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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.

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.

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 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.

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

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.

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.

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.

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.

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.

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.

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.

There is an increased use of Internet-of-Things and wearable sensing devices in the urban marathon to ensure effective response to unforeseen medical needs. However, the massive amount of real-time, heterogeneous movement and psychological data of runners impose great challenges on prompt medical incident analysis and intervention. Conventional approaches compile such data into one dashboard visualization to facilitate rapid data absorption but fail to support joint decision-making and operations in medical encounters. In this paper, we present MaraVis, a real-time urban marathon visualization and coordinated intervention system. It first visually summarizes real-time marathon data to facilitate the detection and exploration of possible anomalous events. Then, it calculates an optimal camera route with an arrangement of shots to guide offline effort to catch these events in time with a smooth view transition. We conduct a within-subjects study with two baseline systems to assess the efficacy of MaraVis.

Programming tutorials are a pervasive, versatile medium for teaching programming. In this paper, we report on the content and structure of programming tutorials, the pain points authors experience in writing them, and a design for a tool to help improve this process. An interview study with 12 experienced tutorial authors found that they construct documents by interleaving code snippets with text and illustrative outputs. It also revealed that authors must often keep related artifacts of source programs, snippets, and outputs consistent as a program evolves. A content analysis of 200 frequently-referenced tutorials on the web also found that most tutorials contain related artifacts—duplicate code and outputs generated from snippets—that an author would need to keep consistent with each other. To address these needs, we designed a tool called Torii with novel authoring capabilities. An in-lab study showed that tutorial authors can successfully use the tool for the unique affordances identified, and provides guidance for designing future tools for tutorial authoring.

As self-tracking practices continue to proliferate, there has been a call for a consideration of how the design of these devices influence the users experience of themselves and their bodies beyond utility, efficacy and accuracy. The research product Ovum was designed to facilitate a DIY, shared, domestic experience, rather than an expert-led, individual, clinical experience of fertility tracking. Ovum uses the method of saliva sampling to determine ovulation. This paper unpacks the findings from a three-month long deployment of Ovum with seven couples trying to conceive. Besides an evaluation of the device in terms of the three experiential qualities aimed for in the design process, we report on the consequences of executing a design deployment that resembles a clinical trial. We contribute our experience in order to develop an understanding of how designing for the body places interaction designers in novel and complex situations.

Mobile devices have become the primary mode for Internet access in developing countries. Yet typical data plans and SMS costs can be overwhelming for low income users in these countries. In this paper, we explore the design and usability of a free but extremely low bit rate communication channel to address this challenge. We propose, a data communication channel that uses to transmit messages between phones, thereby sacrificing performance in exchange for low cost. While the data rate of is extremely low (

On-face wearables are currently limited to piercings, tattoos, or interactive makeup that aesthetically enhances the user, and have been minimally used for scent-delivery methods. However, on-face scent interfaces could provide an advantage for personal scent delivery in comparison with other modalities or body locations since they are closer to the nose. In this paper, we present the mechanical and industrial design details of a series of form factors for on-face olfactory wearables that are lightweight and can be adhered to the skin or attached to glasses or piercings. We assessed the usability of three prototypes by testing with 12 participants in a within-subject study design while they were interacting in pairs at a close personal distance. We compare two of these designs with an "off-face" olfactory necklace and evaluate their social acceptance, comfort as well as perceived odor intensity for both the wearer and observer.

This paper introduces Glissade, a digital pen that generates balance shifting feedback by changing the weight distribution of the pen. A pulley system shifts a brass mass inside the pen to change the pen's center of mass and moment of inertia. When the mass is stationary, the pen delivers a constant yet natural sensation of weight, which can be used to convey a status. The pen can also generate a variety of haptic clues by actuating the mass according to the tilt or rotation of the pen, two commonly-used auxiliary pen input channels. Glissade demonstrates new possibilities that balance shifting feedback can bring to digital pen interactions. We validated the usability of this feedback by determining the recognizability of six balance patterns – a mix of static and dynamic patterns chosen based on our design considerations – in two controlled experiments. The results show that, on average, the participants could distinguish between the patterns with a 94.25% accuracy. At the end, we demonstrate a set of novel interactions enabled by Glissade and discuss the directions for future research.

Voice user interfaces (VUIs) are rapidly increasing in popularity in the consumer space. This leads to a concurrent explosion of available applications for such devices, with many industries rushing to offer voice interactions for their products. This pressure is then transferred to interface designers; however, a large majority of designers have been only trained to handle the usability challenges specific to Graphical User Interfaces (GUIs). Since VUIs differ significantly in design and usability from GUIs, we investigate in this paper the extent to which current educational resources prepare designers to handle the specific challenges of VUI design. For this, we conducted a preliminary scoping scan and syllabi meta review of HCI curricula at more than twenty top international HCI departments, revealing that the current offering of VUI design training within HCI education is rather limited. Based on this, we advocate for the updating of HCI curricula to incorporate VUI design, and for the development of VUI-specific pedagogical artifacts to be included in new curricula.

