Integrating Data Literacy Into Social Studies Education With Discipline-Specific Visualization Tools (Poster 1)

• In Event: Computational Thinking in Humanities

Abstract

Objectives
Data literacy is important for students, especially in a social studies context. They need to be able to question data sources and whether they find the visualization to be believable and informative – or to be yet another source of misinformation. If we want students to transfer these practices into the rest of their lives, data literacy needs to be situated in social studies classes. Visualizations that aim to influence citizens’ behavior, attitudes, or votes are about issues from social studies classes (e.g., history, civics, geography).
We aim to create data visualization resources and tools explicitly for social studies teachers through a process of participatory design.

Background
All 50 states require students to be taught data literacy in social studies classes (Shreiner, 2020). However, few social studies teachers actually teach data literacy, and they are seldom taught how to teach data literacy (Shreiner & Dykes, 2021). There are also few resources for teaching data literacy in social studies and the tools that do exist for K-12 data visualization were typically created for STEM teachers and classes. These tools do not speak to social studies teachers.
We are creating curricular resources and data visualization tools that are specifically created for social studies teachers. We use participatory design approaches to engage social studies teachers in the processes and practices of data literacy (DiSalvo, Yip, Bonsignore, and DiSalvo, 2017). 


Methods & Data Sources
We have used participatory design sessions with both pre-service and in-service social studies teachers (Naimipour, Guzdial, and Shreiner, 2019; Naimipour, Guzdial, & Shreiner, 2020). We present them with a variety of data visualization tools, from CODAP (Finzer & Damelin, 2016) to our tools like DV4L (Naimipour, Rauch, Shreiner, & Guzdial, 2021). We ask them what they like, what they dislike, and what features would make them likely to adopt.

Results
While many indicators suggest that our professional learning sessions have impacted teacher learning and attitudes, we still have very few adoptions of our data literacy resources and tools (Shreiner & Guzdial, 2022). We have framed our work in terms of the Technology Acceptance Model (TAM; Lee, Kozar, & Larsen, 2003). TAM suggests that the critical issues for adoption of a given technology are *usability* and *usefulness*. Our results suggest that a third variable is critical: *context*. If computational tools are uncommon, or even frowned upon in social studies classes in a given school or district, the social studies teacher is fighting against headwinds to adopt.


Scholarly Significance
Our results support our hypothesis that educational technology can help teachers learn about data literacy in social studies, and social studies teachers want simple tools that fit with their existing curricula, give them new project ideas, and help students learn difficult concepts. However, we now believe that making tools useful and usable does not predict adoption; context plays a large role in a social studies teachers’ adoption.

Authors

• Mark J. Guzdial, University of Michigan
  Presenting Author

• Tamara L. Shreiner, Grand Valley State University
  Presenting Author