huashen218/convxai-cia-dataset huggingface dataset:
Title: Examining Design Choices of Questionnaires in VR User Studies
Authors: family: Alexandrovsky
given: Dmitry; family: Putze
given: Susanne; family: Bonfert
given: Michael; family: Höffner
given: Sebastian; family: Michelmann
given: Pitt; family: Wenig
given: Dirk; family: Malaka
given: Rainer; family: Smeddinck
given: Jan David
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Questionnaires are among the most common research tools in virtual reality (VR) user studies. Transitioning from virtuality to reality for giving self-reports on VR experiences can lead to systematic biases. VR allows to embed questionnaires into the virtual environment which may ease participation and avoid biases. To provide a cohesive picture of methods and design choices for questionnaires in VR (inVRQ), we discuss 15 inVRQ studies from the literature and present a survey with 67 VR experts from academia and industry. Based on the outcomes, we conducted two user studies in which we tested different presentation and interaction methods of inVRQs and evaluated the usability and practicality of our design. We observed comparable completion times between inVRQs and questionnaires outside VR (nonVRQs) with higher enjoyment but lower usability for \inVRQs. These findings advocate the application of inVRQs and provide an overview of methods and considerations that lay the groundwork for inVRQ design.
Title: Unmet Needs and Opportunities for Mobile Translation AI
Authors: family: Liebling
given: Daniel J.; family: Lahav
given: Michal; family: Evans
given: Abigail; family: Donsbach
given: Aaron; family: Holbrook
given: Jess; family: Smus
given: Boris; family: Boran
given: Lindsey
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Translation apps and devices are often presented in the context of providing assistance while traveling abroad. However, the spectrum of needs for cross-language communication is much wider. To investigate these needs, we conducted three studies with populations spanning socioeconomic status and geographic regions: (1) United States-based travelers, (2) migrant workers in India, and (3) immigrant populations in the United States. We compare frequent travelers' perception and actual translation needs with those of the two migrant communities. The latter two, with low language proficiency, have the greatest translation needs to navigate their daily lives. However, current mobile translation apps do not meet these needs. Our findings provide new insights on the usage practices and limitations of mobile translation tools. Finally, we propose design implications to help apps better serve these unmet needs.
Title: Button Simulation and Design via FDVV Models
Authors: family: Liao
given: Yi-Chi; family: Kim
given: Sunjun; family: Lee
given: Byungjoo; family: Oulasvirta
given: Antti
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Designing a push-button with desired sensation and performance is challenging because the mechanical construction must have the right response characteristics. Physical simulation of a button's force-displacement (FD) response has been studied to facilitate prototyping; however, the simulations' scope and realism have been limited. In this paper, we extend FD modeling to include vibration (V) and velocity-dependence characteristics (V). The resulting FDVV models better capture tactility characteristics of buttons, including snap. They increase the range of simulated buttons and the perceived realism relative to FD models. The paper also demonstrates methods for obtaining these models, editing them, and simulating accordingly. This end-to-end approach enables the analysis, prototyping, and optimization of buttons, and supports exploring designs that would be hard to implement mechanically.
Title: Exploring Visual Information Flows in Infographics
Authors: family: Lu
given: Min; family: Wang
given: Chufeng; family: Lanir
given: Joel; family: Zhao
given: Nanxuan; family: Pfister
given: Hanspeter; family: Cohen-Or
given: Daniel; family: Huang
given: Hui
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Infographics are engaging visual representations that tell an informative story using a fusion of data and graphical elements. The large variety of infographic design poses a challenge for their high-level analysis. We use the concept of Visual Information Flow (VIF), which is the underlying semantic structure that links graphical elements to convey the information and story to the user. To explore VIF, we collected a repository of over 13K infographics. We use a deep neural network to identify visual elements related to information, agnostic to their various artistic appearances. We construct the VIF by automatically chaining these visual elements together based on Gestalt principles. Using this analysis, we characterize the VIF design space by a taxonomy of 12 different design patterns. Exploring in a real-world infographic dataset, we discuss the design space and potentials of VIF in light of this taxonomy.
Title: Informing the Design of Privacy-Empowering Tools for the Connected Home
Authors: family: Seymour
given: William; family: Kraemer
given: Martin J.; family: Binns
given: Reuben; family: Van Kleek
given: Max
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Connected devices in the home represent a potentially grave new privacy threat due to their unfettered access to the most personal spaces in people's lives. Prior work has shown that despite concerns about such devices, people often lack sufficient awareness, understanding, or means of taking effective action. To explore the potential for new tools that support such needs directly we developed Aretha, a privacy assistant technology probe that combines a network disaggregator, personal tutor, and firewall, to empower end-users with both the knowledge and mechanisms to control disclosures from their homes. We deployed Aretha in three households over six weeks, with the aim of understanding how this combination of capabilities might enable users to gain awareness of data disclosures by their devices, form educated privacy preferences, and to block unwanted data flows. The probe, with its novel affordances-and its limitations-prompted users to co-adapt, finding new control mechanisms and suggesting new approaches to address the challenge of regaining privacy in the connected home.
