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When sketching, we must choose between paper (expressive ease, ruler and eraser) and computational assistance (parametric support, a digital record). PHysically Assisted SKetching provides both, with a pen that displays force constraints with which the sketcher interacts as they draw on paper. Phasking provides passive, "bound" constraints (like a ruler); or actively "brings" the sketcher along a commanded path (e.g., a curve), which they can violate for creative variation. The sketcher modulates constraint strength (control sharing) by bearing down on the pen-tip. Phasking requires untethered, graded force-feedback, achieved by modifying a ballpoint drive that generates force through rolling surface contact. To understand phasking's viability, we implemented its interaction concepts, related them to sketching tasks and measured device performance. We assessed the experience of 10 sketchers, who could understand, use and delight in phasking, and who valued its control-sharing and digital twinning for productivity, creative control and learning to draw.

Current research in HCI with immigrants predominantly focuses on their practical needs and little attention is given to their cultural identities. As such, we aim to understand how newcomers reflect their cultural values within domestic settings. We explore this by provoking memories immigrants associate with physical spaces inside their homes. Hence, we built "Our Home Sketcher": a paper-based home drafting tool that allows novice users to design their homes by sketching and implicitly expressing their space, light, and privacy preferences. The collected drawings are then fed into a computer algorithm that produces 3D models of the sketched houses. This process of design acts as an artifact-driven storytelling for heritage sharing and rapport building within migrant communities. We engage 13 Middle Eastern newcomers in Canada with the tool and use Halbwachs' [44] theory of collective memory to frame how home sketching provokes former experiences. Our findings show a strong longing for reclaiming the past, narrating space-related oral history, and designing beyond current limitations.

Users frequently have trouble finding and changing technology settings, even when adjusting those settings to personalize their technology devices may significantly improve their user experience. This paper describes the Morphic project, a cloud-based auto-personalization tool. Primarily designed for improving accessibility, the auto-personalization in Morphic may also help a broader audience. This paper describes: 1) the technical infrastructure needed to support cloud-based auto-personalization, 2) the interaction design approaches necessary to support users during the personalization of their settings, and 3) which settings and modifications have been most frequently used. This paper presents the evolution of the Morphic project, the building of the infrastructure, the formative evaluation of various interaction design approaches (NFC cards, physical keypads, on-screen buttons, and menus), and implications for researchers and developers. It also includes preliminary findings from six technology probes.

This paper has been selected for a Best Paper award at CHI2020.The SIGCHI “Best of CHI” awards honour exceptional submissions to SIGCHI sponsored conferences.A total of 31 Papers received a Best Paper award (top 1% of submissions), 125 papers received Honourable Mention (remaining top 5% of submissions). Process: the Best Paper Committee, which includes the Awards Chairs and 19 committee members (one from each subcommittee), adjudicated the selection of the Best Papers and Honourable Mentions based on nomination scores and paragraphs that were provided by the CHI Associate Chairs.; International audience; Despite being included in mainstream schools, visually impaired children still face barriers to social engagement and participation. Games could potentially help, but games that cater for both visually impaired and sighted players are scarce. We used a co-design approach to design and evaluate a robot-based educational game that could be inclusive of both visually impaired and sighted children in the context of mainstream education. We ran a focus group discussion with visual impairment educators to understand barriers to inclusive play. And then a series of co-design workshops to engage visually impaired and sighted children and educators in learning about robot technology and exploring its potential to support inclusive play experiences. We present design guidelines and an evaluation workshop of a game prototype, demonstrating group dynamics conducive to collaborative learning experiences, including shared goal setting/execution, closely coupled division of labour, and interaction symmetry.

This paper brings together three distinct case studies to explore how social isolation and notions of liminality shape ontological security within communities on "the edge" of society. Each case study exemplifies the differing nature of liminality in everyday contexts and the extent to which increased digitalisation perturbs it in multiple ways. Taking an ethnographic approach, the research engaged with seafarers onboard container ships in European waters, communities in Greenland and welfare claimants in the North East of England. It posits that technological innovation must attend to the routinisation of everyday life through which people establish ontological security if such innovation is to be supportive. The paper thus moves beyond existing HCI scholarship by foregrounding the contextual and relational aspects of social isolation rather than the technological. It does so by advocating a ground-up design process that considers ontological security in relation to notions of liminality among communities on the edge.

