The user’s experience with a recommender system is significantly shaped by the dynamics of user-algorithm interactions. These interactions are often evaluated using interaction qualities, such as controllability, trust, and autonomy, to gauge their impact. As part of our effort to systematically categorize these evaluations, we explored the suitability of the interaction qualities framework as proposed by Lenz, Dieffenbach and Hassenzahl. During this examination, we uncovered four challenges within the framework itself, and an additional external challenge. In studies examining the interaction between user control options and interaction qualities, interdependencies between concepts, inconsistent terminology, and the entity perspective (is it a user’s trust or a system’s trustworthiness) often hinder a systematic inventory of the findings. Additionally, our discussion underscored the crucial role of the decision context in evaluating the relation of algorithmic affordances and interaction qualities. We propose dimensions of decision contexts (such as ‘reversibility of the decision’, or ‘time pressure’). They could aid in establishing a systematic three-way relationship between context attributes, attributes of user control mechanisms, and experiential goals, and as such they warrant further research. In sum, while the interaction qualities framework serves as a foundational structure for organizing research on evaluating the impact of algorithmic affordances, challenges related to interdependencies and context-specific influences remain. These challenges necessitate further investigation and subsequent refinement and expansion of the framework.
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Introduction: Sensor-feedback systems can be used to support people after stroke during independent practice of gait. The main aim of the study was to describe the user-centred approach to (re)design the user interface of the sensor feedback system “Stappy” for people after stroke, and share the deliverables and key observations from this process. Methods: The user-centred approach was structured around four phases (the discovery, definition, development and delivery phase) which were fundamental to the design process. Fifteen participants with cognitive and/or physical limitations participated (10 women, 2/3 older than 65). Prototypes were evaluated in multiple test rounds, consisting of 2–7 individual test sessions. Results: Seven deliverables were created: a list of design requirements, a personae, a user flow, a low-, medium- and high-fidelity prototype and the character “Stappy”. The first six deliverables were necessary tools to design the user interface, whereas the character was a solution resulting from this design process. Key observations related to “readability and contrast of visual information”, “understanding and remembering information”, “physical limitations” were confirmed by and “empathy” was additionally derived from the design process. Conclusions: The study offers a structured methodology resulting in deliverables and key observations, which can be used to (re)design meaningful user interfaces for people after stroke. Additionally, the study provides a technique that may promote “empathy” through the creation of the character Stappy. The description may provide guidance for health care professionals, researchers or designers in future user interface design projects in which existing products are redesigned for people after stroke.
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This position paper presents a proposal for evaluating interaction with light in a mixed reality setup. Current processes of designing and testing new forms of user interaction (UI) for controlling lighting are long and end up being restricted in actually testing a small number of possible interactions. Apart from the apparent advantage of overcoming testing a small number of potential interactions, the advantages of a simulated environment lie in the fact that such an environment is fully controllable and adaptable to the researchers' needs. Finally, we sketch potential challenges of using a mixed reality setup for evaluating interaction with light.
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Our study introduces an open general-purpose platform for the embodiment of conversational AI systems. Conversational User-interface Based Embodiment (CUBE) is designed to streamline the integration of embodied solutions into text-based dialog managers, providing flexibility for customization depending on the specific use case and application. CUBE is responsible for naturally interacting with users by listening, observing, and responding to them. A detailed account of the design and implementation of the solution is provided, as well as a thorough examination of how it can be integrated by developers and AI dialogue manager integrators. Through interviews with developers, insight was gained into the advantages of such systems. Additionally, key areas that require further research were identified in the current challenges in achieving natural interaction between the user and the embodiments. CUBE bridges some of the gaps by providing controls to further develop natural non-verbal communication.
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Game User Research is an emerging field that ties together Human Computer Interaction, Game Development, and Experimental Psychology, specifically investigating the interaction between players and games. The community of Game User Research has been rapidly evolving for the past few years, extending and modifying existing methodologies used by the HCI community to the environment of digital games. In this workshop, we plan to investigate the different methodologies currently in practice within the field as well as their utilities and drawbacks in measuring game design issues or gaining insight about the players' experience. The outcome of the workshop will be a collection of lessons from the trenches and commonly used techniques published in a public online forum. This will extend the discussion of topics beyond the workshop, and serve as a platform for future work. The workshop will be the first of its kind at CHI, tying together HCI research and Game User Research.
