Home /  [Moved Online] Critical Issues in Mathematics Education 2020: Today’s Mathematics, Social Justice, and Implications for Schools

Workshop

[Moved Online] Critical Issues in Mathematics Education 2020: Today’s Mathematics, Social Justice, and Implications for Schools May 15, 2020
Parent Program: --
Series: Critical Issues
Location: SLMath: Online/Virtual
Organizers Meredith Broussard (New York Unviersity), Victor Donnay (Bryn Mawr College), Courtney Ginsberg (Math for America), Luis Leyva (Vanderbilt University), Candice Price (Smith College), Chris Rasmussen (San Diego State University), LEAD Katherine Stevenson (California State University, Northridge), William Tate (Washington University in St. Louis)
Speaker(s)

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Description
Due to the COVID-19 virus outbreak, the Critical Issues in Mathematics Education 2020 workshop was held online. The full workshop description and list of talks can be found HERE. On May 15 portions of the Critical Issues in Mathematics Education 2020: Today’s Mathematics, Social Justice, and Implications for Schools workshop will be streamed online via Zoom. Friday 5/15: 12pm PST (3pm eastern time) 12:00 - 1:00 Dan Reinholz, Preparing teachers to notice, name, and disrupt racial and gender inequity Workshop Description: Sophisticated computational and quantitative techniques drive important decision-making in modern society.  Such methods and algorithms are meant to improve the efficiency with which we work and the ways in which we live.  An understanding of the mathematical underpinnings of these techniques can be used either to disrupt or to perpetuate inequities, and thus such knowledge constitutes power in the modern world. How does this powerful knowledge get used for the common good and get passed on to our children equitably? What does it imply about the kinds of mathematical skills, practices, and dispositions students should learn in schools, colleges, and universities? Three guiding questions: What are the major areas where computational and quantitative methods have influence, and what does work in these areas imply for mathematics and the mathematics community? Gerrymandering and apportionment Recruitment, enrollment, and retention decision making to drive “academic efficiency” (e.g., Student data analytics to inform access to academic programs and classes) Sentencing, bail, and parole (e.g., artificial intelligence based models used by judges) Systems that guide policing, driving, and medical decisions (e.g., artificial intelligence & visual recognition systems in investigations, navigation, treatment options, drug development) Efficiency and pricing via online systems (e.g., surge pricing , routing algorithms) Determination of loan or insurance terms Surveillance of email, mail, phone, online trace (e.g., Hong Kong, China, England, US) What are the social justice and educational equity implications of mathematical work in these areas? Who is impacted and how are traditionally underserved communities disproportionately and negatively impacted? What are the human capital development implications? Who gets access to these methods? What current and historical inequities is this work exposing or perpetuating? How do computational systems impact privacy and social/political movements? (Surveillance dampens free speech while social media facilitates grassroots action.) How might negative impacts of computational and quantitative methods be countered? Can we use these methods to design for social good? In light of the above, what are the implications for the mathematical knowledge, skills, and ways of interacting to be developed in schools? What might society, as well as specific communities and families, want children to learn in school and students to learn in colleges and universities? What mathematics is important for educators to nurture in order to build a more just society?  How might the enactment of different pedagogical approaches  (e.g., problem-based learning, inquiry based approaches, culturally responsive pedagogy,  flipped classrooms) either broaden or limit opportunities for equitable quantitative and computational learning?  How might various technologies and digital tools be used to promote equitable student learning of computational techniques and concepts?  What are the implications for teacher preparation at the elementary, secondary, and postsecondary levels of mathematics education? 
Keywords and Mathematics Subject Classification (MSC)
Primary Mathematics Subject Classification No Primary AMS MSC
Secondary Mathematics Subject Classification No Secondary AMS MSC
Schedule, Notes/Handouts & Videos
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May 15, 2020
Friday
12:00 PM - 01:00 PM
  Preparing teachers to notice, name, and disrupt racial and gender inequity
Daniel Reinholz (San Diego State University)