A better fit: using data roles to appeal to more learners and promote critical data literacy

There is growing interest in empowering learners to use and critique data due to its rising influence in society. Educational approaches that foster critical uses of data and appeal to a diverse range of learners can more broadly and equitably prepare active data-literate citizens. We develop and explore a role framework intended to support the different processes of critical data literacy and motivate learners with different disciplinary backgrounds and interests. We use our data roles of Journalist, Detective, Scientist, and Artist to help structure curriculum and model ways of participating on a team in a data-driven, advocacy-focused summer program for high-school-aged learners. Through qualitative analysis, we observed that the data roles varied in the types of critical data literacy processes they engaged, suggesting roles could more broadly support the different stages of using data for empowerment and change. Learners also varied in how they connected with roles based on associated experiences, values, and pleasure, suggesting data roles could provide additional ways to motivate learners and appeal to their disciplinary interests. We introduce a new approach for collaboratively supporting critical data literacies and incorporating other disciplinary interests. Our results suggest a role framework for data literacy may offer additional affordances and synergies for using data in transformative ways and may help broaden data’s appeal to learners.