In HCI, frameworks function as a type of theoretical contribution, often supporting ideation, design, and evaluation. Yet, little is known about how they are actually used, what functions they serve, and which scholarly practices that shape them. To address this gap, we conducted a systematic review of 615 papers from a decade of CHI proceedings (2015-2024) that prominently featured the term framework. We classified these papers into six engagement types. We then examined the role, form, and essential components of newly proposed frameworks through a functional typology, analyzing how they are constructed, validated, and articulated for reuse. Our results show that enthusiasm for proposing new frameworks exceeds the willingness to iterate on existing ones. They also highlight the ambiguity in the function of frameworks and the scarcity of systematic validation. Based on these insights, we call for more rigorous, reflective, and cumulative practices in the development and use of frameworks in HCI.

Proliferation of misinformation is a globally acknowledged problem. Cognitive Inoculation helps build resistance to different forms of persuasion, such as misinformation. We investigate Conversational Inoculation, a method to help people build resistance to misinformation through dynamic conversations with a chatbot. We built a Web-based system to implement the method, and conducted a within-subject user experiment to compare it with two traditional inoculation methods. Our results validate Conversational Inoculation as a viable novel method, and show how it was able to enhance participants’ resistance to misinformation. A qualitative analysis of the conversations between participants and the chatbot highlighted adaptability, independence, trust and friction as the main factors affecting Conversational Inoculation. We discuss the opportunities and challenges of using Conversational Inoculation to combat misinformation. Our work contributes a timely investigation and a promising research direction in scalable ways to combat misinformation.

In difficult workplace email conversations, such as layoffs or resource negotiations, the absence of nonverbal cues can exacerbate negative emotions experienced by recipients. While existing tools support senders in refining tone, there is little support for processing emotionally intensive content from the receivers’ side. This study investigated the use of large language models that added positive or neutral reframings, written in either first or third person, to original emails, with the aim of helping recipients view difficult conversations in a different light. In a controlled study with 132 participants, positive reframing reduced receivers’ negative emotions and was rated as more helpful than neutral reframing, regardless of narrative perspective. Although reframing type did not significantly change conflict management behaviors, positive reframing led to fewer power-related words in interpretations of the email. These findings highlight opportunities and challenges for designing AI as a social buffer to facilitate difficult conversations online.

Critical reading is a primary way through which researchers develop their critical thinking skills. While exchanging thoughts and opinions with peers can strengthen critical reading, junior researchers often lack access to peers who can offer diverse perspectives. To address this gap, we designed an in-situ thought exchange interface informed by peer feedback from a formative study (N=8) to support junior researchers’ critical paper reading. We evaluated the effects of thought exchanges under three conditions (no-agent, single-agent, and multi-agent) with 46 junior researchers over two weeks. Our results showed that incorporating agent-mediated thought exchanges during paper reading significantly improved participants’ critical thinking scores compared to the no-agent condition. In the single-agent condition, participants more frequently made reflective annotations on the paper content. In the multi-agent condition, participants engaged more actively with agents’ responses. Our qualitative analysis further revealed that participants compared and analyzed multiple perspectives in the multi-agent condition. This work contributes to understanding in-situ AI-based support for critical paper reading through thought exchanges and offers design implications for future research.

As AI writing support becomes ubiquitous, the question of how disclosing its use affects reader perception remains critical and underexplored. We conducted a controlled study with 261 participants to examine how disclosing varying levels of AI involvement shifts perceptions of the author across six distinct communicative acts. Our analysis of 990 evaluations reveals that disclosure generally erodes perceived trustworthiness, caring, competence, and likability, with the most precipitous declines observed in social and interpersonal writing. A thematic analysis of participant feedback attributes these negative shifts to a perceived loss of human sincerity, diminished authorial effort, and the contextual inappropriateness of AI. Notably, however, we find that higher AI literacy mitigates these negative perceptions, leading to greater tolerance or even appreciation for AI assistance. Our results highlight the nuanced social dynamics of AI-mediated authorship and inform design implications for transparent, context-sensitive writing systems that better preserve trust and authenticity.

Multiparty conversations are ubiquitous and indispensable in diverse social and collaborative contexts. However, current conversational agents (CAs) face significant challenges in effectively engaging in such interactions, particularly within text-based environments. While earlier limitations were often attributed to the inadequacies of AI models, recent advances in large language models now compel us to revisit both our understanding of multiparty conversation and the way we design CAs. This paper synthesizes findings from two complementary qualitative investigations and proposes a conceptual model for designing CAs that can genuinely participate, rather than merely function as tools or outsiders. The first study, employing retrospective think-aloud sessions (N=30) with users in text-based multiparty settings, uncovers 5 key interactional mechanisms (e.g., Turn-taking Management, Presence Management) that underpin successful human-human multiparty interactions, derived from participants’ articulated perceptions and reasoning. Subsequently, the second study, through semi-structured interviews (N=15), identifies user expectations for CA integration and key traits (e.g., proactivity, social authenticity) that shape an ideal CA persona perceived by users as a genuine participant. Drawing from these human-centric insights, we then derive design considerations, aiming to guide the development of CAs capable of more natural, effective, and socially intelligent participation in multiparty conversation.

