The interdisciplinary field of Human-Computer Interaction (HCI) thrives on productive engagement with different domains, yet this engagement often breaks due to idiosyncratic writing styles and unfamiliar concepts. Inspired by the dialogic model of abstract metaphors, as well as the potential of Large Language Models (LLMs) to produce on-demand support, we investigate the use of metaphors to facilitate engagement between Science and Technology Studies (STS) and System HCI. Our reflective-style survey with early-career HCI researchers (N=48) reported that limited prior exposure to STS research can hinder perceived openness of the work, and ultimately interest in reading. The survey also revealed that metaphors enhance likelihood to continue reading STS papers, and alternative perspectives can build critical thinking skills to mitigate potential risks of LLM-generated metaphors. We lastly offer a specified model of metaphor exchange (within this generative context) that incorporates alternative perspectives to construct shared understanding in interdisciplinary engagement.

Improving accuracy, time spent, and ubiquity of delineation has been a long-standing design aim, yet many HCI works have overlooked high-stakes and complex healthcare annotation. We explore contouring, a critical workflow aimed at identifying and segmenting tumors, usually performed on immobile desktop computers in clinics, in which limited support for mobile access leads to prolonged and subpar treatment planning. Following interviews and think-aloud studies (N = 10 physicians), we report key contouring behaviors, and later design a novel cross-device prototype that enables contouring on everyday touch devices. We compared contouring via desktop and touch in a lab study (N = 8 residents) and found that mobile phones not only yielded similar accuracy, but also took significantly less time. Our results point to three broad design guidelines for cross-device solutions deployed within standalone healthcare workflows, and highlight how incorporating different device and input modalities can improve treatment delivery in today’s distributed healthcare environments.

Apprenticeship is the predominant method for transferring specialized medical skills, yet the inter-dynamics between faculty and residents, including methods of feedback exchange are under-explored. We specifically investigate contouring: outlining tumors in preparation for radiotherapy, a critical skill that when performed subpar, severely degrades patient survival. Interviews and design-thinking workshops (N = four faculty; six residents) revealed misalignment between teaching methods and residents who desired timely, relevant, and diverse feedback. We further discuss reasons: overlapping learning content and strategies to ease tensions between clinical and teaching duties, and lack of support for exchange of cognitive processes. The follow-up survey study (N = 67 practitioners from 31 countries), which contained annotation and sketching tasks, provided diverse perspective over effective feedback elements. We lastly present sociotechnical implications in supporting faculty’s teaching duties and learners’ cognitive models, such as systematically leveraging senior learners in providing case-based guidance and supporting double-sided flow of cognitive information via in-situ video snippets.

The surge in remote and hybrid work has provided many benefits in terms of flexibility and autonomy, but it also presents challenges when it comes to team collaboration and meetings. Using a mixed-methods field study, we compare hybrid and remote meeting configurations to better understand how to improve the inclusiveness and effectiveness of these different meeting modalities. Our findings indicate that overall, fully-remote meetings are the most inclusive and effective. Fully-remote meetings are perceived as more inclusive of remote attendees despite their lower chat usage compared to hybrid meetings. We also find that people's preferred format varies depending on the purpose or type of meeting and the skill set of the meeting moderator. We provide recommendations for improving meeting inclusion and effectiveness in both hybrid and remote meetings, such as training moderators and integrating chats with the main meeting.

Decision-making involves biases from past experiences, which are difficult to perceive and eliminate. We investigate a specific type of anchoring bias, in which decision-makers are anchored by their own recent decisions, e.g. a college admission officer sequentially reviewing students. We propose an algorithm that identifies existing anchored decisions, reduces sequential dependencies to previous decisions, and mitigates decision inaccuracies post-hoc with 2% increased agreement to ground-truth on a large-scale college admission decision data set. A crowd-sourced study validates this algorithm on product preferences (5% increased agreement). To avoid biased decisions ex-ante, we propose a procedure that presents instances in an order that reduces anchoring bias in real-time. Tested in another crowd-sourced study, it reduces bias and increases agreement to ground-truth by 7%. Our work reinforces individuals with similar characteristics to be treated similarly, independent of when they were reviewed in the decision-making process.

