Voicing Code in STEM by Pratim Sengupta

Author:Pratim Sengupta
Language: eng
Format: epub
Tags: STEM Education; Science Education; Computing Education; Computational Thinking; Technocentrism;
Publisher: MIT Press

5.5 Designing for Transitional Othering

5.5.1 Setting and Tools

We now provide an example of the learning environment designed to support transitional othering. The setting of this study was a semester-long course in human geography in the Secondary Education Social Studies program in a major private university in the Mid-South. Nineteen students (eight senior undergraduate students and 11 master’s students), all preservice teachers, attended the course. This study took place in the middle of the course. In class sessions prior to the study, students had discussed the relevance of zoning and the impact of the Civil War and Jim Crow laws on urban segregation in the Southern US cities. Our work was motivated by the fact that despite such curricular experiences, prior to introducing multiagent representations, when we asked the class to design lesson plans for teaching about the Civil War and political zoning in the South, none of the students explicitly mentioned or designed any activity that involved explicitly reasoning about race and racial inequalities. Our goal was to see if and how students’ experiences with agent-based computational representations of segregation and ethnocentrism could reshape their lesson plan designs, with the hope that such interactions would facilitate a more direct engagement with issues related to race and racism, as well as other forms of inequality.

We adopted Wilensky and Rand’s implementation53 of Axelrod and Hammond’s model of ethnocentrism54 in the NetLogo multiagent platform.55 We developed a set of programming blocks in the ViMAP block-based programming and modeling platform.56 Using the ViMAP programming blocks, students could control the NetLogo code and the simulation, and doing so also made the underlying rules explicit to them (Figure 5.4). Overall results from running the simulation were displayed in the form of multiple graphs in separate windows. These graphs showed how the populations of the different strategies would compare with each other, as the simulation unfolded.

Figure 5.4

A ViMAP implementation of Wilensky’s code

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