Cafaro, FrancescoLyons, LeilahAntle, Alissa N.2019-12-312019-12-312018-04Cafaro, F., Lyons, L., & Antle, A. N. (2018, April). Framed Guessability: Improving the Discoverability of Gestures and Body Movements for Full-Body Interaction. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (p. 593). ACM. https://doi.org/10.1145/3173574.3174167https://hdl.handle.net/1805/21642The wide availability of body-sensing technologies (such as Nintendo Wii and Microsoft Kinect) has the potential to bring full-body interaction to the masses, but the design of hand gestures and body movements that can be easily discovered by the users of such systems is still a challenge. In this paper, we revise and evaluate Framed Guessability, a design methodology for crafting discoverable hand gestures and body movements that focuses participants' suggestions within a "frame," i.e. a scenario. We elicited gestures and body movements via the Guessability and the Framed Guessability methods, consulting 89 participants in-lab. We then conducted an in-situ quasi-experimental study with 138 museum visitors to compare the discoverability of gestures and body movements elicited with these two methods. We found that the Framed Guessability movements were more discoverable than those generated via traditional Guessability, even though in the museum there was no reference to the frame.enPublisher Policyembodied interactionfull-body interactionhuman-data interactionConference proceedings