5 papers · 1 filter
Enhanced Self-Learning with Epistemologically-Informed LLM Dialogue
Yi-Fan Cao, Kento Shigyo, Yitong Gu +6
Large Language Models (LLMs) have advanced self-learning tools, enabling more personalized interactions. However, learners struggle to engage in meaningful dialogue and process com…
Contextualization or Rationalization? The Effect of Causal Priors on Data Visualization Interpretation
Arran Zeyu Wang, David Borland, Estella Calcaterra +1
Understanding how individuals interpret charts is a crucial concern for visual data communication. This imperative has motivated a number of studies, including past work demonstrat…
Visual Analytics for Causal Reasoning from Real-World Health Data
Arran Zeyu Wang, David Borland, David Gotz
The increasing capture and analysis of large-scale longitudinal health data offer opportunities to improve healthcare and advance medical understanding. However, a critical gap exi…
Beyond Correlation: Incorporating Counterfactual Guidance to Better Support Exploratory Visual Analysis
Arran Zeyu Wang, David Borland, David Gotz
Providing effective guidance for users has long been an important and challenging task for efficient exploratory visual analytics, especially when selecting variables for visualiza…
Causal Priors and Their Influence on Judgements of Causality in Visualized Data
Arran Zeyu Wang, David Borland, Tabitha C. Peck +2
"Correlation does not imply causation" is a famous mantra in statistical and visual analysis. However, consumers of visualizations often draw causal conclusions when only correlati…