Suchergebnisse

Semantic User Interfaces (SUIs), are sets of interrelated, static, domain specific documents having layout and content, whose interpretation is defined through semantic decoration. SUIs are declarative in nature. They allow program composition by the user herself at the user interface level. The operation of SUI based applications follow a service oriented approach. SUI elements referenced in user requests are automatically mapped to reusable service provider components, whose contracts are specified in domain ontologies. This assures semantic separation of user interface components from elements of the underlying application system infrastructure, which allows full separation of concerns during system development; real, application independent, reusable components; user editable applications and generic learnability. This article presents the architecture and components of a SUI framework, basic elements of SUI documents and relevant properties of domain ontologies for SUI documents. The basics of representation and operation of SUI applications are explained through a motivating example.

Se describen cuatro proyectos de interfaces de sistemas de información que se están desarrollando en ESRIN (establecimiento de la Agencia Espacial Europea, en Frascati). Cada uno de ellos muestra un enfoque diferente del diseño de interfaces, pero todos tienen en común el responder a los objetivos, tareas y características de los usuarios. Se sugiere que la próxima generación de sistemas de información científica se tendrá que diseñar para permitir el acceso directo de los usuarios finales a una gran variedad de fuentes de información a través de una interfaz común. El diseño de tales sistemas y de sus interfaces debería basarse en un análisis multinivel de objetivos, tareas y puntos de vista propios de la materia de trabajo de cada usuario.

This paper discusses principles of educational multimedia user interface design. The purpose of these principles is to maximize the learning effectiveness of multimedia applications. The principles are based on the results of studies in psychology, computer science, instructional design, and graphics design. The principles help user interface designers make decisions about the learning materials, learners, tasks that the learners perform, and tests for measuring learning performance.

AbstractThis article presents a task‐analytic methodology for evaluating user interfaces in terms of ease of learning and discusses the results of an empirical study designed to test the validity of the methodology. The proposed methodology represents a tool that enables user interface designers and human factors practitioners to predict the ease of learning of a given interface by a particular user. Ease of learning is measured by the cognitive learning time which is modelled as a function of the cognitive complexity associated with learning a given interface and the learner's prior knowledge. Measures of cognitive complexity and prior knowledge are described and tested. The results of the empirical study are promising. The methodology accurately predicted the relative ease of learning of 27 text‐editing tasks and accounted for more than 77% of the variance among the observed learning times.RésuméCet article décrit une méthodologie pour l'évaluation de lafacilité d'apprentissage des interfaces utilisateur, basée sur l'analyse de tǎches. L'article discute aussi les résultats d'une étude empirique ayant pour but de tester la validité de la méthodologie. Les concepteurs d'interfaces peuvent utiliser cette méthodologie pour prédire la facilité d'apprentissage d'une interface donnée par un utilisateur particulier. La facilité d'apprentissage est mesurée par le temps cognitif d'apprentissage qui est estimé en fonction de la complexité cognitive associée à l'apprentissage d'une interface donnée et les connaissances antérieures de l'utilisateur. Des mesures de la complexité cognitive et les connaissances antérieures sont proposées et testées. Les résultats de l'étude empirique sont prometteurs. La méthodologie a prédit avec précision la facilité d'apprentissage de 27 tǎches de traitement de texte et a expliqué plus de 77% de la variance des temps d'apprentissage observés.

Metadata and User Interfaces: Promises and Problems

Education and self-improvement are key features of human behavior. However, learning in the physical world is not always desirable or achievable. That is how simulators came to be. There are domains where purely virtual simulators can be created in contrast to physical ones. In this research we present a novel environment for learning, using a natural user interface. We, humans, are not designed to operate and manipulate objects via keyboard, mouse or a controller. The natural way of interaction and communication is achieved through our actuators (hands and feet) and our sensors (hearing, vision, touch, smell and taste). That is the reason why it makes more sense to use sensors that can track our skeletal movements, are able to estimate our pose, and interpret our gestures. After acquiring and processing the desired – natural input, a system can analyze and translate those gestures into movement signals.