12,920 research outputs found
The MASTERMIND User Interface Generation Project
Graphical user interfaces are difficult to construct and, consequently, suffer from high development and maintenance costs. Automatic generation from declarative descriptions can reduce costs and enforce design principles. MASTERMIND is a model based approach to user interface generation. Designers model different aspects of an interface using declarative modeling languages, and tools synthesize these models into run-time code. The design process begins with user task and application modeling. These models are then refined into dialogue, presentation, and interaction models and an application API. These latter models drive the synthesis of run-time code. A design tool called Dukas is employed to support the refinement of task models into dialogue models
Robot graphic simulation testbed
The objective of this research was twofold. First, the basic capabilities of ROBOSIM (graphical simulation system) were improved and extended by taking advantage of advanced graphic workstation technology and artificial intelligence programming techniques. Second, the scope of the graphic simulation testbed was extended to include general problems of Space Station automation. Hardware support for 3-D graphics and high processing performance make high resolution solid modeling, collision detection, and simulation of structural dynamics computationally feasible. The Space Station is a complex system with many interacting subsystems. Design and testing of automation concepts demand modeling of the affected processes, their interactions, and that of the proposed control systems. The automation testbed was designed to facilitate studies in Space Station automation concepts
Emerging from the MIST: A Connector Tool for Supporting Programming by Non-programmers
Software development is an iterative process. As user re-quirements emerge software applications must be extended to support the new requirements. Typically, a programmer will add new code to an existing code base of an application to provide a new functionality. Previous research has shown that such extensions are easier when application logic is clearly separated from the user interface logic. Assuming that a programmer is already familiar with the existing code base, the task of writing the new code can be considered to be split into two sub-tasks: writing code for the application logic; that is, the actual functionality of the application; and writing code for the user interface that will expose the functionality to the end user.
The goal of this research is to reduce the effort required to create a user interface once the application logic has been created, toward supporting scientists with minimal pro-gramming knowledge to be able to create and modify pro-grams. Using a Model View Controller based architecture, various model components which contain the application logic can be built and extended. The process of creating and extending the views (user interfaces) on these model components is simplified through the use of our Malleable Interactive Software Toolkit (MIST), a tool set an infrastructure intended to simplify the design and extension of dynamically reconfigurable interfaces.
This paper focuses on one tool in the MIST suite, a connec-tor tool that enables the programmer to evolve the user interface as the application logic evolves by connecting related pieces of code together; either through simple drag-and-drop interactions or through the authoring of Python code. The connector tool exemplifies the types of tools in the MIST suite, which we expect will encourage collabora-tive development of applications by allowing users to inte-grate various components and minimizing the cost of de-veloping new user interfaces for the combined compo-nents
Towards an Intelligent Tutor for Mathematical Proofs
Computer-supported learning is an increasingly important form of study since
it allows for independent learning and individualized instruction. In this
paper, we discuss a novel approach to developing an intelligent tutoring system
for teaching textbook-style mathematical proofs. We characterize the
particularities of the domain and discuss common ITS design models. Our
approach is motivated by phenomena found in a corpus of tutorial dialogs that
were collected in a Wizard-of-Oz experiment. We show how an intelligent tutor
for textbook-style mathematical proofs can be built on top of an adapted
assertion-level proof assistant by reusing representations and proof search
strategies originally developed for automated and interactive theorem proving.
The resulting prototype was successfully evaluated on a corpus of tutorial
dialogs and yields good results.Comment: In Proceedings THedu'11, arXiv:1202.453
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