Taking data feminism to school
A synthesis and review of pre‐collegiate data science education projects
Bibliographic Data
| ID | 21297789 |
|---|---|
| Authors | Victor R Lee (0000-0001-6434-7589, Graduate School of Education Stanford University Stanford California USA, corresponding author), Daniel R Pimentel (0000-0001-9700-8727, Graduate School of Education Stanford University Stanford California USA), Rahul Bhargava (0000-0003-3904-4302, Journalism and Art + Design Northeastern University Boston Massachusetts USA), Catherine D’ignazio (Massachusetts Institute of Technology), Catherine D'Ignazio (Department of Urban Studies and Planning Massachusetts Institute of Technology Cambridge Massachusetts USA) |
| Year | 2022 |
| Volume | 53 |
| Issue | 5 |
| Pages | 1096-1113 |
| Publication date | 2022-09-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | British Journal of Educational Technology (JOURNAL) |
| Journal identifiers | ISSN: 0007-1013 • E-ISSN: 1467-8535 |
| Publisher | Wiley (PUBLISHER • GB) |
| DOI | 10.1111/bjet.13251 |
| OpenAlex | W4283458724 |
| Language | EN |
| Citations received | 8 |
| References cited | 58 |
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. Practitioner notes What is already known about this topic Data feminism is an emergent framework for changing data practices and discourse in service of equity and justice. Data science education is rapidly growing as a topic of interest in the educational technology research and design communities. Many educational technology and design projects have been launched and shared in publications that preceded the widespread distribution of the data feminism framework. What this paper adds Data feminism is partially re‐articulated in terms familiar to educational technology research communities. Prior and recent projects are organized with respect to how they illustrate potential connections to core data feminism principles. This paper identifies specific strategies that recent projects have used that have potential for realizing data feminism principles. Implications for practice and/or policy Educational technologists can use the re‐articulated principles of data feminism for education to inform their future design work. Tractable steps to achieve data justice that are attainable within existing educational systems can be pursued. Communities can and should bring together multiple ways of knowing to support new educational practices and futures with data.
Engineering ethics · Feminism · Pedagogy · Political science · Public relations · Scholarship · Science education · Sociology · Educational Games and Gamification · Engineering · Gender Studies · Statistics Education and Methodologies · Teaching and Learning Programming
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| Unique citing works | 8 |
|---|---|
| Citations per year | 2 |
| Citation span | 2022 - 2026 (5) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 7 |