Miracle-dz/UniFAR-FTUs huggingface dataset:
Groupnamics: Designing an Interface for Overviewing and Managing Parallel Group Discussions in an Online Classroom

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.
Eliciting Security & Privacy-Informed Sharing Techniques for Multi-User Augmented Reality

The HCI community has explored new interaction designs for collaborative AR interfaces in terms of usability and feasibility; however, security & privacy (S&P) are often not considered in the design process and left to S&P professionals. To produce interaction proposals with S&P in mind, we extend the user-driven elicitation method with a scenario-based approach that incorporates a threat model involving access control in multi-user AR. We conducted an elicitation study in two conditions, pairing AR/AR experts in one condition and AR/S&P experts in the other, to investigate the impact of each pairing. We contribute a set of expert-elicited interactions for sharing AR content enhanced with access control provisions, analyze the benefits and tradeoffs of pairing AR and S&P experts, and present recommendations for designing future multi-user AR interactions that better balance competing design goals of usability, feasibility, and S&P in collaborative AR.
Metrics for Peer Counseling: Triangulating Success Outcomes for Online Therapy Platforms

Extensive research has been published on the conversational factors of effective volunteer peer counseling on online mental health platforms (OMHPs). However, studies differ in how they define and measure success outcomes, with most prior work examining only a single success metric. In this work, we model the relationship between previously reported linguistic predictors of effective counseling with four outcomes following a peer-to-peer session on a single OMHP: retention in the community, following up on a previous session with a counselor, users’ evaluation of a counselor, and changes in users’ mood. Results show that predictors correlate negatively with community retention but positively with users following up with and giving higher evaluations to individual counselors. We suggest actionable insights for therapy platform design and outcome measurement based on findings that the relationship between predictors and outcomes of successful conversations depends on differences in measurement construct and operationalization.
A complex Ruelle-Perron-Frobenius theorem and two counterexamples

Abstract In this paper a new proof of a theorem of Ruelle about real Perron-Frobenius type operators is given. This theorem is then extended to complex Perron-Frobenius type operators in analogy with Wielandt's theorem for matrices. Finally two questions raised by Ruelle and Bowen concerning analyticity properties of zeta functions for flows are answered.
Sustainability by Design. How to Encourage Users to Choose Energy-Saving Programs and Settings when Washing Laundry

One way to counteract anthropogenic climate change, is to reduce individual energy consumption. An especially energy-intensive everyday practice is doing the laundry. In Germany, laundry accounts for about 5% of domestic electricity consumption. In part, this is because users do not make use of the energy-saving programs offered by modern washing machines. Based on different principles of behavior change, we created four concepts for washing machine interfaces to encourage users to choose energy-saving programs and settings. These concepts were implemented as functional prototypes. An online experiment (N=400) showed that all concepts increased the choice of energy-saving programs compared to a standard machine. Especially effective was to interrupt impulsive actions and suggest alternative choices (concept B) and to restructure the entry of settings (concept E). This demonstrates how small changes in a standard interfaces can significantly increase the probability of energy conservation in a private setting.
Designing Responsible AI: Adaptations of UX Practice to Meet Responsible AI Challenges

Technology companies continue to invest in efforts to incorporate responsibility in their Artificial Intelligence (AI) advancements, while efforts to audit and regulate AI systems expand. This shift towards Responsible AI (RAI) in the tech industry necessitates new practices and adaptations to roles—undertaken by a variety of practitioners in more or less formal positions, many of whom focus on the user-centered aspects of AI. To better understand practices at the intersection of user experience (UX) and RAI, we conducted an interview study with industrial UX practitioners and RAI subject matter experts, both of whom are actively involved in addressing RAI concerns throughout the early design and development of new AI-based prototypes, demos, and products, at a large technology company. Many of the specific practices and their associated challenges have yet to be surfaced in the literature, and distilling them offers a critical view into how practitioners’ roles are adapting to meet present-day RAI challenges. We present and discuss three emerging practices in which RAI is being enacted and reified in UX practitioners’ everyday work. We conclude by arguing that the emerging practices, goals, and types of expertise that surfaced in our study point to an evolution in praxis, with associated challenges that suggest important areas for further research in HCI.
Factors of Haptic Experience across Multiple Haptic Modalities

