ACM Transactions on Computer-Human Interaction最新文献

The proliferation of new technologies has led to a proliferation of unwanted electronic devices. E-waste is the largest-growing consumer waste-stream worldwide, but also an issue often ignored. In fact, HCI primarily focuses on designing and understanding device interactions during one segment of their lifecycles—while users use them. Researchers overlook a significant space—when devices are no longer “useful” to the user such as after breakdown or obsolescence. We argue that HCI can learn from experts who upcycle e-waste and give it second lives in electronics projects, art projects, educational workshops, and more. To acquire and translate this knowledge to HCI, we interviewed experts who unmake e-waste. We explore their practices through the lens of unmaking both when devices are physically unmade and when the perception of e-waste is unmade once waste becomes, once again, useful. Last, we synthesize findings into takeaways for how HCI can engage with the issue of e-waste.

Household energy use data may contain sensitive inferences into family life, yet its potential for surveillance is imperfectly understood. To explore this space, we developed Household Wattch, a speculative eco-feedback ‘provotype’ that profiles households according to their energy use data. Evaluated by 16 participants from Australian households engaged in an 18-month energy use monitoring trial, Household Wattch elicited perceptions and expectations about the near future of energy use data, as a useful yet potentially sensitive commodity when analysed. We highlight challenges and opportunities for energy use data across three scales: (1) Within the household, (2) Beyond the household- (e.g. sharing energy data with third parties) and (3) Post-household (e.g. what happens to energy data when a household re-configures or disbands). Findings suggest users may require support in understanding the sensitivities of their energy use data, particularly when deciding whether to share it with third parties. Opportunities exist for accidental or deliberate surveillance via energy use data and these need to be identified and managed. Provotypes represent a useful tool for navigating this space, and we provide considerations for how they can support users in speculating over possible energy futures.

Self-determination theory (SDT), a psychological theory of human motivation, is a prominent paradigm in human-computer interaction (HCI) research on games. However, our prior literature review observed a trend towards shallow applications of the theory. This follow-up work takes a broader view – examining SDT scholarship on games, a wider corpus of SDT-based HCI games research (N=259), and perspectives from a games industry practitioner conference – to help explain current applications of SDT. Our findings suggest that perfunctory applications of the theory in HCI games research originate in part from within SDT scholarship on games, which itself exhibits limited engagement with theoretical tenets. Against this backdrop, we unpack the popularity of SDT in HCI games research and identify conditions underlying the theory's current use as an oft-unquestioned paradigm. Finally, we outline avenues for more productive SDT-informed games research and consider ways towards more intentional practices of theory use in HCI.

Individuals are known to differ in cognitive abilities, affecting their behavior and information processing in digital environments. However, we have a limited understanding of which behaviors are affected, how, and whether some features extracted from digital behavior can predict cognitive abilities. Consequently, researchers may miss opportunities to design and support individuals with personalized experiences and detect those who may benefit from additional interventions. To characterize digital behaviors, we collected 24/7 screen recordings, input behavior, and operating system data from the laptops of 20 adults for two weeks. We use cognitive test results from the same individuals to characterize their cognitive abilities: psychomotor speed, processing speed, selective attention, working memory, and fluid intelligence. Our results from regression analysis, path modeling, and machine learning experiments show that cognitive abilities are associated with differences in digital behavior and that naturalistic behavioral data can predict the cognitive abilities of individuals with small error rates. Our findings suggest naturalistic interaction data as a novel source for modeling cognitive differences.

Pointing-based interaction interferences are situations wherein GUI elements appear, disappear, or change shortly before being selected, and too late for the user to inhibit their movement. Their cause lays in the design of most GUIs, for which any user event on an interactive element unquestionably reflects the user’s intention—even one millisecond after that element has changed. Previous work indicate that interferences can cause frustration and sometimes severe consequences. This paper investigates new default behaviors for GUI elements that aim to prevent the occurrences of interferences or to mitigate their consequences. We present a design space of the advantages and technical requirements of these behaviors, and demonstrate in a controlled study how simple rules can reduce the occurrences of so-called “Pop-up-style” interferences, and user frustration. We then discuss their application to various forms of interaction interferences. We conclude by addressing the feasibility and trade-offs of implementing these behaviors in existing systems.

