Emotions, shaped by past experiences, significantly influence decision-making and goal pursuit. Traditional cognitive-behavioral techniques for personal development rely on mental imagery to envision ideal selves, but may be less effective for individuals who struggle with visualization. This paper introduces Emotional Self-Voice (ESV), a novel system combining emotionally expressive language models and voice cloning technologies to render customized responses in the user’s own voice. We investigate the potential of ESV to nudge individuals towards their ideal selves in a study with 60 participants. Across all three conditions (ESV, text-only, and mental imagination), we observed an increase in resilience, confidence, motivation, and goal commitment, and the ESV condition was perceived as uniquely engaging and personalized. We discuss the implications of designing generated self-voice systems as a personalized behavioral intervention for different scenarios.

Joanne Leong, David Ledo, Thomas Driscoll, Tovi Grossman, George Fitzmaurice, and Fraser Anderson. 2025. Paratrouper: Exploratory Creation of Character Cast Visuals Using Generative AI. In Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems (CHI '25). Association for Computing Machinery, New York, NY, USA, Article 189, 1–20.

Fostering students’ interests in learning is considered to have many positive downstream effects. Large language models have opened up new horizons for generating content tuned to one’s interests, yet it is unclear in what ways and to what extent this customization could have positive effects on learning. To explore this novel dimension, we conducted a between-subjects online study (n=272) featuring different variations of a generative AI vocabulary learning app that enables users to personalize their learning examples. Participants were randomly assigned to control (sentence sourced from pre-existing text) or experimental conditions (generated sentence or short story based on users’ text input). While we did not observe a difference in learning performance between the conditions, the analysis revealed that generative AI-driven context personalization positively affected learning motivation. We discuss how these results relate to previous findings and underscore their significance for the emerging field of using generative AI for personalized learning.

This research full paper describes a web-based online learning platform that delivers financial literacy lessons via talking head videos of AI-generated personas with two additional core features: LLM-powered proactive chat-based question-and-answer interactivity, and personal choice of the AI instructor from a list of distinct personas. We conducted two comparative studies with a total of 233 Thai students aged 1825, which aim to 1) investigate the impact of interactivity and instructor selection on the learning experience, and 2) further explore the underlying factors at play with instructor selection by introducing AI instructors' backstories as an extra intervention. We found that enabling interactivity significantly enhanced learning motivation, perceived learning facilitation, engagement, and virtual instructors' humanness compared to the passive setting. Providing learners with a choice of AI instructors provided minimal additional benefit. However, the learner's feeling of relatedness toward the instructor is a significant positive predictor of learning motivation, positive emotion, and agent credibility, while goal alignment with the agent correlates with perceived learning facilitation, and admiration corresponds with perceived agent humanness. These findings underscore the potential of interactive virtual instructors-ones that interactively encourage learners to reflect on the teaching materials throughout the lesson through two-way interaction-in enhancing motivational and experiential aspects of remote education, even if they do not significantly impact comprehension, and the importance of promoting learner's relatedness and goal alignment with the agent in boosting other aspects of the learning experience.

Imagine being able to send a personalized embodied agent to meetings you are unable to attend. This paper explores the idea of a Ditto —an agent that visually resembles a person, sounds like them, possesses knowledge about them, and can represent them in meetings. This paper reports on results from two empirical investigations: 1) focus group sessions with six groups (n=24) and 2) a Wizard of Oz (WOz) study with 10 groups (n=39) recruited from within a large technology company. Results from the focus group sessions provide insights on what contexts are appropriate for Dittos, and issues around social acceptability and representation risk. The focus group results also provide feedback on visual design characteristics for Dittos. In the WOz study, teams participated in meetings with two different embodied agents: a Ditto and a Delegate (an agent which did not resemble the absent person). Insights from this research demonstrate the impact these embodied agents can have in meetings and highlight that Dittos in particular show promise in evoking feelings of presence and trust, as well as informing decision making. These results also highlight issues related to relationship dynamics such as maintaining social etiquette, managing one's professional reputation, and upholding accountability. Overall, our investigation provides early evidence that Dittos could be beneficial to represent users when they are unable to be present but also outlines many factors that need to be carefully considered to successfully realize this vision.