Artificial intelligence (AI) is becoming increasingly integrated in user-facing technology, but public understanding of these technologies is often limited. There is a need for additional HCI research investigating a) what competencies users need in order to effectively interact with and critically evaluate AI and b) how to design learner-centered AI technologies that foster increased user understanding of AI. This paper takes a step towards realizing both of these goals by providing a concrete definition of AI literacy based on existing research. We synthesize a variety of interdisciplinary literature into a set of core competencies of AI literacy and suggest several design considerations to support AI developers and educators in creating learner-centered AI. These competencies and design considerations are organized in a conceptual framework thematically derived from the literature. This paper's contributions can be used to start a conversation about and guide future research on AI literacy within the HCI community.

This paper has been selected for a Honourable Mention award at CHI2020.The SIGCHI “Best of CHI” awards honour exceptional submissions to SIGCHI sponsored conferences.A total of 31 Papers received a Best Paper award (top 1% of submissions), 125 papers received Honourable Mention (remaining top 5% of submissions). Process: the Best Paper Committee, which includes the Awards Chairs and 19 committee members (one from each subcommittee), adjudicated the selection of the Best Papers and Honourable Mentions based on nomination scores and paragraphs that were provided by the CHI Associate Chairs.; International audience; Addressing the needs of visually impaired people is of continued interest in Human Computer Interaction (HCI) research. Yet, one of the major challenges facing researchers in this field continues to be how to design adequate quantitative empirical evaluation for these users in HCI. In this paper, we analyse a corpus of 178 papers on technologies designed for people with visual impairments, published since 1988, and including at least one quantitative empirical evaluation (243 evaluations in total). To inform future research in this area, we provide an overview, historic trends and a unified terminology to design and report quantitative empirical evaluations. We identify open issues and propose a set of guidelines to address them. Our analysis aims to facilitate and stimulate future research on this topic.

This paper explores the disruptive and transformative effects of digital technology on gendered security asymmetries in Greenland. Through ethnographic fieldwork conducted in Greenland and Denmark, research findings emerged through in-depth interviews, collaborative mappings and field observations with 51 participants. Employing a critical feminist lens, the paper identifies how Greenlandic women develop digital security practices to respond to Greenland's ecologically, politically and socially induced transformation processes. By connecting individual security concerns of Greenlandic women with the broader regional context, the findings highlight how digital technology has created transitory spaces in which collective security is cultivated, shaped and challenged. The contribution to HCI scholarship is therefore threefold: (1) identification and acknowledgement of gendered effects of increased usage of digital technology in remote and hard-to-reach communities, (2) a broader conceptualisation of digital security and (3) a recommendation for more contextualised, pluralistic digitalisation policies and design.

A moral dilemma is a decision-making paradox without unambiguously acceptable or preferable options. This paper investigates if and how the virtual enactment of two renowned moral dilemmas---the Trolley and the Mad Bomber---influence decision-making when compared with mentally visualizing such situations. We conducted two user studies with two gender-balanced samples of 60 participants in total that compared between paper-based and virtual-reality (VR) conditions, while simulating 5 distinct scenarios for the Trolley dilemma, and 4 storyline scenarios for the Mad Bomber's dilemma. Our findings suggest that the VR enactment of moral dilemmas further fosters utilitarian decision-making, while it amplifies biases such as sparing juveniles and seeking retribution. Ultimately, we theorize that the VR enactment of renowned moral dilemmas can yield ecologically-valid data for training future Artificial Intelligence (AI) systems on ethical decision-making, and we elicit early design principles for the training of such systems.

This paper joins the growing body of work in postcolonial computing in HCI, and critically examines the impacts of online social media on the urban architecture in the Global South. Based on our nine-month long ethnography at eight residential areas in Dhaka, Bangladesh, this paper reports how online fame drives local users to produce digital images of their houses mimicking various Western standards, which in turn, brings changes to the organization, aesthetics, and functions of domestic spaces. This paper also describes how such digital image mediated transformations to local architecture are diminishing traditional spaces, altering their usual functions, and limiting the movement of many women inside their home. Drawing from a rich body of literature in postcolonialism, critical image theory, architecture, and Islamic feminism, we explain how these practices demonstrate a subaltern experience of using social media in the Global South. We further discuss design implications to both HCI and architecture to address these issues, and connect our findings to the broader agendas of HCI around social justice and global development.

This paper discusses how characteristics of experience-centred and collaborative design can be translated to larger scales. We describe Metro Futures, a region-wide public consultation on the design of new light rail trains, where we followed an experience-centred co-design approach supported by digital media and tools to develop findings with a core group of 20 ?co-researchers' and ~4000 public participants. The paper discusses how the characteristics of a focus on experience, and collaborative design exploration were achieved with co-researchers and, at scale, through online and face-to-face interactions using various digital media and tools. Whilst not at the depth of smaller scales, there are opportunities to retain characteristics of experience-centred co-design at scale to produce findings that can usefully inform ensuing design work, and avoid the averaging of public contributions often evident in large scale public consultations.

