100,498 research outputs found

    THE "POWER" OF TEXT PRODUCTION ACTIVITY IN COLLABORATIVE MODELING : NINE RECOMMENDATIONS TO MAKE A COMPUTER SUPPORTED SITUATION WORK

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    Language is not a direct translation of a speaker’s or writer’s knowledge or intentions. Various complex processes and strategies are involved in serving the needs of the audience: planning the message, describing some features of a model and not others, organizing an argument, adapting to the knowledge of the reader, meeting linguistic constraints, etc. As a consequence, when communicating about a model, or about knowledge, there is a complex interaction between knowledge and language. In this contribution, we address the question of the role of language in modeling, in the specific case of collaboration over a distance, via electronic exchange of written textual information. What are the problems/dimensions a language user has to deal with when communicating a (mental) model? What is the relationship between the nature of the knowledge to be communicated and linguistic production? What is the relationship between representations and produced text? In what sense can interactive learning systems serve as mediators or as obstacles to these processes

    A Plan-Based Model for Response Generation in Collaborative Task-Oriented Dialogues

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    This paper presents a plan-based architecture for response generation in collaborative consultation dialogues, with emphasis on cases in which the system (consultant) and user (executing agent) disagree. Our work contributes to an overall system for collaborative problem-solving by providing a plan-based framework that captures the {\em Propose-Evaluate-Modify} cycle of collaboration, and by allowing the system to initiate subdialogues to negotiate proposed additions to the shared plan and to provide support for its claims. In addition, our system handles in a unified manner the negotiation of proposed domain actions, proposed problem-solving actions, and beliefs proposed by discourse actions. Furthermore, it captures cooperative responses within the collaborative framework and accounts for why questions are sometimes never answered.Comment: 8 pages, to appear in the Proceedings of AAAI-94. LaTeX source file, requires aaai.sty and epsf.tex. Figures included in separate file

    The Structured Process Modeling Theory (SPMT): a cognitive view on why and how modelers benefit from structuring the process of process modeling

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    After observing various inexperienced modelers constructing a business process model based on the same textual case description, it was noted that great differences existed in the quality of the produced models. The impression arose that certain quality issues originated from cognitive failures during the modeling process. Therefore, we developed an explanatory theory that describes the cognitive mechanisms that affect effectiveness and efficiency of process model construction: the Structured Process Modeling Theory (SPMT). This theory states that modeling accuracy and speed are higher when the modeler adopts an (i) individually fitting (ii) structured (iii) serialized process modeling approach. The SPMT is evaluated against six theory quality criteria

    A Research Review on Building Information Modeling in Construction―An Area Ripe for IS Research

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    This article presents a review of the research on Building Information Modeling (BIM) in construction, with the aim of identifying areas in this domain where IS research can contribute. The concept of BIM comprises an infrastructure of IT tools supporting collaborative and integrated design, assembly, and operation of buildings. This integrated construction approach, with all stakeholders editing or retrieving information from commonly shared models, requires major changes to well-established processes, organizational roles, contractual practices, and collaborative arrangements in the construction industry. Through a review of 264 research articles on BIM, we found that this research spans a wide area of technological and organizational topics, of which many have a clear resonance to focal areas in IS research. Our analysis shows that IS, to some extent, serves as a reference discipline and that theories used in IS research are also informing contemporary BIM research. The following areas in need of further IS research were identified: studies on the relationship between BIM’s functional affordance and human agency, adoption and use of BIM for inter-organizational collaboration, the influence of organizational culture on BIM practices, the capabilities of BIM for transforming industry practice, and identifying the business value of BIM. Considering that a well-established knowledge base in IS research can be drawn upon for studying these issues, combined with the exciting potential of BIM for transforming a major industry such as building construction, we conclude that BIM is an area ripe for IS research

    Collaborative Verification-Driven Engineering of Hybrid Systems

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    Hybrid systems with both discrete and continuous dynamics are an important model for real-world cyber-physical systems. The key challenge is to ensure their correct functioning w.r.t. safety requirements. Promising techniques to ensure safety seem to be model-driven engineering to develop hybrid systems in a well-defined and traceable manner, and formal verification to prove their correctness. Their combination forms the vision of verification-driven engineering. Often, hybrid systems are rather complex in that they require expertise from many domains (e.g., robotics, control systems, computer science, software engineering, and mechanical engineering). Moreover, despite the remarkable progress in automating formal verification of hybrid systems, the construction of proofs of complex systems often requires nontrivial human guidance, since hybrid systems verification tools solve undecidable problems. It is, thus, not uncommon for development and verification teams to consist of many players with diverse expertise. This paper introduces a verification-driven engineering toolset that extends our previous work on hybrid and arithmetic verification with tools for (i) graphical (UML) and textual modeling of hybrid systems, (ii) exchanging and comparing models and proofs, and (iii) managing verification tasks. This toolset makes it easier to tackle large-scale verification tasks
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