Title: Virtual Reality Games for People Using Wheelchairs
Authors: family: Gerling
given: Kathrin; family: Dickinson
given: Patrick; family: Hicks
given: Kieran; family: Mason
given: Liam; family: Simeone
given: Adalberto L.; family: Spiel
given: Katta
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Virtual Reality (VR) holds the promise of providing engaging embodied experiences, but little is known about how people with disabilities engage with it. We explore challenges and opportunities of VR gaming for wheelchair users. First, we present findings from a survey that received 25 responses and gives insights into wheelchair users' motives to (non-) engage with VR and their experiences. Drawing from this survey, we derive design implications which we tested through implementation and qualitative evaluation of three full-body VR game prototypes with 18 participants. Our results show that VR gaming engages wheelchair users, though nuanced consideration is required for the design of embodied immersive experiences for minority bodies, and we illustrate how designers can create meaningful, positive experiences.
Title: A View on the Viewer: Gaze-Adaptive Captions for Videos
Authors: family: Kurzhals
given: Kuno; family: Göbel
given: Fabian; family: Angerbauer
given: Katrin; family: Sedlmair
given: Michael; family: Raubal
given: Martin
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Subtitles play a crucial role in cross-lingual distribution of multimedia content and help communicate information where auditory content is not feasible (loud environments, hearing impairments, unknown languages). Established methods utilize text at the bottom of the screen, which may distract from the video. Alternative techniques place captions closer to related content (e.g., faces) but are not applicable to arbitrary videos such as documentations. Hence, we propose to leverage live gaze as indirect input method to adapt captions to individual viewing behavior. We implemented two gaze-adaptive methods and compared them in a user study (n=54) to traditional captions and audio-only videos. The results show that viewers with less experience with captions prefer our gaze-adaptive methods as they assist them in reading. Furthermore, gaze distributions resulting from our methods are closer to natural viewing behavior compared to the traditional approach. Based on these results, we provide design implications for gaze-adaptive captions.
Title: Emoji Accessibility for Visually Impaired People
Authors: family: Tigwell
given: Garreth W.; family: Gorman
given: Benjamin M.; family: Menzies
given: Rachel
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Emoji are graphical symbols that appear in many aspects of our lives. Worldwide, around 36 million people are blind and 217 million have a moderate to severe visual impairment. This portion of the population may use and encounter emoji, yet it is unclear what accessibility challenges emoji introduce. We first conducted an online survey with 58 visually impaired participants to understand how they use and encounter emoji online, and the challenges they experience. We then conducted 11 interviews with screen reader users to understand more about the challenges reported in our survey findings. Our interview findings demonstrate that technology is both an enabler and a barrier, emoji descriptors can hinder communication, and therefore the use of emoji impacts social interaction. Using our findings from both studies, we propose best practice when using emoji and recommendations to improve the future accessibility of emoji for visually impaired people.
Title: BodyLights: Open-Ended Augmented Feedback to Support Training Towards a Correct Exercise Execution
Authors: family: Turmo Vidal
given: Laia; family: Zhu
given: Hui; family: Riego-Delgado
given: Abraham
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Technologies targeting a correct execution of physical training exercises typically use pre-determined models for what they consider correct, automatizing instruction and feedback. This falls short on catering to diverse trainees and exercises. We explore an alternative design approach, in which technology provides open-ended feedback for trainers and trainees to use during training. With a personal trainer we designed the augmentation of 18 strength training exercises with BodyLights: 3D printed wearable projecting lights that augment body movement and orientation. To study them, 15 trainees at different skill levels trained three times with our personal trainer and BodyLights. Our findings show that BodyLights catered to a wide range of trainees and exercises, and supported understanding, executing and correcting diverse technique parameters. We discuss design features and methodological aspects that allowed this; and what open-ended feedback offered in comparison to current technology approaches to support training towards a correct exercise execution.
Title: ShArc: A Geometric Technique for Multi-Bend/Shape Sensing
Authors: family: Shahmiri
given: Fereshteh; family: Dietz
given: Paul H.
