Caret Manipulation using Deformable Input in Mobile Devices

Eady, Alexander Keith; Girouard, Audrey

doi:10.1145/2677199.2687916

Cited by 10 publications

(3 citation statements)

References 10 publications

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“…By holding one key on the keyboard, Ando et al leveraged the device tilt [3] and slide gesture [4] to complete the caret control, target selection, and a particular command (e.g., copy) at the same time. Eady et al [19] built a deformable interface and proposed a bend gesture on the corner of the device to control the caret. Sindhwani et al [37] used a matching algorithm to highlight potential correction position(s) based on users' input.…”

Section: Caret Control Enhancementmentioning

confidence: 99%

Swap: A Replacement-based Text Revision Technique for Mobile Devices

Sarcar

Kim

et al. 2020

Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

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Text revision is an important task to ensure the accuracy of text content. Revising text on mobile devices is cumbersome and time-consuming due to the imprecise caret control and the repetitive use of the backspace. We present Swap, a novel replacement-based technique to facilitate text revision on mobile devices. We conducted two user studies to validate the feasibility and the effectiveness of Swap compared to traditional text revision techniques. Results showed that Swap reduced efforts in caret control and repetitive backspace pressing during the text revision process. Most participants preferred to use the replacement-based technique rather than backspace and caret. They also commented that the new technique is easy to learn, and it makes text revision rapid and intuitive.

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Section: Caret Control Enhancementmentioning

confidence: 99%

Swap: A Replacement-based Text Revision Technique for Mobile Devices

Sarcar

Kim

et al. 2020

Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

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“…They suggested many unique uses for this device such as scooping and shaking to perform tasks such as 3D modelling and document navigation. Researchers have also used deformation interaction to perform music (Troiano, Pedersen, & Hornbaek, 2015), manipulate word processing carets (Eady & Girouard, 2015), create secure passwords (Maqsood, Chiasson, & Girouard, 2013), and control a TV as a remote (Lee et al, 2011). It is important for us to understand how deformation gestures are classified and used in order to test our prototype effectively.…”

Section: Researchers Have Used Various Deformation Gestures For Numermentioning

confidence: 99%

An Exploration of In-Game Action Mappings with a Deformable Game Controller

Shorey¹

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Deformation input consists of methods of interaction that make use of material deformation in order to control on-screen variables. In this thesis, we explore controller input mappings for games using a deformable prototype that combines deformation gestures with standard button input. In experiment one, we tested discrete gestures using three games. We categorized the control schemes as binary (traditional), action, and navigation, the latter two named based on the game mechanics the gestures were mapped to. We found that the binary scheme performed the best, but gesture-based control schemes are stimulating and appealing.Results also suggest that the deformation gestures are best mapped to simple and natural tasks. In experiment two we tested continuous gestures in a 3D racing game using the same control scheme categorization. Results were mostly consistent with experiment one but showed an improvement in performance and preference for the action control scheme.iii

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“…We felt that using bend gestures that were easy to remember would defeat the purpose of testing for memorability since there is no difficulty in remembering the bends. Complex tasks were found to be unsuitable for deformable interactions (Eady & Girouard, 2015), therefore, we looked at bend gesture sets used in previous work (Grijincu, Nacenta, & Kristensson, 2014;Lahey et al, 2011;Troiano et al, 2014) and created our own set of bend gesture mappings from those.…”

Section: Interaction Languagementioning

confidence: 99%

Effects of Bend Gesture Training on Learnability and Memorability in a Mobile Game

Fares¹

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Flexible displays are making their way into handheld devices. Users can benefit from ways of interacting with these devices using bend gestures to activate a command.However, these devices may have a higher learning curve due to their complex degree of interaction. We developed a new deformable device that detects bend gestures, and created Paper Ninja, a mobile game that is played using bends. We compared the effect of training on learnability and memorability through three conditions and attempted to validate the Guidance Hypothesis. Participants played the mobile game in two sessions and received one of the following: 1) training on how to perform bend gestures, 2) bend gesture training as well as what action mapped to the gesture, 3) no training. Our study revealed that mapping training produced a similar outcome as no training, while gesture training led to a negative outcome. Our findings suggest training is not essential for users to learn bend gesture interactions and learning by discovery is feasible.iii

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Caret Manipulation using Deformable Input in Mobile Devices

Cited by 10 publications

References 10 publications

Swap: A Replacement-based Text Revision Technique for Mobile Devices

Swap: A Replacement-based Text Revision Technique for Mobile Devices

An Exploration of In-Game Action Mappings with a Deformable Game Controller

Effects of Bend Gesture Training on Learnability and Memorability in a Mobile Game

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