Haptic Experience (HX) is a proposed set of quality criteria useful to haptics, with prior evidence for a 5-factor model with vibrotactile feedback. We report on an ongoing process of scale development to measure HX, and explore whether these criteria hold when applied to more diverse devices, including vibrotactile, force feedback, surface haptics, and mid-air haptics. From an in-person user study with 430 participants, exploratory factor analysis (EFA), and confirmatory factor analysis (CFA), we extract an 11-item and 4-factor model (Realism, Harmony, Involvement, Expressivity) with only a partial overlap to the previous model. We compare this model to the previous vibrotactile model, finding that the new 4-factor model is more generalized and can guide attributes or applications of new haptic systems. Our findings suggest that HX may vary depending on the modalities used in an application, but these four factors are general constructs that might overlap with modality-specific concepts of HX. These factors can inform designers about the right quality criteria to use when designing or evaluating haptic experiences for multiple modalities.
GlanceWriter: Writing Text by Glancing Over Letters with Gaze

Writing text with eye gaze only is an appealing hands-free text entry method. However, existing gaze-based text entry methods introduce eye fatigue and are slow in typing speed because they often require users to dwell on letters of a word, or mark the starting and ending positions of a gaze path with extra operations for entering a word. In this paper, we propose GlanceWriter, a text entry method that allows users to enter text by glancing over keys one by one without any need to dwell on any keys or specify the starting and ending positions of a gaze path when typing a word. To achieve so, GlanceWriter probabilistically determines the letters to be typed based on the dynamics of gaze movements and gaze locations. Our user studies demonstrate that GlanceWriter significantly improves the text entry performance over EyeSwipe, a dwell-free input method using “reverse crossing” to identify the starting and ending keys. GlanceWriter also outperforms the dwell-free gaze input method of Tobii’s Communicator 5, a commercial eye gaze-based communication system. Overall, GlanceWriter achieves dwell-free and crossing-free text entry by probabilistically decoding gaze paths, offering a promising gaze-based text entry method.
Happje: Stimulating Collaborative Cooking for People with Dementia

People with dementia often experience difficulty performing daily activities, including cooking. Previous studies have focused on creating technological interventions for guiding people with dementia individually through cooking tasks and reducing errors. However, collaborative cooking can often promote social engagement and increase self-esteem. This paper presents the iterative development of an easy-to-use recipe tool Happje with step-by-step instructions designed for and with people with dementia. Throughout the project, 13 iterations of the prototype were built and evaluated in the homes and meeting centres of people with dementia. Happje is designed to meet the cognitive abilities of people with dementia and promote collaboration. Moreover, Happje supports informal caregivers in creating personalised recipes. The present study emphasises the significance of utilising intuitive technology and fostering collaboration in daily living activities to promote autonomy and social engagement for individuals with dementia.
Exploring User Motivations Behind iOS App Tracking Transparency Decisions

Apple’s App Tracking Transparency framework allows users to decide whether they want to allow their activity to be tracked for advertising purposes. In this work we examine the tracking decisions made by 312 participants and their associations with privacy concern and personality factors, and conduct a thematic analysis on participants’ reasons for choosing to accept or reject tracking requests. Despite 51% of participants reporting that they had rejected tracking for privacy reasons, higher privacy concern scores did not correlate with a lower rate of tracking acceptance. Additionally, 43% of participants held incorrect beliefs about what tracking does, including nearly a quarter who mistakenly believed that accepting a tracking request would share their location with the requesting app. We suggest explanations for these misconceptions and provide recommendations that may improve usability of both App Tracking Transparency and future Privacy Enhancing Technologies.
Don’t Just Tell Me, Ask Me: AI Systems that Intelligently Frame Explanations as Questions Improve Human Logical Discernment Accuracy over Causal AI explanations

Critical thinking is an essential human skill. Despite the importance of critical thinking, research reveals that our reasoning ability suffers from personal biases and cognitive resource limitations, leading to potentially dangerous outcomes. This paper presents the novel idea of AI-framed Questioning that turns information relevant to the AI classification into questions to actively engage users’ thinking and scaffold their reasoning process. We conducted a study with 204 participants comparing the effects of AI-framed Questioning on a critical thinking task; discernment of logical validity of socially divisive statements. Our results show that compared to no feedback and even causal AI explanations of an always correct system, AI-framed Questioning significantly increase human discernment of logically flawed statements. Our experiment exemplifies a future style of Human-AI co-reasoning system, where the AI becomes a critical thinking stimulator rather than an information teller.
Blockchain (not) for Everyone: Design Challenges of Blockchain-based Applications

