huashen218/convxai-cia-dataset huggingface dataset:
Title: The "Comadre" Project: An Asset-Based Design Approach to Connecting Low-Income Latinx Families to Out-of-School Learning Opportunities
Authors: family: Cho
given: Alexander; family: Herrera
given: Roxana G.; family: Chaidez
given: Luis; family: Uriostegui
given: Adilene
Venue: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems
Keywords: sms, hispanic, informal learning, appreciative inquiry, education, human-centered design, women, asset-based

Abstract: Participation in out-of-school learning programs has been shown to generate significant academic, social/emotional, and institutional benefits for young learners, and today's wealthy families are disproportionately reaping these benefits. This paper presents the results of an asset-based/human-centered design research process and pilot aimed at connecting low-income families in a Southern California city with local low-cost out-of-school learning opportunities. Based on background research including qualitative interviewing, home visits, technology inventories and use walkthroughs with 40 low-income, majority Latinx families, we created and piloted a free subscription SMS service that automatically pushes bilingual SMS messages with curated information on local low-cost enrichment learning opportunities to low-income families. We framed our human-centered design process through an intersectional, "asset-based approach," which recognizes that marginalized communities have already developed robust, culturally-specific social practices to enable them to navigate the world, seeks to amplify them, and refrains from imposing a top-down or pre-conceived "idea" of intervention.
Title: Transformation through Provocation?
Authors: family: Roussou
given: Maria; family: Perry
given: Sara; family: Katifori
given: Akrivi; family: Vassos
given: Stavros; family: Tzouganatou
given: Angeliki; family: McKinney
given: Sierra
Venue: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems
Keywords: conversational agents, chatbots, ux design, provocative interaction, emotional engagement, cultural informatics

Abstract: Can a chatbot enable us to change our conceptions, to be critically reflective? To what extent can interaction with a technologically 'minimal' medium such as a chatbot evoke emotional engagement in ways that can challenge us to act on the world? In this paper, we discuss the design of a provocative bot, a 'bot of conviction', aimed at triggering conversations on complex topics (e.g. death, wealth distribution, gender equality, privacy) and, ultimately, soliciting specific actions from the user it converses with. We instantiate our design with a use case in the cultural sector, specifically a Neolithic archaeological site that acts as a stage of conversation on such hard themes. Our larger contributions include an interaction framework for bots of conviction, insights gained from an iterative process of participatory design and evaluation, and a vision for bot interaction mechanisms that can apply to the HCI community more widely.
Title: Understanding Metamaterial Mechanisms
Authors: family: Ion
given: Alexandra; family: Lindlbauer
given: David; family: Herholz
given: Philipp; family: Alexa
given: Marc; family: Baudisch
given: Patrick
Venue: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems
Keywords: fabrication, computational design, microstructure, metamaterials, mechanism

Abstract: In this paper, we establish the underlying foundations of mechanisms that are composed of cell structures---known as metamaterial mechanisms. Such metamaterial mechanisms were previously shown to implement complete mechanisms in the cell structure of a 3D printed material, without the need for assembly. However, their design is highly challenging. A mechanism consists of many cells that are interconnected and impose constraints on each other. This leads to unobvious and non-linear behavior of the mechanism, which impedes user design. In this work, we investigate the underlying topological constraints of such cell structures and their influence on the resulting mechanism. Based on these findings, we contribute a computational design tool that automatically creates a metamaterial mechanism from user-defined motion paths. This tool is only feasible because our novel abstract representation of the global constraints highly reduces the search space of possible cell arrangements.
Title: Measuring and Understanding Photo Sharing Experiences in Social Virtual Reality
Authors: family: Li
given: Jie; family: Kong
given: Yiping; family: Röggla
given: Thomas; family: De Simone
given: Francesca; family: Ananthanarayan
given: Swamy; family: de Ridder
given: Huib; family: El Ali
given: Abdallah; family: Cesar
given: Pablo
Venue: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems
Keywords: immersion, photo sharing, presence, questionnaire, virtual reality, social

Abstract: Millions of photos are shared online daily, but the richness of interaction compared with face-to-face (F2F) sharing is still missing. While this may change with social Virtual Reality (socialVR), we still lack tools to measure such immersive and interactive experiences. In this paper, we investigate photo sharing experiences in immersive environments, focusing on socialVR. Running context mapping (N=10), an expert creative session (N=6), and an online experience clustering questionnaire (N=20), we develop and statistically evaluate a questionnaire to measure photo sharing experiences. We then ran a controlled, within-subject study (N=26 pairs) to compare photo sharing under F2F, Skype, and Facebook Spaces. Using interviews, audio analysis, and our questionnaire, we found that socialVR can closely approximate F2F sharing. We contribute empirical findings on the immersiveness differences between digital communication media, and propose a socialVR questionnaire that can in the future generalize beyond photo sharing.
