DOLLama: Fostering Family Anti-Bullying Learning through AI-Augmented, Toy-Mediated Educational DramaEducational drama is a proven method for anti-bullying education, but its traditional reliance on teachers and peers limits its accessibility to children and families outside of school. HCI has rarely explored how to augment this practice with AI-infused, interactive role-playing or how to involve parents in the process. We introduce DOLLama, an AI-powered projection-augmented interactive system that transforms children's toys and family-created stories into gamified anti-bullying vignettes. A study with 20 families demonstrated how DOLLama facilitated children’s and parents’ learning. Children used their toys to enact the roles of the one being bullied and bystanders, developing empathy and practicing coping strategies in co-performance with AI-controlled toy characters. By observing this play, parents gained new insights into their child’s strengths and challenges and identified their own knowledge gaps. Based on these findings, we derive HCI design implications for AI-enhanced, toy-mediated educational drama that supports anti-bullying education for children and their families.2026DLDi Liu et al.Southern University of Science and TechnologyCollaborative Learning & Peer TeachingChild-Computer Interaction DesignMental Health Technology for YouthCHI
Novobo: Supporting Teachers' Peer Learning of Instructional Gestures by Teaching a Mentee AI-Agent TogetherInstructional gestures are essential for teaching, enhancing communication and student comprehension. Current training methods for developing these skills can be time-consuming, isolating, or overly prescriptive, e.g., watching lengthy, one-size-fits-all videos. Conversely, research suggests that developing these tacit, experiential skills requires teachers’ peer learning, where they learn from each other and build shared knowledge. While much HCI exploration has applied learning-by-teaching to students’ peer learning, little has explored this approach for teacher professionalization. We present Novobo, an apprentice AI-agent stimulating teachers' peer learning of instructional gestures through verbal and bodily inputs. An evaluation with 30 teachers in 10 collaborative sessions showed Novobo prompted teachers to externalize and share tacit knowledge through dialogue and movement. Teaching an AI mentee together reduced their pressure, facilitating peer exchange and the co-construction of practical knowledge. This work contributes a novel design and empirical insights into how teachable AI-agents can facilitate peer learning in teacher professionalization.2026JJJiaqi Jiang et al.Southern University of Science and TechnologyBrain-Computer Interface (BCI) & NeurofeedbackFull-Body Interaction & Embodied InputHuman Pose & Activity RecognitionCHI
Agentic Audio Moderators vs Humans in Think-Aloud Usability TestingAgentic AI holds promise for usability testing, yet its role as an audio moderator in think-aloud protocols is not well understood. This study explores: (1) how to design and develop an agentic audio moderator for think-aloud usability testing, and (2) how participants moderated by an agentic moderator differ from those moderated by a human regarding task performance, verbalization behaviors, user experience, and social perceptions of the moderator. Using a design-based research approach, we interviewed nine UX experts, iteratively developed an AI moderator, and evaluated it in a randomized controlled trial (N=60) with a note-taking application. Results suggest that significant differences were not observed between AI and human moderators in task performance or verbalization behaviors, though AI moderators received lower social perception ratings. This work contributes the first design-oriented evaluation of AI moderators in usability testing, offering implications for developing more acceptable and effective agentic audio moderators.2026WZWangda Zhu et al.The Hong Kong Polytechnic UniversityGenerative AI (Text, Image, Music, Video)AI-Assisted Decision-Making & AutomationExplainable AI (XAI)CHI
ProjecTA: A Semi-Humanoid Robotic Teaching Assistant with In-Situ Projection for Guided ToursRobotic teaching assistants (TAs) often use body-mounted screens to deliver content. In nomadic, walk-and-talk learning, such as tours in makerspaces, these screens can distract learners from real-world objects, increasing extraneous cognitive load. HCI research lacks empirical comparisons of potential alternatives, such as robots with in-situ projection versus screen-based counterparts; little knowledge has been derived for designing such alternatives. We introduce ProjecTA, a semi-humanoid, gesture-capable TA that guides learners while projecting near-object overlays coordinated with speech and gestures. In a mixed-method study (N=24) in a university makerspace, ProjecTA significantly reduced extraneous load and outperformed its screen-based counterpart in perceived usability, usefulness of visual display, and cross-modal complementarity. Qualitative analyses revealed how ProjecTA’s coordinated projections, gestures and speech anchored explanations in place and time, enhancing understanding in ways a screen could not. We derive key design implications for future robotic TAs leveraging spatial projection to support mobile learning in physical environments.2026HZHanqing Zhou et al.Southern University of Science and TechnologySocial Robot InteractionTangible Interaction in EducationCitizen Science & Crowdsourced DataCHI
