Pixel Memories: Do Lifelog Summaries Fail to Enhance Memory but Offer Privacy-Aware Memory Assessments?We explore the metaphorical "daily memory pill" concept – a brief pictorial lifelog recap aimed at reviving and preserving memories. Leveraging psychological strategies, we explore the potential of such summaries to boost autobiographical memory. We developed an automated lifelogging memory prosthesis and a research protocol (Automated Memory Validation ``AMV'') for conducting privacy-aware, in-situ evaluations. We conducted a real-world lifelogging experiment for a month (n=11). We also designed a browser ``Pixel Memories’’ for browsing one-week worth of lifelogs. The results suggest that daily timelapse summaries, while not yielding significant memory augmentation effects, also do not lead to memory degradation. Participants' confidence in recalled content remains unaltered, but the study highlights the challenge of users' overestimation of memory accuracy. Our core contributions, the AMV protocol and "Pixel Memories" browser, advance our understanding of memory augmentations and offer a privacy-preserving method for evaluating future ubicomp systems.2025PEPassant ElAgroudy et al.German Research Centre for Artificial Intelligence (DFKI); RPTU KaiserslauternContext-Aware ComputingUbiquitous ComputingCHI
Wheel of Plush: A Co-Design Toolkit for Exploring the Design Space of Smart Soft Toy MaterialitySoft toys foster strong and enduring early childhood attachments, with positive effects extending into adulthood. Smart toys are vulnerable to exploits and can harm users. Bridging this contrast, pairs of smart objects, equipped with only simple sensors and actuators, may support peripheral and emotional awareness. At the same time, how exactly such pairs should negotiate the soft/smart spectrum to yield positive long-term impacts for people connecting through them is a design challenge. We engage this with the Wheel of Plush co-design toolkit. It enables 8x8 different sensor-actuator combinations in plush for co-designers to explore multimodal interactions for smart soft toy pairs connected over distance. We detail our design process and offer insights on designing a toolkit that combines artisanal plush material with simple sensors and actuators. With the Wheel of Plush, we contribute a toolkit for exploring smart soft toy materiality, data-frugal multimodal interaction, and opportunities for smart soft toy pair co-design.2024NSNatalie Sontopski et al.Haptic WearablesShape-Changing Interfaces & Soft Robotic MaterialsDIS
Towards a Haptic Taxonomy of Emotions: Exploring Vibrotactile Stimulation in the Dorsal RegionThe implicit communication of emotional states between persons is a key use case for novel assistive and augmentation technologies. It can serve to expand individuals' perceptual capabilities and assist neurodivergent individuals. Notably, vibrotactile rendering is a promising method for delivering emotional information with minimal interference with visual or auditory perception. To date, the subjective individual association between vibrotactile properties and emotional states remains unclear. Previous approaches relied on analogies or arbitrary variations, limiting generalization. To address this, we conducted a study with 40 participants, analyzing associations between attributes of self-generated vibrotactile patterns (\textsc{amplitude}, \textsc{frequency}, \textsc{spatial location} of stimulation) and four emotional states (\textsc{Anger}, \textsc{Happiness}, \textsc{Neutral}, \textsc{Sadness}). We fin a preference for symmetrically arranged patterns, as well as distinct amplitude and frequency profiles for different emotions. These insights can aid in creating standardized vibrotactile patterns for universal emotional communication.2023SVSteeven Villa et al.Vibrotactile Feedback & Skin StimulationUbiComp
Investigating Various Dynamics in the Box Task Combined With a Detection Response Task: Are There Performance Differences Between Uniform and Non-uniform Box Dynamics?The Box Task combined with a Detection Response Task (BT + DRT) is a relatively less investigated but promising method for evaluating visual-manual and cognitive task demand due to the interaction with in-vehicle information systems while driving. The BT includes the tracking of a dynamic box whose size and position follow a sinusoidal pattern with uniform amplitudes and frequencies. However, it is unclear whether participants are able to predict and adapt to these uniform dynamics, which might lead to a reduced sensitivity of the BT + DRT. Within the present study, it was aimed to examine differences in BT + DRT performance depending on uniform and non-uniform BT dynamics. A laboratory study was conducted with N = 41 participants. The experimental conditions differed in the type and