Title: HoloDoc: Enabling Mixed Reality Workspaces that Harness Physical and Digital Content
Authors: family: Li
given: Zhen; family: Annett
given: Michelle; family: Hinckley
given: Ken; family: Singh
given: Karan; family: Wigdor
given: Daniel
Venue: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems
Keywords: augmented reality, mixed reality, digital pen input, reading behavior

Abstract: Prior research identified that physical paper documents have many positive attributes, for example natural tangibility and inherent physical flexibility. When documents are presented on digital devices, however, they can provide unique functionality to users, such as the ability to search, view dynamic multimedia content, and make use of indexing. This work explores the fusion of physical and digital paper documents. It first presents the results of a study that probed how users perform document-intensive analytical tasks when both physical and digital versions of documents were available. The study findings then informed the design of HoloDoc, a mixed reality system that augments physical artifacts with rich interaction and dynamic virtual content. Finally, we present the interaction techniques that HoloDoc affords, and the results of a second study that assessed HoloDoc's utility when working with digital and physical copies of academic articles.
Title: Considering Parents in Coding Kit Design: Understanding Parents' Perspectives and Roles
Authors: family: Yu
given: Junnan; family: Bai
given: Chenke; family: Roque
given: Ricarose
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: As education researchers, policymakers, and industry leaders recognize the importance of computing, many coding kits (toys and apps) have emerged to help young children learn to code at home. However, how parents perceive and support their children's use of the kits at home are less understood. In this study, we performed semi-structured interviews with eighteen parents who obtained coding kits for their young children for home use. The results show parents expected their kids to have fun and meaningful interactions with the kits. In supporting the play, parents took on various roles, mostly acting as spectator, scaffolder, and teacher. While parents perceived benefits of coding kits like a changed perspective on coding, they also reported concerns, such as their limited programming knowledge to provide help. Finally, we reflect on design and research implications to develop coding kits that consider parents' perspectives and important roles in supporting young children's exploration with computational thinking.
Title: Evaluating 'Prefer not to say' Around Sensitive Disclosures
Authors: family: Warner
given: Mark; family: Kitkowska
given: Agnieszka; family: Gibbs
given: Jo; family: Maestre
given: Juan F.; family: Blandford
given: Ann
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: As people's offline and online lives become increasingly entwined, the sensitivity of personal information disclosed online is increasing. Disclosures often occur through structured disclosure fields (e.g., drop-down lists). Prior research suggests these fields may limit privacy, with non-disclosing users being presumed to be hiding undesirable information. We investigated this around HIV status disclosure in online dating apps used by men who have sex with men. Our online study asked participants (N=183) to rate profiles where HIV status was either disclosed or undisclosed. We tested three designs for displaying undisclosed fields. Visibility of undisclosed fields had a significant effect on the way profiles were rated, and other profile information (e.g., ethnicity) could affect inferences that develop around undisclosed information. Our research highlights complexities around designing for non-disclosure and questions the voluntary nature of these fields. Further work is outlined to ensure disclosure control is appropriately implemented around online sensitive information disclosures.
Title: Understanding the Care Ecologies of Veterans with PTSD
Authors: family: Evans
given: Hayley; family: Lakshmi
given: Udaya; family: Watson
given: Hue; family: Ismail
given: Azra; family: Sherrill
given: Andrew M.; family: Kumar
given: Neha; family: Arriaga
given: Rosa I.
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Post-traumatic stress disorder (PTSD) disproportionately affects United States veterans, yet they may be reluctant to seek or engage in care. We interview 21 participants, including veterans with PTSD, clinicians who treat veterans and friends and family that support veterans through mental health ordeals. We investigate the military identity these veterans share. We explore how this may add to their reluctance in care-seeking behaviors. We also explore the roles of human and non-human intermediaries in ecologies of care and the potential for enhancing patient empowerment in current clinical treatment contexts. We discuss how military culture can be utilized in clinical care, how multiple perspectives can be leveraged to create a more holistic view of the patient, and finally, how veterans can be empowered during treatment. We conclude with recommendations for the design of sociotechnical systems that prioritize the above in support of the mental well-being of veterans with PTSD.
