Radical Gender Neutrality: Agender Euphoria in Gaming and Play ExperiencesAgender euphoria is a new term representing the powerful feelings of happiness, joy, and contentment derived from experiences in gender-free embodiments, spaces, and activities. People with and without agender and adjacent identities (e.g., genderless, gender-free, non-binary, gender-apathetic) may have such experiences under the right circumstances. Video games can offer gender minorities a safe haven for gender euphoric experiences. However, the possibility of agender euphoric experiences was unexplored. We considered this overlooked frame of self-actualization with 142 people who identified as having or desiring agender euphoric experiences. Using the critical incident technique (CIT), we uncovered how games and play experiences create (and inhibit) agender euphoria. We surface this experiential phenomenon and provide empirically-grounded criteria for the design of games to elicit agender euphoric experiences for everyone, but especially agender and agender adjacent players. This work adds to the growing critical literatures on marginalized experiences in games research and human-computer interaction.2026KSKatie Seaborn et al.Institute of Science TokyoGame UX & Player BehaviorGender & Race Issues in HCIEmpowerment of Marginalized GroupsCHI
Capturing Team Cognition: A Multimodal Dataset for Adaptive Collaborative InterfacesWe introduce a multimodal dataset and experimental setup designed to support the development of adaptive collaborative systems. Data were collected from distributed teams working simultaneously across two continents, demonstrating the feasibility of sensing team cognition in geographically dispersed settings. The dataset includes synchronized EEG, audio transcripts, screen recordings, and behavioral annotations, enabling fine-grained analysis of collaboration in naturalistic settings. Our setup integrates neural and behavioral sensing to model team processes, using metrics such as task engagement, neural synchrony, and interaction patterns. These analyses reveal relationships between cognitive states and team dynamics, suggesting new directions for brain-computer interfaces that respond to team-level signals. By providing a shareable dataset, robust sensing infrastructure, and techniques for modeling distributed collaboration, this work enables future interactive systems that sense and support distributed teamwork in real time.2026CMChristopher Micek et al.Worcester Polytechnic InstituteBrain-Computer Interface (BCI) & NeurofeedbackDistributed Team CollaborationComputational Methods in HCICHI
Evaluation-First Design for Data Visualization InterfacesExisting frameworks in visualization and HCI emphasize iteration, data grounding, and stakeholder needs; however, they have not fully explored how evaluation might persist across phases, adapt to compressed timelines, and aid stakeholder engagement and elicitation. Building on prior frameworks, we introduce an evaluation-first design that centers evaluation as a material component in the design process, expanding evaluation to include when it occurs, who participates, how results inform design, and how metrics anchor stakeholder engagement and adoption. Evaluation-first design (EvalOps) emphasizes tighter feedback loops, co-evaluation with stakeholders, malleable forms of evaluation, and goals-to-metrics grounding. We illustrate how EvalOps shapes design outcomes through two case studies of data-visualization and LLM-enabled reasoning tools, demonstrating how evaluation-driven design facilitates alignment and trust, uncovers opportunities earlier, and supports cohesiveness under rapidly changing constraints. We contrast EvalOps with current visualization design methodologies and discuss opportunities for expanding evaluation-centered framings to other active areas of design research.2026BSBijayan Shrestha et al.Worcester Polytechnic InstituteInteractive Data VisualizationExplainable AI (XAI)User Research Methods (Interviews, Surveys, Observation)CHI
MindfulAgents: Personalizing Mindfulness Meditation via an Expert-Aligned Multi-Agent SystemMindfulness meditation is a widely accessible and evidence-based method for supporting mental health. Despite the proliferation of mindfulness meditation apps, sustaining user engagement remains a persistent challenge. Personalizing the meditation experience is a promising strategy to improve engagement, but it often requires costly and unscalable manual effort. We present MindfulAgents, a multi-agent system powered by large language models that: (1) generates guided meditation scripts based on an expert-established mindfulness framework, (2) encourages users' reflection on emotional states and mindfulness skills, and (3) enables real-time personalization of the mindfulness meditation experience for each user. In a formative lab study (N=13), MindfulAgents significantly improved in-session engagement (p = 0.011) and self-awareness (p = 0.014), as well as reduced momentary stress (p = 0.020). Furthermore, a four-week deployment study (N=62) demonstrated a notable increase (p = 0.002) in long-term engagement and level of mindfulness (p = 0.023). Participants reported that MindfulAgents offered more relevant meditation sessions personalized to individual needs in various contexts, supporting sustained practice. Our findings highlight the potential of LLM-driven personalization for enhancing user engagement in digital mindfulness meditation interventions.2026MWMengyuan Wu et al.Columbia UniversityMental Health Apps & Online Support CommunitiesAffective Human-Computer DialogueHuman-LLM CollaborationCHI
