3,109 research outputs found

    A reflective characterisation of occasional user

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    This work revisits established user classifications and aims to characterise a historically unspecified user category, the Occasional User (OU). Three user categories, novice, intermediate and expert, have dominated the work of user interface (UI) designers, researchers and educators for decades. These categories were created to conceptualise user's needs, strategies and goals around the 80s. Since then, UI paradigm shifts, such as direct manipulation and touch, along with other advances in technology, gave new access to people with little computer knowledge. This fact produced a diversification of the existing user categories not observed in the literature review of traditional classification of users. The findings of this work include a new characterisation of the occasional user, distinguished by user's uncertainty of repetitive use of an interface and little knowledge about its functioning. In addition, the specification of the OU, together with principles and recommendations will help UI community to informatively design for users without requiring a prospective use and previous knowledge of the UI. The OU is an essential type of user to apply user-centred design approach to understand the interaction with technology as universal, accessible and transparent for the user, independently of accumulated experience and technological era that users live in

    Collaboration, Dialogue, and Human-Robot Interaction

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    CON-INFO: A Context-based Methodology for Designing and Assessing the Quality of Adaptable MUIs in Healthcare Applications

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    Mobile technology is an integral part of the modern healthcare environment. The mobile user interface (MUI) serves as the bridge between the application and healthcare professionals. It is important that the physician be able to easily express his needs on the MUI and correctly interpret the information displayed. However, there are many challenges that face the designer in designing and developing context-sensitive MUIs in this environment. The adaptability of the MUI is considered to be one of the most important issues to address. According to the World Health Organization (WHO), MUI adaptability is a major problem in the healthcare context. For the designer, the hope is that new technologies will be developed, such as mobile devices adaptable to different environments, to enable customization of the application to the user’s context. In this thesis, we propose a new methodology for designing a context-based adaptable MUI for healthcare applications. This methodology offers a new approach to automated MUI context adaptation, and provides a solution for both the provider (designer) of the healthcare application and the consumer (physician). New techniques for adapting MUIs offer new opportunities for the MUI designer to maximize the benefits of mobile health technology by providing the best possible way for healthcare professionals to perform their tasks efficiently and effectively. The proposed methodology is based on research contributions in four areas: (1) a new quality-in-use measurement model for validation purposes; (2) user stereotype modeling with a set of context descriptors, which formalize the domain expertise of the users; (3) context information modeling; and (4) use of the decision table technique to adapt the MUI features based on the context and the user stereotypes. The proposed quality-in-use model is inspired by the ISO/IEC 25010 and ISO/IEC 25022 international standards and adapted to healthcare applications. The first contribution is used in validating the quality-in-use of a software product developed according to the CON-INFO methodology, and the last three contributions are linked to form a methodology for development. The MUI features adapted to the needs of healthcare professionals have been implemented on the iPhone™ for validation purposes. An example of software for medical application is the Phoenix Health Information System (PHIS), which is in use at King Abdulaziz University Hospital (KAUH). PHIS2 is an updated desktop version developed based on Human-Computer Interaction (HCI) principles. A new mobile-based version of PHIS2 (PHIS2-M) has since been introduced, to make PHIS accessible from a mobile-based platform. The proposed context-based and rule-based approach for MUI feature adaptability resulted in a new version of PHIS2-M – PHIS2-MA (MA stands for mobile adaptation). This thesis validates the proposed methodology and clearly demonstrates its usefulness, providing details of the four empirical studies conducted with the end-users (physicians) in a real environment at the KAUH. The results of the formal studies reveal that our CON-INFO methodology for designing an adaptable MUI led to improvements to the current application and allowed researchers to test successive versions of the ‘final’ application

    Model-driven design, simulation and implementation of service compositions in COSMO

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    The success of software development projects to a large extent depends on the quality of the models that are produced in the development process, which in turn depends on the conceptual and practical support that is available for modelling, design and analysis. This paper focuses on model-driven support for service-oriented software development. In particular, it addresses how services and compositions of services can be designed, simulated and implemented. The support presented is part of a larger framework, called COSMO (COnceptual Service MOdelling). Whereas in previous work we reported on the conceptual support provided by COSMO, in this paper we proceed with a discussion of the practical support that has been developed. We show how reference models (model types) and guidelines (design steps) can be iteratively applied to design service compositions at a platform independent level and discuss what tool support is available for the design and analysis during this phase. Next, we present some techniques to transform a platform independent service composition model to an implementation in terms of BPEL and WSDL. We use the mediation scenario of the SWS challenge (concerning the establishment of a purchase order between two companies) to illustrate our application of the COSMO framework

