"Piecing Data Connections Together Like a Puzzle": Effects of Increasing Task Complexity on the Effectiveness of Data Storytelling Enhanced Visualisations

要旨

The emerging concept of data storytelling (DS) suggests that enhancing visualisations with annotations and narratives can make complex data more insightful than conventional visualisations. Previous works found that DS-enhanced visualisations are more effective than conventional visualisations for simple tasks like identifying key data points or the main message. However, no previous work has explored the extent to which DS enhancements influence task completion across different levels of cognitive complexity. We address this gap by presenting the results of a study where 128 participants completed tasks based on four visualisations (two line charts and two choropleth maps, either with or without DS elements) spanning a range of complexity based on Bloom's taxonomy, which has been applied in data visualisation to categorise tasks hierarchically from lower to higher-order thinking. Results suggest that while DS-enhanced visualisations effectively support lower-order tasks (finding data points and understanding insights), they don't necessarily aid the correct completion of higher-order tasks (application, analysis, evaluation and creation). However, DS enhancements improve how efficiently participants complete complex tasks.

著者
Mikaela Elizabeth. Milesi
Monash University, Melbourne, Australia
Paola Mejia-Domenzain
EPFL, Lausanne, Switzerland
Laura Brandl
LMU Munich, Munich, Germany
Vanessa Echeverria
Monash University, Clayton, Australia
Yueqiao Jin
Monash University, Clayton, Victoria, Australia
Dragan Gasevic
Monash University, Clayton, Victoria, Australia
Yi-Shan Tsai
Monash University, Melbourne, Australia
Tanja Käser
EPFL, Lausanne, Switzerland
Roberto Martinez-Maldonado
Monash University, Melbourne, Victoria, Australia
DOI

10.1145/3706598.3714270

論文URL

https://dl.acm.org/doi/10.1145/3706598.3714270

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: Interactive Data Visualization

G304
7 件の発表
2025-04-29 18:00:00
2025-04-29 19:30:00
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