Crowdsourced Think-Aloud StudiesThe think-aloud (TA) protocol is a useful method for evaluating user interfaces, including data visualizations. However, TA studies are time-consuming to conduct and hence often have a small number of participants. Crowdsourcing TA studies would help alleviate these problems, but the technical overhead and the unknown quality of results have restricted TA to synchronous studies. To address this gap we introduce CrowdAloud, a system for creating and analyzing asynchronous, crowdsourced TA studies. CrowdAloud captures audio and provenance (log) data as participants interact with a stimulus. Participant audio is automatically transcribed and visualized together with events data and a full recreation of the state of the stimulus as seen by participants. To gauge the value of crowdsourced TA studies, we conducted two experiments: one to compare lab-based and crowdsourced TA studies, and one to compare crowdsourced TA studies with crowdsourced text prompts. Our results suggest that crowdsourcing is a viable approach for conducting TA studies at scale.2025ZCZach Cutler et al.University of Utah, Visualization Design LabTime-Series & Network Graph VisualizationUser Research Methods (Interviews, Surveys, Observation)Prototyping & User TestingCHI
Designed & Discovered Euphoria: Insights from Trans-Femme Players' Experiences of Gender Euphoria in Video GamesMany transgender (and cisgender) people experience gender euphoria -- satisfaction and relief caused by self-actualization and gender congruence -- a term that has been overlooked by the design community. Video games create intense experiences involving identities, bodies, and social interaction, providing opportunities to empower people through gender euphoria. We develop themes for creating and supporting gender euphoria in games within the Design, Dynamics, Experience Game Design Framework from a reflexive thematic analysis of 25 games, with an in-depth analysis of four of them. The analysis combines the authors' positionalities as trans gamers with close reading and content analysis of the games, employing perspectives from critical discourse analysis. We contribute an operational understanding of gender euphoria to support design, in-depth case studies of particularly euphoric game experiences, and identify themes that designers and researchers can use to develop new games and analyze existing ones.2025SLShano Liang et al.Worcester Polytechnic InstituteMultiplayer & Social GamesRole-Playing & Narrative GamesGender & Race Issues in HCICHI
Perceptions and Preferences: Deaf ASL-Signing Users' Insights on Video Elements, Styles and LayoutsVideo components are a central element of user interfaces that deliver content in a signed language (SL), but the potential of video components extends beyond content accessibility. SL videos may be designed as user interface elements: layered with interactive features to create navigation cues, page headings, and menu options. To be effective for signing users, novel SL video-rich interfaces require informed design choices across many parameters. To align with the specific needs and shared conventions of the Deaf community and other ASL-signers in this context, we present a user study involving deaf ASL-signers who interacted with an array of designs for SL video elements. Their responses offer some insights into how the Deaf community may perceive and prefer video elements to be designed, positioned, and implemented to guide user experiences. Through a qualitative analysis, we take initial steps toward understanding deaf ASL-signers’ perceptions of a set of emerging design principles, paving the way for future SL-centric user interfaces containing customized video elements and layouts with primary consideration for signed language-related usage and requirements.2025KAKhulood Alkhudaidi et al.Worcester Polytechnic InstituteForce Feedback & Pseudo-Haptic WeightVoice AccessibilityDeaf & Hard-of-Hearing Support (Captions, Sign Language, Vibration)CHI
