While the Quantified Self movement emphasizes the informed self through self-tracking and data representation, limited research has explored how to foster reflective engagement with personal data to cultivate a higher qualified self. To address this gap, we extend the focus onto fidgeting behavior, which is often considered subconscious with its qualitative meaning relatively less explored. We design MindSeed, an interactive system that enables users to track, co-create and reflect on their fidgeting data. We deployed MindSeed in a seven-day field study with eight participants who carried and interacted with it across different daily contexts. Analysis of the logged data and the interviews provides preliminary insights into how people adopt MindSeed into their daily lives, and how it may support meaningful reflection on daily subjective experiences that might otherwise go unnoticed. Building on these exploratory findings, we discuss how our works might inform future research agenda and design practices related to the qualified self.

Educational 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.

Generative AI has shown the potential to support older adults to reminisce about the past by producing personalized memory-related content despite the person’s varied ability to elaborate or the lack of memory cues. We present two studies to investigate how generative AI can support older adults in individual and group reminiscence. In Study 1, we conducted individual co‑design sessions with 16 older adults, during which participants created textile collages inspired by personal memories and then used generative AI to transform these creations into memory‑related video content. In the second study, we incorporate the textile collages and AI-generated videos into an interactive artifact, Reminiscope, and introduce it in a series workshops with 15 participants (with 14 returning participants from Study 1) to support group reminiscence. Findings from these studies reveal how older adults’ perspectives towards collaborating with generative AI for creating memory-related content, and their experiences of engaging with an AI‑enhanced interactive artifact during shared reminiscence activities. Our work contributes to the emerging trend of leveraging generative AI to support reminiscence in older adults, and provide design implications for future reminiscence technologies.

Generative AI (Gen-AI) is increasingly integrated into the design of digital cultural heritage. However, most of these applications remain screen-based or virtual, limiting opportunities for visitors to encounter the AI-enhanced heritage in real-world settings. Inspired by a formative study with heritage inheritors of traditional Chinese handicrafts and the Chinese cultural heritage of Zou Ma lanterns, we design an AI-enhanced interactive installation, namely ZOMA. With this design, we explore how Gen-AI can be integrated into a hybrid heritage artifact that provides personalized, engaging and reflective experiences. We deployed the design in an exhibition space in a school of design for three weeks, and collected feedback from on-site visitors (n=100) through questionnaires and follow-up interviews with participants selected from these visitors (n=11). The analysis of the data from the on-site visitors (including system logs and the questionnaires) reveals that ZOMA could engage people in embodied and personalized heritage experiences with positive feedback on the integration of Gen-AI into the design. Our interpretation of the follow-up interviews highlights the participants’ perceptions of the interaction qualities of ZOMA and their reflections on the potential tensions in applying Gen-AI in the design of heritage exhibitions. Our work extends the existing discussions on the topics of hybrid heritage crafts, tangible and embodied interaction, participatory heritage exhibitions, and ethical concerns regarding AI hallucination in heritage. We provide design implications for future design practices integrating Gen-AI in heritage contexts.

HCI technologies are increasingly used to promote the wellbeing of young people. While mental health professionals are significant resources to support young people in dealing with mental health challenges, little research has explored the distinctive perspectives between young people and professionals and how technology can be designed to navigate the tensions between them. To fill this gap, we conducted a two-stage study consisting of semi-structured interviews and a co-design workshop with university students and mental health professionals. Findings from the interviews revealed convergent and divergent perspectives between these two groups on the factors that motivate or discourage young people from seeking help from the professionals. In the workshop, insights of the interviews were further distilled into a set of card-based tools to facilitate shared understanding and collaboration between these two groups as they envisioned future technologies that address the interests and concerns of two groups. Our work contributes to ongoing discussions in HCI about how emerging technologies can be designed to promote shared understanding between these two groups and enable technology‑mediated mental healthcare tailored to individual needs and institutional contexts.

With the digitalization and mobilization of the society, older people face the challenge of maintaining high-quality communication with their younger family members who move out and lead separate lives at a distance. In HCI, little work is done to understand the social dynamics between distributed families and their remote communication mediated by the technologies. To identify design opportunities to support their remote communication, we conducted interviews with nine family pairs composed of distributed intergenerational family members. In addition, we interviewed eight community volunteers to formulate a perspective of social service providers. Our paper contributes to the HCI community by providing an account of the social dynamics mediated by communication technologies between older adults and their remote families, and opportunities to promote their social connections from a multi-stakeholder perspective. This paper presents valuable insights for designers aiming to enhance wellbeing of older adults within the context of distributed families.

This paper presents the design of a novel social robot, namely Patbot, to engage people in playful interactions to help reduce their anxiety in waiting environments. We introduce the rationale and design decisions made during the development of the robot. We evaluated the robot’s usability through an experiment within a simulated waiting environment, followed by interviews with the participants. The study indicated a positive effect of interacting with Patbot regarding STAI-6 anxiety measures. Other quantitative and qualitative measures, including Godspeed questionnaires, observation, and post-interviews, revealed positive impressions made by Patbot regarding its likability and animacy and that it could engage individuals in intuitive and playful activities. Our findings suggest the promise of designing social robots for entertainment and relaxation to enhance people’s emotional experiences in waiting environments.