Faced with public speaking anxiety, one common piece of advice is to picture the audience in a new light, using your mind’s eye. With Augmented Reality (AR) face filters, it becomes possible to literally change how one sees oneself or others. In this paper, we explore privately applied AR filters during online public speaking. Private means that these effects are only visible to the speaker. To investigate this possibly controversial concept, we conducted an online survey with 100 respondents to gather a diverse set of initial impressions, possible boundaries, and guidelines. Following this, we built a prototype of a private AR web-based video-calling application, and pilot-tested it with 16 participants to gain more in-depth insights. Based on our results, we outline key user perspectives and opportunities for the private application of AR face filters during online public speaking and discuss them in the context of previous literature on this topic.

Ubiquitous computing encapsulates the idea for technology to be interwoven into the fabric of everyday life. As computing blends into everyday physical artifacts, powerful opportunities open up for social connection. Prior connected media objects span a broad spectrum of design combinations. Such diversity suggests that people have varying needs and preferences for staying connected to one another. However, since these designs have largely been studied in isolation, we do not have a holistic understanding around how people would configure and behave within a ubiquitous social ecosystem of physically-grounded artifacts. In this paper, we create a technology probe called Social Wormholes, that lets people configure their own home ecosystem of connected artifacts. Through a field study with 24 participants, we report on patterns of behaviors that emerged naturally in the context of their daily lives and shine a light on how ubiquitous computing could be leveraged for social computing.

(Dis)Appearables is an approach for actuated Tangible User Interfaces (TUIs) to appear and disappear. This technique is supported by Stages: physical platforms inspired by theatrical stages. Self-propelled TUI’s autonomously move between front and back stage allowing them to dynamically appear and disappear from users’ attention. This platform opens up a novel interaction design space for expressive displays with dynamic physical affordances.

This paper presents the results of a study with 134 participants to explore the effects of learning from an AI-generated virtual instructor that resembles a person one likes or admires. Given the important role instructors play in shaping learning experiences, as well as the recent surge in demand for online education, we investigate the potential for AI-generated instructors to motivate learning. Recent advances in generative AI have made it easy to create virtual instructors based on the likeness of a present-day, historical or fictional person, thereby enabling customization of video instructors based on the material, context and student. We found that while greater degrees of liking and admiration do not result in increased test scores, they can significantly improve students’ motivation towards learning, foster more positive emotions, and boost their appraisal of the AI-generated instructor as serving as an effective instructor.

We propose a novel fabrication method for 3D objects based on the principle of spooling. By wrapping off-the-shelf materials such as thread, ribbon, tape or wire onto a core structure, new objects can be created and existing objects can be augmented with desired aesthetic and functional qualities. Our system, WraPr, enables gesture-based modelling and controlled thread deposition. We outline and explore the design space for this approach. Various examples are fabricated to demonstrate the possibility to attain a range of physical and functional properties. The simplicity of the proposed method opens the grounds for a light-weight fabrication approach for the generation of new structures and the customization of existing objects using soft materials.

Introducing interactive components into furniture has proven difficult due to the different lifespans of furniture and digital devices. We present Foxels, a modular, smart furniture concept that allows users to create their own interactive furniture on demand by simply snapping together individual building blocks. The modular design makes the system flexible to accommodate a variety of interactive furniture setups, making it particularly well-suited for re-configurable spaces. Considering the trade-off between ease-of-use and high versatility, we explored a number of interaction methods that can be applied to modular interactive furniture, thereby extending the well-known tangible programming paradigm. After explaining our implementation, we demonstrate the validity of the proposed concepts by presenting how Foxels can be used in an ideation workshop along with many additional real-world examples.

We introduce HERMITS, a modular interaction architecture for self-propelled Tangible User Interfaces (TUIs) that incorporates physical add-ons, referred to as mechanical shells. The mechanical shell add-ons are intended to be dynamically reconfigured by utilizing the locomotion capability of self-propelled TUIs (e.g. wheeled TUIs, swarm UIs). We developed a proof-of-concept system that demonstrates this novel architecture using two-wheeled robots and a variety of mechanical shell examples. These mechanical shell add-ons are passive physical attatchments that extend the primitive interactivities (e.g. shape, motion and light) of the self-propelled robots.