Title: HapBead: On-Skin Microfluidic Haptic Interface using Tunable Bead
Authors: family: Han
given: Teng; family: Bansal
given: Shubhi; family: Shi
given: Xiaochen; family: Chen
given: Yanjun; family: Quan
given: Baogang; family: Tian
given: Feng; family: Wang
given: Hongan; family: Subramanian
given: Sriram
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: On-skin haptic interfaces using soft elastomers which are thin and flexible have significantly improved in recent years. Many are focused on vibrotactile feedback that requires complicated parameter tuning. Another approach is based on mechanical forces created via piezoelectric devices and other methods for non-vibratory haptic sensations like stretching, twisting. These are often bulky with electronic components and associated drivers are complicated with limited control of timing and precision. This paper proposes HapBead, a new on-skin haptic interface that is capable of rendering vibration like tactile feedback using microfluidics. HapBead leverages a microfluidic channel to precisely and agilely oscillate a small bead via liquid flow, which then generates various motion patterns in channel that creates highly tunable haptic sensations on skin. We developed a proof-of-concept design to implement thin, flexible and easily affordable HapBead platform, and verified its haptic rendering capabilities via attaching it to users' fingertips. A study was carried out and confirmed that participants could accurately tell six different haptic patterns rendered by HapBead. HapBead enables new wearable display applications with multiple integrated functionalities such as on-skin haptic doodles, visuo-haptic displays and haptic illusions.
Title: Developing a Personality Model for Speech-based Conversational Agents Using the Psycholexical Approach
Authors: family: Völkel
given: Sarah Theres; family: Schödel
given: Ramona; family: Buschek
given: Daniel; family: Stachl
given: Clemens; family: Winterhalter
given: Verena; family: Bühner
given: Markus; family: Hussmann
given: Heinrich
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: We present the first systematic analysis of personality dimensions developed specifically to describe the personality of speech-based conversational agents. Following the psycholexical approach from psychology, we first report on a new multi-method approach to collect potentially descriptive adjectives from 1) a free description task in an online survey (228 unique descriptors), 2) an interaction task in the lab (176 unique descriptors), and 3) a text analysis of 30,000 online reviews of conversational agents (Alexa, Google Assistant, Cortana) (383 unique descriptors). We aggregate the results into a set of 349 adjectives, which are then rated by 744 people in an online survey. A factor analysis reveals that the commonly used Big Five model for human personality does not adequately describe agent personality. As an initial step to developing a personality model, we propose alternative dimensions and discuss implications for the design of agent personalities, personality-aware personalisation, and future research.
Title: MicroMentor: Peer-to-Peer Software Help Sessions in Three Minutes or Less
Authors: family: Joshi
given: Nikhita; family: Matejka
given: Justin; family: Anderson
given: Fraser; family: Grossman
given: Tovi; family: Fitzmaurice
given: George
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: While synchronous one-on-one help for software learning is rich and valuable, it can be difficult to find and connect with someone who can provide assistance. Through a formative user study, we explore the idea of fixed-duration, one-on-one help sessions and find that 3 minutes is often enough time for novice users to explain their problem and receive meaningful help from an expert. To facilitate this type of interaction, we developed MicroMentor, an on-demand help system that connects users via video chat for 3-minute help sessions. MicroMentor automatically attaches relevant supplementary materials and uses contextual information, such as command history and expertise, to encourage the most qualified users to accept incoming requests. These help sessions are recorded and archived, building a bank of knowledge that can further help a broader audience. Through a user study, we find MicroMentor to be useful and successful in connecting users for short teaching moments.
Title: Understanding Users' Perception Towards Automated Personality Detection with Group-specific Behavioral Data
Authors: family: Kim
given: Seoyoung; family: Thakur
given: Arti; family: Kim
given: Juho
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Thanks to advanced sensing and logging technology, automatic personality assessment (APA) with users' behavioral data in the workplace is on the rise. While previous work has focused on building APA systems with high accuracy, little research has attempted to understand users' perception towards APA systems. To fill this gap, we take a mixed-methods approach: we (1) designed a survey (n=89) to understand users'social workplace behavior both online and offline and their privacy concerns; (2) built a research probe that detects personality from online and offline data streams with up to 81.3% accuracy, and deployed it for three weeks in Korea (n=32); and (3) conducted post-interviews (n=9). We identify privacy issues in sharing data and system-induced change in natural behavior as important design factors for APA systems. Our findings suggest that designers should consider the complex relationship between users' perception and system accuracy for a more user-centered APA design.
