Please use this identifier to cite or link to this item: https://repository.isls.org//handle/1/10242
Title: Constructing “Kinds of People” With Data in Classroom Talk: Operationalizing Racial Data Literacy
Authors: Radinsky, Josh
Tabak, Iris
Keywords: Learning Sciences
Issue Date: 2023
Publisher: International Society of the Learning Sciences
Citation: Radinsky, J. & Tabak, I. (2023). Constructing “kinds of people” with data in classroom talk: Operationalizing racial data literacy. In Blikstein, P., Van Aalst, J., Kizito, R., & Brennan, K. (Eds.), Proceedings of the 17th International Conference of the Learning Sciences - ICLS 2023 (pp. 226-233). International Society of the Learning Sciences.
Abstract: In this conceptual paper we use vignettes from classroom interactions to examine the construct of racial data literacy. Two cases of teaching and learning with data visualizations about racialized populations in the United States – African Americans and Mexican Americans – are used to illustrate the ways racial literacy and data literacy can intertwine in classroom discourse, with stakes for learning and learners. Examining our own teaching, the paper invites the Learning Sciences community to take up the project of further operationalizing racial data literacy, and building a shared understanding of how we can promote it in classroom practice.
Description: Long Paper
URI: https://doi.org/10.22318/icls2023.647362
https://repository.isls.org//handle/1/10242
Appears in Collections:ISLS Annual Meeting 2023

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