Situating Data Science: Exploring How Relationships to Data Shape Learning

TLDR

Data Science has profoundly impacted science and society, prompting calls for a dedicated field of Data Science Education, yet its scope, responsibilities, and implementation remain under‑conceptualized. This special issue investigates how Data Science’s focus on socially and environmentally embedded data shapes learning and education. The learning sciences examine how such contextual embeddings influence learners’ engagement with data across conceptual, experiential, communal, racialized, spatial, and political dimensions. The issue shows that learners’ relationships with data are richly layered and essential for navigating data as social text, offering a vision for a more expansive, agentive, and socially aware Data Science Education.

Abstract

The emerging field of Data Science has had a large impact on science and society. This has led to over a decade of calls to establish a corresponding field of Data Science Education. There is still a need, however, to more deeply conceptualize what a field of Data Science Education might entail in terms of scope, responsibility, and execution. This special issue explores how one distinguishing feature of Data Science—its focus on data collected from social and environmental contexts within which learners often find themselves deeply embedded—suggests serious implications for learning and education. The learning sciences is uniquely positioned to investigate how such contextual embeddings impact learners' engagement with data including conceptual, experiential, communal, racialized, spatial, and political dimensions. This special issue demonstrates the richly layered relationships learners build with data and reveals them to be not merely utilitarian mechanisms for learning about data, but a critical part of navigating data as social text and understanding Data Science as a discipline. Together, the contributions offer a vision of how the learning sciences can contribute to a more expansive, agentive and socially aware Data Science Education.