Examining How Students Code With Socioscientific Data to Tell Stories About Climate Change (Poster 49)

• In Event: AERA Poster Session Two
  In Poster Session: STEM Learning and Technology

Abstract

Data and computational literacies are important in our data-driven society. However, there are few opportunities for youth to learn to wrangle data, visualize data, and tell data stories about important socioscientific issues. To fill this gap, we conducted a design-based research project, in which high school youth learned to code with large datasets to build data visualizations and tell data stories about climate change. To understand student learning trajectories across computing and storytelling activities, we used interaction analysis methods to develop the Computational Data Literacies Model. We describe students’ participation in various computational data literacies practices and their use of various data tools in our model. Our findings shed light on learning designs for supporting data practices about socioscientific issues.

Authors

• Changzhao Wang, University of Southern California
  Presenting Author

• Hamid Sanei, North Carolina State University
  Presenting Author

• Rabia Yalcinkaya, North Carolina State University
  Presenting Author

• Shiyan Jiang, North Carolina State University
  Presenting Author

• Jennifer Beth Kahn, University of Miami
  Presenting Author