Title: Robots for Inclusive Play: Co-designing an Educational Game With Visually Impaired and sighted Children
Authors: family: Metatla
given: Oussama; family: Bardot
given: Sandra; family: Cullen
given: Clare; family: Serrano
given: Marcos; family: Jouffrais
given: Christophe
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Despite being included in mainstream schools, visually impaired children still face barriers to social engagement and participation. Games could potentially help, but games that cater for both visually impaired and sighted players are scarce. We used a co-design approach to design and evaluate a robot-based educational game that could be inclusive of both visually impaired and sighted children in the context of mainstream education. We ran a focus group discussion with visual impairment educators to understand barriers to inclusive play. And then a series of co-design workshops to engage visually impaired and sighted children and educators in learning about robot technology and exploring its potential to support inclusive play experiences. We present design guidelines and an evaluation workshop of a game prototype, demonstrating group dynamics conducive to collaborative learning experiences, including shared goal setting/execution, closely coupled division of labour, and interaction symmetry.
Title: Expert Discussions Improve Comprehension of Difficult Cases in Medical Image Assessment
Authors: family: Schaekermann
given: Mike; family: Cai
given: Carrie J.; family: Huang
given: Abigail E.; family: Sayres
given: Rory
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Medical data labeling workflows critically depend on accurate assessments from human experts. Yet human assessments can vary markedly, even among medical experts. Prior research has demonstrated benefits of labeler training on performance. Here we utilized two types of labeler training feedback: highlighting incorrect labels for difficult cases ("individual performance" feedback), and expert discussions from adjudication of these cases. We presented ten generalist eye care professionals with either individual performance alone, or individual performance and expert discussions from specialists. Compared to performance feedback alone, seeing expert discussions significantly improved generalists' understanding of the rationale behind the correct diagnosis while motivating changes in their own labeling approach; and also significantly improved average accuracy on one of four pathologies in a held-out test set. This work suggests that image adjudication may provide benefits beyond developing trusted consensus labels, and that exposure to specialist discussions can be an effective training intervention for medical diagnosis.
Title: An Honest Conversation: Transparently Combining Machine and Human Speech Assistance in Public Spaces
Authors: family: Reitmaier
given: Thomas; family: Robinson
given: Simon; family: Pearson
given: Jennifer; family: Kalarikalayil Raju
given: Dani; family: Jones
given: Matt
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: There is widespread concern over the ways speech assistant providers currently use humans to listen to users' queries without their knowledge. We report two iterations of the TalkBack smart speaker, which transparently combines machine and human assistance. In the first, we created a prototype to investigate whether people would choose to forward their questions to a human answerer if the machine was unable to help. Longitudinal deployment revealed that most users would do so when given the explicit choice. In the second iteration we extended the prototype to draw upon spoken answers from previous deployments, combining machine efficiency with human richness. Deployment of this second iteration shows that this corpus can help provide relevant, human-created instant responses. We distil lessons learned for those developing conversational agents or other AI-infused systems about how to appropriately enlist human-in-the-loop information services to benefit users, task workers and system performance.
Title: MRAT: The Mixed Reality Analytics Toolkit
Authors: family: Nebeling
given: Michael; family: Speicher
given: Maximilian; family: Wang
given: Xizi; family: Rajaram
given: Shwetha; family: Hall
given: Brian D.; family: Xie
given: Zijian; family: Raistrick
given: Alexander R. E.; family: Aebersold
given: Michelle; family: Happ
given: Edward G.; family: Wang
given: Jiayin; family: Sun
given: Yanan; family: Zhang
given: Lotus; family: Ramsier
given: Leah E.; family: Kulkarni
given: Rhea
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Significant tool support exists for the development of mixed reality (MR) applications; however, there is a lack of tools for analyzing MR experiences. We elicit requirements for future tools through interviews with 8 university research, instructional, and media teams using AR/VR in a variety of domains. While we find a common need for capturing how users perform tasks in MR, the primary differences were in terms of heuristics and metrics relevant to each project. Particularly in the early project stages, teams were uncertain about what data should, and even could, be collected with MR technologies. We designed the Mixed Reality Analytics Toolkit (MRAT) to instrument MR apps via visual editors without programming and enable rapid data collection and filtering for visualizations of MR user sessions. With MRAT, we contribute flexible interaction tracking and task definition concepts, an extensible set of heuristic techniques and metrics to measure task success, and visual inspection tools with in-situ visualizations in MR. Focusing on a multi-user, cross-device MR crisis simulation and triage training app as a case study, we then show the benefits of using MRAT, not only for user testing of MR apps, but also performance tuning throughout the design process.