Supporting Elementary Students' Data Science Literacies Through Interest-Based Learning Activities

• In Event: Fairmont Roundtable Session Three
  In Roundtable Session: Critical Media, Information, and Data Literacies (Table 10)

Abstract

Our research is aimed at improving the capacity of rural elementary teachers to hone students’ data science skills. Connected Learning is used to theorize our work as we explore how interest-based learning and related extension activities promote data science literacies among elementary-aged students. In this paper we focus on how teachers approach developing data science curriculum related to students’ interests, and garner student perspectives. Qualitative research assists in exploring ways teachers created data science activities and how students responded to the activities. We discuss findings based the analysis of observations, teachers’ reflective journals, teacher and student interviews, and artifacts. We demonstrate ways to deepen elementary students' data science engagement through locally relevant problems and interest-based activities to extend learning.

Authors

• Danielle C. Herro, Clemson University
  Presenting Author

• Dara Abimbade, Clemson University
  Presenting Author

• Ibrahim Oluwajoba Adisa, Clemson University
  Presenting Author

• Golnaz Arastoopour Irgens, Clemson University
  Presenting Author

• Shanna E. Hirsch, Clemson University
  Presenting Author

• Matthew J. Madison, University of Georgia
  Presenting Author