Mental disorders deteriorate well-being in many ways. Clinical mental health care is insufficient and struggles to keep up with the growing demand for services in many parts of the world. Human–Computer Interaction researchers have focused on building different interactive systems that support mental well-being. In our work, we focus on collecting, peer-assessing, and assisting in the discovery of mental health self-care techniques through an online tool. Our target demographic is the higher education community. The implemented tool can offer new self-care techniques to its users, and our user studies validate its usefulness in capturing and offering valuable mental health care information. Further, we study how source disclosure affects the perception of the discovered techniques, finding no major differences in the measured variables. Finally, we discuss how user-generated self-care suggestions in this context warrants caution and the implications of our study.

Premenstrual syndrome (PMS) is a prevalent disorder among women, often exacerbated by a lack of peer support due to associated stigmatization.Drawing inspiration from the established benefits of group therapy, particularly the sense of belonging it fosters, we developed a multi-chatbot group motivational interviewing system.The system consists of a facilitator bot and two peer bots, and simulates a group counseling environment for PMS management using Large Language Models (LLMs).We conducted a study with 63 participants and divided them into three conditions (no intervention, 1-on-1 chatbot, group chatbots) over two menstruation cycles for evaluation.Our findings revealed that participants in the group chat condition exhibited higher levels of engagement and language convergence with the chatbots.These participants were also able to engage in social learning and demonstrated motivation in coping through interactions with the chatbots.Finally, we discuss design implications for multi-chatbot interactions in supporting mental health.

Teaching and learning physical drawing remotely pose user-experience challenges. In an online physical drawing course, instructors must interact with students through a camera for demonstrations, supervision, communication, and annotations in real-time. However, these activities are not well supported by commonly used video conferencing services. We conduct a qualitative study with seven instructors and five students to understand their practices and challenges in teaching and learning of physical drawing in a remote setting. Our study identifies four design considerations that a system supporting remote teaching and learning of physical drawing should take into account. We then demonstrate the technical feasibility of these design considerations by building a working prototype called SharedCanvas. We also validate our design considerations through a user study with SharedCanvas, revealing how they better supported interactions between instructors and students. We conclude by discussing our work in light of related studies on online drawing education and present future research opportunities to improve remote teaching of drawing.

Psychotherapy, such as cognitive-behavioral therapy (CBT), is effective in treating various mental disorders. Technology-facilitated mental health therapy improves client engagement through methods like digitization or gamification. However, these innovations largely cater to individual therapy, ignoring the potential of group therapy-a treatment for multiple clients concurrently, which enables individual clients to receive various perspectives in the treatment process and also addresses the scarcity of healthcare practitioners to reduce costs. Notwithstanding its cost-effectiveness and unique social dynamics that foster peer learning and community support, group therapy, such as group CBT, faces the issue of attrition. While existing medical work has developed guidelines for therapists, such as establishing leadership and empathy to facilitate group therapy, understanding about the interactions between each stakeholder is still missing. To bridge this gap, this study examined a group CBT program called the Serigaya Methamphetamine Relapse Prevention Program (SMARPP) as a case study to understand stakeholder coordination and communication, along with factors promoting and hindering continuous engagement in group therapy. In-depth interviews with eight facilitators and six former clients from SMARPP revealed the motivators and demotivators for facilitator-facilitator, client-client, and facilitator-client communications. Our investigation uncovers the presence of discernible conflicts between clients' intrapersonal motivation as well as interpersonal motivation in the context of group therapy through the lens of self-determination theory. We discuss insights and research opportunities for the HCI community to mediate such tension and enhance stakeholder communication in future technology-assisted group therapy settings.

Expressive writing is an established approach for stress management. Recently, information technologies, such as smartphones, have also been explored for expressive writing. Although mobile interfaces have the potential to support various daily writing activities, interface designs for mobile expressive writing and their effects on stress relief still lack empirical understanding. We examined the interface design of mobile expressive writing by investigating the influence of input modalities and visual feedback designs on usability and perceived cathartic effects through field studies. While our studies confirmed the stress-relieving effects of mobile expressive writing, our results offer important insights into interface design. We found keyboard-based text entry more suited and preferred over voice messages for its privacy and reflective nature. Participants expressed different reasons for preferring different post-writing visual feedback depending on the cause and type of stress. This work advances interface design for mobile expressive writing and deepens understanding of its effects.