    Modeling views in the layered view model for XML using UML

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    In data engineering, view formalisms are used to provide flexibility to users and user applications by allowing them to extract and elaborate data from the stored data sources. Conversely, since the introduction of Extensible Markup Language (XML), it is fast emerging as the dominant standard for storing, describing, and interchanging data among various web and heterogeneous data sources. In combination with XML Schema, XML provides rich facilities for defining and constraining user-defined data semantics and properties, a feature that is unique to XML. In this context, it is interesting to investigate traditional database features, such as view models and view design techniques for XML. However, traditional view formalisms are strongly coupled to the data language and its syntax, thus it proves to be a difficult task to support views in the case of semi-structured data models. Therefore, in this paper we propose a Layered View Model (LVM) for XML with conceptual and schemata extensions. Here our work is three-fold; first we propose an approach to separate the implementation and conceptual aspects of the views that provides a clear separation of concerns, thus, allowing analysis and design of views to be separated from their implementation. Secondly, we define representations to express and construct these views at the conceptual level. Thirdly, we define a view transformation methodology for XML views in the LVM, which carries out automated transformation to a view schema and a view query expression in an appropriate query language. Also, to validate and apply the LVM concepts, methods and transformations developed, we propose a view-driven application development framework with the flexibility to develop web and database applications for XML, at varying levels of abstraction

    People's Perceptions Toward Bias and Related Concepts in Large Language Models: A Systematic Review

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    Large language models (LLMs) have brought breakthroughs in tasks including translation, summarization, information retrieval, and language generation, gaining growing interest in the CHI community. Meanwhile, the literature shows researchers' controversial perceptions about the efficacy, ethics, and intellectual abilities of LLMs. However, we do not know how lay people perceive LLMs that are pervasive in everyday tools, specifically regarding their experience with LLMs around bias, stereotypes, social norms, or safety. In this study, we conducted a systematic review to understand what empirical insights papers have gathered about people's perceptions toward LLMs. From a total of 231 retrieved papers, we full-text reviewed 15 papers that recruited human evaluators to assess their experiences with LLMs. We report different biases and related concepts investigated by these studies, four broader LLM application areas, the evaluators' perceptions toward LLMs' performances including advantages, biases, and conflicting perceptions, factors influencing these perceptions, and concerns about LLM applications

    A Reference Architecture for Data-Driven and Adaptive Internet-Delivered Psychological Treatment Systems: Software Architecture Development and Validation Study

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    Background: Internet-delivered psychological treatment (IDPT) systems are software applications that offer psychological treatments via the internet. Such IDPT systems have become one of the most commonly practiced and widely researched forms of psychotherapy. Evidence shows that psychological treatments delivered by IDPT systems can be an effective way of treating mental health morbidities. However, current IDPT systems have high dropout rates and low user adherence. The primary reason is that the current IDPT systems are not flexible, adaptable, and personalized as they follow a fixed tunnel-based treatment architecture. A fixed tunnel-based architecture follows predefined, sequential treatment content for every patient, irrespective of their context, preferences, and needs. Moreover, current IDPT systems have poor interoperability, making it difficult to reuse and share treatment materials. There is a lack of development and documentation standards, conceptual frameworks, and established (clinical) guidelines for such IDPT systems. As a result, several ad hoc forms of IDPT models exist. Consequently, developers and researchers have tended to reinvent new versions of IDPT systems, making them more complex and less interoperable. Objective: This study aimed to design, develop, and evaluate a reference architecture (RA) for adaptive systems that can facilitate the design and development of adaptive, interoperable, and reusable IDPT systems. Methods: This study was conducted in collaboration with a large interdisciplinary project entitled INTROMAT (Introducing Mental Health through Adaptive Technology), which brings together information and communications technology researchers, information and communications technology industries, health researchers, patients, clinicians, and patients’ next of kin to reach its vision. First, we investigated previous studies and state-of-the-art works based on the project’s problem domain and goals. On the basis of the findings from these investigations, we identified 2 primary gaps in current IDPT systems: lack of adaptiveness and limited interoperability. Second, we used model-driven engineering and Domain-Driven Design techniques to design, develop, and validate the RA for building adaptive, interoperable, and reusable IDPT systems to address these gaps. Third, based on the proposed RA, we implemented a prototype as the open-source software. Finally, we evaluated the RA and open-source implementation using empirical (case study) and nonempirical approaches (software architecture analysis method, expert evaluation, and software quality attributes). Results: This paper outlines an RA that supports flexible user modeling and the adaptive delivery of treatments. To evaluate the proposed RA, we developed an open-source software based on the proposed RA. The open-source framework aims to improve development productivity, facilitate interoperability, increase reusability, and expedite communication with domain experts. Conclusions: Our results showed that the proposed RA is flexible and capable of adapting interventions based on patients’ needs, preferences, and context. Furthermore, developers and researchers can extend the proposed RA to various health care interventions.publishedVersio

    Designing for practice-based context-awareness in ubiquitous e-health environments

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    Existing approaches for supporting context-aware knowledge sharing in ubiquitous healthcare give little attention to practice-based structures of knowledge representation. They guide knowledge re-use at an abstract level and hardly incorporate details of actionable tasks and processes necessary for accomplishing work in a real-world context. This paper presents a context-aware model for supporting clinical knowledge sharing across organizational and geographical boundaries in ubiquitous e-health. The model draws on activity and situation awareness theories as well as the Belief-Desire Intention and Case-based Reasoning techniques in intelligent systems with the goal of enabling clinicians in disparate locations to gain a common representation of relevant situational information in each other's work contexts based on the notion of practice. We discuss the conceptual design of the model, present a formal approach for representing practice as context in a ubiquitous healthcare environment, and describe an application scenario and a prototype system to evaluate the proposed approach
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