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: We present ShArc, a precision, geometric measurement technique for building multi-bend/shape sensors. ShArc sensors are made from flexible strips that can be dynamically formed into complex curves in a plane. They measure local curvature by noting the relative shift between the inner and outer layers of the sensor at many points and model shape as a series of connected arcs. Unlike jointed systems where angular errors sum with each joint measured, ShArc sensors do not accumulate angular error as more measurement points are added. This allows for inexpensive, robust sensors that can accurately model curves with multiple bends. To demonstrate the efficacy of this technique, we developed a capacitive ShArc sensor and evaluated its performance. We conclude with examples of how ShArc sensors can be employed in applications like gesture input devices, user interface controllers, human motion tracking and angular measurement of free-form objects.
Title: Cheat Sheets for Data Visualization Techniques
Authors: family: Wang
given: Zezhong; family: Sundin
given: Lovisa; family: Murray-Rust
given: Dave; family: Bach
given: Benjamin
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: This paper introduces the concept of 'cheat sheets' for data visualization techniques, a set of concise graphical explanations and textual annotations inspired by infographics, data comics, and cheat sheets in other domains. Cheat sheets aim to address the increasing need for accessible material that supports a wide audience in understanding data visualization techniques, their use, their fallacies and so forth. We have carried out an iterative design process with practitioners, teachers and students of data science and visualization, resulting six types of cheat sheet (anatomy, construction, visual patterns, pitfalls, false-friends and well-known relatives) for six types of visualization, and formats for presentation. We assess these with a qualitative user study using 11 participants that demonstrates the readability and usefulness of our cheat sheets.
Title: Learn with Haptics: Improving Vocabulary Recall with Free-form Digital Annotation on Touchscreen Mobiles
Authors: family: Sheshadri
given: Smitha; family: Zhao
given: Shengdong; family: Chen
given: Yang; family: Fjeld
given: Morten
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Mobile vocabulary learning interfaces typically present material only in auditory and visual channels, underutilizing the haptic modality. We explored haptic-integrated learning by adding free-form digital annotation to mobile vocabulary learning interfaces. Through a series of pilot studies, we identified three design factors: annotation mode, presentation sequence, and vibrotactile feedback, that influence recall in haptic-integrated vocabulary interfaces. These factors were then evaluated in a within-subject comparative study using a digital flashcard interface as baseline. Results using a 84-item vocabulary showed that the 'whole word' annotation mode is highly effective, yielding a 24.21% increase in immediate recall scores and a 30.36% increase in the 7-day delayed scores. Effects of presentation sequence and vibrotactile feedback were more transient; they affected the results of immediate tests, but not the delayed tests. We discuss the implications of these factors for designing future mobile learning applications.
Title: Guess the Data: Data Work to Understand How People Make Sense of and Use Simple Sensor Data from Homes
Authors: family: Kurze
given: Albrecht; family: Bischof
given: Andreas; family: Totzauer
given: Sören; family: Storz
given: Michael; family: Eibl
given: Maximilian; family: Brereton
given: Margot; family: Berger
given: Arne
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Simple smart home sensors, e.g. for temperature or light, increasingly collect seemingly inconspicuous data. Prior work has shown that human sensemaking of such sensor data can reveal domestic activities. Such sensemaking presents an opportunity to empower people to understand the implications of simple smart home sensors. To investigate, we developed and field-tested the Guess the Data method, which enabled people to use and make sense of live data from their homes and to collectively interpret and reflect on anonymized data from the homes in our study. Our findings show how participants reconstruct behavior, both individually and collectively, expose the sensitive personal data of others, and use sensor data as evidence and for lateral surveillance within the household. We discuss the potential of our method as a participatory HCI method for investigating design of the IoT and implications created by doing data work on home sensors.
Title: Please Call the Specialism: Using WeChat to Support Patient Care in China
Authors: family: Wang
given: Ding; family: Kale
given: Santosh D.; family: O'Neill
given: Jacki
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: We examine how WeChat has been adopted to support nurse-patient communication in an IVF clinic in China. In this setting, the biggest challenge to delivering high-quality patient-centred care is the large number of patients. Nurses typically spend less than five minutes with each patient during clinical visits. To compensate for such minimal in-person consultation, nurse-facilitated patient groups were created on WeChat, to extend medical care and facilitate peer support. Through an ethnographic study, we examined how these groups fit into the clinic's communication ecosystem, and the challenges they raise for nurse-facilitators who receive thousands of messages daily. We propose a set of design suggestions aiming to make the work of the nurse-facilitator easier and more effective. In highlighting the opportunities and challenges of using chat to extend care beyond the clinic, we contribute to a burgeoning discussion of how chat can support patient care in the Global South.
