Taking data feminism to school: A synthesis and review of pre‐collegiate data science education projects
Name
Brit J Educational Tech - 2022 - Lee - Taking data feminism to school A synthesis and review of pre‐collegiate data.pdf
Description
Published version
Size
1.33 MB
Format
Adobe PDF
Checksum (MD5)
dbdcf6cf09563268e1af99a470b09eb6
Author(s)
Lee, Victor R
Pimentel, Daniel R
Bhargava, Rahul
D'Ignazio, Catherine
Date Issued
September 2022
Journal
British Journal of Educational Technology
Publisher
Wiley
Citation
Lee, Victor R, Pimentel, Daniel R, Bhargava, Rahul and D'Ignazio, Catherine. 2022. "Taking data feminism to school: A synthesis and review of pre‐collegiate data science education projects." British Journal of Educational Technology, 53 (5).
Version
Final published version
Abstract
As the field of K-12 data science education continues to take form, humanistic approaches to teaching and learning about data are needed. Data feminism is an approach that draws on feminist scholarship and action to humanize data and contend with the relationships between data and power. In this review paper, we draw on principles from data feminism to review 42 different educational research and design approaches that engage youth with data, many of which are educational technology intensive and bear on future data-intensive educational technology research and design projects. We describe how the projects engage students with examining power, challenging power, elevating emotion and lived experience, rethinking binaries and hierarchies, embracing pluralism, considering context, and making labour visible. In doing so, we articulate ways that current data education initiatives involve youth in thinking about issues of justice and inclusion. These projects may offer examples of varying complexity for future work to contend with and, ideally, extend in order to further realize data feminism in K-12 data science education.
MIT Department
Massachusetts Institute of Technology. Department of Urban Studies and Planning
Terms of Use
Creative Commons Attribution-NonCommercial-NoDerivs
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1111/bjet.13251