This Game SUX: Why & How to Design Sh@*!y User ExperiencesWhile normative – "good" – game design and user experiences have been established, we look to games that challenge those notions. Intentional frustration and failure can be worthwhile. Through a reflexive thematic analysis of 31 games we identify how intentionally non-normative design choices lead to meaningful experiences. Working within the established Mechanics Dynamics Aesthetics (MDA) Game Design Framework, we lay out themes to design Shitty User Experiences (SUX). We contribute SUX MDA themes for designers and researchers to counter the status quo and identify new forms of play and interaction.2025MCMichelle V Cormier et al.Monash University, Exertion Games LaboratoryGame UX & Player BehaviorSerious & Functional GamesGamification DesignCHI
Is Resistance Futile?: Early Career Game Developers, Generative AI, and Ethical SkepticismThis paper presents a study that examines developer perceptions and usage of generative AI (GAI) in a summer professional development program for game development interns focused on mobile game design. GAI applications are in common usage worldwide, yet the impacts of this technology in game development remain relatively underexplored. Through a qualitative study using ethnographic interviews and participatory observation, this paper explores how GAI impacted the workflows, creative processes, and professional identities of early career game developers. We present a case of GAI integration that was not a straightforward adoption. Focusing on the interns' resistance, negotiation, and reimagining, we show that the interns were actively developing a new professional culture both with and against generative AI. For the interns, their ethical commitments to fellow game developers and the future of their profession were as important as their practical concerns about usability, utility, and efficacy of GAI tools.2024JBJosiah D Boucher et al.WPIBrain-Computer Interface (BCI) & NeurofeedbackGenerative AI (Text, Image, Music, Video)AI Ethics, Fairness & AccountabilityCHI
How Can Deep Neural Networks Aid Visualization Perception Research?: Three Studies on Correlation Judgments in ScatterplotsHow deep neural networks can aid visualization perception research is a wide-open question. This paper provides insights from three perspectives—prediction, generalization, and interpretation—via training and analyzing deep convolutional neural networks on human correlation judgments in scatterplots across three studies. The first study assesses the accuracy of twenty-nine neural network architectures in predicting human judgments, finding that a subset of the architectures (e.g., VGG-19) has comparable accuracy to the best-performing regression analyses in prior research. The second study shows that the resulting models from the first study display better generalizability than prior models on two other judgment datasets for different scatterplot designs. The third study interprets visual features learned by a convolutional neural network model, providing insights about how the model makes predictions, and identifies potential features that could be investigated in human correlation perception studies. Together, this paper suggests that deep neural networks can serve as a tool for visualization perception researchers in devising potential empirical study designs and hypothesizing about perpetual judgments. The preprint, data, code, and training logs are available at https://doi.org/10.17605/osf.io/exa8m.2023FYFumeng Yang et al.Northwestern UniversityVisualization Perception & CognitionCHI
Smooth as - The Effects of Frame Rate Variation on Game Player Quality of ExperienceFor gamers, high frame rates are important for a smooth visual display and good quality of experience (QoE). However, high frame rates alone are not enough as variations in the frame display times can degrade QoE even as the average frame rate remains high. While the impact of steady frame rates on player QoE is fairly well-studied, the effects of frame rate variation is not. This paper presents a 33-person user study that evaluates the impact of frame rate variation on users playing three different computer games. Analysis of the results shows average frame rate alone is a poor predictor of QoE, and frame rate variation has a significant impact on player QoE. While the standard deviation of frame times is promising as a general predictor for QoE, frame time standard deviation may not be accurate for all individual games. However, 95% frame rate floor -– the bottom 5% of frame rates the player experiences –- appears to be an effective predictor of both QoE overall and for the individual games tested.2023SLShengmei Liu et al.Worcester Polytechnic InstituteGame UX & Player BehaviorGamification DesignCHI
The Impact of Latency on Navigation in a First-Person Perspective GameCompetitive first-person shooter games are played over a network, where latency can degrade player performance. To better understand latency's impact, a promising approach is to study how latency affects individual game actions, such as moving and shooting. While target selection (aiming and shooting at an opponent) is fairly well studied, navigation (moving an avatar into position) is not. This paper presents results from a 30-person user study that evaluates the impact of latency on first-person navigation using a custom ``hide and seek'' game that isolates avatar movement in a manner intended to be similar to movement in a first-person shooter game. Analysis of the results shows latency has pronounced effects on player performance (score and seek positioning), with subjective opinions on Quality of Experience following suit.2022SLShengmei Liu et al.Worcester Polytechnic InstituteGame UX & Player BehaviorMultiplayer & Social GamesCHI