Learning to speak in foreign languages is hard. Speech shadowing has been rising as a proven way to practice speaking, which asks a learner to listen and repeat a native speech template as simultaneously as possible. However, shadowing can be hard to do because learners can frequently fail to follow the speech and unintentionally interrupt a practice session. Worse, as a technical way to evaluate shadowing performance in real-time has not been established, no automated solutions are available to help. In this paper, we propose a technical framework with context-dependent speech recognition to evaluate shadowing in real-time. We propose a shadowing tutor system called WithYou, which can automatically adjust the playback and the difficulty of a speech template when learners fail, so shadowing becomes smooth and tailored. Results from a user study show that WithYou provides greater speech improvements (14%) than the conventional method (2.7%) with a lower cognitive load.

People with visual impairments often require mobility assistance of sighted guides but they are not always available. Recent technological strides have opened up new directions for sighted guidance services, assigning guides from a network of remote workers to provide real-time assistance via audio/video communication. However, little has been known regarding desirable support characteristics of remote guides or challenges experienced in guide practices without the requisite expertise. To recommend support strategies that contribute to facilitating a successful platform for remote sighted guidance, this paper presents a comparative study of the performance of trained and untrained sighted guides who are recruited for a remote scenario in assisting people with visual impairments in indoor navigation. As an outcome of this research, we provide a deeper understanding of design opportunities for HCI to scaffold requirements of remote guides, such that their collaborative efforts and environmental knowledge influence the user experience. Based on our empirical insights, we suggest to develop the expertise of remote guides through: a) preliminary guidance cooperation awareness b) guidelines for verbal description methods, and c) approaches to compensate for the lack of environmental knowledge.

A novel eye-tracked measure of pupil diameter oscillation is derived as an indicator of cognitive load. The new metric, termed the Low/High Index of Pupillary Activity (LHIPA), is able to discriminate cognitive load (vis-a-vis task difficulty) in several experiments where the Index of Pupillary Activity fails to do so. Rationale for the LHIPA is tied to the functioning of the human autonomic nervous system yielding a hybrid measure based on the ratio of Low/High frequencies of pupil oscillation. The paper's contribution is twofold. First, full documentation is provided for the calculation of the LHIPA. As with the IPA, it is possible for researchers to apply this metric to their own experiments where a measure of cognitive load is of interest. Second, robustness of the LHIPA is shown in analysis of three experiments, a restrictive fixed-gaze number counting task, a less restrictive fixed-gaze n-back task, and an applied eye-typing task.

Modeling the endpoint uncertainty of moving target selection with crossing is essential to understand factors such as speed-accuracy trade-off and interaction efficiency in crossing-based user interfaces with dynamic contents. However, there have been few studies looking into this research topic in the HCI field. This paper presents a Quaternary-Gaussian model to quantitatively measure the endpoint uncertainty in crossing-based moving target selection. To validate this model, we conducted an experiment with discrete crossing tasks on five factors, i.e., initial distance, size, speed, orientation, and moving direction. Results showed that our model fit the data of μ and σ accurately with adjusted R2 of 0.883 and 0.920. We also demonstrated the validity of our model in predicting error rates in crossing-based moving target selection. We concluded with a set of implications for future designs.

Mid-air arm movements are ubiquitous in VR, AR, and gestural interfaces. While mouse movements have received some attention, the dynamics of mid-air movements are understudied in HCI. In this paper we present an exploratory analysis of the dynamics of aimed mid-air movements. We explore the 3rd order lag (3OL) and existing 2nd order lag (2OL) models for modeling these dynamics. For a majority of movements the 3OL model captures mid-air dynamics better, in particular acceleration. The models can effectively predict the complete time series of position, velocity and acceleration of aimed movements given an initial state and a target using three (2OL) or four (3OL) free parameters.

Employing anthropomorphism in physical appearance and behavior is the most widespread strategy for designing social robots. In the present paper, we argue that imitating humans impedes the full exploration of robots' social abilities. In fact, their very 'thingness' (e.g., sensors, rationality) is able to create 'superpowers' that go beyond human abilities, such as endless patience. To better identify these special abilities, we develop a performative method called 'Techno-Mimesis' and explore it in a series of workshops with robot designers. Specifically, we create 'prostheses' to allow designers to transform themselves into their future robot to experience use cases from the robot's perspective, e.g., 'seeing' with a distance sensor rather than with eyes. This imperfect imitation helps designers to experience being human and being robot at the same time, making differences apparent and facilitating the discovery of a number of potential physical, cognitive, and communicational robotic superpowers.

