This paper reports on how 10 middle and high school preservice teachers (PSTs) designed a social justice focused lesson using the culturally responsive mathematics teaching (CRMT) tool. Results from our analysis indicate that most of the PSTs were able to select appropriate social justice topics, though not all the PSTs integrated mathematics and social justice throughout their lessons. The results show that most of the PSTs need more experience with mathematization, handling controversial discussions, and developing transformative student action. Our work also led to a modification of the tool (CRMT-M). We discuss the implications of the study for mathematics teacher preparation.

In this article we analyze the current state of the didactics of mathematics in the U.S. as it relates to research on equity. The sociopolitical turn in U.S. mathematics education resulted in a push for critical mathematics pedagogies (CMPs) in which predominantly marginalized populations of students explore social injustices through mathematics. We argue that mathematics education for equity must access broader populations of students and develop students’ ethical reasoning skills to build an ethical and equitable future. To address didactical limitations in U.S. mathematics education, we introduce the Ethical Reasoning in Mathematics Framework (ERiM) as a tool to analyze high school students’ ethical reasoning in real-world mathematics tasks. Using data from the initial phase of a Design Research project with students of privilege, we show how the ERiM Framework can be used to design lessons that elicit students’ critical math consciousness (CMC). We end the article with design implications and recommendations for future research on the didactics of equitable mathematics.

The emergence of data science, Big Data Analytics, and other related methodologies have resulted in differential outcomes for people situated differently in society. Exacerbating these effects is the privilege hazard (D’Ignazio & Klein, 2020) that occurs when teams of data scientists are composed primarily of individuals from privileged backgrounds. Therefore, the purpose of this article is to understand how educators may support students from different backgrounds (both relatively privileged and marginalized) to participate equitably and meaningfully in ethical data science discussions in order to safeguard against the privilege hazard. To do this, we draw on the literature regarding STEM identity formation, use Cobb and Yackel’s (1996) framework for analyzing social norms for discourse in inquiry-based classrooms, and draw on Hodge and Cobb’s Cultural Participation Orientation towards developing an inclusive classroom environment. Finally, we describe the course design elements (task structures, participation structures, and discursive moves) that supported students’ equitable participation in ethical data science discussions (Sandoval, 2004).

Proceedings of the 16th International Conference. King's College, August 8 - 13, 2022 Band 7 der Reihe Conference Proceedings in Mathematics Education Münster 2022, ca. 600 S. Print: ISBN 978-3-95987-217-1, 69,90 € Ebook: ISBN 978-3-95987-218-8, 60,90 € To appear August 2022 This volume contains the papers presented at the International Conference Building on the Past