The richness of the information in photos can often threaten privacy, thus image editing methods are often employed for privacy protection. Existing image privacy protection techniques, like blurring, often struggle to maintain the balance between robust privacy protection and preserving image usability. To address this, we introduce a generative content replacement (GCR) method in image privacy protection, which seamlessly substitutes privacy-threatening contents with similar and realistic substitutes, using state-of-the-art generative techniques. Compared with four prevalent image protection methods, GCR consistently exhibited low detectability, making the detection of edits remarkably challenging. GCR also performed reasonably well in hindering the identification of specific content and managed to sustain the image’s narrative and visual harmony. This research serves as a pilot study and encourages further innovation on GCR and the development of tools that enable human-in-the-loop image privacy protection using approaches similar to GCR.

Online reviews help people make better decisions. Review platforms usually depend on typed input, where leaving a good review requires significant effort because users must carefully organize and articulate their thoughts. This may discourage users from leaving comprehensive and high-quality reviews, especially when they are on the go. To address this challenge, we developed Vocalizer, a mobile application that enables users to provide reviews through voice input, with enhancements from a large language model (LLM). In a longitudinal study, we analysed user interactions with the app, focusing on AI-driven features that help refine and improve reviews. Our findings show that users frequently utilized the AI agent to add more detailed information to their reviews. We also show how interactive AI features can improve users self-efficacy and willingness to share reviews online. Finally, we discuss the opportunities and challenges of integrating AI assistance into review-writing systems.

Timbre exploration and creation are key tasks in electronic music composition. Modern synthesizers can produce thousands of unique timbres, but this complexity hinders musicians’ ability to explore these timbres effectively. We contribute SoundTraveller, an interactive timbre exploration system aimed at fostering electronic musicians’ creative processes. SoundTraveller allows the user to explore the timbral space using two modes: evolutionary and morphing, with which they can generate hundreds of unique timbres without the need to edit individual parameters. Our user study confirmed that SoundTraveller supported participants’ exploration, decreased their cognitive load, and increased their perceived creativity. Through analysis of our interview study, we contribute design considerations for timbre exploration systems, and for exploring large aesthetic parameter spaces more generally. Finally, we discuss how systems like SoundTraveller can fit into the existing workflows of electronic music composers, and how shared agency with creative technologies can impact the creative process.

Instructors facilitating online classes have a limited ability to see and hear interactions of student groups working in parallel, which prevents them from interacting with students effectively. In this work, we explore interface design for providing an overview of parallel group discussions in online classrooms. We derive design considerations through a participatory design process and instantiate them in our visualization interface, Groupnamics. Groupnamics visualizes recent vocal activities and discussion statuses of each group in a one-page view, facilitating identification of groups where intervention may be needed. Our user study with 16 instructors confirmed that Groupnamics can successfully provide cues for when instructors should join group discussions and improvements on the perceived usefulness and ease of use over the baseline interface representing existing videoconferencing tools. Our qualitative results suggest future research directions in interface design for online parallel group discussions.

Artificial Intelligence is seen as humanity’s current best bet to solve the looming crisis in healthcare. Conversational Agents, or chatbots, rely on advances in AI and are increasingly investigated in the context of digital mental health care. Given how they are end-user-facing and interactive communication tools, the user engagement felt when interacting with the bots is a critical consideration. In this work, we examine the effects of chatbot personalities on the experienced user engagement with the bot. We employed personalities that rely on the Big-5 Personality Theory. Among other findings, our quantitative results indicate that a highly conscientious chatbot is likely to foster the highest user engagement. Our qualitative and content analysis also reveals desired and undesired personality features for future mental health chatbots. We discuss our findings in light of digital mental health and propose novel research directions.

Interactive Machine Teaching (IMT) systems allow non-experts to easily create Machine Learning (ML) models. However, existing vision-based IMT systems either ignore annotations on the objects of interest or require users to annotate in a post-hoc manner. Without the annotations on objects, the model may misinterpret the objects using unrelated features. Post-hoc annotations cause additional workload, which diminishes the usability of the overall model building process. In this paper, we develop LookHere, which integrates in-situ object annotations into vision-based IMT. LookHere exploits users’ deictic gestures to segment the objects of interest in real time. This segmentation information can be additionally used for training. To achieve the reliable performance of this object segmentation, we utilize our custom dataset called HuTics, including 2040 front-facing images of deictic gestures toward various objects by 170 people. The quantitative results of our user study showed that participants were 16.3 times faster in creating a model with our system compared to a standard IMT system with a post-hoc annotation process while demonstrating comparable accuracies. Additionally, models created by our system showed a significant accuracy improvement (ΔmIoU = 0.466) in segmenting the objects of interest compared to those without annotations.

