Effective Modelling

3 Key excerpts on "Effective Modelling"

• 

  eBook - ePub

  Constructing Worlds through Science Education

  The Selected Works of John K. Gilbert

  • John K. Gilbert(Author)
  • 2013(Publication Date)
  • Routledge

    (Publisher)

  In science education, the learning of a consensus model – which falls within what Hodson (1992) calls ‘learning science’ – does entail the formation of a mental model through the process of modelling. The major context for modelling in science education should, however, be the formation of a mental model of a phenomenon for which none is available to the student – this falls within what Hodson calls ‘learning to do science’. The development and use of the skills of modelling in science education are widely, if often obliquely, advocated in the UK (DfEE 1999b), the US (Rutherford and Ahlgren 1990), Australia (Curriculum Corporation 1994) and New Zealand (Ministry of Education 1993). This is a recognition of the core commitment of science to produce causal explanations of the world-as-experienced. A model in science or science education, once produced, is a simplification of a phenomenon produced for the purpose of making predictions about its behaviour under different circumstances, predictions that are then experimentally tested.

  The core commitment of design and technology is to produce solutions to human problems. For this purpose, two interactive roles for modelling were identified by Kimbell et al. (1991). They are modelling ideas in the mind (the role of communicating with oneself) and modelling ideas in a material form (the role of communicating with others). Two main modes of representation seem to dominate the activity of modelling in material form. The first of these is the visual mode, making especial use of sketching, technical drawing and pseudo-3D images – for example, through computer-based formats. The second is the material (or concrete) mode. The 3D representations are typically made in modelling clay, shaped in polystyrene foam or constructed from softwood. In design and technology per se , material models (often called mock-ups or prototypes ) are translated into the final outcome (or product), a process that often involves a change of scale and a change of medium. Because of the special circumstances of schools, particularly the lack of resources, of skills in making and of the traditional values of the field, together with the tyranny of an inflexible timetable, the material model is all too often the only product. The purpose of a model in both the industrial and educational contexts is to permit efficient and economical evaluation of the fitness for purpose

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  eBook - ePub

  Developing Information Systems

  Practical guidance for IT professionals

  • Tahir Ahmed, Julian Cox, Lynda Girvan, Alan Paul, Debra Paul, Peter Thompson, James Cadle(Authors)
  • 2014(Publication Date)
  • BCS, The Chartered Institute for IT

    (Publisher)

  In the early days of solution development, there was often little IT involved in the existing system, so jumping straight across from the Physical As-Is to the Physical To-Be risked potentially missing important new business requirements, while carrying forward redundant legacy features. This pattern is still applicable today, particularly when migrating solution components to new technologies. Ongoing maintenance activities may often skip across the physical level but doing so is not without risk.

  RATIONALE FOR MODELLING

  Modelling is employed in many disciplines for many reasons, for example:

  • Building architects commission three-dimensional models of new structures that allow the client to get an early vision of what the finished structure will look like.
  • Engineers produce structural models that allow them to perform various calculations that validate the integrity of the structure.
  • Economists produce dynamic models of the economy that allow them to run various scenarios in an attempt to predict likely outcomes.
  • Formula One car designers produce scale models of body components that can be placed in wind tunnels to test their aerodynamics and to refine the shapes until the finished version is produced and used on the actual car.

  One can relate each of these examples to how modelling can be employed within solution development with the ultimate aim of developing a solution which meets key stakeholder requirements; in other words a quality solution.

  What does modelling facilitate?

  Modelling is more than simply producing a model in place of documentation to hand over as part of a process; when appropriate useful models are produced, they facilitate a range of development activities that assist the aim of developing a high-quality solution.

  Communication and understanding

  At the most fundamental level, a model is not useful if it does not capture and communicate a level of understanding of the system. Such communication can occur during collaborative modelling activities, for example developing models during workshops; or through models as deliverable artefacts, for example at development stage handovers.

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  eBook - ePub

  Simulation and Modeling of Systems of Systems

  • Pascal Cantot, Dominique Luzeaux, Pascal Cantot, Dominique Luzeaux(Authors)
  • 2013(Publication Date)
  • Wiley-ISTE

    (Publisher)

  Chapter 2

  Principles of Modeling 1

  2.1. Introduction to modeling

  Modeling is the activity by which a model is designed. In this chapter, we shall see how a model can be designed and some of the most widespread types of model. Note that modeling for simulation obeys more or less the same rules as modeling in complex systems engineering, albeit with certain specific constraints which, although they are not limited to the field of simulation, are particularly strong in this case; these include the validation, the choice of levels of refinement (which has an impact on the model), and the need to take installation (e.g. the capacities of the target computer platform) into account.

  We start by laying down some basic principles of modeling: – The model is constructed to solve a specific problem and is, therefore, subjective. A model, although representative of a system, is not necessarily valid or relevant.

  – The same problems occur again. There is much to be gained by systematically checking whether the model has already developed with similar principles. If so, attempts should be made to modify the existing model, assuring that its validity and availability can be guaranteed.

  Continuing with the same principle, a model should be able to exist, as hypotheses concerning a system may change (particularly in the case of studies being carried out for a future system) or the system itself may exist (in the case of a simulation used while the system is already operational, e.g. a flight simulator which must remain coherent with the real platform).

  – Simplicity and efficiency are essential. Unnecessarily complex setups, which are understood only by the author (if that), must be avoided. The level of refinement of the model should be strictly limited to the minimum. In general, a basic rule of successful engineering should be applied: the KISS method (Keep It Simple, Stupid!).

  – Simulation is not necessarily the most appropriate tool in all cases. We should always check for alternatives (constraint programming, expert advice, and so on).

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