Upon its arrival, the Ethereum blockchain promised to introduce a new paradigm of Internet-based applications that would revolutionize multiple fields, from finance to IoT to the public sector. Until now, scientific efforts have been primarily focused on theoretical discussions about the implications of the technology and on technical proposals to improve and consolidate the underlying infrastructure, neglecting the experience of people using blockchain-based systems. However, for this technology to permeate the mainstream, blockchain technology should be easily accessible to the general public. This paper reports on evaluations conducted with first-time blockchain users of two Internet-mediated communities using prototype applications built on Ethereum. Results unveil that even users familiar with technology experienced severe difficulties using blockchain-based apps. Also, we saw how blockchain metaphors and transaction-mediated interactions challenge established mental models for modern applications, imposing heavy workloads on users. We conclude the paper by discussing design implications resulting from blockchain’s paradigm change.
The Influence of Human Factors on the Intention to Report Phishing Emails

Phishing attacks are a main threat to organizations and individuals. Current widespread defenses based on spam filters and domain blacklisting are unfortunately insufficient. Prior work identifies phishing reporting as a key, largely untapped resource to mitigate phishing threats. Yet, its practice suffers from very low reporting rates and generally too low an uptake from users. Whereas it is known that phishing reporting behavior is affected by a number of ‘human factors’, a comprehensive view of the different theories and their effects on (intent to) report is not yet developed. To address this gap, we evaluate theories and factors analyzed in the extant literature, build a cohesive theoretical view of their effects and constructs, and develop, model, and empirically evaluate (by means of an online questionnaire, n=284) the resulting hypothesis structure. We discuss both theoretical implications of our findings and research directions for practice at a research and organizational level.
Why, when, and from whom: considerations for collecting and reporting race and ethnicity data in HCI

Engaging diverse participants in HCI research is critical for creating safe, inclusive, and equitable technology. However, there is a lack of guidelines on when, why, and how HCI researchers collect study participants’ race and ethnicity. Our paper aims to take the first step toward such guidelines by providing a systematic review and discussion of the status quo of race and ethnicity data collection in HCI. Through an analysis of 2016–2021 CHI proceedings and a survey with 15 authors who published in these proceedings, we found that reporting race and ethnicity of participants is very rare (<3%) and that researchers are far from consensus. Drawing from multidisciplinary literature and our findings, we devise considerations for HCI researchers to decide why, when, and from whom to collect race and ethnicity data. For truly inclusive, equitable technologies, we encourage deliberate decisions rather than default omissions.
Multiuser Privacy and Security Conflicts in the Cloud

Collaborative cloud platforms make it easier and more convenient for multiple users to work together on files (GoogleDocs, Office365) and store and share them (Dropbox, OneDrive). However, this can lead to privacy and security conflicts between the users involved, for instance when a user adds someone to a shared folder or changes its permissions. Such multiuser conflicts (MCs), though known to happen in the literature, have not yet been studied in-depth. In this paper, we report a study with 1,050 participants about MCs they experienced in the cloud. We show what are the MCs that arise when multiple users work together in the cloud and how and why they arise, what is the prevalence and severity of MCs, what are their consequences on users, and how do users work around MCs. We derive recommendations for designing mechanisms to help users avoid, mitigate, and resolve MCs in the cloud.
Boundary Layer Experiment - 1983,

Abstract Interactions between fair-weather cumulus clouds and mixed-layer thermals were the focus of a one-month field experiment in Oklahoma. This experiment, called Boundary Layer Experiment—1983 (BLX83), combined remote sensors, surface observations, balloon platforms, and aircraft measurements to study the kinematics at the top of the daytime convective boundary layer. Emphasis was placed on the study of the entrainment zone, and on the relationship between individual therma1s as identified by lidar and turbulent motions and fluxes as measured by aircraft and sodar.
Point of no Undo: Irreversible Interactions as a Design Strategy

Despite irreversibility being omnipresent in the lifeworld, research on interactions making use of irreversibility in computing systems is still in the early stages. User freedom – provided by the undo functionality – is considered to be a pillar of “usable” computer systems, overcoming irreversibility. Within this paper, we set up a thought experiment, challenging the “undo feature” and instead take advantage of irreversibility in the interaction with physical computing systems (tangibles, robots, etc). First, we present three material speculations, each inherently utilizing irreversibility. Second, we elaborate on the concept of irreversible interactions by contextualizing our work with critical HCI discourses and deducing three design strategies. Finally, we discuss irreversibility as a design element for self-reflection, meaningful acting, and a sustainable relationship with technology. While previously individual aspects of irreversibility have been explored, we contribute a comprehensive discussion of irreversible interactions in HCI presenting artifacts, a conceptualization, design strategies, and application purposes.
Modified convolutional neural network for pattern recognition of malaria cells