difficulty level of the secondary tasks as well as in the BT dynamics (uniform, varying amplitude, varying frequency). While the uniform BT dynamics could be more predictable, the non-uniform BT dynamics were designed slightly easier in their difficulty using a lower frequency or amplitude. The results revealed no performance benefits when performing uniform BT dynamics compared to non-uniform BT dynamics. The frequency BT condition was related to a significantly lower variability of box position and higher gaze duration on the secondary task compared to the uniform BT dynamics. These findings suggest that participants are not or only negligible able to adapt to the uniform BT dynamics. Therefore, it is recommended to use the uniform BT dynamics as suggested and implemented in previous studies.2023DTDaniel Trommler et al.Head-Up Display (HUD) & Advanced Driver Assistance Systems (ADAS)Eye Tracking & Gaze InteractionAutoUI
Relevance, Effort, and Perceived Quality: Language Learners' Experiences with AI-Generated Contextually Personalized Learning MaterialArtificial intelligence has enabled scalable auto-creation of context-based personalized learning materials. However, it remains unclear how content personalization shapes the learners' experience. We developed one personalized and two non-personalized, crowdsourced versions of a mobile language learning app: (1) with personalized auto-generated photo flashcards, (2) the same flashcards provided through crowdsourcing, and (3) manually generated flashcards based on the same photos. A two-week in-situ study (n=64) showed that learners assessed the quality of the non-personalized auto-generated material to be on par with manually generated material, which means that auto-generation is viable. However, when the auto-generation was personalized, the learners' quality rating was significantly lower. Further analyses suggest that aspects such as prior expectations and required efforts must be addressed before learners can actually benefit from context-based personalization with auto-generated material. We discuss resulting design implications and provide an outlook on the role of content personalization in AI-supported learning.2023FDFiona Draxler et al.Generative AI (Text, Image, Music, Video)Programming Education & Computational ThinkingIntelligent Tutoring Systems & Learning AnalyticsDIS
Accidentally Evil: On Questionable Values in Smart Home Co-DesignAn ongoing mystery of HCI is how do well-intentioned designers consistently enable products with unintentionally evil consequences. Using “questionable values” as a lens, we retell and analyze four design scenarios for smart homes that were created by participants with an IoT toolkit we designed. The selected design scenarios reveal practices that violate principles of responsible smart home design. Through our analysis we show (1) how participants explore sensor-driven objectification of the home then leverage data for surveillance, nudging, and control over others; (2) how the dominant technosolutionist narratives of efficiency and productivity ground such questionable values; (3) and how the materiality of mass-produced sensors pre-mediates questionable design scenarios. We discuss how to attend to and utilize questionable values in design: Making space for questionable values will empower design researchers to better “look around corners”, anticipating tomorrow’s concerns and forestalling the worst of their harms.2023ABArne Berger et al.Anhalt University of Applied SciencesSmart Home Interaction DesignSmart Home Privacy & SecurityTechnology Ethics & Critical HCICHI
BrailleBuddy: A Tangible User Interface to Support Children with Visual Impairment in Learning BrailleLearning to read Braille is crucial to academic success for people with blindness or severe visual impairment. In our work, we investigate how we can support early learning of Braille with tangible computing. In a human-centered inclusive design process with interviews, six design iterations with prototypes, and feedback from experts, students, and teachers, we created BrailleBuddy. BrailleBuddy is a tangible user interface supporting children with visual impairments in learning Braille. We evaluated BrailleBuddy in a user study with children with blindness. Our results show that BrailleBuddy provides intrinsic motivation for learning Braille and can be used by children without supervision. BrailleBuddy complements the educational program as it allows children to play with and explore Braille characters at their own pace, thus lowering the challenge of learning to read Braille. In addition, an open-source toolkit is provided to enable educators and researchers to support individual requirements.2023FLFlorian Lang et al.LMU MunichVisual Impairment Technologies (Screen Readers, Tactile Graphics, Braille)Special Education TechnologyCHI
