Social justice mathematical modeling is powerful in helping teachers build awareness of social issues, critique existing systems, and engage in rich mathematical reasoning. In this article, we document a task in which 28 preservice teachers (PSTs) explored if teacher pay is fair and how to define “fair” mathematically. Through qualitative analysis of PSTs’ reflections, we studied the effectiveness of the task through the lens of critical consciousness. Twenty-six of the participants reported developing social and mathematical agency with respect to the task. Because the task related to PSTs’ lived experiences, it allowed them to examine their assumptions about teacher pay, empowered them to use mathematics to explore different perspectives, and helped them envision ways they could enact change.
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Modeling for social justice: A Model-Eliciting Activity on gerrymandering
Mathematics educators and researches have recommended that pre-service secondary mathematics teachers (PSTs) need opportunities both to engage in rich mathematical modeling and also to examine issues of social justice and equity. This poster describes a model-eliciting activity which aims to engage PSTs in mathematizing and modeling the social justice issue of gerrymandering. In the activity, PSTs are given a variety of data (including printed maps as well as the area and perimeter of congressional districts) and challenged to construct a mathematical model of “compactness.” PSTs must iteratively refine their model to rank congressional districts from most to least compact. This model-eliciting activity draws on geometric topics including a consideration of area, perimeter, scale, and attributes of shapes, while simultaneously provoking PSTs to reflect on the use of mathematics to inform public policy and positively transform our world.
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- Award ID(s):
- 1852846
- PAR ID:
- 10168680
- Date Published:
- Journal Name:
- Proceedings of the 41st Annual Meeting of the North American Chapter of the International Group for the Psychology of Mathematics Education
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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