Taking Data Feminism to School: A Synthesis and Review of Pre-Collegiate Data Science Education Projects

Autor/inn/en	Lee, Victor R.; Pimentel, Daniel R.; Bhargava, Rahul; D'Ignazio, Catherine
Titel	Taking Data Feminism to School: A Synthesis and Review of Pre-Collegiate Data Science Education Projects
Quelle	In: British Journal of Educational Technology, 53 (2022) 5, S.1096-1113 (18 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Lee, Victor R.)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0007-1013
DOI	10.1111/bjet.13251
Schlagwörter	Data; Feminism; Scholarship; Humanization; Power Structure; Educational Research; Research Design; Educational Technology; Cultural Pluralism; Social Justice; Inclusion; Statistics Education; Elementary Secondary Education + Suchen Sie Ihr Suchwort? Daten; Feminismus; Scholarships; Stipendium; Humanisierung; Bildungsforschung; Pädagogische Forschung; Forschungsdesign; Unterrichtsmedien; Kulturpluralismus; Soziale Gerechtigkeit; Inklusion
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. (As Provided).
Anmerkungen	Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01