Pet-Robot or Appliance? Care Home Residents with Dementia Respond to a Zoomorphic Floor Washing Robot Any active entity that shares space with people is interpreted as a social actor. Based on this notion, we explore how robots that integrate functional utility with a social role and character can integrate meaningfully into daily practice. Informed by interviews and observations, we designed a zoomorphic floor cleaning robot which playfully interacts with care home residents affected by dementia. A field study shows that playful interaction can facilitate the introduction of utilitarian robots in care homes, being nonthreatening and easy to make sense of. Residents previously reacted with distress to a Roomba robot, but were now amused by and played with our cartoonish cat robot or simply tolerated its presence. They showed awareness of the machine-nature of the robot, even while engaging in pretend-play. A playful approach to the design of functional robots can thus explicitly conceptualize such robots as social actors in their context of use.2022EMEmanuela Marchetti et al.SDU Syddansk UniversitetElderly Care & Dementia SupportDomestic RobotsEmpowerment of Marginalized GroupsCHI
Guess the Data: Data Work to Understand How People Make Sense of and Use Simple Sensor Data from HomesSimple smart home sensors, e.g. for temperature or light, increasingly collect seemingly inconspicuous data. Prior work has shown that human sensemaking of such sensor data can reveal domestic activities. Such sensemaking presents an opportunity to empower people to understand the implications of simple smart home sensors. To investigate, we developed and field-tested the Guess the Data method, which enabled people to use and make sense of live data from their homes and to collectively interpret and reflect on anonymized data from the homes in our study. Our findings show how participants reconstruct behavior, both individually and collectively, expose the sensitive personal data of others, and use sensor data as evidence and for lateral surveillance within the household. We discuss the potential of our method as a participatory HCI method for investigating design of the IoT and implications created by doing data work on home sensors.2020AKAlbrecht Kurze et al.Chemnitz University of TechnologyIoT Device PrivacySmart Home Privacy & SecurityCHI
The Inflatable Cat: Idiosyncratic Ideation of Smart Objects for the HomeResearch on product experience has a history in investigating the sensory and emotional qualities of interacting with objects. However, this notion has not been fully expanded to the design space of co-designing smart objects. In this paper, we report on findings from a series of co-design workshops where we used the toolkit Loaded Dice in conjunction with a card set that aimed to support participants in reflecting the sensory qualities of domestic smart objects. We synthesize and interpret findings from our study to help illustrate how the workshops supported co-designers in creatively ideating concepts for emotionally valuable smart objects that better connect personal inputs with the output of smart objects. Our work contributes a case example of how a co-design approach that emphasizes situated sensory exploration can be effective in enabling co-designers to ideate concepts of idiosyncratic smart objects that closely relate to the characteristics of their domestic living situations.2019ABChristopher Frauenberger et al.Chemnitz University of TechnologySmart Home Interaction DesignParticipatory DesignCHI
P3 - How Usability Can Save the Day – Methodological Considerations for Making Automated Driving a Success StoryIt will not be long until Level 3 Automated Driving Systems (L3 ADS) enter the consumer market. An important role corresponds to methodology development. The present paper gives impetus to the process of developing robust methods for evaluating Human-Machine Interfaces (HMI) for L3 ADS. First, a literature review on automotive interfaces concerning methodology application is outlined showing that studies often lack to provide both self-report and observational data. To derive a comprehensive image of HMI quality, we recommend multi-method approach in user research. Subsequently, we provide an overview of state-of-the-art self-report and observational measures. From the availability of measures and the necessity to include both in user studies, the issue of the performance-preference dissociation arises. It threatens study designs and interpretation of results. Following methodological recommendations from the present work supports researchers and practitioners in the area of automated driving for proper study design and interpretation of study results.2018YFYannick Forster et al.Automated Driving Interface & Takeover DesignAutoUI