Depression is a leading cause of disability worldwide, which has inspired the design of mobile health (mHealth) applications for disease monitoring, prediction, and diagnosis. Less mHealth research has, however, focused on the treatment of depressive disorders. Clinical evidence shows that depressive symptoms can be reduced through a behavior change method known as Behavioral Activation (BA). This paper presents MUBS; a smartphone-based system for BA, which specifically contributes a personalized content-based activity recommendation model using a unique list of validated activities. An 8-week feasibility study with 17 depressive patients provided detailed insight into how MUBS provided inspiration and motivation for planning and engaging in more pleasant activities, thereby facilitating the core components of BA. Based on this study, the paper discusses how recommender technology can be used in the design of mHealth technology for BA.

Users may face challenges while designing graphical user interfaces, due to a lack of relevant experience and guidance. This paper aims to investigate the issues that users with no experience face during the design process, and how to resolve them. To this end, we conducted semi-structured interviews, based on which we built a GUI prototyping assistance tool called GUIComp. This tool can be connected to GUI design software as an extension, and it provides real-time, multi-faceted feedback on a user's current design. Additionally, we conducted two user studies, in which we asked participants to create mobile GUIs with or without GUIComp, and requested online workers to assess the created GUIs. The experimental results show that GUIComp facilitated iterative design and the participants with GUIComp had better a user experience and produced more acceptable designs than those who did not., Comment: 10 pages, 3 figures, accepted paper to CHI 2020 conference

Everyday interactions with computers are increasingly likely to involve elements of Artificial Intelligence (AI). Encompassing a broad spectrum of technologies and applications, AI poses many challenges for HCI and design. One such challenge is the need to make AI's role in a given system legible to the user in a meaningful way. In this paper we employ a Research through Design (RtD) approach to explore how this might be achieved. Building on contemporary concerns and a thorough exploration of related research, our RtD process reflects on designing imagery intended to help increase AI legibility for users. The paper makes three contributions. First, we thoroughly explore prior research in order to critically unpack the AI legibility problem space. Second, we respond with design proposals whose aim is to enhance the legibility, to users, of systems using AI. Third, we explore the role of design-led enquiry as a tool for critically exploring the intersection between HCI and AI research.

Game studios aim to develop titles that deliver a fun and engaging experience for players. Playtesting promises to help identify opportunities to improve player experience and assist developers in achieving their design intent. However, a lack of research on the added value of playtesting means that many studios are still uncertain about its commercial viability and impact on product success. This gap in understanding is further complicated by the vague definition of "success" afforded by sales figures and review scores. In this paper, we assess reported feature quality of three commercial titles by analyzing playtesting reports and game reviews. By comparing themes and design issues expressed in game reviews to the results of pre-release playtesting for each game, we aim to highlight the value of playtesting and propose a set of guidelines for selecting playtest methods based on the needs of a given game evaluation. Through the real-world case studies presented, this paper contributes to the growing domain of games user research and highlights the value of playtesting in game development.

Crosswords are a popular recreational game that relies on the spatial relationship between words. As a player answers clues, they begin to organize words to form an intersecting grid. A good non-visual representation should convey the interrelation of words and support the user in building a practical spatial image of the crossword grid. This paper looks at two approaches to representing a crossword puzzle for visually impaired users: a screen reader based crossword, and an audio-tactile crossword puzzle. We evaluate the designs in a study with 10 visually impaired participants. The audio-tactile representation was found to support the practical use of the crossword's spatial structure while the screen reader based puzzle leveraged participant's prior experience in navigating websites. The paper discusses critical aspects of our study and presents a perspective on the use of multimodal interfaces for such spatial applications.

Grid layouts are used by designers to spatially organise user interfaces when sketching and wireframing. However, their design is largely time consuming manual work. This is challenging due to combinatorial explosion and complex objectives, such as alignment, balance, and expectations regarding positions. This paper proposes a novel optimisation approach for the generation of diverse grid-based layouts. Our mixed integer linear programming (MILP) model offers a rigorous yet efficient method for grid generation that ensures packing, alignment, grouping, and preferential positioning of elements. Further, we present techniques for interactive diversification, enhancement, and completion of grid layouts (Figure 1). These capabilities are demonstrated using GRIDS1, a wireframing tool that provides designers with real-time layout suggestions. We report findings from a ratings study (N = 13) and a design study (N = 16), lending evidence for the benefit of computational grid generation during early stages of design., 13 pages, 10 figures, ACM CHI 2020 Full Paper

The study of human-computer interaction requires consideration of aspects of interactions with technology that may be outside of the control of both user and designer. One example of when a user's question of "can I do this?" may have an answer beyond technological affordances is that of legal constraints. This paper considers an example of this phenomenon: section 1201 of the Digital Millennium Copyright Act (DMCA) in the United States, which criminalizes circumventing copyright protection such as digital rights management (DRM). The DMCA also includes a triennial policymaking process that considers exemptions to the law to protect "lawful users" from adverse effects. Through an analysis of public comments of support for exemptions, this paper explores the ways in which users see the law as a hindrance to desired uses of technology. This analysis sheds light on users' expectations for rights of use, how these expectations clash with policy, and what this might mean for technology designers. Drawing lessons from the infrastructure problem in HCI, this paper concludes with laying out solutions that can both work within policy constraints, and more importantly, work to change them.

