Recently, a new colleague Katie Stofer and I visited Hatfield Marine Science Center, a research site affiliated with Oregon State University, in Newport, OR, to conduct an observational study of how visitors to a public science center use gestures to interact with tech-enabled exhibits. In our case, we looked at exhibits running on a touch table and a touch wall already in use at the center. We wrote a guest blog post about our visit for the Free-Choice Learning Laboratory’s website. The Free-Choice Learning Laboratory focuses on how people learn in informal settings, typically when the learning is at their own pace and by their own choice. I’m particularly interested in how gestural interactions on touchscreens both hinder and afford learning. Read the blog post here.
Category Archives: Publication
More work with my University of Maryland collaborators, including assistant professor Leah Findlater, has been accepted for publication! Look for our short paper “Understanding Child-Defined Gestures and Children’s Mental Models for Touchscreen Tabletop Interaction” to appear at the upcoming Interaction Design and Children (IDC) 2014 conference. We extended prior work by Jacob O. Wobbrock and colleagues in a paper from CHI 2009 on eliciting gesture interactions for touchscreen tabletops directly from users themselves; in our case, we asked children to define the gestures, and compared them to similar gestures designed by adults. Here is the abstract:
Creating a pre-defined set of touchscreen gestures that caters to all users and age groups is difficult. To inform the design of intuitive and easy to use gestures specifically for children, we adapted a user-defined gesture study by Wobbrock et al.  that had been designed for adults. We then compared gestures created on an interactive tabletop by 12 children and 14 adults. Our study indicates that previous touchscreen experience strongly influences the gestures created by both groups; that adults and children create similar gestures; and that the adaptations we made allowed us to successfully elicit user-defined gestures from both children and adults. These findings will aid designers in better supporting touchscreen gestures for children, and provide a basis for further user-defined gesture studies with children.
You can see the camera-ready version of the paper here. The conference will be held in Aarhus, Denmark (home of LEGO!). Unfortunately, I won’t be attending, but first-author (and graduating Master’s student) Karen Rust will present the paper at the conference. Look for her in the short paper madness session, and the poster session!
In April, I received a very nice email from Computing Reviews, a joint publication of the ACM and ThinkLoud, that our CHI 2013 paper “Analyzing User-Generated YouTube Videos to Understand Touchscreen Use by People with Motor Impairments” was acknowledged as a notable paper in computer science for 2013! Out of all the papers published in computer science in 2013, only 94 papers were acknowledged in this way. There is even a brief review summarizing the work and its expected impact as part of the honor. This work also received a ‘CHI Best Paper Award,’ an honor only the top 1% of papers appearing at that conference receives. I did that work while at UMBC, and my co-authors are from the University of Maryland (including assistant professor Leah Findlater). We are very proud of this paper, and we hope that this publicity will serve to broaden the scope of its impact, enabling further improvements to the accessibility of touchscreens, and other technologies, for adults and children with disabilities.
We are pleased to announce that a new paper on the MTAGIC project has been accepted to the International Journal of Child-Computer Interaction! The paper, entitled “Children (and Adults) Benefit From Visual Feedback during Gesture Interaction on Mobile Touchscreen Devices,” is an extension of our IDC 2013 paper on visual feedback and gestural interaction for children and adults. The journal version examines more features and additional recognizers to uncover the effects of presence or absence of visual feedback during gestural interaction. Here is the abstract:
Surface gesture interaction styles used on mobile touchscreen devices often depend on the platform and application. Some applications show a visual trace of gesture input being made by the user, whereas others do not. Little work has been done examining the usability of visual feedback for surface gestures, especially for children. In this paper, we extend our previous work on an empirical study conducted with children, teens, and adults to explore characteristics of gesture interaction with and without visual feedback. We analyze 9 simple and 7 complex gesture features to determine whether differences exist between users of different age groups when completing surface gestures with and without visual feedback. We find that the gestures generated diverge significantly in ways that make them difficult to interpret by some recognizers. For example, users tend to make gestures with fewer strokes in the absence of visual feedback, and tend to make shorter, more compact gestures using straighter lines in the presence of visual feedback. In addition, users prefer to see visual feedback. Based on these findings, we present design recommendations for surface gesture interfaces for children, teens, and adults on mobile touchscreen devices. We recommend providing visual feedback, especially for children, wherever possible.
When this article is officially published, I’ll add a link, but until then, you can check out the preprint version.
The $-family of gesture recognizers project has been working on more ways to characterize patterns in how users make gestures, in the form of new gesture accuracy measures (see our GI 2013 paper for the first set of measures we developed). This new set focuses on relative accuracy, or degree to which two gestures match locally rather than just simply global absolutes. Our paper introducing these measures has been accepted to ICMI 2013! My co-authors are Radu-Daniel Vatavu and Jacob O. Wobbrock. Here is the abstract:
Current measures of stroke gesture articulation lack descriptive power because they only capture absolute characteristics about the gesture as a whole, not fine-grained features that reveal subtleties about the gesture articulation path. We present a set of twelve new relative accuracy measures for stroke gesture articulation that characterize the geometric, kinematic, and articulation accuracy of single and multistroke gestures. To compute the accuracy measures, we introduce the concept of a gesture task axis. We evaluate our measures on five public datasets comprising 38,245 samples from107 participants, about which we make new discoveries; e.g., gestures articulated at fast speed are shorter in path length than slow or medium-speed gestures, but their path lengths vary the most, a finding that helps understand recognition performance. This
work will enable a better understanding of users’ stroke gesture articulation behavior, ultimately leading to better gesture set designs and more accurate recognizers.