Data science skills and practices assist people of all ages in making informed decisions to better understand risks for individuals and broader society. The increasing visibility of data science competencies in K-12 standards and teaching signifies data science as a valued area of study. However, the integration of data science into elementary school education is still limited.
Our research investigates the ways that children think and learn about data visualizations, how they engage in data storytelling, and how to design spaces and tools that facilitate excitement around data science literacies.
Our approach to AI education combines foundational technical knowledge of how AI systems work with a deep understanding of their social, ethical, and political impacts. It involves critically engaging with how these systems are designed, who they serve, and what consequences they carry.
To develop a critical awareness of AI, learners must also have foundational technical literacies such as how people use data to train algorithms to make predictions. This appraoch empowers individuals not just to use AI tools, but to question, challenge, and create them.