Given the prevalence and adverse impact of anxiety, there is considerable interest in using technology to regulate anxiety. Evaluating the efficacy of such technology in terms of both the average effect (the intervention efficacy) and the heterogeneous effect (for whom and in what context the intervention was effective) is of paramount importance. In this paper, we demonstrate the efficacy of PIV, a personalized breathing pacer, in reducing anxiety in the presence of a cognitive stressor. We also quantify the relation between our specific stressor and PIV-user engagement. To our knowledge, this is the first mixed-design study of a vibrotactile affect regulation technology which accounts for a specific stressor and for individual differences in relation to the technology's efficacy. Guidelines in this paper can be applied for designing and evaluating other affect regulation technologies.

This paper introduces document theory as a mechanism to analyze intimate platforms as sociotechnical systems. The theory, developed in documentation studies and applied to HCI, focuses on the casting mold or how agents, through particular means and modes, produce documents that govern social relations. We studied the process of creating a profile by identifying and mapping out the fields asked among the ten most popular online dating apps in the US. By looking at dating profiles as documents and their creation as a process of documentation, we argue that the current casting mold of these intimate platforms is designed to extract profit via invisibilization of labor in digital networks leading to the emergence of a constrained rational market agent. Our study illustrates how document theory makes visible the assumptions of technological systems, calling on us to imagine alternatives beyond incremental design changes given broader structural realities of market and power.

Textual comments from peers with informational and emotional support are beneficial to members of online mental health communities (OMHCs). However, many comments are not of high quality in reality. Writing support technologies that assess (AS) the text or recommend (RE) writing examples on the fly could potentially help support providers to improve the quality of their comments. However, how providers perceive and work with such technologies are under-investigated. In this paper, we present a technological prototype MepsBot which offers providers in-situ writing assistance in either AS or RE mode. Results of a mixed-design study with 30 participants show that both types of MepsBots improve users' confidence in and satisfaction with their comments. The AS-mode MepsBot encourages users to refine expressions and is deemed easier to use, while the RE-mode one stimulates more support-related content re-editions. We report concerns on MepsBot and propose design considerations for writing support technologies in OMHCs.

This paper reports on the value conflicts that beneficiaries experience when engaging in the monthly ritual of the biometric authentication of their fingerprints to claim state-sponsored food entitlements in India. Drawing on value-based orientations to HCI inquiry, the study locates the interactions around the biometric process to illustrate the ways in which beneficiaries find their values of time, dignity, and privacy, consistently disregarded by the interactive demands of the biometric system. Additionally, to cope with these value conflicts, some beneficiaries pass on the responsibilities of completing the biometric process to the children in their families. While adult beneficiaries are vocal and articulate about the value tensions in their lives, children cope with the anxieties of interacting with the biometric process, silently; even as they experience conflicts in their education, play, and study time.

We describe the iterative co-design process and evaluation of an early autism screening tool (EAST). EAST is an intermediary interactive tablet based app that assists in the early-detection of Autism Spectrum Disorder (ASD) by screening preschoolers in Pakistan through play-based activities in a home, school or clinical setting. Medical professionals, parents of autistic children and teachers were surveyed through focus groups to understand the reasons that contribute to the increasing number of missed early detections, and late- or misdiagnoses. We also evaluate the acceptability, usability and validity of our tool. We tested EAST with both typically developed and autistic children on how they relate to people, imitation, motor skills, visual and intellectual response. They were scored via time taken, the number of wrong attempts, or incorrect answers and audiovisual feedback. This paper contributes towards a digital autism screening tool that delivers insights into the child's behaviour and enables collaboration among parents, teachers and medical professionals.

In this paper, we present a foundation for understanding the elements that enable people with visual impairment to engage with digital games. This is defined by the gamer's relation- ships with information and with elements of control provided by the game, and is mediated through in-game metaphors and affordances when gamers interact as users or creators. This work complements previous research exploring the points of view of gamers with visual impairment by focusing on the games they play and prioritising the relationships between the key enablers of access to digital games. Using the framework to examine existing and missing components will enable de- signers to consider broader aspects of accessibility in game design.

