1,229 research outputs found
PickCells: A Physically Reconfigurable Cell-composed Touchscreen
Touchscreens are the predominant medium for interactions with digital services; however, their current fixed form factor narrows the scope for rich physical interactions by limiting interaction possibilities to a single, planar surface. In this paper we introduce the concept of PickCells, a fully reconfigurable device concept composed of cells, that breaks the mould of rigid screens and explores a modular system that affords rich sets of tangible interactions and novel acrossdevice relationships. Through a series of co-design activities – involving HCI experts and potential end-users of such systems – we synthesised a design space aimed at inspiring future research, giving researchers and designers a framework in which to explore modular screen interactions. The design space we propose unifies existing works on modular touch surfaces under a general framework and broadens horizons by opening up unexplored spaces providing new interaction possibilities. In this paper, we present the PickCells concept, a design space of modular touch surfaces, and propose a toolkit for quick scenario prototyping
Gamification of a To-Do List with Emotional Reinforcement
Gamification can change how and why people interact with software. A common approach is to use quantitative feedback to give users a feeling of progress or achievement. There are, however, other ways to provide users with motivation or meaning during normal computer interactions, such as using emotional reinforcement. This could provide a powerful new tool to allow the positive effects of gamification to reach wider contexts. This paper investigates the design and evaluation of a mobile to-do list application, 'Tamu To-Do', which utilises gamified emotional reinforcement, as seen in Figure 1. A week-long field study (N=9) recorded user activity and impressions with the application. The results supported emotional reinforcement's potential as a gamification strategy to improve user motivation and engagement
Automating the Administration and Analysis of Psychiatric Tests: the Case of Attachment in School Age Children
This article presents the School Attachment Monitor, a novel interactive system that can reliably administer the Manch- ester Child Attachment Story Task (a standard psychiatric test for the assessment of attachment in children) without the supervision of trained professionals. Attachment prob- lems in children cause significant mental health issues and costs to society which technology has the potential to re- duce. SAM collects, through instrumented doll-play games, enough information to allow a human assessor to manually identify the attachment status of children. Experiments show that the system successfully does this in 87.5% of cases. In addition, the experiments show that an automatic approach based on deep neural networks can map the information collected into the attachment condition of the children. The outcome SAM matches the judgment of expert human asses- sors in 82.8% of cases. This is the first time an automated tool has been successful in measuring attachment. This work has significant implications for psychiatry as it allows profes- sionals to assess many more children cost effectively and to direct healthcare resources more accurately and efficiently to improve mental health
Airport Accessibility and Navigation Assistance for People with Visual Impairments
People with visual impairments often have to rely on the assistance of sighted guides in airports, which prevents them from having an independent travel experience. In order to learn about their perspectives on current airport accessibility, we conducted two focus groups that discussed their needs and experiences in-depth, as well as the potential role of assistive technologies. We found that independent navigation is a main challenge and severely impacts their overall experience. As a result, we equipped an airport with a Bluetooth Low Energy (BLE) beacon-based navigation system and performed a real-world study where users navigated routes relevant for their travel experience. We found that despite the challenging environment participants were able to complete their itinerary independently, presenting none to few navigation errors and reasonable timings. This study presents the first systematic evaluation posing BLE technology as a strong approach to increase the independence of visually impaired people in airports
Designing for digital playing out
We report on a design-led study in the UK that aimed to understand barriers to children (aged 5 to 14 years) 'playing out' in their neighbourhood and explore the potential of the Internet of Things (IoT) for supporting children's free play that extends outdoors. The study forms a design ethnography, combining observational fieldwork with design prototyping and co-creative activities across four linked workshops, where we used BBC micro:bit devices to co-create new IoT designs with the participating children. Our collective account contributes new insights about the physical and interactive features of micro:bits that shaped play, gameplay, and social interaction in the workshops, illuminating an emerging design space for supporting 'digital playing out' that is grounded in empirical instances. We highlight opportunities for designing for digital playing out in ways that promote social negotiation, supports varying participation, allows for integrating cultural influences, and accounts for the weaving together of placemaking and play
Passquerade: Improving Error Correction of Text Passwords on Mobile Devices by using Graphic Filters for Password Masking
Entering text passwords on mobile devices is a significant challenge. Current systems either display passwords in plain text: making them visible to bystanders, or replace characters with asterisks shortly after they are typed: making editing them harder. This work presents a novel approach to mask text passwords by distorting them using graphical filters. Distorted passwords are difficult to observe by attackers because they cannot mentally reverse the distortions. Yet passwords remain readable by their owners because humans can recognize visually distorted versions of content they saw before. We present results of an online questionnaire and a user study where we compared Color-halftone, Crystallize, Blurring, and Mosaic filters to Plain text and Asterisks when 1) entering, 2) editing, and 3) shoulder surfing one-word passwords, random character passwords, and passphrases. Rigorous analysis shows that Color-halftone and Crystallize filters significantly improve editing speed, editing accuracy and observation resistance compared to current approaches
Measuring and understanding photo sharing experiences in social virtual reality
Millions of photos are shared online daily, but the richness of interaction compared with face-to-face (F2F) sharing is still missing. While this may change with social Virtual Reality (socialVR), we still lack tools to measure such immersive and interactive experiences. In this paper, we investigate photo sharing experiences in immersive environments, focusing on socialVR. Running context mapping (N=10), an expert creative session (N=6), and an online experience clustering questionnaire (N=20), we develop and statistically evaluate a questionnaire to measure photo sharing experiences. We then ran a controlled, within-subject study (N=26 pairs) to compare photo sharing under F2F, Skype, and Facebook Spaces. Using interviews, audio analysis, and our questionnaire, we found that socialVR can closely approximate F2F sharing. We contribute empirical findings on the immersiveness differences between digital communication media, and propose a socialVR questionnaire that can in the future generalize beyond photo sharing
Improving fairness in machine learning systems: What do industry practitioners need?
The potential for machine learning (ML) systems to amplify social inequities
and unfairness is receiving increasing popular and academic attention. A surge
of recent work has focused on the development of algorithmic tools to assess
and mitigate such unfairness. If these tools are to have a positive impact on
industry practice, however, it is crucial that their design be informed by an
understanding of real-world needs. Through 35 semi-structured interviews and an
anonymous survey of 267 ML practitioners, we conduct the first systematic
investigation of commercial product teams' challenges and needs for support in
developing fairer ML systems. We identify areas of alignment and disconnect
between the challenges faced by industry practitioners and solutions proposed
in the fair ML research literature. Based on these findings, we highlight
directions for future ML and HCI research that will better address industry
practitioners' needs.Comment: To appear in the 2019 ACM CHI Conference on Human Factors in
Computing Systems (CHI 2019
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