This paper considers how subjectivities are enlivened in algorithmic systems. We first review related literature to clarify how we see “subjectivities” as emerging through a tangled web of processes and actors. We then offer two case studies exemplifying the emergence of algorithmic subjectivities: one involving computational topic modeling of blogs written by parents with children on the autism spectrum, and one involving algorithmic moderation of social media content. Drawing on these case studies, we then articulate a series of qualities that characterizes algorithmic subjectivities. We also compare and contrast these qualities with a number of related concepts from prior literature to articulate how algorithmic subjectivities constitutes a novel theoretical contribution, as well as how it offers a focal lens for future empirical investigation and for design. In short, this paper points out how certain worlds are being made and/or being made possible via algorithmic systems, and it asks HCI to consider what other worlds might be possible.

Self-tracking technology can help users develop new knowledge about themselves, supporting their health and general wellbeing. Most of these devices inform users about their lives by autonomously generating data about highly constrained topics. Recent research has started to explore more flexible, manual self-tracking systems, which allow users to express themselves through their data and learn by engaging with their experiences in-the-moment. This paper describes a field trial using the Chromatize app, designed to explore the value of minimalism and flexibility – including in data histories – in personal tracking systems. Our data indicates that low-burden experience logging systems which focus on the creation of symbolically-rich, self-defined data can support self-awareness, reflection and regulation at opportune moments. The analysis also contributes a formulation of reflection in the context of self-tracking technologies that is more meaningful than the loose use of ‘reflection’ used in much of the literature.

Achieving temporal synchrony between sensory modalities is crucial for natural perception of object interaction in virtual reality. While subjective questionnaires are currently used to evaluate users’ VR experiences, leveraging behavior and psychophysiological responses can provide additional insights.

We investigated motion and ocular behavior as discriminators between realistic and unrealistic object interactions. Participants grasped and placed a virtual object while experiencing sensory feedback that either matched their expectations or occurred too early. We also explored visual-only feedback vs. combined visual and haptic feedback. Due to technological limitations, a condition with delayed feedback was added post-hoc.

Gaze-based metrics revealed discrimination between high and low feedback realism. Increased interaction uncertainty was associated with longer fixations on the avatar hand and temporal shifts in the gaze-action relationship. Our findings enable real-time evaluation of users’ perception of realism in interactions. They facilitate the optimization of interaction realism in virtual environments and beyond.

When people need help from their supervisors or peers, they often have to manage up to get things done. However, unlike managing subordinates (managing down), managing people of equal or higher status (managing up) are not obligated to help. These requests often involve collaborative tasks between requesters and performers. Through interviews, we found that these collaborative tasks require coordination work that is not materialized in existing management tools. We also found that requesters are willing to take on this coordination work to see their requests fulfilled. To address this issue, we propose a system called TaskLight, which allows requesters to handle coordination work themselves. For example, requesters can collect useful context and information for their performers. We conducted two deployment studies and found that TaskLight leads to better outcomes because requesters are able to assist performers more effectively. Our findings demonstrate a new way to reduce the social burdens of managing up and improve collaboration.

Wearables integrating movement sonification can support body-perception changes and relatedly physical activity; yet, we lack design principles for such sonifications. Through two mixed-methods studies, we investigate sound pitch and movement direction interaction effects on self-perception during squats exercises. We measured effects on body-perception, affective quality of the experience, actual and perceived movement, and compared them to two control conditions: no-sound and vibrotactile feedback. Results show that regardless of movement direction, ascending pitch enhances several body feelings and overall experience quality, while descending pitch increases movement acceleration. These effects were moderated by exercise physical demand. Sound and vibrotactile feedback enhanced flexibility and strength feelings respectively and contributed to exercise completion in different ways. Sound was perceived as an internal-to-body force while vibrotactile feedback as an external-to-body force. Feedback effects were stronger in people with lower fitness levels. We discuss results in terms of malleability of body-perceptions and highlight opportunities to support demanding physical activity through wearable devices.