Playtesting of games often relies on a mixed-methods approach to obtain more holistic insights about and, in turn, improve the player experience. However, triangulating the different data sources and visualizing them in an integrated manner such that they contextualize each other still proves challenging. Despite its potential value for gauging player behaviour, this area of research continues to be underexplored. In this paper, we propose a visualization approach that combines commonly tracked movement data with - from a visualization perspective rarely considered - gaze behaviour and emotional responses. We evaluated our approach through a qualitative expert study with five professional game developers. Our results show that both the individual visualization of gaze, emotions, and movement but especially their combination are valuable to understand and form hypotheses about player behaviour. At the same time, our results stress that careful attention needs to be paid to ensure that the visualization remains legible and does not obfuscate information.

The conventional dwell-based methods for text entry by gaze are typically slow and uncomfortable. A swipe-based method that maps gaze path into words offers an alternative. However, it requires the user to explicitly indicate the beginning and ending of a word, which is typically achieved by tedious gaze-only selection. This paper introduces TAGSwipe, a bi-modal method that combines the simplicity of touch with the speed of gaze for swiping through a word. The result is an efficient and comfortable dwell-free text entry method. In the lab study TAGSwipe achieved an average text entry rate of 15.46 wpm and significantly outperformed conventional swipe-based and dwell-based methods in efficacy and user satisfaction.

HCI researchers are increasingly interested in describing the complexity of design practice, including ethical, organizational, and societal concerns. Recent studies have identified individual practitioners as key actors in driving the design process and culture within their respective organizations, and we build upon these efforts to reveal practitioner concerns regarding ethics on their own terms. In this paper, we report on the results of an interview study with eleven UX practitioners, capturing their experiences that highlight dimensions of design practice that impact ethical awareness and action. Using a bottom-up thematic analysis, we identified five dimensions of design complexity that influence ethical outcomes and span individual, collaborative, and methodological framing of UX activity. Based on these findings, we propose a set of implications for the creation of ethically-centered design methods that resonate with this complexity and inform the education of future UX practitioners.

Artificial Intelligence (AI) plays an increasingly important role in improving HCI and user experience. Yet many challenges persist in designing and innovating valuable human-AI interactions. For example, AI systems can make unpredictable errors, and these errors damage UX and even lead to undesired societal impact. However, HCI routinely grapples with complex technologies and mitigates their unintended consequences. What makes AI different? What makes human-AI interaction appear particularly difficult to design? This paper investigates these questions. We synthesize prior research, our own design and research experience, and our observations when teaching human-AI interaction. We identify two sources of AI's distinctive design challenges: 1) uncertainty surrounding AI's capabilities, 2) AI's output complexity, spanning from simple to adaptive complex. We identify four levels of AI systems. On each level, designers encounter a different subset of the design challenges. We demonstrate how these findings reveal new insights for designers, researchers, and design tool makers in productively addressing the challenges of human-AI interaction going forward.

Distributed collaboration on physical tasks is a social process that involves all actors iteratively proposing, assessing and modifying the view of a shared workspace. In this paper, we describe the ways in which a view of a shared workspace is shaped by a remote expert to weave their expertise into the accomplishment of a complex physical task during surgical telementoring. We focus on the communicative functions of talk and actions used by the remote experts and local workers and identify strategies the experts employ to remotely shape the view. This analysis reveals the possibility for collaborative shaping of a view in surgical telementoring as well as other mechanism for a remote expert to craft and present a view of the shared workspace.

Adolescents with chronic conditions must work with family caregivers to manage their illness experiences. To explore how technology can support collaborative documentation of these experiences, we designed and distributed a paper diary probe kit in a two-week field deployment with 12 adolescent-parent dyads (24 participants). Three insights emerged from the study that highlight how technology can support shared illness management: 1) provide scaffolds to recognize physical and emotional experiences in the context of daily activities; 2) help families reconstruct patient experiences; and 3) adapt to individual preferences for capturing, representing and sharing experiences. We discuss opportunities for HCI research that follow from these findings and conclude by reflecting on the benefits and limitations of using diary probes with adolescent patients and their parental caregivers.

Current approaches to AI and Assistive Technology (AT) often foreground task completion over other encounters such as expressions of care. Our paper challenges and complements such task-completion approaches by attending to the care work of access-the continual affective and emotional adjustments that people make by noticing and attending to one another. We explore how this work impacts encounters among people with and without vision impairments who complete tasks together. We find that bound up in attempts to get things done are concerns for one another and how well people are doing together. Reading this work through emerging disability studies and feminist STS scholarship, we account for two important forms of work that give rise to access: (1) mundane attunements and (2) non-innocent authorizations. Together these processes work as sensitizing concepts to help HCI scholars account for the ways that intelligent ATs both produce access while sometimes subverting people with disabilities.

