20 resultados para Model transformation learning

em University of Queensland eSpace - Australia


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Model transformations are an integral part of model-driven development. Incremental updates are a key execution scenario for transformations in model-based systems, and are especially important for the evolution of such systems. This paper presents a strategy for the incremental maintenance of declarative, rule-based transformation executions. The strategy involves recording dependencies of the transformation execution on information from source models and from the transformation definition. Changes to the source models or the transformation itself can then be directly mapped to their effects on transformation execution, allowing changes to target models to be computed efficiently. This particular approach has many benefits. It supports changes to both source models and transformation definitions, it can be applied to incomplete transformation executions, and a priori knowledge of volatility can be used to further increase the efficiency of change propagation.

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The Virtual Learning Environment (VLE) is one of the fastest growing areas in educational technology research and development. In order to achieve learning effectiveness, ideal VLEs should be able to identify learning needs and customize solutions, with or without an instructor to supplement instruction. They are called Personalized VLEs (PVLEs). In order to achieve PVLEs success, comprehensive conceptual models corresponding to PVLEs are essential. Such conceptual modeling development is important because it facilitates early detection and correction of system development errors. Therefore, in order to capture the PVLEs knowledge explicitly, this paper focuses on the development of conceptual models for PVLEs, including models of knowledge primitives in terms of learner, curriculum, and situational models, models of VLEs in general pedagogical bases, and particularly, the definition of the ontology of PVLEs on the constructivist pedagogical principle. Based on those comprehensive conceptual models, a prototyped multiagent-based PVLE has been implemented. A field experiment was conducted to investigate the learning achievements by comparing personalized and non-personalized systems. The result indicates that the PVLE we developed under our comprehensive ontology successfully provides significant learning achievements. These comprehensive models also provide a solid knowledge representation framework for PVLEs development practice, guiding the analysis, design, and development of PVLEs. (c) 2005 Elsevier Ltd. All rights reserved.

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Many Australian grain growers need to change their management approach to ensure their continued viability, but do not have the required knowledge and skills. Uptake of relevant education and training is poor, despite the positive correlation between learning, change and farm viability. As men are generally occupied with the operational aspects of the farm, much of the management role has been taken on by their partners, despite their lack of relevant formal qualifications. Professional development of farm partners therefore has the potential to improve the viability of grain growers. A model combining learning circles and action learning projects is proposed.

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Models and model transformations are the core concepts of OMG's MDA (TM) approach. Within this approach, most models are derived from the MOF and have a graph-based nature. In contrast, most of the current model transformations are specified textually. To enable a graphical specification of model transformation rules, this paper proposes to use triple graph grammars as declarative specification formalism. These triple graph grammars can be specified within the FUJABA tool and we argue that these rules can be more easily specified and they become more understandable and maintainable. To show the practicability of our approach, we present how to generate Tefkat rules from triple graph grammar rules, which helps to integrate triple graph grammars with a state of a art model transformation tool and shows the expressiveness of the concept.

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In this paper, we present a framework for pattern-based model evolution approaches in the MDA context. In the framework, users define patterns using a pattern modeling language that is designed to describe software design patterns, and they can use the patterns as rules to evolve their model. In the framework, design model evolution takes place via two steps. The first step is a binding process of selecting a pattern and defining where and how to apply the pattern in the model. The second step is an automatic model transformation that actually evolves the model according to the binding information and the pattern rule. The pattern modeling language is defined in terms of a MOF-based role metamodel, and implemented using an existing modeling framework, EMF, and incorporated as a plugin to the Eclipse modeling environment. The model evolution process is also implemented as an Eclipse plugin. With these two plugins, we provide an integrated framework where defining and validating patterns, and model evolution based on patterns can take place in a single modeling environment.

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Since the object management group (OMG) commenced its model driven architecture (MDA) initiative, there has been considerable activity proposing and building automatic model transformation systems to help implement the MDA concept. Much less attention has been given to the need to ensure that model transformations generate the intended results. This paper explores one aspect of validation and verification for MDA: coverage of the source and/or target metamodels by a set of model transformations. The paper defines the property of metamodel coverage and some corresponding algorithms. This property helps the user assess which parts of a source (or target) metamodel are referenced by a given model transformation set. Some results are presented from a prototype implementation that is built on the eclipse modeling framework (EMF).

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This paper describes the implementation and evaluation of a three-way model of service development mentoring. This population health mentoring program was funded by the Commonwealth Department of Health and Ageing to enable staff from eight Divisions of General Practice in South Australia to gain a sound understanding of population health concepts relevant to their workplace. The distinguishing features of service development mentoring were that the learning was grounded within an individual's work setting and experience; there was an identified population health problem or issue confronting the Division of General Practice; and there was an expectation of enhanced organisational performance. A formal evaluation found a consensus among all learners that mentoring was a positive and worthwhile experience, where they had achieved what they had set out to do. Mentors found the model of learning agreeable and effective. Division executive officers recognised enhanced skills among their "learner" colleagues, and commented positively on the benefits to their organisations through the development of well researched and relevant projects, with the potential to improve the efficiency of their population health activities.

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Recentiy a neuropsychological model of learning has been proposed Qackson, 2002) which argues that Responsibility provides a cognitive re-expression of Impulsivit)' in the prediction of functional and dysfunctional behaviour. Jackson argues that primitive, instinctive impulses lead to antisocial behaviours and socio-cognitive regulators such as Responsibility leads to the re-expression of Impulsivity in terms of pro-social behaviours. Study 1 tests and supports the measurement properties of the assessment methodology associated with the model. Study 2 provides evidence in favour of the instinctive basis of Impulsivity and the conscious basis of Responsibility, which reinforces the underlying neuropsychological basis of the model. Study 3 uses structural equation modelling to determine if Responsibility mediates Impulsivity in the prediction of a latent variable representing work performance, work commitment and team performance, but does not mediate Impulsivit}' in the prediction of a latent variable representing sexual proclivity, workplace deviancy, gambling and beer consumption. Results provide strong support for Jackson's model and suggest that Impulsivity and Responsibility are fundamental to both functional and dysfunctional learning

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This paper presents a formal but practical approach for defining and using design patterns. Initially we formalize the concepts commonly used in defining design patterns using Object-Z. We also formalize consistency constraints that must be satisfied when a pattern is deployed in a design model. Then we implement the pattern modeling language and its consistency constraints using an existing modeling framework, EMF, and incorporate the implementation as plug-ins to the Eclipse modeling environment. While the language is defined formally in terms of Object-Z definitions, the language is implemented in a practical environment. Using the plug-ins, users can develop precise pattern descriptions without knowing the underlying formalism, and can use the tool to check the validity of the pattern descriptions and pattern usage in design models. In this work, formalism brings precision to the pattern language definition and its implementation brings practicability to our pattern-based modeling approach.