Beyond Time and Accuracy: Strategies in Visual Problem-Solving

要旨

In this paper, we explore viewers’ strategies in visual problem-solving tasks. We build on the traditional metrics of accuracy and time to better understand the learning that occurs as individuals interact with visualizations. We conducted an in-lab eye-tracking user study with 53 participants from diverse demographic backgrounds. Using questions from the Visualization Literacy Assessment Test (VLAT), we examined participants’ problem-solving strategies. We employed a mixed-methods approach capturing quantitative data on performance and gaze patterns, as well as qualitative data through think-alouds and sketches by participants as they reported on their problem-solving approach. Our analysis reveals not only the various cognitive strategies leading to correct answers but also the nature of mistakes and the conceptual misunderstandings that underlie them. This research contributes to the enhancement of visualization design guidelines by incorporating insights into the diverse strategies and cognitive processes employed by users.

著者
Eric Mörth
Harvard Medical School, Boston, Massachusetts, United States
Zona Kostic
Harvard University, Boston, Massachusetts, United States
Nils Gehlenborg
Harvard Medical School, Boston, Massachusetts, United States
Hanspeter Pfister
Harvard University, Cambridge, Massachusetts, United States
Johanna Beyer
Harvard University, Cambridge, Massachusetts, United States
Carolina Nobre
University of Toronto, Toronto, Ontario, Canada
DOI

10.1145/3706598.3714024

論文URL

https://dl.acm.org/doi/10.1145/3706598.3714024

動画

会議: CHI 2025

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2025.acm.org/)

セッション: Technologies for Decision Making

G402
6 件の発表
2025-04-30 23:10:00
2025-05-01 00:40:00
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