How Learners Sketch Data Stories
R. Bhargava (1), D. Williams (1), D. D'Ignazio (2) ((1) Northeastern, University, (2) MIT)

TL;DR
This paper analyzes 101 data sketches created by learners, revealing common practices and preferences in visual encodings and storytelling methods to inform educational tools and programs.
Contribution
It introduces a classification of learner-created data sketches and provides insights into their common visual and structural features, bridging a gap in data storytelling education.
Findings
Preference for positional and shape-based encodings
Frequent use of symbolic and textual representations
High prevalence of stories comparing data subsets
Abstract
Learning data storytelling involves a complex web of skills. Professional and academic educational offerings typically focus on the computational literacies required, but professionals in the field employ many non-technical methods; sketching by hand on paper is a common practice. This paper introduces and classifies a corpus of 101 data sketches produced by participants as part of a guided learning activity in informal and formal settings. We manually code each sketch against 12 metrics related to visual encodings, representations, and story structure. We find evidence for preferential use of positional and shape-based encodings, frequent use of symbolic and textual representations, and a high prevalence of stories comparing subsets of data. These findings contribute to our understanding of how learners sketch with data. This case study can inform tool design for learners, and help…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsData Visualization and Analytics · Video Analysis and Summarization · Species Distribution and Climate Change