ASafePlace: User-Led Personalization of VR Relaxation via an Art Therapy ActivityTo overcome the lack of deep personalization in standard biofeedback methods, we introduce ASafePlace, a system utilizing an AI-powered, art-therapy-inspired exercise called The Safe Place, to create a personalized VR biofeedback experience. In our system, users sketch a personal sanctuary from memory, which is then transformed into a customized 360° virtual environment with personalized audio guidance for relaxation training. A study with 52 participants showed this approach effectively reduced anxiety and increased user presence, while the integration of art-therapy-inspired activity and biofeedback produced strong improvements in physiological relaxation, measured by heart rate variability and respiration rate. Qualitative results showed how participants' sense of familiarity and presence was enhanced by the symbolic elements and natural sanctuaries created from their autobiographical memories. Our findings demonstrate that art-therapy-inspired activity is a powerful tool for creating highly effective and individualized relaxation experiences, naturally connecting the virtual environment to a user's core memories and emotions.2026CZChuyang Zhang et al.Southern University of Science and TechnologyImmersion & Presence ResearchVR Medical Training & RehabilitationAffective Feedback & Emotion Regulation InterfacesCHI
When Generative AI Is Intimate, Sexy, and Violent: Examining Not-Safe-For-Work (NSFW) Chatbots on FlowGPTUser-created chatbots powered by generative AI offer new ways to share and interact with Not-Safe-For-Work (NSFW) content. However, little is known about the characteristics of these GenAI-based chatbots and their user interactions. Drawing on the functional theory of NSFW on social media, this study analyzes 376 NSFW chatbots and 307 public conversation sessions on FlowGPT. Findings identify four chatbot types: roleplay characters, story generators, image generators, and do-anything-now bots. AI Characters portraying fantasy personas and enabling hangout-style interactions are most common, often using explicit avatar images to invite engagement. Sexual, violent, and insulting content appears in both user prompts and chatbot outputs, with some chatbots generating explicit material even when users do not create erotic prompts. In sum, the NSFW experience on FlowGPT can be understood as a combination of virtual intimacy, sexual delusion, violent thought expression, and unsafe content acquisition. We conclude with implications for chatbot design, creator support, user safety, and content moderation.2026XLXian Li et al.Southern University of Science and TechnologyGenerative AI (Text, Image, Music, Video)Agent Personality & AnthropomorphismOnline Harassment & Counter-ToolsCHI
"Can I Decorate My Teeth With Diamonds?": Exploring Multi-Stakeholder Perspectives on Using VR to Reduce Children's Dental AnxietyDental anxiety is prevalent among children,often leading to missed treatment and potential negative effects on their mental well-being. While several interventions (e.g., pharmacological and psychotherapeutic techniques) have been introduced for anxiety alleviation, the recently emerged virtual reality (VR) technology, with its immersive and playful nature,opened new opportunities for complementing and enhancing the therapeutic effects of existing interventions. In this light, we conducted a series of co-design workshops with 13 children aged 10-12 to explore how they envisioned using VR to address their fear and stress associated with dental visits, followed by interviews with parents (n = 13) and two dentists. Our findings revealed that children expected VR to provide immediate relief, social support, and a sense of control during dental treatment, parents sought educational opportunities for their children to learn about oral health, and dentists prioritized treatment efficiency and safety issues. Drawing from the findings, we discuss the considerations of multi-stakeholders for developing VR-assisted anxiety management applications for children within and beyond dental settings.2025YMYaxuan MAO et al.Perspectives on VRCSCW
ClassComet: Exploring and Designing AI-generated Danmaku in Educational Videos to Enhance Online LearningDanmaku, users’ live comments synchronized with, and overlaying on videos, has recently shown potential in promoting online video-based learning. However, user-generated danmaku can be scarce—especially in newer or less viewed videos—and its quality is unpredictable, limiting its educational impact. This paper explores how large multimodal models (LMM) can be leveraged to automatically generate effective, high-quality danmaku. We first conducted a formative study to identify the desirable characteristics of content- and emotion-related danmaku in educational videos. Based on the obtained insights, we developed ClassComet, an educational video platform with novel LMM-driven techniques for generating relevant types of danmaku to enhance video-based learning. Through user studies, we examined the quality of generated danmaku and their influence on learning experiences. The results indicate that our generated danmaku is comparable to human-created ones, and videos with both content- and emotion-related danmaku showed significant improvement in viewers' engagement and learning outcome.2025ZJZipeng Ji et al.Human-LLM CollaborationOnline Learning & MOOC PlatformsDIS
