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  3. Data Literacy in the Real World: Conversations & Case Studies

Data Literacy in the Real World: Conversations & Case Studies

Edited by Kristin Fontichiaro, Amy Lennex, Tyler Hoff, Kelly Hovinga and Jo Angela Oehrli
Open Access Open Access
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  • Overview

  • Contents

Knowing how to recognize the role data plays in our lives is critical to navigating today’s complex world. In this volume, you’ll find two kinds of professional development tools to support that growth. Part I contains pre-made professional development via links to webinars from the 2016 and 2017 4T Virtual Conference on Data Literacy, along with discussion questions and activities that can animate conversations around data in your school. Part II explores data “in the wild” with case studies pulled from the headlines, along with provocative discussion questions, professionals and students alike can explore multiple perspectives at play with Big Data, data privacy, personal data management, ethical data use, and citizen science.
  • Cover Page
  • Title Page
  • Copyright Page
  • Contents
  • Introduction
  • Part I. Webinars
    • A. “But it’s a number, so it has to be true!”: An introduction to data literacy, Part I
    • B. “But it’s a number, so it has to be true!”: An introduction to data literacy, Part II
    • C. Where the rubber meets the road: Data literacy in the content areas
    • D. Information literacy includes data literacy!
    • E. Close reading: Unpacking the impact language has on how we understand statistics
    • F. Real world data fluency: How to use raw data
    • G. Gathering data via action research: A plan for librarians, classroom teachers, and students
    • H. Data literacy and voting
    • I. Making sense of data visualization
    • J. DataBasic.io: Tools & activities that help introduce newcomers to data storytelling
    • K. Data presentation: Showcasing your data with charts and graphs
    • L. Using Social Explorer to help students gain insight
    • M. Infographics: An instructional lens
    • N. Tools for preserving your personal and intellectual privacy
    • O. Big Data and you: Normalizing the practices of privacy
    • P. The right to obscurity vs. the digital Eye of Sauron
    • Q. Student data privacy: Protecting the personal information that informs instruction
    • R. DataRefuge: Preserving data and growing literacy
    • S. Science in the wild: How to make the most of citizen science projects at your school
  • Part II. Case Studies
    • Personal Data Management
      • 1. Your presence on social media
      • 2. Tracking student physical activity in school
      • 3. Amazon Echo Look
      • 4. Smart home devices in court
      • 5. DNA mapping
      • 6. When insurance gives you a fitness tracker
      • 7. Hiding from digital marketing
      • 8. ISP consumer data collection
      • 9. Encrypted data, privacy, and government access
      • 10. Protecting your rights through civic engagement
      • 11. What is a reasonable expectation of privacy?
      • 12. Intergenerational differences and data privacy: Generational shift or developmental stage?
      • 13. Comparing United States and European Union approaches to privacy
      • 14. Be strategic! Reading and understanding terms of service and privacy policies
      • 15. What does Cambridge Analytica have about you?
    • Citizen Science
      • 1. Scientists and citizen scientists: Cooperation and reservations
      • 2. Candy Crush and Zooniverse: The psychology of citizen science
      • 3. Citizen science techniques to uncover insights in the humanities
      • 4. Tour of the Leafsnap leaf identification app
      • 5. Habitat Network: Learning about and managing the landscape we share
      • 6. Smithsonian Institution Transcription Center
      • 7. Where does federal data go?
      • 8. Native knowledge meets scientific knowledge through citizen science
      • Bonus feature: Choosing a citizen science project for your classroom
    • Big Data
      • 1. Unroll.me email tracking and data sale
      • 2. Big Data and discrimination
      • 3. Television sets collecting data without notifying consumers
      • 4. Big Data and self-driving trucks
      • 5. Predictive policing: The seduction of technology
      • 6. Big Data in banking and loans
      • 7. Bias in student predictive analytics data: Does it help or hinder potential prospects/relationships?
      • 8. Cross conversion tracking: Linking in-store purchases with online ads
      • 9. The ethics of Mechanical Turk
      • 10. The dark side of data: Using data as a means of stalking, surveilling, or preying on vulnerable populations
    • Ethical Data Use
      • 1. The personal information you are giving away
      • 2. Protecting student data in schools
      • 3. SAT and ACT information: What happens to it?
      • 4. Surveillance cameras in schools and the case of special education
      • 5. Student privacy in the age of cloud storage
      • 6. Big Data and government nudges
      • 7. The fear factor: Hyped-up use of data to sway public opinion/behavior
      • 8. Those smart devices are smarter than you think
      • 9. Canaries in the mine: Chicago and Flint — haves vs. have-nots in use of data
      • 10. The implications of privacy regulation on Internet privacy
      • 11. Data philanthropy
  • Appendix A: Data literacy rules of thumb
  • Data literacy related standards
  • Creating Data Literate Students
  • Contributors
  • Index
Citable Link
Published: 2017
Publisher: Michigan Publishing, University of Michigan Library
ISBN(s)
  • 9781607854531 (ebook)
  • 9781607854524 (hardcover)
Series
  • Maize Books
Subject
  • LANGUAGE ARTS & DISCIPLINES / Library & Information Science/General
  • EDUCATION / Computers & Technology
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