Title: Monsters, Metaphors, and Machine Learning
Authors: family: Dove
given: Graham; family: Fayard
given: Anne-Laure
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Machine learning (ML) poses complex challenges for user experience (UX) designers. Typically unpredictable and opaque, it may produce unforeseen outcomes detrimental to particular groups or individuals, yet simultaneously promise amazing breakthroughs in areas as diverse as medical diagnosis and universal translation. This results in a polarized view of ML, which is often manifested through a technology-as-monster metaphor. In this paper, we acknowledge the power and potential of this metaphor by resurfacing historic complexities in human-monster relations. We (re)introduce these liminal and ambiguous creatures, and discuss their relation to ML. We offer a background to designers' use of metaphor, and show how the technology-as-monster metaphor can generatively probe and (re)frame the questions ML poses. We illustrate the effectiveness of this approach through a detailed discussion of an early-stage generative design workshop inquiring into ML approaches to supporting student mental health and well-being.
Title: Collective Support and Independent Learning with a Voice-Based Literacy Technology in Rural Communities
Authors: family: Madaio
given: Michael A.; family: Yarzebinski
given: Evelyn; family: Kamath
given: Vikram; family: Zinszer
given: Benjamin D.; family: Hannon-Cropp
given: Joelle; family: Tanoh
given: Fabrice; family: Akpe
given: Yapo Hermann; family: Seri
given: Axel Blahoua; family: Jasińska
given: Kaja K.; family: Ogan
given: Amy
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Access to literacy is critical to children's futures, but formal education may be insufficient for fostering early literacy, especially in low-resource contexts. Educational technologies used at home may be able to help, but it is unclear whether or how children (and families) will use such technologies at home in rural communities, particularly in low-literate families. In this paper, we investigate these questions with a voice-based literacy technology deployed with families in 8 rural communities in Côte d'Ivoire for 4 months. We use interviews and observations with 37 families to investigate motivations, methods, and barriers for rural families' engagement with a literacy technology accessible via feature phones. We contribute insights into how families view digital literacy as a learning goal, leverage networks of supporters, and over time, transition from explicit to implicit support for children's learning.
Title: The TA Framework: Designing Real-time Teaching Augmentation for K-12 Classrooms
Authors: family: An
given: Pengcheng; family: Holstein
given: Kenneth; family: d'Anjou
given: Bernice; family: Eggen
given: Berry; family: Bakker
given: Saskia
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Recently, the HCI community has seen increased interest in the design of teaching augmentation (TA): tools that extend and complement teachers' pedagogical abilities during ongoing classroom activities. Examples of TA systems are emerging across multiple disciplines, taking various forms: e.g., ambient displays, wearables, or learning analytics dashboards. However, these diverse examples have not been analyzed together to derive more fundamental insights into the design of teaching augmentation. Addressing this opportunity, we broadly synthesize existing cases to propose the TA framework. Our framework specifies a rich design space in five dimensions, to support the design and analysis of teaching augmentation. We contextualize the framework using existing designs cases, to surface underlying design trade-offs: for example, balancing actionability of presented information with teachers' needs for professional autonomy, or balancing unobtrusiveness with informativeness in the design of TA systems. Applying the TA framework, we identify opportunities for future research and design.
Title: "We have been magnified for years - Now you are under the microscope!": Co-researchers with Learning Disabilities Created an Online Survey to Challenge Public Understanding of Learning Disabilities
Authors: family: Chapko
given: Dorota; family: Frumiento
given: Pino; family: Edwards
given: Nalini; family: Emeh
given: Lizzie; family: Kennedy
given: Donald; family: McNicholas
given: David; family: Overton
given: Michaela; family: Snead
given: Mark; family: Steward
given: Robyn; family: Sutton
given: Jenny M.; family: Jeffreys
given: Evie; family: Long
given: Catherine; family: Croll-Knight
given: Jess; family: Connors
given: Ben; family: Castell-Ward
given: Sam; family: Coke
given: David; family: McPeake
given: Bethany; family: Renel
given: William; family: McGinley
given: Chris; family: Remington
given: Anna; family: Whittuck
given: Dora; family: Kieffer
given: John; family: Ewans
given: Sarah; family: Williams
given: Mark; family: Grierson
given: Mick
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Public attitudes towards learning disabilities (LDs) are generally reported as positive, inclusive and empathetic. However, these findings do not reflect the lived experiences of people with LDs. To shed light on this disparity, a team of co-researchers with LDs created the first online survey to challenge public understanding of LDs, asking questions in ways that are important to them and represent how they see themselves. Here, we describe and evaluate the process of creating an accessible survey platform and an online survey in a research team consisting of academic and non-academic professionals with and without LDs or autism. Through this inclusive research process, the co-designed survey met the expectations of the co-researchers and was well-received by the initial survey respondents. We reflect on the co-researchers' perspectives following the study completion, and consider the difficulties and advantages we encountered deploying such approaches and their potential implications on future survey data analysis.