Co-customizations are collaborative customizations in messaging apps that all conversation members can view and change, e.g. the color of chat bubbles on Facebook Messenger. Co-customizations grant new opportunities for expressing intimacy; however, most apps offer private customizations only. To investigate how people in close relationships integrate co-customizations into their established communication app ecosystems, we built DearBoard: an Android keyboard that allows two people to co-customize its color theme and a toolbar of expression shortcuts (emojis and GIFs). In a 5-week field study with 18 pairs of couples, friends, and relatives, participants expressed their shared interests, history, and knowledge of each other through co-customizations that served as meaningful decorations, interface optimizations, conversation themes, and non-verbal channels for playful, affectionate interactions. The co-ownership of the co-customizations invited participants to negotiate who customizes what and for whom they customize. We discuss how co-customizations mediate intimacy through place-making efforts and suggest design opportunities.

A nudge is a method to influence individual choices without taking away freedom of choice. We are interested in whether nudges can help adolescents avoid privacy and safety threats on social network services (SNS). We conducted an online survey to compare how 11 different nudge designs influence decisions on 9 scenarios featuring various privacy and safety threats. We collected 29,608 responses from adolescent SNS users (self-claimed high school and university students), and found that nudges can help to educe potentially risk choices. Participants were more likely to avoid potentially risky choices when presented with negative frames (e.g., "90% of users would not share a photo without permission'') than affirmative ones (e.g., "10% of users would''). Social nudges displaying statistics on how likely other people would make potentially risky decisions can have a negative effect in comparison to a nudge with only general privacy and safety suggestions. We conclude by providing design considerations for privacy/safety nudges targeting adolescent SNS users.

Repetitive patterns are ubiquitous in natural and human-made objects, and can be created with a variety of tools and methods. Manual authoring provides unmatched degree of freedom and control, but can require significant artistic expertise and manual labor. Computational methods can automate parts of the manual creation process, but are mainly tailored for discrete pixels or elements instead of more general continuous structures. We propose an example-based method to synthesize continuous curve patterns from exemplars. Our main idea is to extend prior sample-based discrete element synthesis methods to consider not only sample positions (geometry) but also their connections (topology). Since continuous structures can exhibit higher complexity than discrete elements, we also propose robust, hierarchical synthesis to enhance output quality. Our algorithm can generate a variety of continuous curve patterns fully automatically. For further quality improvement and customization, we also present an autocomplete user interface to facilitate interactive creation and iterative editing. We evaluate our methods and interface via different patterns, ablation studies, and comparisons with alternative methods.

Musical instrument playing is a skill many people desire to acquire, and learners now have a wide variety of learning materials. However, their volume is enormous, and novice learners may easily get lost in which songs they should practice first. We develop Strummer: an interactive multimedial system for guitar practice. Strummer provide data-driven and personalized practice for learners in order to identify important and easy-to-learn chords and songs. This practice design is intended to encourage smooth skill transfers to songs that learners even have not seen. Our user study confirms the benefits and possible improvements of the Strummer system. In particular, participants expressed their positive impressions on lessons provided by the system.

Video consumption is being shifted from sit-and-watch to selective skimming. Existing video player interfaces, however, only provide indirect manipulation to support this emerging behavior. Video summarization alleviates this issue to some extent, shortening a video based on the desired length of a summary as an input variable. But an optimal length of a summarized video is often not available in advance. Moreover, the user cannot edit the summary once it is produced, limiting its practical applications. We argue that video summarization should be an interactive, mixed-initiative process in which users have control over the summarization procedure while algorithms help users achieve their goal via video understanding. In this paper, we introduce ElasticPlay, a mixed-initiative approach that combines an advanced video summarization technique with direct interface manipulation to help users control the video summarization process. Users can specify a time budget for the remaining content while watching a video; our system then immediately updates the playback plan using our proposed cut-and-forward algorithm, determining which parts to skip or to fast-forward. This interactive process allows users to fine-tune the summarization result with immediate feedback. We show that our system outperforms existing video summarization techniques on the TVSum50 dataset. We also report two lab studies (22 participants) and a Mechanical Turk deployment study (60 participants), and show that the participants responded favorably to ElasticPlay.

Prior studies have addressed many negative aspects of mobile distractions in group activities. In this paper, we present Lock n' LoL. This is an application designed to help users focus on their group activities by allowing group members to limit their smartphone usage together. In particular, it provides synchronous social awareness of each other's limiting behavior. This synchronous social awareness can arouse feelings of connectedness among group members and can mitigate social vulnerability due to smartphone distraction (e.g., social exclusion) that often results in poor social experiences. After following an iterative prototyping process, we conducted a large-scale user study (n = 976) via real field deployment. The study results revealed how the participants used Lock n' LoL in their diverse contexts and how Lock n' LoL helped them to mitigate smartphone distractions.