Interaction with Touch-Sensitive Knitted Fabrics: User Perceptions and Everyday Use ExperimentsRecent work has investigated the construction of touch-sensitive knitted fabrics, capable of being manufactured at scale, and having only two connections to external hardware. Additionally, several sensor design patterns and application prototypes have been introduced. Our aim is to start shaping the future of this technology according to user expectations. Through a formative focus group study, we explore users' views of using these fabrics in different contexts and discuss potential concerns and application areas. Subsequently, we take steps toward addressing relevant questions, by first providing design guidelines for application designers. Furthermore, in one user study, we demonstrate that it is possible to distinguish different swipe gestures and identify accidental contact with the sensor, a common occurrence in everyday life. We then present experiments investigating the effect of stretching and laundering of the sensors on their resistance, providing insights about considerations necessary to include in computational models.2022DMDenisa Qori McDonald et al.Drexel UniversityHaptic WearablesShape-Changing Interfaces & Soft Robotic MaterialsCHI
Towards Sign Language-Centric Design of ASL Survey ToolsQuestionnaires are fundamental learning and research tools for gathering insights and information from individuals, and now can be created easily using online tools. However, existing resources for creating questionnaires are designed for written languages (e.g. English) and do not support sign languages (e.g. American Sign Language). Sign languages (SLs) have unique visual characteristics that do not fit into user interface paradigms designed for written, text-based languages. Through a series of formative studies with the ASL signing community, this paper takes steps towards understanding the viability, potential benefit, challenges, and user interest in SL-centric surveys, a novel approach for creating questionnaires that meet the needs of deaf individuals using sign languages, without obligatory reliance on a written language to complete a questionnaire.2022SMShruti Mahajan et al.Worcester Polytechnic InstituteMultilingual & Cross-Cultural Voice InteractionVisual Impairment Technologies (Screen Readers, Tactile Graphics, Braille)Augmentative & Alternative Communication (AAC)CHI
Exploring A Reporting Tool to Empower Individuals with Intellectual and Developmental Disabilities to Self-Report AbuseIn the US, abuse of individuals with intellectual and developmental disabilities (I/DD) is at epidemic proportions. Further, abuse inci- dents of individuals with I/DD are woefully under-reported. We surveyed practitioners who help individuals with I/DD post-abuse to get a broader context on the problem. We found that abuse of individuals with I/DD was often reported by someone other than the survivor as survivors faced impediments in reporting. Conse- quently, we argue for developing a mobile-computing-based reporting tool for empowering individuals with I/DD to self-report abuse. Next, we conducted focus groups of individuals with I/DD to evaluate the tool’s viability, with respect to their ability to recognize/report abuse and use mobile-computing devices. We found individuals with I/DD could recognize/report abuse well when they received appropriate training. We also found individuals with I/DD could independently use their devices though they shared access to them with family. Based on these findings, we call for several lines of accessibility research in designing an abuse self-reporting tool for individuals with I/DD.2021KVKrishna Venkatasubramanian et al.University of Rhode IslandCognitive Impairment & Neurodiversity (Autism, ADHD, Dyslexia)Special Education TechnologyInclusive DesignCHI
Lower is Better? The Effects of Local Latencies on Competitive First-Person Shooter Game PlayersVideo game play is among the most popular forms of entertainment in the world and eSports is a multi-billion dollar industry. Esports gamers, and competitive gamers more broadly, want fast game systems to maximize their chances of winning. In general, the faster the game system, the lower the latency between a player's action and the intended outcome. But how much small reductions in local latencies benefit competitive players is not known. This paper presents results from a 43-person user study that evaluates the impact of system latencies for high-end gaming systems (below 125 ms) on experienced Counter-strike: Global Offensive (CS:GO) players. Analysis of the results show pronounced benefits to CS:GO player performance (accuracy and score) for even small reductions in latency, with subjective opinions on Quality of Experience following suit.2021SLShengmei Liu et al.Worcester Polytechnic InstituteGame UX & Player BehaviorMultiplayer & Social GamesCHI
