Interpreting Data Intersectionally
Data visualization literacy: A feminist starting point
Catherine D’Ignazio and Rahul Bhargava
STEM is a field dominated by white cisgender men. Accordingly, data viz skills often taught in a way that misses important elements that reflect the lived experiences of marginalized communities. D'Ignazio and Bhargava present an emancipatory feminist approach to teaching that will allow young people to become familiar with data visualization and interpretation in a way that enables inclusive inquiry and analysis. This particular type of pedagogy stresses that access to data as well as data analysis and reporting tools are often unavailable for underserved communities. Instead, a pluralistic approach to visual literacy is necessary. By inviting students to consider the context that the data is taken from, using data sets that they can personally connect with, and leaving room for alternative explanations, educators can better develop their students' visual literacy skills in the classroom. Access the text here.