Contouring is an indispensable step in Radiotherapy (RT) treatment planning. However, today’s contouring software is constrained to only work with a 2D display, which is less intuitive and requires high task loads. Virtual Reality (VR) has shown great potential in various specialties of healthcare and health sciences education due to the unique advantages of intuitive and natural interactions in immersive spaces. VR-based radiation oncology integration has also been advocated as a target healthcare application, allowing providers to directly interact with 3D medical structures. We present VRContour and investigate how to effectively bring contouring for radiation oncology into VR. Through an autobiographical iterative design, we defined three design spaces focused on contouring in VR with the support of a tracked tablet and VR stylus, and investigating dimensionality for information consumption and input (either 2D or 2D + 3D). Through a within-subject study (n = 8), we found that visualizations of 3D medical structures significantly increase precision, and reduce mental load, frustration, as well as overall contouring effort. Participants also agreed with the benefits of using such metaphors for learning purposes.

Accurately drawing non-planar 3D curves in immersive Virtual Reality (VR) is indispensable for many precise 3D tasks. However, due to lack of physical support, limited depth perception, and the non-planar nature of 3D curves, it is challenging to adjust mid-air strokes to achieve high precision. Instead of creating new interaction techniques, we investigated how task geometric shapes and input modalities affect precision-first drawing performance in a within-subject study (n=12) focusing on 3D target tracing in commercially available VR headsets. We found that compared to using bare hands, VR controllers and pens yield nearly 30% of precision gain, and that the tasks with large curvature, forward-backward or left-right orientations perform best. We finally discuss opportunities for designing novel interaction techniques for precise 3D drawing. We believe that our work will benefit future research aiming to create usable toolboxes for precise 3D drawing.

This paper investigates in-class interactions in synchronous online classrooms when the choice of modality is discretionary, such that students choose when and if they turn on their cameras and microphones. Instructor interviews (N = 7) revealed that most students preferred not to share videos and verbally participate. This hindered instructors’ ability to read their classrooms and make deeper connections with students. Survey results (N = 102) suggested that students felt a lacking sense of community in online vs. in-person lectures. Some students felt uncomfortable broadcasting their appearances to everyone in the class, and some were unaware of the benefits for instructors. Most students favored using the text chat to participate. Considering the needs of both instructors and students, we propose recommendations to mitigate the loss of classroom interactions by collecting and presenting less invasive social cues in an aggregated format, and incorporating opportunities for informal exchanges and individual control to spark peer bonding.

Discussion fora of instructional videos contain previously-discussed questions and answers. These video comments can resolve many points of confusion for learners. However, finding relevant content in a separated discussion forum is challenging and disruptive to learning flow. This paper introduces Adjacent Display of Relevant Discussion (ADRD): it displays threaded comments in a panel adjacent to the video and dynamically updates the content of the panel based on the time of the video. In a between-subjects lab study (n=20), ADRD helped participants resolve confusion points, skim and read comments, and encouraged video interaction.

Team dating, or small-group interactions, can expose people to diverse perspectives and inform the potential for longer-term collaboration. However, rapidly configuring groups and facilitating interactions among strangers can be difficult, especially in co-located settings. We present ProtoTeams, a system that leverages personal mobile devices to support rapid group formation, to facilitate group activities, and to collect data about the potential for future collaboration. We report on a field study where 406 students in eight different project-based classes used ProtoTeams to interact with classmates through multiple rounds of brief discussion activities before selecting teammates for a term project. We found that the system enables groups to form in about one minute, allows for meaningful interactions with a diverse range of peers, and can significantly influence subsequent teammate selection. We discuss design implications and challenges for in-person team dating in classrooms and other contexts.

As videos become increasingly ubiquitous, so is video-based commenting. To contextualize comments, people often reference specific audio/visual content within video. However, the literature falls short of explaining the types of video content people refer to, how they establish references and identify referents, how video characteristics (e.g., genre) impact referencing behaviors, and how references impact social engagement. We present a taxonomy for classifying video references by referent type and temporal specificity. Using our taxonomy, we analyzed 2.5K references with quotations and timestamps collected from public YouTube comments. We found: 1) people reference intervals of video more frequently than time-points, 2) visual entities are referenced more often than sounds, and 3) comments with quotes are more likely to receive replies but not more "likes". We discuss the need for in-situ dereferencing user interfaces, illustrate design concepts for typed referencing features, and provide a dataset for future studies.