abstract: Advances in technology are fueling a movement toward ubiquity for beyond-the-desktop systems. Novel interaction modalities, such as free space or full body gestures are becoming more common, as demonstrated by the rise of systems such as the Microsoft Kinect. However, much of the interaction design research for such systems is still focused on desktop and touch interactions. Current thinking in free-space gestures are limited in capability and imagination and most gesture studies have not attempted to identify gestures appropriate for public walk-up-and-use applications. A walk-up-and-use display must be discoverable, such that first-time users can use the system without any training, flexible, and not fatiguing, especially in the case of longer-term interactions. One mechanism for defining gesture sets for walk-up-and-use interactions is a participatory design method called gesture elicitation. This method has been used to identify several user-generated gesture sets and shown that user-generated sets are preferred by users over those defined by system designers. However, for these studies to be successfully implemented in walk-up-and-use applications, there is a need to understand which components of these gestures are semantically meaningful (i.e. do users distinguish been using their left and right hand, or are those semantically the same thing?). Thus, defining a standardized gesture vocabulary for coding, characterizing, and evaluating gestures is critical. This dissertation presents three gesture elicitation studies for walk-up-and-use displays that employ a novel gesture elicitation methodology, alongside a novel coding scheme for gesture elicitation data that focuses on features most important to users’ mental models. Generalizable design principles, based on the three studies, are then derived and presented (e.g. changes in speed are meaningful for scroll actions in walk up and use displays but not for paging or selection). The major contributions of this work are: (1) an elicitation methodology that aids users in overcoming biases from existing interaction modalities; (2) a better understanding of the gestural features that matter, e.g. that capture the intent of the gestures; and (3) generalizable design principles for walk-up-and-use public displays. / Dissertation/Thesis / Doctoral Dissertation Computer Science 2019
| Identifer | oai:union.ndltd.org:asu.edu/item:53451 |
| Date | January 2019 |
| Contributors | Danielescu, Lavinia Andreea (Author), Walker, Erin A (Advisor), Burleson, Winslow (Advisor), VanLehn, Kurt (Committee member), Kuznetsov, Anastasia (Committee member), Maher, Mary Lou (Committee member), Arizona State University (Publisher) |
| Source Sets | Arizona State University |
| Language | English |
| Detected Language | English |
| Type | Doctoral Dissertation |
| Format | 187 pages |
| Rights | http://rightsstatements.org/vocab/InC/1.0/ |
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