A design method card deck helps designers understand and provoke thinking by presenting each method in a simple format and allow designers to switch between methods seamlessly by maintaining the same simple format across the deck. However, recent observations have shown designers hesitate to use a card deck due to the lack of support, while other tools have provided identified support with generative AI. Through a formative study, we identified the specific support designers need when applying the design method cards and intentions in integrating generative AI. Accordingly, we developed the intelligent design method card deck, I-Card, which integrates generative AI to provide applicable design methods, design knowledge and data support, and interactive and dynamic support. A user study demonstrates that I-Card improved the design efficiency and applicability by offering personalized guidance, enhanced decision-making with comprehensive data generation and provided more design inspiration via interactive support.

The advancement of wearable intelligent systems presents a unique opportunity to transform how humans interact with digital content. This workshop explores the design of Interactive Multimodal Information Retrieval and Access systems specifically tailored for Heads-Up Computing environments. By leveraging multimodal inputs, such as voice, gaze, and gesture, these systems enable real-time, hands-free access to digital information, facilitating seamless and efficient interaction. The goal is to support tasks requiring rapid information access in dynamic environments while ensuring users remain "heads-up" and engaged with the real world. This half-day workshop will share research outcomes and best practices, foster community building, and facilitate discussions on key challenges. By bringing together researchers and practitioners, it aims to drive further advancements in both research and practical applications within this rapidly evolving field.

To enhance the engagement and significance of olfaction as a novel medium in multimedia systems, we aim to integrate different hedonic odorous cues into narratives to augment immersion in virtual experiences. We introduce the ScentClue system, comprising (1) an original and murder-themed experimental film incorporating four distinct hedonic odor cues synchronized with audiovisual elements, (2) a neck-worn scent delivery device capable of dispensing four different odors, and (3) an Unreal Engine-based virtual cinema environment enabling rapid control of video playback and odor dissemination. Experimenting with 18 participants divided into control groups with and without odor stimuli, we validated the system’s usability and effectiveness of odor cue settings. Furthermore, we found that the use of odors with different hedonic qualities could enhance odor recognition, amplify thematic story ambiance, and aid in the rapid differentiation of complex relationships. Finally, we discussed expanded scenarios and interaction modalities for ScentClue, proposing future narrative-driven olfaction-enhanced multimedia designs with considerations for odor cue settings, odor material selection, and scent-releasing setup, particularly unpleasant odors.

Artificial intelligence (AI) is reshaping health information consumption on social media by tailoring content through algorithmic personalization. While user engagement with online health content has been widely studied, less is known about how technological features influence intention to use AI-powered social media for health information. Building on the affordance theory, this study proposes a research model linking algorithmic affordances with usage intention. An online survey with 1,051 users showed that content filtering was positively related to perceived information usefulness and willingness to rely on the platform. In contrast, automated decision-making and human-algorithm interplay were negatively related to willingness to rely on the platform and information usefulness, respectively. Both information usefulness and willingness to rely on the platform were positively related to intention to use these AI-driven platforms. The findings advance theoretical understanding of algorithmic affordances in health communication and provide practical guidance for improving user experiences on AI-driven platforms.

Airflow is recognized as an effective method for inducing the illusion of self-motion (vection) and reducing motion sickness in virtual reality. However, the quantitative relationship between virtual motion and the airflow perceived as consistent with it has not been fully explored. To address this gap, this study conducted three experiments. In Experiment 1, we carried out a series of cross-modal matching tasks to establish the relationship between the speed of virtual motion and the airflow speed perceived as consistent with it, revealing a strong linear correlation. In Experiment 2, we introduced the concept of an "Airflow Gradient" to simulate the bodily sensation of curvilinear motion and examined the relationship between the radius and angular velocity of the motion and the difference in airflow speed between the left and right sides. The results indicated a linear relationship between the radius and the left-right airflow speed difference, while the angular velocity showed a near-quadratic pattern, similar to the centripetal acceleration formula. Based on these findings, Experiment 3 developed a dynamic airflow scheme and compared it with constant airflow and no-airflow conditions during locomotion tasks in a complex urban environment. The results demonstrated that dynamic airflow, which ensures consistency between visual and bodily vection, further reduces motion sickness, enhances presence, and provides a more natural and consistent virtual motion experience.

