Augmenting Feature Importance Analysis: How Color and Size Can Affect Context-Aware AR Explanation Visualizations?

Augmented Reality (AR) has shown significant potential in supporting in-situ decision-making in various application areas. Many prior works have shown how AR can visualize the decision support data in various contexts. However, prior research about AR-based decision support systems rarely explored how the explanations were visualized. Providing context-aware explanations within AR-based recommendation systems may help users instantly understand the recommendations they have been given. Therefore, this paper presents the world-first user study exploring AR explanation visualization designs. Three feature importance analysis visualizations that apply different color-coding and size-scaling strategies were designed to explain the recommendations provided by a context-aware AR shopping assistant system. Twenty-four participants were recruited to evaluate these three explanations in a shopping scenario. The results revealed novel findings that could help guide the appropriate utilization of descriptive parameters when designing AR explanation artifacts. The results also show the potential of providing intuitive visualization to explain recommendations in AR.