowing students to create more sophisticated models (Myers, 2000). During the Fall of 2017, models developed by undergraduate Computer Science student Mica Kohl and curricula developed by  graduate student Max Sherard were used to teach students about ecosystem species interactions in a week-long unit exploring how wolves shape rivers in Yellowstone National Park (“How Wolves Change Rivers [Remastered],” 2017). The models were used at two school sites with almost 400 students in fifth and sixth grade level science classrooms, with approximately two-thirds of students being economically disadvantaged. Continued partnership with these two teachers is planned for the Spring of 2018.

The GbCC for STEM Education is a National Science Foundation funded project that is the product of collaboration between four universities: Northwestern, Vanderbilt, University of Massachusetts at Dartmouth, and the University of Texas at Austin. Dr. Anthony Petrosino coordinates the implementation, development, and demoing of GbCC Model-based curricula with (1) the UTeach program and pre-service teachers, (2) graduate students in STEM Education, (3) in-service teachers, and (4) learning science and education conference attendees around the country. This past summer, Dr. Petrosino and Dr. Walter Stroup of the University Massachusetts at Dartmouth presented progress on developing 12 open-source GbCC models lesson to attendees at the annual convention of the American Society of Engineering Education (Petrosino, Stroup, Harron, & Sherard, 2017). Most recently, Dr. Petrosino implemented segregation models in his graduate course Systemic Reform. Graduate students engaged with the segregation model to discuss how this tool could be used to inform systemic initiatives related to equity in school reform.

GbCC models are designed with the capacity to simulate complex problems; however, these models are only as sophisticated as the learning experiences in which are used. The work of Dr. Anthony Petrosino and his colleagues seeks to design meaningful learning experiences with individuals, contexts, and equitably access to learning in mind.

Project: Group-based Cloud Computing for STEM Education

Website: https://www.gbccstem.com/