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E-raamat: Advancing Data Science Education in K-12: Foundations, Research, and Innovations [Taylor & Francis e-raamat]

  • Formaat: 154 pages, 4 Tables, black and white; 4 Line drawings, color; 9 Line drawings, black and white; 3 Halftones, color; 3 Halftones, black and white; 7 Illustrations, color; 12 Illustrations, black and white
  • Ilmumisaeg: 24-Feb-2025
  • Kirjastus: Routledge
  • ISBN-13: 9781003385264
  • Taylor & Francis e-raamat
  • Hind: 161,57 €*
  • * hind, mis tagab piiramatu üheaegsete kasutajate arvuga ligipääsu piiramatuks ajaks
  • Tavahind: 230,81 €
  • Säästad 30%
  • Formaat: 154 pages, 4 Tables, black and white; 4 Line drawings, color; 9 Line drawings, black and white; 3 Halftones, color; 3 Halftones, black and white; 7 Illustrations, color; 12 Illustrations, black and white
  • Ilmumisaeg: 24-Feb-2025
  • Kirjastus: Routledge
  • ISBN-13: 9781003385264

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.



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 to 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.

1. Data Everywhere
2. Data Literacy, Data Science, and Terms that Trip Us Up
3. Humans Thinking About Data
4. Teaching Data Science in Schools
5. Learning Data Science Outside of Schools
6. Expansive Views for Data Science Education
7. Onward - A Data Science Education Research Ecosystem

Victor R. Lee is Associate Professor in the Graduate School of Education at Stanford University, USA. His previous books are Reconceptualizing Libraries: Perspectives from the Information and Learning Sciences and Learning Technologies and the Body: Integration and Implementation in Formal and Informal Learning Environments. He received his PhD in Learning Sciences from Northwestern University and holds bachelors degrees in Cognitive Science and Mathematics from the University of California San Diego.