Beyond Numeracy, a Data Literacy Topical Scoping Review (2011–2023)

• Main Author: Vermeire, Lotte
• Publication Date: 2025
• Other Authors: Van den Broeck, Wendy, Petersen, Fazlyn, Van Audenhove, Leo
• Format: Article
• Language: eng
• Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
• Download full: https://doi.org/10.17645/mac.9237
• topic: data literacy; data skills; media education; topical evolution; understanding data; using data

As society increasingly recognises the value of data, proficiency in using and understanding data has become crucial. However, there is no universal consensus on the definition of data literacy. Therefore, this study provides the first extensive, mixed methods scoping review of the topical evolution of data literacy within social and educational sciences from 2011 to 2023. By identifying key themes and research trends, this review offers a comprehensive understanding of the dynamic nature of data literacy. Our sample consists of 210 English-language, peer-reviewed articles from Scopus and Web of Science. The findings reveal a field that is evolving alongside media and digital literacy discussions, with notable growth in publications, particularly in 2019, 2020, and 2023, thus highlighting data literacy’s recognition as a distinct paradigm. Data literacy is shifting beyond traditional frameworks, with increasing attention to issues of equity and accessibility—areas still underexplored in current literature. Notably, the research demonstrates a shift from simply developing individual data skills to fostering a socially aware form of data literacy that empowers citizens to critically engage with data and navigate a datafied society actively and responsibly. This review emphasises the need for a nuanced, context-specific approach to data literacy, much like digital literacy, as different demographics and contexts encounter varying needs and challenges. As a dynamic, ever-evolving concept, future research and programs must address these diverse levels of engagement and expertise, ensuring that data literacy is inclusive, adaptable, and supported by social structures.