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As interactive systems become increasingly complex and entwined with the environment, technology is becoming more and more invisible. This means that much of the technology that people come across every day goes unnoticed and that the (potential) workings of ambient systems are not always clearly communicated to the user. The projects discussed in this paper are aimed at increasing public understanding of the existence, workings and potential of screens and ambient technology by visualizing its potential. To address issues and implications of visibility and system transparency, this paper presents work in progress as example cases for engaging people in ambient monitoring and public screening. This includes exploring desired scenarios for ambient monitoring with users as diverse as elderly people or tourists and an interactive tool for mapping public screens.
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BACKGROUND: Non-use of and dissatisfaction with ankle foot orthoses (AFOs) occurs frequently. The objective of this study is to gain insight in the conversation during the intake and examination phase, from the clients’ perspective, at two levels: 1) the attention for the activities and the context in which these activities take place, and 2) the quality of the conversation. METHODOLOGY: Semi-structured interviews were performed with 12 AFO users within a two-week period following intake and examination. In these interviews, and subsequent data analysis, extra attention was paid to the needs and wishes of the user, the desired activities and the environments in which these activities take place. RESULTS AND CONCLUSION: Activities and environments were seldom inquired about or discussed during the intake and examination phase. Also, activities were not placed in the context of their specific environment. As a result, profundity lacks. Consequently, orthotists based their designs on a ‘reduced reality’ because important and valuable contextual information that might benefit prescription and design of assistive devices was missed. A model is presented for mapping user activities and user environments in a systematic way. The term ‘user practices’ is introduced to emphasise the concept of activities within a specific environment.
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Background: During the process of decision-making for long-term care, clients are often dependent on informal support and available information about quality ratings of care services. However, clients do not take ratings into account when considering preferred care, and need assistance to understand their preferences. A tool to elicit preferences for long-term care could be beneficial. Therefore, the aim of this qualitative descriptive study is to understand the user requirements and develop a web-based preference elicitation tool for clients in need of longterm care. Methods: We applied a user-centred design in which end-users influence the development of the tool. The included end-users were clients, relatives, and healthcare professionals. Data collection took place between November 2017 and March 2018 by means of meetings with the development team consisting of four users, walkthrough interviews with 21 individual users, video-audio recordings, field notes, and observations during the use of the tool. Data were collected during three phases of iteration: Look and feel, Navigation, and Content. A deductive and inductive content analysis approach was used for data analysis. Results: The layout was considered accessible and easy during the Look and feel phase, and users asked for neutral images. Users found navigation easy, and expressed the need for concise and shorter text blocks. Users reached consensus about the categories of preferences, wished to adjust the content with propositions about well-being, and discussed linguistic difficulties. Conclusion: By incorporating the requirements of end-users, the user-centred design proved to be useful in progressing from the prototype to the finalized tool ‘What matters to me’. This tool may assist the elicitation of client’s preferences in their search for long-term care.
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From an interspecies perspective, we advocate for a theoretical foundation aimed at facilitating further research towards digitally mediated human-animal interaction. The proposed framework follows an approach we call 'digitally complemented zoomorphism' and recognizes 'play' as a free and voluntary activity that is shared by both animals and humans. As a result, three initial design guidelines will emerge. Our work is pursued in order to provide animals with stimulations which stem from a closer understanding of their perceptions and are not solely designed around human subjectivity.
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Algorithmic affordances are defined as user interaction mechanisms that allow users tangible control over AI algorithms, such as recommender systems. Designing such algorithmic affordances, including assessing their impact, is not straightforward and practitioners state that they lack resources to design adequately for interfaces of AI systems. This could be amended by creating a comprehensive pattern library of algorithmic affordances. This library should provide easy access to patterns, supported by live examples and research on their experiential impact and limitations of use. The Algorithmic Affordances in Recommender Interfaces workshop aimed to address key challenges related to building such a pattern library, including pattern identification features, a framework for systematic impact evaluation, and understanding the interaction between algorithmic affordances and their context of use, especially in education or with users with a low algorithmic literacy. Preliminary solutions were proposed for these challenges.
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