Integration of soft haptic devices into garments can improve their usability and wearability for daily computing interactions. In this paper, we introduce PneuSleeve, a fabric-based, compact, and highly expressive forearm sleeve which can render a broad range of haptic stimuli including compression, skin stretch, and vibration. The haptic stimuli are generated by controlling pneumatic pressure inside embroidered stretchable tubes. The actuation configuration includes two compression actuators on the proximal and distal forearm, and four uniformly distributed linear actuators around and tangent to the forearm. Further, to ensure a suitable grip force, two soft mutual capacitance sensors are fabricated and integrated into the compression actuators, and a closed-loop force controller is implemented. We physically characterize the static and dynamic behavior of the actuators, as well as the performance of closed-loop control. We quantitatively evaluate the psychophysical characteristics of the six actuators in a set of user studies. Finally, we show the expressiveness of PneuSleeve by evaluating combined haptic stimuli using subjective assessments.

Social media provides a critical communication platform for political figures, but also makes them easy targets for harassment. In this paper, we characterize users who adversarially interact with political figures on Twitter using mixed-method techniques. The analysis is based on a dataset of 400~thousand users' 1.2~million replies to 756 candidates for the U.S. House of Representatives in the two months leading up to the 2018 midterm elections. We show that among moderately active users, adversarial activity is associated with decreased centrality in the social graph and increased attention to candidates from the opposing party. When compared to users who are similarly active, highly adversarial users tend to engage in fewer supportive interactions with their own party's candidates and express negativity in their user profiles. Our results can inform the design of platform moderation mechanisms to support political figures countering online harassment.

Biases in language influence how we interact with each other and society at large. Language affirming gender stereotypes is often observed in various contexts today, from recommendation letters and Wikipedia entries to fiction novels and movie dialogue. Yet to date, there is little agreement on the methodology to quantify gender stereotypes in natural language (specifically the English language). Common methodology (including those adopted by companies tasked with detecting gender bias) rely on a lexicon approach largely based on the original BSRI study from 1974. In this paper, we reexamine the role of gender stereotype detection in the context of modern tools, by comparatively analyzing efficacy of lexicon-based approaches and end-to-end, ML-based approaches prevalent in state-of-the-art natural language processing systems. Our efforts using a large dataset show that even compared to an updated lexicon-based approach, end-to-end classification approaches are significantly more robust and accurate, even when trained by moderately sized corpora.

As healthcare providers have transitioned from paper to electronic health records they have gained access to increasingly sophisticated documentation aids such as custom note templates. However, little is known about how providers use these aids. To address this gap, we examine how 48 ophthalmologists and their staff create and use content-importing phrases — a customizable and composable form of note template — to document office visits across two years. In this case study, we find 1) content-importing phrases were used to document the vast majority of visits (95%), 2) most content imported by these phrases was structured data imported by data-links rather than boilerplate text, and 3) providers primarily used phrases they had created while staff largely used phrases created by other people. We conclude by discussing how framing clinical documentation as end-user programming can inform the design of electronic health records and other documentation systems mixing data and narrative text.

Machine learning models risk encoding unfairness on the part of their developers or data sources. However, assessing fairness is challenging as analysts might misidentify sources of bias, fail to notice them, or misapply metrics. In this paper we introduce Silva, a system for exploring potential sources of unfairness in datasets or machine learning models interactively. Silva directs user attention to relationships between attributes through a global causal view, provides interactive recommendations, presents intermediate results, and visualizes metrics. We describe the implementation of Silva, identify salient design and technical challenges, and provide an evaluation of the tool in comparison to an existing fairness optimization tool.

Participants in video meetings have long struggled with asymmetrical attention levels, especially when participants are distributed unevenly. While technological advances offer exciting opportunities to augment remote users' attention, the phenomenological complexity of attention means that to design attention-fostering features we must first understand what aspects of it are functionally meaningful to support. In this paper, we present a functional classification of observable attention for video meetings. The classification was informed by two studies on sense-making and selectiveness of attention in work meetings. It includes categories of attention accessible for technological support, their functions in a meeting process, and meeting-related activities that correspond to these functions. This classification serves as a multi-level representation of attention and informs the design of features aiming to support remote participants' attention in video meetings.

