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Models, representations and simulations help make the invisible – visible. This is how we people share understanding attempt to connect empirical observation and inference. (ie. the broken-red line of the graphic organizers above). Modeling requires students to manipulate ideas and materials, focus on detail, and use criticaland creative thinking. Younger students often create models of living and non-living things, such as animals, plants, soil, simple machines, and habitats. Older students use physical as well as operational, mathematical and graphical models to help visualize and understand complex systems and subjects.
Scientific modelling is a scientific activity the aim of which is to make a particular part or feature of the world easier to understand, define, quantify, visualize, or simulate. It requires selecting and identifying relevant aspects of a situation in the real world and then using different types of models for different aims, such as conceptual models to better understand, operational models to operationalize, mathematical models to quantify, and graphical models to visualize the subject. Modelling is an essential and inseparable part of scientific activity, and many scientific disciplines have their own ideas about specific types of modelling.[1][2] There is also an increasing attention to scientific modelling[3] in fields such as philosophy of science, systems theory, and knowledge visualization. There is growing collection of methods, techniques and meta-theory about all kinds of specialized scientific modelling. - from: http://en.wikipedia.org/wiki/Scientific_modelling
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