Influencer: Empowering Everyday Users in Creating Promotional Posts via AI-infused Exploration and CustomizationCreating promotional posts on social platforms enables everyday users to disseminate their creative outcomes, engage in community exchanges, or generate additional income from micro-businesses. However, crafting eye-catching posts with appealing images and effective captions can be challenging and time-consuming for everyday users since they are mostly design novices. We propose Influencer, an interactive tool that helps novice creators quickly generate ideas and create high-quality promotional post designs through AI. Influencer offers a multi-dimensional recommendation system for ideation through example-based image and caption suggestions. Further, Influencer implements a holistic promotional post-design system supporting context-aware exploration considering brand messages and user-specified design constraints, flexible fusion of content, and a mind-map-like layout for idea tracking. Our user study, comparing the system with industry-standard tools, along with two real-life case studies, indicates that Influencer is effective in assisting design novices to generate ideas as well as creative and diverse promotional posts with user-friendly interaction.2025XLXuye Liu et al.University of WaterlooGenerative AI (Text, Image, Music, Video)Recommender System UXCHI
VRCaptions: Design Captions for DHH Users in Multiplayer Communication in VRAccessing auditory information remains challenging for DHH individuals in real-world situations and multiplayer VR interactions. To improve this, we investigated caption designs that specialize in the needs of DHH users in multiplayer VR settings. First, we conducted three co-design workshops with DHH participants, social workers, and designers to gather insights into the specific needs of design directions for DHH users in the context of a room escape game in VR. We further refined our designs with 13 DHH users to determine the most preferred features. Based on this, we developed VRCaptions, a caption prototype for DHH users to better experience multiplayer conversations in VR. We lastly invited two mixed-hearing groups to participate in the VR room escape game with our VRCaptions to validate. The results demonstrate that VRCaptions can enhance the ability of DHH participants to access information and reduce the barrier to communication in VR.2025TXTianze Xie et al.Southern University of Science and TechnologyConversational ChatbotsSocial & Collaborative VRDeaf & Hard-of-Hearing Support (Captions, Sign Language, Vibration)CHI
LumaDreams: Designing Positive Dream Meaning-Making for Daily EmpowermentDreams contribute to cognitive and emotional health, yet tools for everyday dream engagement remain largely underexplored outside clinical settings. In this paper, we introduce LumaDreams, a mobile application designed to foster daily empowerment through positive dream transformation using generative AI. Informed by meaning-making theories, LumaDreams enables users to journal dreams through sketches and text, which are then transformed into positive images and stories for users to revisit and reflect on. We conducted a mixed-method study with 14 participants over 14 days. Our findings show that LumaDreams strengthened participants’ daily empowerment through cognitive and emotional shifts that arise from the positive meaning-making process. Qualitative insights further revealed how users’ perceptions and trust of AI-driven dream transformation were shaped through their interactions. In conclusion, we propose an inspiring approach that enables users to co-create positive meanings in dream experiences with generative AI, promoting cognitive and emotional shifts, fostering positive mindsets, and ultimately strengthening daily empowerment.2025BLBolin Lyu et al.Southeast University, School of Computer Science and EngineeringGenerative AI (Text, Image, Music, Video)Mental Health Apps & Online Support CommunitiesCHI
Breaking Barriers or Building Dependency? Exploring Team-LLM Collaboration in AI-infused Classroom DebateClassroom debates are a unique form of collaborative learning characterized by fast-paced, high-intensity interactions that foster critical thinking and teamwork. Despite the recognized importance of debates, the role of AI tools, particularly LLM-based systems, in supporting this dynamic learning environment has been under-explored in HCI. This study addresses this opportunity by investigating the integration of LLM-based AI into real-time classroom debates. Over four weeks, 22 students in a Design History course participated in three rounds of debates with support from ChatGPT. The findings reveal how learners prompted the AI to offer insights, collaboratively processed its outputs, and divided labor in team-AI interactions. The study also surfaces key advantages of AI usage—reducing social anxiety, breaking communication barriers, and providing scaffolding for novices—alongside risks, such as information overload and cognitive dependency, which could limit learners' autonomy. We thereby discuss a set of nuanced implications for future HCI exploration.2025ZZZihan Zhang et al.Southern University of Science and Technology, School of DesignHuman-LLM CollaborationCollaborative Learning & Peer TeachingCHI
Walk in Their Shoes to Navigate Your Own Path: Learning About Procrastination Through A Serious GameProcrastination, the voluntary delay of tasks despite potential negative consequences, has prompted numerous time and task management interventions in the HCI community. While these interventions have shown promise in addressing specific behaviors, psychological theories suggest that learning about procrastination itself may help individuals develop their own coping strategies and build mental resilience. However, little research has explored how to support this learning process through HCI approaches. We present ProcrastiMate, a text adventure game where players learn about procrastination's causes and experiment with coping strategies by guiding in-game characters in managing relatable scenarios. Our field study with 27 participants revealed that ProcrastiMate facilitated learning and self-reflection while maintaining psychological distance, motivating players to integrate newly acquired knowledge in daily life. This paper contributes empirical insights on leveraging serious games to facilitate learning about procrastination and offers design implications for addressing psychological challenges through HCI approaches.2025RZRunhua ZHANG et al.Tongji University, College of Design and Innovation; Hong Kong University of Science and Technology, IIP (Human-Computer Interaction)Serious & Functional GamesSTEM Education & Science CommunicationMental Health Apps & Online Support CommunitiesCHI