Toothbrushing plays an important role in daily dental plaque removal for preventive dentistry. Prior work has investigated improvements on toothbrushing with sensing technologies. But existing toothbrushing support focuses mostly on estimating brushing coverage. Users thus only have indirect information about how well their toothbrushing removes dental plaque. We present LumiO, a toothbrush that offers users continuous feedback on the amount of plaque on teeth. Lumio uses a well-known method for plaque detection, called Quantitative Light-induced Fluorescence (QLF). QLF exploits a red fluorescence property that bacterium in the plaque demonstrates when a blue-violet ray is cast. Blue-violet light excites this fluorescence property, and a camera with an optical filter can capture plaque in pink. We incorporate this technology into an electric toothbrush to achieve improvements in performance on plaque removal in daily dental care. This paper first discusses related work in sensing for oral activities and interaction as well as dental care with technologies. We then describe the principles of QLF, the hardware design of LumiO, and our vision-based plaque detection method. Our evaluations show that the vision-based plaque detection method with three machine learning techniques can achieve F-measures of 0.68 -- 0.92 under user-dependent training. Qualitative evidence also suggests that study participants were able to have improved awareness of plaque and build confidence on their toothbrushing.

Good alignment and repetition of objects across presentation slides can facilitate visual processing and contribute to audience understanding. However, creating and maintaining such consistency during slide design is difficult. To solve this problem, we present two complementary tools: (1) StyleSnap, which increases the alignment and repetition of objects by adaptively clustering object edge positions and allowing parallel editing of all objects snapped to the same spatial extent; and (2) FlashFormat, which infers the least-general generalization of editing examples and applies it throughout the selected range. In user studies of repetitive styling task performance, StyleSnap and FlashFormat were 4-5 times and 2-3 times faster respectively than conventional editing. Both use a mixed-initiative approach to improve the consistency of slide decks and generalize to any situations involving direct editing across disjoint visual spaces.

Our preliminary study reveals that individuals use various management strategies for limiting smartphone use, ranging from keeping smartphones out of reach to removing apps. However, we also found that users often had difficulties in maintaining their chosen management strategies due to lack of self-regulation. In this paper, we present NUGU, a group-based intervention app for improving self-regulation of limiting smartphone use through leveraging social support: groups of people limit their use together by sharing their limiting information. NUGU is designed based on social cognitive theory, and it has been developed iteratively through two pilot tests. Our three-week user study (n = 62) demonstrated that compared with its non-social counterpart, the NUGU users' usage amount significantly decreased and their perceived level of managing disturbances improved. Furthermore, our exit interview confirmed that NUGU's design elements are effective for achieving limiting goals.

Hand-drawn animation is a major art form and communication medium, but can be challenging to produce. We present a system to help people create frame-by-frame animations through manual sketches. We design our interface to be minimalistic: it contains only a canvas and a few controls. When users draw on the canvas, our system silently analyzes all past sketches and predicts what might be drawn in the future across spatial locations and temporal frames. The interface also offers suggestions to beautify existing drawings. Our system can reduce manual workload and improve output quality without compromising natural drawing flow and control: users can accept, ignore, or modify such predictions visualized on the canvas by simple gestures. Our key idea is to extend the local similarity method in [Xing et al. 2014], which handles only low-level spatial repetitions such as hatches within a single frame, to a global similarity that can capture high-level structures across multiple frames such as dynamic objects. We evaluate our system through a preliminary user study and confirm that it can enhance both users' objective performance and subjective satisfaction.

The negative aspects of smartphone overuse on young adults, such as sleep deprivation and attention deficits, are being increasingly recognized recently. This emerging issue motivated us to analyze the usage patterns related to smartphone overuse. We investigate smartphone usage for 95 college students using surveys, logged data, and interviews. We first divide the participants into risk and non-risk groups based on self-reported rating scale for smartphone overuse. We then analyze the usage data to identify between-group usage differences, which ranged from the overall usage patterns to app-specific usage patterns. Compared with the non-risk group, our results show that the risk group has longer usage time per day and different diurnal usage patterns. Also, the risk group users are more susceptible to push notifications, and tend to consume more online content. We characterize the overall relationship between usage features and smartphone overuse using analytic modeling and provide detailed illustrations of problematic usage behaviors based on interview data.

Once upon a time, people told stories unencumbered by slides. What modern presentations gain through visual slide support, however, is often at the expense of storytelling. We present TurningPoint, a probe to investigate the potential use of narrative-driven talk planning in slideware. Our study of TurningPoint reveals a delicate balance between narrative templates focusing author attention in ways that save time, and fixating attention in ways that limit experimentation.

