Advancing Data Science Education in K-12：Research and Theory for Teaching and Learning

Advancing Data Science Education in K-12 offers a highly accessible, research-based treatment of the foundations of data science education and its increasingly vital role in K-12 instructional content.

As federal education initiatives and developers of technology-enriched curricula attempt to incorporate the study of data science—the generation, capture, and computational analysis of data at large scale—into schooling, a new slate of skills, literacies, and approaches is needed to ensure an informed, effective, and unproblematic deployment for young learners. Friendly to novices and experts alike, this book provides an authoritative synthesis of the most important research and theory behind data science education, its implementation into K-12 curricula, and clarity into the distinctions between data literacy and data science. Learning with and about data hold equal and interdependent importance across these chapters, conveying the variety of issues, situations, and decision-making integral to a well-rounded, critically minded perspective on data science education.

Students and faculty in teaching, leadership, curriculum development, and educational technology programs will come away with essential insights into the breadth of our current and future engagements with data; the real-world opportunities and challenges data holds when taught in conjunction with other subject matter in formal schooling; and the nature of data as a human and societal construct that demands new competencies of today’s learners.