Direct observation of behavior provides a unique type of data for reflecting on during a process of behavioral intervention. This study focuses on practitioners who specialize in operationalizing, recording, and monitoring behavior using data collection through paper-and-pencil or, increasingly, mobile computing. Applying an action research approach, we conducted fieldwork to understand observational data collection among practitioners providing children with special education support for behavioral needs. We present a model of collaborative data collection, which describes how practices are situated in the process of collecting data that are useful for reflection by teams of practitioners. We discuss how computer-assisted data collection could promote more systematic and rigorous practices, and design considerations for the collaborative aspects of collecting and reflecting on behavioral data. This study builds on research describing the practices of individuals who track their own behavioral data, and improves our understanding of informal documentation practices in organizations.

Conceptual diagrams are used extensively to understand abstract relationships, explain complex ideas, and solve difficult problems. To illustrate concepts effectively, experts find appropriate visual representations and translate concepts into concrete shapes. This translation step is not supported explicitly by current diagramming tools. This paper investigates how domain experts create conceptual diagrams via semi-structured interviews with 18 participants from diverse backgrounds. Our participants create, adapt, and reuse visual representations using both sketches and digital tools. However, they had trouble using current diagramming tools to transition from sketches and reuse components from earlier diagrams. Our participants also expressed frustration with the slow feedback cycles and barriers to automation of their tools. Based on these results, we suggest four opportunities of diagramming tools — exploration support, representation salience, live engagement, and vocabulary correspondence — that together enable a natural diagramming experience. Finally, we discuss possibilities to leverage recent research advances to develop natural diagramming tools.

Two-factor authentication is a widely recommended security mechanism and already offered for different services. However, known methods and physical realizations exhibit considerable usability and customization issues. In this paper, we propose 3D-Auth, a new concept of two-factor authentication. 3D-Auth is based on customizable 3D-printed items that combine two authentication factors in one object. The object bottom contains a uniform grid of conductive dots that are connected to a unique embedded structure inside the item. Based on the interaction with the item, different dots turn into touch-points and form an authentication pattern. This pattern can be recognized by a capacitive touchscreen. Based on an expert design study, we present an interaction space with six categories of possible authentication interactions. In a user study, we demonstrate the feasibility of 3D-Auth items and show that the items are easy to use and the interactions are easy to remember.

Capturing 3D foot models is important for applications such as manufacturing customized shoes and creating clubfoot orthotics. In this paper, we propose a novel prototype, Sensock, to offer a fully wearable solution for the task of 3D foot reconstruction. The prototype consists of four soft stretchable sensors, made from silk fibroin yarn. We identify four characteristic foot girths based on the existing knowledge of foot anatomy, and measure their lengths with the resistance value of the stretchable sensors. A learning-based model is trained offline and maps the foot girths to the corresponding 3D foot shapes. We compare our method with existing solutions using red-green-blue (RGB) or RGBD (RGB-depth) cameras, and show the advantages of our method in terms of both efficiency and accuracy. In the user experiment, we find that the relative error of Sensock is lower than 0.55%. It performs consistently across different trials and is considered comfortable and suitable for long-term wearing.

The development of a statistical modeling program requires example data to observe and verify the behavior of the program. Such example data are either taken from an existing dataset or synthesized using commands. Programmers may want to directly design an arbitrary dataset or modify it interactively, but it is difficult to do so in current development environments. We therefore propose combining a code editor with an interactive scatter plot editor to efficiently understand the behavior of statistical modeling algorithms. The user interactively creates and modifies the dataset on the scatter plot editor, while the system continuously executes the code in the editor, taking the data as input, and shows the result in the editor. This paper presents the design rationale behind the system and introduces several usage scenarios.

In Dunhuang Mogao Grottoes, unique Buddhist murals of ancient China are preserved. Unfortunately, the exquisite murals are suffering from degradation. Experts have been trying to enhance public's awareness of mural protection, but there's no efficacious means to attract interest and popularize knowledge yet. In this paper, we propose RestoreVR, an interactive virtual reality (VR) system engaging users to experience Dunhuang mural restoration in a digital tour in the cave. Based on an online survey with the public and in-depth interviews with five Dunhuang experts, we derive a set of design requirements for generating embodied knowledge and situated experience in VR to bridge the gap between highly specialized experts and general audiences. Accordingly, we design RestoreVR and conduct a between-subjects user study to compare our system with traditional methods. The results suggest that RestoreVR significantly improves user experience and awareness of CH protection over existing methods.

Questionnaires are among the most common research tools in virtual reality (VR) evaluations and user studies. However, transitioning from virtual worlds to the physical world to respond to VR experience questionnaires can potentially lead to systematic biases. Administering questionnaires in VR (inVRQs) is becoming more common in contemporary research. This is based on the intuitive notion that inVRQs may ease participation, reduce the Break in Presence (BIP) and avoid biases. In this paper, we perform a systematic investigation into the effects of interrupting the VR experience through questionnaires using physiological data as a continuous and objective measure of presence. In a user study (n=50), we evaluated question-asking procedures using a VR shooter with two different levels of immersion. The users rated their player experience with a questionnaire either inside or outside of VR. Our results indicate a reduced BIP for the employed inVRQ without affecting the self-reported player experience.