Text entry in virtual reality (VR) often faces challenges in terms of efficiency and task loads. Prior research has explored various solutions, including specialized keyboard layouts, tracked physical devices, and hands-free interaction. Yet, these efforts often fall short of replicating the efficiency of real-world text entry, or introduce additional spatial and device constraints. This study leverages the extensive capabilities of large language models (LLMs) in context perception and text prediction to enhance text entry efficiency by reducing users’ manual keystrokes. Three LLM-assisted text entry methods - Simplified Spelling, Content Prediction, and Keyword-to-Sentence Generation - are introduced, aligning with user cognition and the contextual predictability of English text at word, grammatical structure, and sentence levels. Through user experiments encompassing various text entry tasks on an Oculus-based VR prototype, these methods demonstrate a 16.4%, 49.9%, 43.7% reduction in manual keystrokes, translating to efficiency gains of 21.4%,74.0%, 76.3%, respectively. Importantly, these methods do not increase manual corrections compared to manual typing, while significantly reducing physical, mental, and temporal loads and enhancing overall usability. Long-term observations further reveal users’ strategies for using these LLM-assisted methods, showing that users’ proficiency with the methods can reinforce their positive effects on text entry efficiency.

Collective 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.

The amount and quality of mathematical language in the family are positively associated with promoting children’s mathematical abilities. However, mathematical language in many families is poor. Through need-finding investigation, we developed MathKingdom, a voice-agent-based game that helps children aged 4–7 learn and use rich, accurate mathematical language (e.g., mathematical expressions related to measurement, sequence, patterns). The game has four flows, in which users can wake up, transform, decorate, and perform as their avatars, as well as practice basic mathematical vocabulary, mathematical single sentences, coherent mathematical statements, and free expression. We refined the system design through wizard-of-oz testing and then evaluated it with 18 families. The results showed that MathKingdom effectively engaged children, enhanced their mathematical language skills and mathematical abilities, and encouraged parent-child conversations about math.

Autonomous learning regards students as the center and orientation rather than teachers’ guidance. During autonomous learning, information seeking is not only a process of interactions with systems and stakeholders, but also a process of learning and cognitive transformation from low-level to high-level activities. This study investigated users’ cognitive process and cognitive paths, as well as the creation strategies for independent topic selection during the information seeking process. We conducted a longitudinal study through tracking interviews with eight university students who planned to select a topic for their theses or independent study. The interviews were conducted weekly to collect data of their cognitive process and seeking behaviors. It is found that: (1) four lower levels of cognitive process (understanding, applying, analyzing and evaluating) often occur during the stages before formulation, while creating occurs in the formulation stage; (2) three cognitive paths for topic selection were identified: "understand - apply - create", "understand - analyze - create" and "understand - analyze - evaluate - create", and (3) two creation strategies for topic selection according to the duration of creation stages were identified: Incubation and Verification. These results shed light on the design of search systems that could better assist the autonomous learning process and for users to accomplish creative learning tasks.

Creating personalized 3D printing objects has become increasingly popular with the advance in end-user modeling tools and fabrication techniques. However, it remains challenging for novice makers to design and fabricate functional objects with mechanical motion such as linear or rotational. To empower users to add mechanical movements to their models for particular needs, we first investigate the commonly used 3D printable mechanisms and parameterize four mechanical primitives. We then provide a computational approach to reconfigure the mechanical primitives to user-provided 3D models, with an underlying structural optimization procedure according to a specified bending force. We further showcase a set of design examples and conduct a user study to demonstrate the potential of our approach in creating personalized functional artifacts.

Repetitive tasks widely exist in applied fields of human-computer interaction. One underestimated example is parcel scanning, which has consistent operation difficulty but comprises multiple processes (e.g., label seeking and scanning, result confirming, and parcel relocating), involving respective cognitive requirements. Many devices are developed to facilitate repetitive operations, but few are to reduce fluctuating cognitive load throughout task processes. We present the eye-tracking augmented reality headset that integrates foveated vision detection and smooth pursuit of eye tracking and investigate how it can reduce cognitive load in the repetitive task. In total, 33 participants completed a set of parcel scanning tasks with the headset and their visual and cognitive performance were assessed. The results show that the headset maintained high scanning efficiency and lower cognitive load across the tasks with varying difficulties and it significantly reduced the participants’ cognitive load during the processes of barcode seeking and scanning and result confirmation. The headset demonstrated good usability and ease of use. Implications for how the case study result could be used in generalizing applications are discussed.