We present RESi (Resistive tExtile Sensor Interfaces), a novel sensing approach enabling a new kind of yarn-based, resistive pressure sensing. The core of RESi builds on a newly designed yarn, which features conductive and resistive properties. We run a technical study to characterize the behaviour of the yarn and to determine the sensing principle. We demonstrate how the yarn can be used as a pressure sensor and discuss how specific issues, such as connecting the soft textile sensor with the rigid electronics can be solved. In addition, we present a platform-independent API that allows rapid prototyping. To show its versatility, we present applications developed with different textile manufacturing techniques, including hand sewing, machine sewing, and weaving. RESi is a novel technology, enabling textile pressure sensing to augment everyday objects with interactive capabilities.

The increased interest in interactive soft materials, such as smart clothing and responsive furniture, means that there is a need for flexible and deformable electronics. In this paper, we focus on stitch-based elastic sensors, which have the benefit of being manufacturable with textile craft tools that have been used in homes for centuries. We contribute to the understanding of stitch-based stretch sensors through four experiments and one user study that investigate conductive yarns from textile and technical perspectives, and analyze the impact of different stitch types and parameters. The insights informed our design of new stretch-based interaction techniques that emphasize eyes-free or causal interactions. We demonstrate with StretchEBand how soft, continuous sensors can be rapidly fabricated with different parameters and capabilities to support interaction with a wide range of performance requirements across wearables, mobile devices, clothing, furniture, and toys.

Constructive assemblies are tangible user interfaces (TUIs) that involve the interconnection of modular parts. As such, they offer a unique means to support us in our various and diverse activities. However, little information is available for understanding the intricacies of taking a modular, constructive assembly approach to TUI design. Based on an analysis of extensive data collected from interviews with eight world-class TUI experts, we propose a descriptive, conceptual framework to facilitate systematic investigation and critical consideration of constructive assemblies. The paper presents a lifecycle model for constructive assemblies and discusses their main design qualities and associated parameters. We demonstrate how this can be used to structure critical discussions by applying the principles to existing works and the design of our own constructive assembly.

Ambient light is starting to be commercially used to enhance the viewing experience for watching TV. We believe that ambient light can add value in meeting and control rooms that use large vertical interactive surfaces. Therefore, we equipped a large interactive whiteboard with a peripheral ambient light display and explored its utility for different scenarios by conducting two controlled experiments. In the first experiment, we investigated how ambient light can be used for peripheral notifications, and how perception is influenced by the user's position and the type of work they are engaged in. The second experiment investigated the utility of ambient light for off-screen visualization. We condense our findings into several design recommendations that we then applied to application scenarios to show the versatility and usefulness of ambient light for large surfaces.

Today's commercially available prosthetic limbs lack tactile sensation and feedback. Recent research in this domain focuses on sensor technologies designed to be directly embedded into future prostheses. We present a novel concept and prototype of a prosthetic-sensing wearable that offers a non-invasive, self-applicable and customizable approach for the sensory augmentation of present-day and future low to mid-range priced lower-limb prosthetics. From consultation with eight lower-limb amputees, we investigated the design space for prosthetic sensing wearables and developed novel interaction methods for dynamic, user-driven creation and mapping of sensing regions on the foot to wearable haptic feedback actuators. Based on a pilot-study with amputees, we assessed the utility of our design in scenarios brought up by the amputees and we summarize our findings to establish future directions for research into using smart textiles for the sensory enhancement of prosthetic limbs.

Structuring and rearranging free-hand sketches on large interactive surfaces typically requires making multiple stroke selections. This can be both time-consuming and fatiguing in the absence of well-designed selection tools. Investigating the concept of automated clustering, we conducted a background study which highlighted the fact that people have varying perspectives on how elements in sketches can and should be grouped. In response to these diverse user expectations, we present cLuster, a flexible, domain-independent clustering approach for free-hand sketches. Our approach is designed to accept an initial user selection, which is then used to calculate a linear combination of pre-trained perspectives in real-time. The remaining elements are then clustered. An initial evaluation revealed that in many cases, only a few corrections were necessary to achieve the desired clustering results. Finally, we demonstrate the utility of our approach in a variety of application scenarios.