This paper provides insight into the use of data tools in the American labor movement by analyzing the practices of staff employed by unions to organize alongside union members. We interviewed 23 field-level staff organizers about how they use data tools to evaluate membership. We find that organizers work around and outside of these tools to develop access to data for union members and calibrate data representations to meet local needs. Organizers mediate between local and central versions of the data, and draw on their contextual knowledge to challenge campaign strategy. We argue that networked data tools can compound field organizers' lack of discretion, making it more difficult for unions to assess and act on the will of union membership. We show how the use of networked data tools can lead to less accurate data, and discuss how bottom-up approaches to data gathering can support more accurate membership assessments.

This paper introduces the Designing for Extended Latency (DELAY) Framework meant to inspire new systems that support social interaction in high-latency settings such as interplanetary communication, intermittent internet access, and time-zone incompatibilities. The framework includes six dimensions: Goal, Communication Genre, Sequencing, Cardinality, Mutability, and Responsiveness. We describe the iterative design process used to create the Framework, as well as three novel prototypes designed to increase social connectedness and social presence in high-latency situations: 1) the InSync app that allows partners to perform activities simultaneously even though they only see proof of their synchronicity later; 2) the After the Beep system that lets users leave IoT messages that are triggered by the recipients; and 3) the Surrogate platform where players play group battle games against "surrogate" artificial intelligence avatars that mimic unavailable individuals. Data from two design workshops validates the usefulness of the framework for generating new solutions to high-latency scenarios.

openaire: EC/H2020/637991/EU//COMPUTED Relatively little is known about eye and finger movement in typing with mobile devices. Most prior studies of mobile typing rely on log data, while data on finger and eye movements in typing come from studies with physical keyboards. This paper presents new findings from a transcription task with mobile touchscreen devices. Movement strategies were found to emerge in response to sharing of visual attention: attention is needed for guiding finger movements and detecting typing errors. In contrast to typing on physical keyboards, visual attention is kept mostly on the virtual keyboard, and glances at the text display are associated with performance. When typing with two fingers, although users make more errors, they manage to detect and correct them more quickly. This explains part of the known superiority of two-thumb typing over one-finger typing. We release the extensive dataset on everyday typing on smartphones.

Collaborative Virtual Environments (CVEs) offer unique opportunities for human communication. Humans can interact with each other over a distance in any environment and visual embodiment they want. Although deictic gestures are especially important as they can guide other humans' attention, humans make systematic errors when using and interpreting them. Recent work suggests that the interpretation of vertical deictic gestures can be significantly improved by warping the pointing arm. In this paper, we extend previous work by showing that models enable to also improve the interpretation of deictic gestures at targets all around the user. Through a study with 28 participants in a CVE, we analyzed the errors users make when interpreting deictic gestures. We derived a model that rotates the arm of a pointing user's avatar to improve the observing users' accuracy. A second study with 24 participants shows that we can improve observers' accuracy by 22.9%. As our approach is not noticeable for users, it improves their accuracy without requiring them to learn a new interaction technique or distracting from the experience.

© 2020 ACM. Personalization of eating such that everyone consumes only what they need allows improving our management of food waste. In this paper, we explore the use of food 3D printing to create perceptual illusions for controlling the level of perceived satiety given a defined amount of calories. We present FoodFab, a system that allows users to control their food intake through modifying a food's internal structure via two 3D printing parameters: infill pattern and infill density. In two experiments with a total of 30 participants, we studied the effect of these parameters on users' chewing time that is known to affect people's feeling of satiety. Our results show that we can indeed modify the chewing time by varying infill pattern and density, and thus control perceived satiety. Based on the results, we propose two computational models and integrate them into a user interface that simplifies the creation of personalized food structures.

Venous Materials is a novel concept and approach of an interactive material utilizing fluidic channels. We present a design method for fluidic mechanisms that respond to deformation by mechanical inputs from the user, such as pressure and bending. We designed a set of primitive venous structures that act as embedded analog fluidic sensors, displaying flow and color change. In this paper, we consider the fluid as the medium to drive tangible information triggered by deformation, and at the same time, to function as a responsive display of that information. To provide users with a simple way to create and validate designs of fluidic structures, we built a software platform and design tool UI. This design tool allows users to quickly design the geometry, and simulate the flow with intended mechanical force dynamically. We present a range of applications that demonstrate how Venous Materials can be utilized to augment interactivity of everyday physical objects.

This paper presents an approach for coupling robotic capability with human ability in dynamic motor skills, called "Human-Machine Mutual Actuation (HMMA)." We focus specifically on throwing motions and propose a method to control the release timing computationally. A system we developed achieves our concept, HMMA, by a robotic handheld device that acts as a release controller. We conducted user studies to validate the feasibility of the concept and clarify related technical issues to be tackled. We recognized that the system successfully performs on throwing according to the target while it exploits human ability. These empirical experiments suggest that robotic capability can be embedded into the users' motions without losing their senses of control. Throughout the user study, we also revealed several issues to be tackled in further research contributing to HMMA.