Museum exhibitions on traditional Chinese paintings are gaining popularity for educational and cultural value. Chinese paintings are characterized by a long history and implicit emotional expression, and it is challenging for non-professional and non-Chinese visitors to understand. To enhance museum visitors’ interest and comprehension of Chinese artworks, we design an EEG-based interactive installation. The installation simulates the process of creation of a work of art, in this case a painting. Visitors can control the generation of lines, colors, and movements of characters by wearing a commercial EEG headset. Our interactive design contributes a novel experience of ’painting with your mind’ and at the same time transform the exhibition into an enjoyable game experience.

Recent advances in Artificial Intelligence raise interest in its participation in design activity, which is commonly considered to be complex and human-dominated. In this work, we aim to examine AI roles in early design stages. The human ideation components and design tools related to AI are discussed in a framework of AI-augmented design support. The framework develops a hierarchy of design cognition (basis), approaches and principles. The cognitive models are constructed in an empirical study of 30 designers (26 for analysis, 4 for pilot study) by concurrent Think-Aloud protocol and behavior analysis. The process of producing new design ideas is explained by a transparent analysis of designers’ language and behaviors. Three strategies to organize cognitive activities in design ideation are summarized: develop structured consideration, relate to a scenario, and stick-to designing. These strategies suggest AI could act as (1) representation creation, (2) empathy trigger and (3) engagement, in principles of “knowledge-driven” and “decompose-and-integrate”. The design support with AI provides new perspectives on computer-based design tools that limit to well-defined design variables. The framework is built on a generic notion of design activity and “mimic” human design rationales, expected to benefit research of domain-independent computational design supports and cognitive supports.

More and more social Q&A platforms are launching a new business model to monetize online knowledge. This monetizing process introduces a more complicated cost and benefit tradeoff to users, especially for askers' concerns. Much of the previous research was conducted in the context of free‐based Q&A platform, which hardly explains the triggers that motivate askers' pay intention. Based on the theories of social exchange and social capital, this study aims to identify and examine the antecedents of askers' pay intention from the perspective of benefit and cost. We empirically test our predictions based on survey data collected from 322 actual askers in a well‐known trilateral payment‐based social Q&A platform in China. The results by partial least squares (PLS) analysis indicate that besides noneconomic benefits including self‐enhancement, social support, and entertainment, financial factors such as cost and benefit have significant influences on the perceived value of using trilateral payment‐based Q&A platforms. More important, we further identify that the effect of financial benefit is moderated by perceived reciprocity belief, and the effect of perceived value is moderated by perceived trust in answerers. Our findings contribute to the previous literature by proposing a theoretical model that explains askers' behavioral intention, and the practical implications for payment‐based Q&A service providers and participants.

This paper describes conceptual, technological and information environmental terrain across which scholarship in the inter-related disciplines of information and learning sciences occurs. The aim is to encourage researchers across these fields to find one another's work, as we engage in ongoing theory-building around inquiry and learning phenomena, to enrich scholarship and pragmatic design of learning innovations across both domains.

In motion-sensing interaction with large displays through bare hands, we can observe that users alternate their hands and move their bodies frequently. What cause such actions and how these actions affect free hand interaction results are less systematically investigated. To address this gap in knowledge, we conducted studies on Pointer-Acceleration (PA)-based free hand interactions of target selection and found that (1) users made more frequent hand alternations when selecting small targets with large movement amplitudes, as in such cases users were not only affected by observable arm fatigue, but were also motivated to switch hands for higher selection accuracy and convenience; (2) hand alternation led to the hand orientation effects: target selection on display areas at the operating hand’s side was more efficient and accurate than that at the opposite side; (3) large movement amplitudes on the user interface increased users’ physical movements in front of the large display, which harmed selection efficiency; (4) selection of small targets led to a closer interaction distance, while large movement amplitudes led to a larger interaction distance; and (5) selection results were affected by interaction distances, as users gained high efficiency, but low accuracy at a large distance and low efficiency, but high accuracy at a close distance. Given these results, this article discusses practical implications for applying PA-based free hand interaction techniques and designing related user interfaces on large displays.

