Iterative Design of Gestures During Elicitation: Understanding the Role of Increased Production
This work addresses the problem of legacy bias in gesture design for HCI researchers, though it is incremental as it builds on prior studies of increased production.
The study investigated how increased gesture production during elicitation affects gesture quality and variety, finding that users refine promising gestures and the time to find them varies by participant, with refinements offering insights into meaningful gestural features.
Previous gesture elicitation studies have found that user proposals are influenced by legacy bias which may inhibit users from proposing gestures that are most appropriate for an interaction. Increasing production during elicitation studies has shown promise moving users beyond legacy gestures. However, variety decreases as more symbols are produced. While several studies have used increased production since its introduction, little research has focused on understanding the effect on the proposed gesture quality, on why variety decreases, and on whether increased production should be limited. In this paper, we present a gesture elicitation study aimed at understanding the impact of increased production. We show that users refine the most promising gestures and that how long it takes to find promising gestures varies by participant. We also show that gestural refinements provide insight into the gestural features that matter for users to assign semantic meaning and discuss implications for training gesture classifiers.