EmoWear: Exploring Emotional Teasers for Voice Message Interaction on SmartwatchesVoice messages, by nature, prevent users from gauging the emotional tone without fully diving into the audio content. This hinders the shared emotional experience at the pre-retrieval stage. Research scarcely explored "Emotional Teasers"—pre-retrieval cues offering a glimpse into an awaiting message's emotional tone without disclosing its content. We introduce EmoWear, a smartwatch voice messaging system enabling users to apply 30 animation teasers on message bubbles to reflect emotions. EmoWear eases senders' choice by prioritizing emotions based on semantic and acoustic processing. EmoWear was evaluated in comparison with a mirroring system using color-coded message bubbles as emotional cues (N=24). Results showed EmoWear significantly enhanced emotional communication experience in both receiving and sending messages. The animated teasers were considered intuitive and valued for diverse expressions. Desirable interaction qualities and practical implications are distilled for future design. We thereby contribute both a novel system and empirical knowledge concerning emotional teasers for voice messaging.2024PAPengcheng An et al.Southern University of Science and TechnologyHaptic WearablesVoice User Interface (VUI) DesignIntelligent Voice Assistants (Alexa, Siri, etc.)CHI
"When He Feels Cold, He Goes to the Seahorse"—Blending Generative AI into Multimaterial Storymaking for Family Expressive Arts TherapyStorymaking, as an integrative form of expressive arts therapy, is an effective means to foster family communication. Yet, the integration of generative AI as expressive materials in therapeutic storymaking remains underexplored. And there is a lack of HCI implications on how to support families and therapists in this context. Addressing this, our study involved five weeks of storymaking sessions with seven families guided by a professional therapist. In these sessions, the families used both traditional art-making materials and image-based generative AI to create and evolve their family stories. Via the rich empirical data and commentaries from four expert therapists, we contextualize how families creatively melded AI and traditional expressive materials to externalize their ideas and feelings. Through the lens of Expressive Therapies Continuum (ETC), we characterize the therapeutic implications of AI as expressive materials. Desirable interaction qualities to support children, parents, and therapists are distilled for future HCI research.2024DLDi Liu et al.Southern University of Science and TechnologyGenerative AI (Text, Image, Music, Video)AI-Assisted Creative WritingInteractive Narrative & Immersive StorytellingCHI
Eggly: Designing Mobile Augmented Reality Neurofeedback Training Games for Children with Autism Spectrum DisorderAutism Spectrum Disorder (ASD) is a neurodevelopmental disorder that affects how children communicate and relate to other people and the world around them. Emerging studies have shown that neurofeedback training (NFT) games are an effective and playful intervention to enhance social and attentional capabilities for autistic children. However, NFT is primarily available in a clinical setting that is hard to scale. Also, the intervention demands deliberately-designed gamified feedback with fun and enjoyment, where little knowledge has been acquired in the HCI community. Through a ten-month iterative design process with four domain experts, we developed Eggly, a mobile NFT game based on a consumer-grade EEG headband and a tablet. Eggly uses novel augmented reality (AR) techniques to offer engagement and personalization, enhancing their training experience. We conducted two field studies (a single-session study and a three-week multi-session study) with a total of five autistic children to assess Eggly in practice at a special education center. Both quantitative and qualitative results indicate the effectiveness of the approach as well as contribute to the design knowledge of creating mobile AR NFT games. https://dl.acm.org/doi/10.1145/35962512023YLYUE LYU et al.Brain-Computer Interface (BCI) & NeurofeedbackAR Navigation & Context AwarenessParticipatory DesignUbiComp
Co-constructing Stories Based on Users Lived Experiences to Investigate Visualization Design for Collective Stress ManagementCollective stress is the stress within a group or an organization. It affects individuals' well-being and group productivity. HCI research has started exploring collective stress visualization to facilitate group awareness and collective coping via testing prototypes in controlled settings. However, an in-depth understanding of users' needs and envisaged scenarios based on their authentic experiences are still lacking. In this study, we utilized a participatory approach called co-constructing stories to investigate how a collective stress visualization would be used in office workers' authentic workday routines. We constructed use case stories with a group of office workers separately based on their personal lived experiences, using a design probe called AffectiveGarden. Our results categorized six clusters of benefits for collective coping through visualization and their implications for future design practice.2023MXMengru Xue et al.Interactive Data VisualizationCollaborative Learning & Peer TeachingNotification & Interruption ManagementDIS