Human epidermis, as the largest organ on body, has become a new design platform for wearable computing. The availability of miniature electronics makes more possibilities for on-skin designs. In this paper, we present AnimSkin, a thin-film interface, which will emit dynamic color animations directly on skin. This is done by using thermochromic material embedded with transparent electrode acting as a capacitive sensor. Moreover, an accessible and low-cost fabrication method is introduced. Individuals could also customize aesthetic graphic designs by following the detailed fabrication process to achieve personalized patterns. We propose four different dynamic types of color animation by applying certain voltage to the heating circuitry. With two examples, Email Reminder and Light Control System, we demonstrate how AnimSkin can be integrated into everyday life, and specifically, we show how AnimSkin can benefit areas such as on-skin design, thin-film interface and beauty technology.

The "Search as Learning" (SAL) workshop is focused on an area within the information retrieval field that is only beginning to emerge: supporting users in their learning whilst interacting with information content.

Current large display-based user interfaces are mainly derived from normal-sized desktop screens and the extra-large size causes difficulties in information navigation and perception. Therefore, user engagement in large display-based information interaction is relatively low. In order to address the user engagement issue, in this paper we propose the distance-driven adaptive interface, which specialises in performing navigation tasks within large displays. We conducted an initial exploratory study with 30 participants to examine how the distance correlated with interaction performances in large displays. Given the findings we conducted an experimental study with an additional 31 participants to further investigate how the distance-driven interface satisfies users’ distance requirements and improves user engagement within six dimensions. The results show that the distance-driven interface offered a statistically significant user engagement improvement in terms of novelty, felt involvement, focused attention and endurability. Importantly, linear correlations between the distance, interaction efficiency and accuracy were identified—in that efficiency increased and accuracy decreased with increasing distance.

A proposal summary for the EuroHCIR workshop at SIGIR2013.

The "How Was Your Day" (HWYD) companion is an embodied conversational agent that can discuss work-related issues, entering free-form dialogues while discussing issues surrounding a typical work day. The open-ended nature of these interactions requires new models of evaluation. Here, we describe a paradigm and methodology for evaluating the main aspects of such functionality in conjunction with overall system behavior, with respect to three parameters: functional ability (i.e., does it do the "rightâ thing conversationally), content (i.e., does it respond appropriately to the semantic context), and emotional behavior (i.e., given the emotional input from the user, does it respond in an emotionally appropriate way). We demonstrate the functionality of our evaluation paradigm as a method for both grading current system performance, and targeting areas for particular performance review. We show correlation between, for example, automatic speech recognition performance and overall system performance (as is expected in systems of this type), but beyond this, we show where individual utterances or responses, indicated as positive or negative, characterize system performance, and demonstrate how our combination evaluation approach highlights issues (both positive and negative) in the companion system's interaction behavior.

Abstract Today information‐intensive work tasks in professional settings involve highly dynamic information utilization in which information seeking and searching tasks are taking a more central role. This article considers the concept of task in the context of information studies in order to provide a definitional clarity for task‐based information seeking and retrieval studies. We identify (1) the central task levels as well as (2) the kinds of dimensions connected to the levels from the perspective of information studies. The analysis is aimed to serve as a conceptual starting point for empirical studies in the research area. The focus is on some central aspects of tasks that are recognized within information studies as well as related research areas (e.g., organizational studies). We define two levels of information‐related subtasks: information seeking tasks and information search tasks. Information retrieval tasks are explicitly considered as a specific type of information search task. We describe differences and connections between these task levels. Finally, the implications of the proposed conceptual framework for information studies are discussed.

Abstract This report presents a case study of the development of an interface for a novel and complex form of document retrieval: searching for texts written in foreign languages based on native language queries. Although the underlying technology for achieving such a search is relatively well understood, the appropriate interface design is not. A study involving users from the beginning of the design process is described, and it covers initial examination of user needs and tasks, preliminary design and testing of interface components, building, testing, and refining the interface, and, finally, conducting usability tests of the system. Lessons are learned at every stage of the process, leading to a much more informed view of how such an interface should be built.

This paper reports on the user-centered design methodology and techniques used for the elicitation of user requirements and how these requirements informed the first phase of the user interface design for a Cross-Language Information Retrieval System. We describe a set of factors involved in analysis of the data collected and, finally discuss the implications for user interface design based on the findings.