Rehearsal is a critical component of preparing to give an oral presentation, yet it is frequently abbreviated, performed in ways that are inefficient or ineffective, or simply omitted. We conducted an exploratory study to understand the relationship between the theory and practice of presentation rehearsal, classifying our qualitative results into five themes to motivate more structured rehearsal support deeply integrated in slide presentation software. In a within-subject study (N=12) comparing against participants' existing rehearsal practices, we found that our resulting PitchPerfect system significantly improved overall presentation quality and content coverage as well as provided greater support for content mastery, time management, and confidence building.

Review comments posted in online websites can help the user decide a product to purchase or place to visit. They can also be useful to closely compare a couple of candidate entities. However, the user may have to read different webpages back and forth for comparison, and this is not desirable particularly when she is using a mobile device. We present ReviewCollage, a mobile interface that aggregates information about two reviewed entities in a one-page view. ReviewCollage uses attribute-value pairs, known to be effective for review text summarization, and highlights the similarities and differences between the entities. Our user study confirms that ReviewCollage can support the user to compare two entities and make a decision within a couple of minutes, at least as quickly as existing summarization interfaces. It also reveals that ReviewCollage could be most useful when two entities are very similar.

Managing time while presenting is challenging, but mobile devices offer both convenience and flexibility in their ability to support the end-to-end process of setting, refining, and following presentation time targets. From an initial HCI-Q study of 20 presenters, we identified the need to set such targets per 'zone' of consecutive slides (rather than per slide or for the whole talk), as well as the need for feedback that accommodates two distinct attitudes to time management. These findings led to the design of TalkZones, a mobile application for timing support. When giving a 20-slide, 6m40s rehearsed but interrupted talk, 12 participants who used TalkZones registered a mean overrun of only 8s, compared with 1m49s for 12 participants who used a regular timer. We observed a similar 2% overrun in our final study of 8 speakers giving rehearsed 30-minute talks in 20 minutes. Overall, we show that TalkZones can encourage presenters to advance slides before it is too late to recover, even under the adverse timing conditions of short and shortened talks.

With a general trend worldwide towards greater life expectancies, interventions and tools that can help caregivers working in elder care are becoming increasingly important. In China, with a greater number and proportion of elders due to the long-term effects of the one-child policy, these interventions and tools are needed even more. Improved communication between care staff of an institutional home can reduce medical errors and improve coordination of care. At the same time, increased conversation with elders with cognitive impairments like dementia or Alzheimer's can help the elder to maintain their cognitive ability, and can reduce negative feelings like loneliness. Our qualitative study with eleven institutional caregivers in Beijing delved into the communication patterns that exist between caregivers and elders with dementia. We found that knowing more about each individual resident's disposition and personal history was helpful in maintaining quality care, that many care staff in China use placating talk as a means to calm or guide elders to a desired action, and that care staff found the topic of past careers or past 'glories ' to be the most efficient in getting elders to chat. In addition, we also found that much of the information that is gleaned through working with an elder long-term is not recorded or shared in any official capacity with other care workers, an area where technology could be particularly helpful.

Presentations are a crucial form of modern communication, yet there is a dissonance between everyday practices with presentation tools and best practices from the presentation literature. We conducted a grounded theory study to gain a better understanding of the activity of presenting, discovering the potential for a more dynamic, automated, and story-centered approach to prototyping slide presentations that are themselves dynamic in their ability to help presenters rehearse and deliver their story. Our prototype tool for dynamic presentation prototyping, which we call HyperSlides, uses a simple markup language for the creation of hierarchically structured scenes, which are algorithmically transformed into hyperlinked slides of a consistent and minimalist style. Our evaluation suggests that HyperSlides helps idea organization, saves authoring time, creates aesthetic layouts, and supports more flexible rehearsal and delivery than linear slides, at the expense of reduced layout control and increased navigation demands.

Presentation authoring is an important activity, but often requires the secondary task of collecting the information and media necessary for both slides and speech. Integration of implicit search and peripheral displays into presentation authoring tools may reduce the effort to satisfy not just active needs the author is aware of, but also latent needs that she is not aware of until she encounters content of perceived value. We develop SidePoint, a peripheral panel that supports presentation authoring by showing concise knowledge items relevant to the slide content. We study SidePoint as a technology probe to examine the benefits and issues associated with peripheral knowledge panels for presentation authoring. Our results show that peripheral knowledge panels have the potential to satisfy both types of needs in ways that transform presentation authoring for the better.

