Conceptualizing Data Literacy for Citizenship

Abstract This survey paper opens a Special Issue of ZDM – Mathematics Education on “Enhancing data literacy for citizenship: Innovative approaches in data science and statistics education.” In this paper we aim to conceptualize ‘data literacy for citizenship’ (DataLitCit), going beyond prior conceptualizations of statistical and data literacies. We propose a working definition of DataLitCit that integrates notions of citizenship with the landscape of statistical and data literacies, and elaborate on four key areas that we consider particularly relevant for developing DataLitCit, including: criticality, data argumentation and evidentiary practices, models and modeling, and creating a bridge to AI literacy. We end with a discussion of the key contributions of the paper, and implications for education and future research directions.