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Models in science

Gilbert, J. K., Boulter, C. J., Elmer, R. (2000). Positioning models in science education and in design and technology education. In J. K. Gilbert C. J. Boulter (Eds.), Developing models in science education (pp. 3-18). Dordrecht Kluwer. [Pg.8]

J.K. Gilbert, D. Treagust (eds.). Multiple Representations in Chemical Education, Models and Modeling in Science Education 4, DOI 10.1007/978-l-4020-8872-8 3, Springer Science+Business Media B.V. 2009... [Pg.31]

Chi, M. T. H. (1992). Conceptual change within and across ontological categories Examples from learning and discovery in science. In R. N. Giere (Ed.), Cognitive models in science (pp. 129-186). Minneapolis University of Minnesota Press. [Pg.103]

Harrison, A. G. Treagust, D. F. (1998). Modelling in science lessons Are there better ways to learn with models School Science and Mathematics, PS(8), 420-429. [Pg.150]

As many researchers have pointed out, models provide some means of visual representation (Woody, 1995), development of historical models in science (Oversby, 2000 Justi, 2000), and linkage between phenomena, expressed models, and mental models (Buckley and Boulter, 2000). Models and modeling play central roles for... [Pg.272]

E. Castillo and M. R. Ruiz-Cobo, Functional Equations and Modelling in Science and Engineering (1992)... [Pg.769]

Basmadjian, D., The Art of Modeling in Science and Engineering, Chapman Hall, CRC, Boca Raton, FL, 1999. [Pg.391]

J- N. Kanpur, Maximum-Entropy Models in Science and Engineering, Wiley, New York 1993. [Pg.192]

Gilbert, J. K. Boulter, C. J. Elmer, R. In Developing Models in Science Education Kluwer Academic Publishers Dordrecht, the Netherlads, 2000. [Pg.108]

Like all models in science, the one treated in this chapter makes many unrealistic assumptions. These were pointed out at the end of Section 2. The most notable deficiencies are that the model inadequately reflects the cell division process and neglects the energy required for cell maintenance. It should be pointed out, however, that the main predictions of the simple (even less realistic) models of Chapters 1 and 2 survive intact in the more complex model treated in this chapter. Therefore, it is not unreasonable to expect that many of the predictions made on the basis of Theorem 4.1 will continue to hold for more realistic models. [Pg.228]

Basak, S.C., Magnuson, V.R. and Veith, G.D. (1987b). Topological Indices Their Nature, Mutual Relatedness, and Applications. In Mathematical Modelling in Science and Technology (Avula, X.J.R., Leitmann, G., Mote, C.D.Jr. and Rodin, E.Y., eds.), Pergamon Press, Oxford (UK), pp. 300-305. [Pg.535]

Roy, A.B., Basak, S.C., Harriss, D.K. and Magnuson, V.R. (1984) Neighborhood complexities and symmetry of chemical graphs and their biological applications, in Mathematical Modelling in Science and Technology (eds X.J.R. Avula, R.E. Kalman, A.l. Liapis and E.Y. Rodin), Pergamon Press, New York, pp. 745-750. [Pg.1159]

P. Duhem was fundamentally disinclined to accept any kind of model in science and held the view that a scientiflc theory should be deductive, abstract, logical, and systematizing. Campbell opposed this approach and suggested that all theories should have an intelligible interpretation... [Pg.1]

Bames, N. (2000). Teaching and learning about chemistry and modelling with a computer managed modelling system. In J. Gilbert, C. Boulter (Eds.), Developing Models in Science Education, (pp. 307-323). Dordrecht, The Netherlands Kluwer. [Pg.63]

Gilbert, J. (Ed.) (1993). Models modelling in science education. Hatfield, UK The Association for Science Education. [Pg.64]


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