Learning an environment can be challenging for people with visual impairments. Braille maps allow their users to understand the spatial relationship between a set of places. However, physical Braille maps are often costly, may not always cover an area of interest with sufficient detail, and might not present up-to-date information. We built a handheld system for representing geographical information called SpaceSense, which includes custom spatial tactile feedback hardware-multiple vibration motors attached to different locations on a mobile touch-screen device. It offers high-level information about the distance and direction towards a destination and bookmarked places through vibrotactile feedback to help the user maintain the spatial relationships between these points. SpaceSense also adapts a summarization technique for online user reviews of public and commercial venues. Our user study shows that participants could build and maintain the spatial relationships between places on a map more accurately with SpaceSense compared to a system without spatial tactile feedback. They pointed specifically to having spatial tactile feedback as the contributing factor in successfully building and maintaining their mental map.

Mobile and handheld devices have become platforms to support remote collaboration. But, their small form-factor may impact the effectiveness of the visual feedback channel often used to help users maintain an awareness of their partner's activities during synchronous collaborative tasks. We investigated how visual and tactile feedback affects collaboration on mobile devices, with emphasis on spatial coordination in a shared workspace. From two user studies, our results highlight different benefits of each feedback channel in collaborative handheld systems. Visual feedback can provide precise spatial information for collaborators, but degrades collaboration when the feedback is occluded, and sometimes can distract the user's attention. Spatial tactile feedback can reduce the overload of information in visual space and gently guides the user's attention to an area of interest. Our results also show that visual and tactile feedback can complement each other, and systems using both feedback channels can support better spatial coordination than systems using only one form of feedback.

Accurate activity recognition enables the development of a variety of ubiquitous computing applications, such as context-aware systems, lifelogging, and personal health systems. Wearable sensing technologies can be used to gather data for activity recognition without requiring sensors to be installed in the infrastructure. However, the user may need to wear multiple sensors for accurate recognition of a larger number of different activities. We developed a wearable acoustic sensor, called BodyScope, to record the sounds produced in the user's throat area and classify them into user activities, such as eating, drinking, speaking, laughing, and coughing. The F-measure of the Support Vector Machine classification of 12 activities using only our BodyScope sensor was 79.5%. We also conducted a small-scale in-the-wild study, and found that BodyScope was able to identify four activities (eating, drinking, speaking, and laughing) at 71.5% accuracy.

Many people read online reviews written by other users to learn more about a product or venue. However, the overwhelming amount of user-generated reviews and variance in length, detail and quality across the reviews make it difficult to glean useful information. In this paper, we present the iterative design of our system, called Review Spotlight. It provides a brief overview of reviews using adjective-noun word pairs, and allows the user to quickly explore the reviews in greater detail. Through a laboratory user study which required participants to perform decision making tasks, we showed that participants could form detailed impressions about restaurants and decide between two options significantly faster with Review Spotlight than with traditional review webpages.

Many people read online reviews written by other users to learn more about a product or venue. However, the overwhelming amount of user-generated reviews and variance in length, detail and quality across the reviews make it difficult to glean useful information. In this paper, we present a summarization system called Review Spotlight. It provides a brief overview of reviews by using adjective-noun word pairs extracted from the review text. The system also allows the user to click any word pair to read the original sentences from which the word pair was extracted. We present our system implementation as a Google Chrome browser extension, and an evaluation on how two word pair scoring methods (TF and TF-IDF) affect the identification of useful word pairs. 1

Current soft QWERTY keyboards often consume a large portion of the screen space on portable touchscreens. This space consumption can diminish the overall user experi-ence on these devices. In this paper, we present the 1Line keyboard, a soft QWERTY keyboard that is 140 pixels tall (in landscape mode) and 40% of the height of the native iPad QWERTY keyboard. Our keyboard condenses the three rows of keys in the normal QWERTY layout into a single line with eight keys. The sizing of the eight keys is based on users' mental layout of a QWERTY keyboard on an iPad. The system disambiguates the word the user types based on the sequence of keys pressed. The user can use flick gestures to perform backspace and enter, and tap on the bezel below the keyboard to input a space. Through an evaluation, we show that participants are able to quickly learn how to use the 1Line keyboard and type at a rate of over 30 WPM after just five 20-minute typing sessions. Using a keystroke level model, we predict the peak expert text entry rate with the 1Line keyboard to be 66--68 WPM.

We describe techniques for direct pen+touch input. We observe people's manual behaviors with physical paper and notebooks. These serve as the foundation for a prototype Microsoft Surface application, centered on note-taking and scrapbooking of materials. Based on our explorations we advocate a division of labor between pen and touch: the pen writes, touch manipulates, and the combination of pen + touch yields new tools. This articulates how our system interprets unimodal pen, unimodal touch, and multimodal pen+touch inputs, respectively. For example, the user can hold a photo and drag off with the pen to create and place a copy; hold a photo and cross it in a freeform path with the pen to slice it in two; or hold selected photos and tap one with the pen to staple them all together. Touch thus unifies object selection with mode switching of the pen, while the muscular tension of holding touch serves as the "glue" that phrases together all the inputs into a unitary multimodal gesture. This helps the UI designer to avoid encumbrances such as physical buttons, persistent modes, or widgets that detract from the user's focus on the workspace.

