LLM-assisted writing has seen rapid adoption in interpersonal communication, yet current systems often fail to capture the subtle tones essential for effectiveness. Email writing exemplifies this challenge: effective messages require careful alignment with intent, relationship, and context beyond mere fluency. Through formative studies, we identified three key challenges: articulating nuanced communicative intent, making modifications at multiple levels of granularity, and reusing effective tone strategies across messages. We developed PersonaMail, a system that addresses these gaps through structured communication factor exploration, granular editing controls, and adaptive reuse of successful strategies. Our evaluation compared PersonaMail against standard LLM interfaces, and showed improved efficiency in both immediate and repeated use, alongside higher user satisfaction. We contribute design implications for AI-assisted communication systems that prioritize interpersonal nuance over generic text generation.

Unlike the free exploration of childhood, the demands of daily life reduce our motivation to explore our surroundings, leading to missed opportunities for informal learning. Traditional tools for knowledge acquisition are reactive, relying on user initiative and limiting their ability to uncover hidden interests. Through formative studies, we introduce AiGet, a proactive AI assistant integrated with AR smart glasses, designed to seamlessly embed informal learning into low-demand daily activities (e.g., casual walking and shopping). AiGet analyzes real-time user gaze patterns, environmental context, and user profiles, leveraging large language models to deliver personalized, context-aware knowledge with low disruption to primary tasks. In-lab evaluations and real-world testing, including continued use over multiple days, demonstrate AiGet's effectiveness in uncovering overlooked yet surprising interests, enhancing primary task enjoyment, reviving curiosity, and deepening connections with the environment. We further propose design guidelines for AI-assisted informal learning, focused on transforming everyday moments into enriching learning experiences. © 2025 Copyright held by the owner/author(s).

Live drills are the gold standard for mass casualty incident (MCI) training but are often too resource-intensive for widespread implementation. Immersive technologies offer a promising alternative, but can they deliver comparable fidelity and effectiveness? Working with a local disaster response academy, this paper investigated the potential of Augmented Virtuality (AV) in MCI training through two phases. First, we conducted a landscape analysis of 126 papers across the virtuality continuum, revealing trends in population, training focus, and evaluation metrics. Second, we empirically evaluated an AV system for mass casualty triage training against traditional role-playing and Virtual Reality (VR) approaches, involving 60 trainees in an operational curriculum. Results indicated that both AV and VR surpassed traditional simulations, with AV’s tactile integration significantly enhancing physical engagement, satisfaction, and triage accuracy. Through the lens of triage, we discussed the broader practical implications of integrating immersive technologies like AV into real-world MCI education.

Given the widespread presence of screens during meals, the notion that digital engagement is inherently incompatible with mindfulness. We demonstrate how the strategic design of digital content can enhance two core aspects of mindful eating: slow eating and food awareness. Our research unfolded in three sequential studies: (1). Zoom Eating Study: Contrary to the assumption that video-watching leads to distraction and overeating, this study revealed that subtle video speed manipulations—can promote slower eating (by 15.31%) and controlled food intake (by 9.65%) while maintaining meal satiation and satisfaction. (2). Co-design workshop: Informed the development of ViFeed, a video playback system strategically incorporating subtle speed adjustments and glanceable visual cues. (3). Field Study: A week-long deployment of ViFeed in daily eating demonstrated its efficacy in fostering food awareness, food appreciation, and sustained engagement. By bridging the gap between ideal mindfulness practices and screen-based behaviors, this work offers insights for designing digital-wellbeing interventions that align with, rather than against, existing habits. © 2025 Copyright held by the owner/author(s).

While effective for recording and sharing experiences, traditional in-context writing tools are relatively passive and unintelligent, serving more like instruments rather than companions. This reduces primary task (e.g., travel) enjoyment and hinders high-quality writing. Through formative study and iterative development, we introduce PANDALens, a Proactive AI Narrative Documentation Assistant built on an Optical See-Through Head Mounted Display that supports personalized documentation in everyday activities. PANDALens observes multimodal contextual information from user behaviors and environment to confirm interests and elicit contemplation, and employs Large Language Models to transform such multimodal information into coherent narratives with significantly reduced user effort. A real-world travel scenario comparing PANDALens with a smartphone alternative confirmed its effectiveness in improving writing quality and travel enjoyment while minimizing user effort. Accordingly, we propose design guidelines for AI-assisted in-context writing, highlighting the potential of transforming them from tools to intelligent companions.

Co-creative systems have been widely explored in the field of computational creativity. However, existing AI partners of these systems are mostly virtual agents. As sketching on paper with embodied robots could be more engaging for designers' early-stage ideation and collaborative practices, we envision the possibility of Cobbie, a mobile robot that ideates iteratively with designers by generating creative and diverse sketches. To evaluate the differences in co-creativity and user experience between the co-creative robots and virtual agents, we conducted a comparative experiment and analyzed the data collected from quantitative scales, observation, and semi-structured interview. The results reveal that Cobbie is more satisfying in motivating exploration, provoking unexpected ideas and engaging designers in the collaborative ideation process. Based on these findings, we discussed the prospects of co-creative robots for future developments of human-AI collaborative systems.

Mobile vocabulary learning interfaces typically present material only in auditory and visual channels, underutilizing the haptic modality. We explored haptic-integrated learning by adding free-form digital annotation to mobile vocabulary learning interfaces. Through a series of pilot studies, we identified three design factors: annotation mode, presentation sequence, and vibrotactile feedback, that influence recall in haptic-integrated vocabulary interfaces. These factors were then evaluated in a within-subject comparative study using a digital flashcard interface as baseline. Results using a 84-item vocabulary showed that the 'whole word' annotation mode is highly effective, yielding a 24.21% increase in immediate recall scores and a 30.36% increase in the 7-day delayed scores. Effects of presentation sequence and vibrotactile feedback were more transient; they affected the results of immediate tests, but not the delayed tests. We discuss the implications of these factors for designing future mobile learning applications.