English

Cultivating Visualization Literacy for Children Through Curiosity and Play

Human-Computer Interaction 2022-08-11 v1

Abstract

Fostering data visualization literacy (DVL) as part of childhood education could lead to a more data literate society. However, most work in DVL for children relies on a more formal educational context (i.e., a teacher-led approach) that limits children's engagement with data to classroom-based environments and, consequently, children's ability to ask questions about and explore data on topics they find personally meaningful. We explore how a curiosity-driven, child-led approach can provide more agency to children when they are authoring data visualizations. This paper explores how informal learning with crafting physicalizations through play and curiosity may foster increased literacy and engagement with data. Employing a constructionist approach, we designed a do-it-yourself toolkit made out of everyday materials (e.g., paper, cardboard, mirrors) that enables children to create, customize, and personalize three different interactive visualizations (bar, line, pie). We used the toolkit as a design probe in a series of in-person workshops with 5 children (6 to 11-year-olds) and interviews with 5 educators. Our observations reveal that the toolkit helped children creatively engage and interact with visualizations. Children with prior knowledge of data visualization reported the toolkit serving as more of an authoring tool that they envision using in their daily lives, while children with little to no experience found the toolkit as an engaging introduction to data visualization. Our study demonstrates the potential of using the constructionist approach to cultivate children's DVL through curiosity and play.

Keywords

Cite

@article{arxiv.2208.05015,
  title  = {Cultivating Visualization Literacy for Children Through Curiosity and Play},
  author = {S. Sandra Bae and Rishi Vanukuru and Ruhan Yang and Peter Gyory and Ran Zhou and Ellen Yi-Luen Do and Danielle Albers Szafir},
  journal= {arXiv preprint arXiv:2208.05015},
  year   = {2022}
}

Comments

11 pages, 8 figures, 1 table, accepted to IEEE Transaction on Visualization and Graphics (also appearing in the proceedings of IEEE VIS 2022)