A review and analysis of known solutions to the problem of detecting malaria from blood pictures of patients using machine learning algorithms was carried out. After developing a machine learning model to solve the given problem based on convolutional neural networks, the accuracy of the model was tested and compared with the analogs discussed above. Based on the results of the testing, it was established that the model is at the level of the best considered models in terms of classification accuracy, with a classification accuracy of 98.08%.
An Examination of Motivation in Physical Therapy Through the Lens of Self-Determination Theory: Implications for Game Design

While it is widely assumed that games can engage patients in therapy through their inherent ‘motivational pull’, relatively little attention has been paid to what HCI games research can learn from strategies employed by therapists. We address this gap by leveraging Self-Determination Theory (SDT) and its mini-theories Basic Psychological Needs Theory and Organismic Integration Theory as a theoretical lens on physical therapy for children and adolescents. Results from in-depth interviews with twelve therapists show that they carefully adjust sessions to allow patients to experience competence, making more comprehensive adjustments than currently offered by games. Additionally, we highlight how therapists leverage their relationship with patients to support motivation, but struggle to reconcile meaningful experiences of autonomy with therapeutic goals. On this basis, we reflect on implications for researchers and designers who create games for physical therapy, and the potential of SDT to provide a foundation for game design and therapeutic practice.
Unsettling Care Infrastructures: From the Individual to the Structural in a Digital Maternal and Child Health Intervention

Information services for maternal and child health are increasingly being implemented at scale and integrated into public health infrastructures in Global South countries. These services often disseminate tailored health information and provide channels for families to ask questions to health workers. With increasing uptake, these services are intervening into a highly gendered space and shaping care work and information-seeking in new ways. We present a study of a patient education program and associated WhatsApp-based information service deployed across multiple states in India, drawing on observations, interviews, and analysis of chat records. Building on notions of “unsettling care” [63], we examine what it means to deploy such an intervention in inequitable, fragmented health systems. We find that even as the intervention focuses on individual behavior change, it also runs up against structural issues, such as the overburden of health workers, an illegible health system, and gendered power dynamics that extend beyond the realm of the home. We use our findings to unsettle notions of how the intervention provides care, and to reframe how we might think about the design and implementation of health information services to also engage with structural issues.
Spectroscopic characterization of Nd:Y 2 O 3 : application toward a differential absorption lidar system for remote sensing of ozone

Neodymium-doped yttria (Nd:Y2O3) is investigated as a solid-state laser material for frequency-tripled generation of ultraviolet laser wavelengths for use in remote sensing of ozone. Emphasis is placed both on the spectroscopy of the fundamental wavelengths at ∼0.914 µm and ∼0.946 µm to assess their feasibility for laser oscillation and on the absorption spectroscopy in the 0.8-µm wavelength region for determination of suitable pump sources. The temperature dependence of the emission and absorption characteristics of Nd:Y2O3 are examined, since aggressive cooling may be required for efficient ∼0.914-µm lasing due to its quasi four-level nature. Data for flash-lamp-pumped laser performance on the 4F3/2→4I11/2 is presented for Nd:Y2O3 and compared with Nd:YAG. Diode-pumped threshold-fluence and threshold-pump energy estimates for Nd:Y2O3 lasing on the 4F3/2→4I9/2 at 0.914 µm and 0.946 µm are calculated based on the data presented here. The measurements presented here for the Nd:Y2O3 indicate favorable absorption and emission properties. Favorable absorption properties in the ∼0.8-µm pump wavelength are compatible with a variety of potential pump sources. Favorable emission properties at reduced temperatures near 150 K indicate that Nd:Y2O3 operating at 0.914 µm and 0.946 µm will have normal-mode laser thresholds similar to that of room-temperature Nd:YAG operating at 0.946 µm. In Q-switched operation, however, Nd:Y2O3 is predicted to exceed the performance of Nd:YAG due to the lower 1.06/0.94 cross-section ratio, which helps to limit amplified spontaneous-emission effects. Although Nd:Y2O3 is not a new material, it has not been the topic of study due to growth problems associated with its high melting point. New advances in growth techniques and the favorable spectroscopic features of Nd:Y2O3 have inspired a new examination of this material.