Leveraging existing popular games such as Pokemon GO to promote health can engage people in healthy activities without sacrificing gaming appeal. However, little is known about what potential tensions arise from incorporating new health-related features to already existing and popular games and how to resolve those tensions from players' perspectives. In this paper, we identify design tensions surrounding the appeals of Pokemon GO, perspectives on different health needs, and mobile health technologies. By conducting surveys and design workshops with 20 avid Pokemon GO players, we demonstrate four design tensions: (1) diverse goals and rewards vs. data accuracy, (2) strong bonds between players and characters vs. gaming obsession, (3) collaborative play vs. social anxiety, and (4) connection of in-real-life experiences with the game vs. different individual contexts. We provide design implications to resolve these tensions in Pokemon GO and discuss how to extend our findings to the broader context of health promotion in location-based games.

Video-Reflection is a common approach to realize reflection in the field of executive coaching for professional development, which presents a video recording of the coaching session to a coachee in order to make the coachee reflectively think about oneself. However, it requires a great deal of time to watch the full length of the video and is highly dependent on the skills of the coach. We expect that the quality and efficiency of video-reflection can be improved with the support of computers. In this paper, we introduce INWARD, a computational tool that leverages human behavior analysis and video-based interaction techniques. The results of a user study involving 20 coaching sessions with five coaches indicate that INWARD enables efficient video-reflection and, by leveraging meta-reflection, realizes the ameliorated outcome of executive coaching. Moreover, discussions based on comments from the participants support the effectiveness of INWARD and suggest further possibilities of computer-supported approaches.

Connected devices present new opportunities to advance design through data collection in the wild, similar to the way digital services evolve through analytics. However, it is still unclear how live data transmitted by connected devices informs the design of these products, going beyond performance optimisation to support creative practices. Design can be enriched by data captured by connected devices, from usage logs to environmental sensors, and data about the devices and people around them. Through a series of workshops, this paper contributes industry and academia perspectives on the future of data-driven product design. We highlight HCI challenges, issues and implications, including sensemaking and the generation of design insight. We further challenge current notions of data-driven design and envision ways in which future HCI research can develop ways to work with data in the design process in a connected, rich, human manner.

Design studies are frequently used to conduct problem-driven visualization research by working with real-world domain experts. In visualization pedagogy, design studies are often introduced but rarely practiced due to their large time requirements. This limits students to a classroom curriculum, often involving projects that may not have implications beyond the classroom. Thus we present the Design Study "Lite" Methodology, a novel framework for implementing design studies with novice students in 14 weeks. We utilized the Design Study "Lite" Methodology in conjunction with Service-Learning to teach five Data Visualization courses and demonstrate that it benefits not only the students but also the community through service to non-profit partners. In this paper, we provide a detailed breakdown of the methodology and how Service-Learning can be incorporated with it. We also include an extensive reflection on the methodology and provide recommendations for future applications of the framework for teaching visualization courses and research.

Adaptive instruction for online education can increase learning gains and decrease the work required of learners, instructors, and course designers. Reinforcement Learning (RL) is a promising tool for developing instructional policies, as RL models can learn complex relationships between course activities, learner actions, and educational outcomes. This paper demonstrates the first RL model to schedule educational activities in real time for a large online course through active learning. Our model learns to assign a sequence of course activities while maximizing learning gains and minimizing the number of items assigned. Using a controlled experiment with over 1,000 learners, we investigate how this scheduling policy affects learning gains, dropout rates, and qualitative learner feedback. We show that our model produces better learning gains using fewer educational activities than a linear assignment condition, and produces similar learning gains to a self-directed condition using fewer educational activities and with lower dropout rates.

Mid-air haptic (MAH) feedback, providing touch feedback through ultrasound, has been considered an attractive substitute for the absence of physical touch during gesture-based interaction. Although the impact of MAH feedback on workload has already received some attention, the impact on other qualities of the user experience, including general attractiveness and experienced pleasure have been less investigated. In this preregistered study, involving 32 participants, we observed an added value of MAH feedback, on top of visual feedback, by increasing the attractiveness and experienced pleasure during gesture-based interaction, but not by decreasing workload. The added value regarding pleasure and attractiveness disappeared however after statistically controlling for perceived novelty. This paper highlights the importance of statistically controlling for novelty when testing the user experience of new technology during first-time use.