reVISit: Looking Under the Hood of Interactive Visualization StudiesQuantifying user performance with metrics such as time and accuracy does not show the whole picture when researchers evaluate complex, interactive visualization tools. In such systems, performance is often influenced by different analysis strategies that statistical analysis methods cannot account for. To remedy this lack of nuance, we propose a novel analysis methodology for evaluating complex interactive visualizations at scale. We implement our analysis methods in reVISit, which enables analysts to explore participant interactions performance metrics, and responses in the context of users' analysis strategies. Replays of participant sessions can aid in identifying usability problems during pilot studies and make individual analysis processes salient. To demonstrate the applicability of reVISit to visualization studies, we analyze participant data from two published crowdsourced studies. Our findings show that reVISit can be used to reveal and describe novel interaction patterns, to analyze performance differences between different analysis strategies, and to validate or challenge design decisions.2021CNCarolina Nobre et al.Harvard UniversityInteractive Data VisualizationVisualization Perception & CognitionCHI
Exploring How Game Genre in Student-Designed Games Influences Computational Thinking DevelopmentGame design is increasingly used in modern education to foster Computational Thinking (CT). Yet, it is unclear how and if the game genre of student-designed games impact CT and programming. We explore how game genre impacts CT development and programming routines in Scratch games designed by 8th-grade students using a metrics-based approach (i.e., Dr. Scratch). Our findings show that designing particular games (e.g., action, storytelling) impact CT and programming development. We observe, for instance, that CT skills develop and consolidate fast, after which students can focus on aspects more specific to game design. Based on the results, we suggest that researchers and educators in constructionist learning consider the impact of game genre when designing game-based curricula for the learning of programming and CT.2020GTGiovanni Maria Troiano et al.Northeastern UniversityGamification DesignProgramming Education & Computational ThinkingSTEM Education & Science CommunicationCHI
Evaluating Multivariate Network Visualization Techniques Using a Validated Design and Crowdsourcing ApproachVisualizing multivariate networks is challenging because of the trade-offs necessary for effectively encoding network topology and encoding the attributes associated with nodes and edges. A large number of multivariate network visualization techniques exist, yet there is little empirical guidance on their respective strengths and weaknesses. In this paper, we describe a crowdsourced experiment, comparing node-link diagrams with on-node encoding and adjacency matrices with juxtaposed tables. We find that node-link diagrams are best suited for tasks that require close integration between the network topology and a few attributes. Adjacency matrices perform well for tasks related to clusters and when many attributes need to be considered. We also reflect on our method of using validated designs for empirically evaluating complex, interactive visualizations in a crowdsourced setting. We highlight the importance of training, compensation, and provenance tracking.2020CNCarolina Nobre et al.University of UtahInteractive Data VisualizationTime-Series & Network Graph VisualizationCHI
Friend, Collaborator, Student, Manager: How Design of an AI-Driven Game Level Editor Affects CreatorsMachine learning advances have afforded an increase in algorithms capable of creating art, music, stories, games, and more. However, it is not yet well-understood how machine learning algorithms might best collaborate with people to support creative expression. To investigate how practicing designers perceive the role of AI in the creative process, we developed a game level design tool for Super Mario Bros.-style games with a built-in AI level designer. In this paper we discuss our design of the Morai Maker intelligent tool through two mixed-methods studies with a total of over one-hundred participants. Our findings are as follows: (1) level designers vary in their desired interactions with, and role of, the AI, (2) the AI prompted the level designers to alter their design practices, and (3) the level designers perceived the AI as having potential value in their design practice, varying based on their desired role for the AI.2019MGMatthew Guzdial et al.Georgia Institute of TechnologyGame UX & Player BehaviorAI-Assisted Creative WritingCreative Collaboration & Feedback SystemsCHI