Abstract
Throughout this book, we have focused on the cognitive processes underlying simulation use and dynamic model building and, in particular on several processes that are crucial to learning (e.g., creating analogies and metaphors, generating inferences, reorganizing mental models and schemas). The present section will conversely examine an aspect of instructional simulation not yet directly discussed herein and, that is, what to teach via simulation.
Imagination has given us the steam engine, the telephone, the talking-machine, and the automobile, for these things had to be dreamed of before they became realities.
L. Frank Baum, Introduction to The Lost Princess of Oz (1917)
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Notes
- 1.
The instructional use of simulation requires time and resources; it is therefore important for teachers and educators to verify whether it is actually justified for a given instructional situation or whether other instructional technologies and/or methods are more effective in achieving the same learning objectives.
- 2.
Methodologically, the development of higher-order skills was included in the instructional repertoire and goals of the then-developing constructivist pedagogy.
- 3.
This is particularly evident in the case of the system dynamics simulation paradigm: despite the great potential of this method for modeling and simulating all kinds of systems, the tendency to consider it mostly as an instrument for developing “systems thinking skills” (Forrester 1996; Richmond 1993), and to focus on large-scale and highly complex problems only, is one of the reasons it is little used as an instrument to teach the standard science curriculum. Researchers at the Creative Learning Exchange organization (http://www.clexchange.org/) have recently undertaken an effort to more closely link system dynamics to educational standards. See also, Fisher (2001) for an integration of system dynamics with mathematical education standards.
- 4.
Note how this description focuses on “practices” (versus “skills”), as the Science College Board Standards do; note also the consideration accorded to engineering alongside pure science.
- 5.
The covariation of A and B is not, in and of itself, a criterion for stating that A causes B. It may be that a third factor C causes both A and B and that A and B covary only, as in the case of “spurious correlation.” Other instances are those in which B causes A but A does not causes B (reverse causation), or in which A and B are both causes of each other (e.g., the variations of pressure and temperature in an ideal gas).
- 6.
The terms “microscopic” and “submicroscopic” are sometimes used to respectively indicate a portion of the world that can be seen under magnification, as with an optical or electron microscope, and a portion which, conversely, is so small that cannot be directly seen with any instrument.
- 7.
The Molecular Workbench creators use these and other laws as test cases to ensure the validity of the computational engine underlying the simulation program.
- 8.
It is based on a theoretical approach—continuum mechanics—which was introduced as a branch of classical mechanics during the nineteenth century by the French mathematician Augustin-Louis Cauchy. (Many of his theorems in the field of infinitesimal calculus were conceived in the context of continuum mechanics). It was then reorganized upon rigorous mathematical foundations in the twentieth century by Clifford Truesdell.
- 9.
It fact, Chaucy’s theorems of infinitesimal calculus were developed in the context of continuum mechanics. The same holds for “tensor calculus,” which was originally developed for calculating stresses acting within a deformable body and has since found applications in many other fields, including Maxwell’s theory of electromagnetism and Einstein’s relativity theory.
- 10.
Fuch’s approach conceptually derives from the “Karlsruhe Physics Course,” in which “extensive” or “substance-like” physical quantities play the role of basic concepts. These quantities are mass, energy, electric charge, amount of substance, momentum, angular momentum, and entropy. (The course material is available at: http://www.physikdidaktik.uni-karlsruhe.de/index_en.html).
- 11.
In the National Science Education Standards and the Science College Board Standards for College Success, the term “form” is used in place of “structure”—a choice that highlights a focus on natural forms, as opposed to man-made structures.
- 12.
Student comprehension in both instances may rely on mental simulation.
- 13.
In the system dynamics modeling method, it is frequently stated that a system’s behavior can be explained in terms of its structure, but this statement is based on the premise that only simulation use allows for this type of explanation, because the model would remain otherwise opaque.
- 14.
Also, the method advocated in classical instructional design (Clark 2008).
- 15.
From an embodied cognition perspective, this mapping between temperature and color is based on our interactions with physical objects (e.g., a red hot iron, the blue of water in a swimming pool), and on bodily experiences of an interoceptive nature (e.g., flushing red with fever).
- 16.
This type of representation has become familiar for many of us, thanks to the use of infrared thermography images (in which thermal imaging cameras detect radiation in the infrared range of the electromagnetic spectrum and produce images called “thermograms”).
- 17.
We are focusing on this specific topic here, as it illustrates the fact that teaching a scientific concept may require not only innovative instructional methods, but also a more accurate re-examination of the concept itself, from historical and epistemological perspectives.
- 18.
- 19.
Lautrup (2011) notes that “Although continuum physics is always an approximation to the underlying discrete atomic level, this is not the end of the story. At a deeper level it turns out that matter is best described by another continuum formalism, relativistic quantum field theory, in which the discrete particles—electrons, protons, neutrons, nuclei, atoms and everything else—arise as quantum excitations in the fields. […] It appears that we do not know, and perhaps will never know, whether matter at its deepest level is truly continuous or truly discrete.” (p. 10).
- 20.
Schwaninger and Groesser (2009) conducted a review of these methods. See also Robinson (2004).
- 21.
Bechtel and Abrahamsen (2010) termed the strategy of modeling a system with ordinary differential equations dynamic mechanistic explanation. This strategy should not be confused with the philosophical notion of mechanism, which implies the belief that living things are like man-made machines or artifacts.
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Landriscina, F. (2013). Simulation-Based Instruction. In: Simulation and Learning. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-1954-9_7
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