  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.