Visually demanding interfaces on a mobile phone can diminish the user experience by monopolizing the user's attention when they are focusing on another task and impede accessibility for visually impaired users. Because mobile devices are often located in pockets when users are mobile, explicit foot movements can be defined as eyes-and-hands-free input gestures for interacting with the device. In this work, we study the human capability associated with performing foot-based interactions which involve lifting and rotation of the foot when pivoting on the toe and heel. Building upon these results, we then developed a system to learn and recognize foot gestures using a single commodity mobile phone placed in the user's pocket or in a holster on their hip. Our system uses acceleration data recorded by a built-in accelerometer on the mobile device and a machine learning approach to recognizing gestures. Through a lab study, we demonstrate that our system can classify ten different foot gestures at approximately 86% accuracy.

In co-located software development, diagramming practices, such as sketching ideas out with a pen and paper, support the creative process and allow designers to shape, analyze, and communicate their ideas. This study focuses on the diagramming practices used in the design of Open Source Software (OSS), where the norm is highly distributed group work. In OSS, text-based communication (e.g., mailing lists) dominates, and sketching and drawing diagrams collaboratively remains difficult due to the barriers imposed by distance and technology. Previous studies have examined these practices and barriers in the context of individual projects. To understand how contributors across OSS projects use diagrams in design-related activities, we conducted a survey of 230 contributors from 40 different OSS projects, and interviewed eight participants. Our results show that although contributors understand the advantages of using diagrams for design-related activities, diagrams are infrequently used in OSS. This motivated us to examine how and why diagramming occurs, and the factors that prevent widespread use in OSS. Finally, we propose new ideas for supporting design activities in OSS projects.

Some of the most interesting differences between Open Source Software (OSS) development and commercial co-located software development lie in the communication and collaboration practices of these two groups of developers. One interesting practice is that of diagramming. Though well studied and important in many aspects of co-located software development (including communication and collaboration among developers), its role in OSS development has not been thoroughly studied. In this paper, we report our investigation on how and why Ubuntu contributors use diagrams in their work. Our study shows that diagrams are not actively used in many scenarios where they commonly would in co-located software development efforts. We describe differences in the use and practices of diagramming, their possible reasons, and present design considerations for potential systems aimed at better supporting diagram use in OSS development.

One of the challenges with using mobile touch-screen devices is that they do not provide tactile feedback to the user. Thus, the user is required to look at the screen to interact with these devices. In this paper, we present SemFeel, a tactile feedback system which informs the user about the presence of an object where she touches on the screen and can offer additional semantic information about that item. Through multiple vibration motors that we attached to the backside of a mobile touch-screen device, SemFeel can generate different patterns of vibration, such as ones that flow from right to left or from top to bottom, to help the user interact with a mobile device. Through two user studies, we show that users can distinguish ten different patterns, including linear patterns and a circular pattern, at approximately 90% accuracy, and that SemFeel supports accurate eyes-free interactions.

Many mobile devices have touch-sensitive screens that people interact with using fingers or thumbs. However, such interaction is difficult because targets become occluded, and because fingers and thumbs have low input resolution. Recent research has addressed occlusion through visual techniques. However, the poor resolution of finger and thumb selection still limits selection speed. In this paper, we address the selection speed problem through a new target selection technique called Escape. In Escape, targets are selected by gestures cued by icon position and appearance. A user study shows that for targets six to twelve pixels wide, Escape performs at a similar error rate and at least 30% faster than Shift, an alternative technique, on a similar task. We evaluate Escape's performance in different circumstances, including different icon sizes, icon overlap, use of color, and gesture direction. We also describe an algorithm that assigns icons to targets, thereby improving Escape's performance.

Effective text entry on handheld devices remains a significant problem in the field of mobile computing. On a personal digital assistant (PDA), text entry methods traditionally support input through the motion of a stylus held in the user's dominant hand. In this paper, we present the design of a two-handed software keyboard for a PDA which specifically takes advantage of the thumb in the non-dominant hand. We compare our chorded keyboard design to other stylus-based text entry methods in an evaluation that studies user input in both stationary and mobile settings. Our study shows that users type fastest using the miniqwerty keyboard, and most accurately using our two-handed keyboard. We also discovered a difference in input performance with the mini-qwerty keyboard between stationary and mobile settings. As a user walks, text input speed decreases while error rates and mental workload increases; however, these metrics remain relatively stable in our two-handed technique despite user mobility.