Simulations - Dr Matthew J Koehler
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(Science) Education and Simulations Matthew J. Koehler CEP 909, 11-03-05 School Science vs. Practiced Science aka…. Houston: We have a problem …. School Science Theories (models) are presented Data is presented in support of the theory (model) Theories (models) are proved as true, or factually correct Theories (models) are “rigid” Science as practiced Theories (model) are created Theories (models) are a conceptual undertaking (as well as empirical) Data is for evaluating fit Theories (models) are in flux Science as Theory Building NOTE - The views presented here are overly simplified. Science isn’t really this clean cut, as the fields of science history and philosophy of science have pointed out. But, this has some utility that we will use here. Collect Data Use Theory Or Teach to Kids NOTE: Science Ed is often reduced to dissemination of theories, and not all the cool stuff on the right. Most reform efforts seek to remedy this situation by including some or all of the stuff to the right. Revise Theory Make a Theory Evaluate Theory Science as Theory Building There is some phenomena or system that could be better understood The motion of objects The functioning of a body organ How altruism can have an evolutionary explanation How termites can build a mound with limited intelligence Science as Theory Building Collect observations (data) Measure the luminosity and positions of stars (e.g. Tyco Brahe) Collect field information about species diversity (e.g. Darwin) Measure time and position of falling objects (e.g. Galileo) Dissect animals to collect information on the characteristics of bodily organs Etc. Science as Theory Building Now, simply make a theory :) In other words, mix together: One part logic One part art One part inspiration One part insight One part magic (the part that nobody understands) SIDEBAR - What’s a theory We build the theory because we wish to understand something. Indicators of this understanding: Predict Explain Control Simplify Theories have many forms Text (e.g. Darwin) - Mutation and Selection drive the evolution of species Equations (e.g. Newton) - F=mA Analogies Models (e.g. Keppler) Simulations (e.g. Start of the universe models) Science as Theory Building Theories are Evaluated. Usually through comparisons to existing data. Or by “running experiments.” How well do they ____________ ?: Predict Explain Simplify How do they compare to rival theories? Which theory accounts for the data? (empirical) Which theory explains better? (conceptual) Which is more compelling? Do they make different predictions in some (yet) untested condition? Science as Theory Building Theories are revised To better predict To better explain This often necessitates collecting more observations and starting the cycle all over again. Simulations Most broadly, refer to any virtual experience. Many of which are not particular to science Online communications (virtual community) Art (virtual depictions) Training (Flight simulators) The rest of this presentation focuses on simulations in science education Simulation in Science Education Observing and collecting data Theory Building Collecting data virtually for data that is hard to get during school hours (e.g. star positions) Training for collection procedures (e.g. cow eye dissection) Having kids write simulations as embodiments of theories (e.g. Star Logo, Model_It! ) Theory Evaluation Getting data faster - Virtual lab environments where you can “run experiments” much faster than the real world Conducting experiments - Simulation makes predictions for certain conditions. Could compare results to “real world.” Simulation in Science Education Theory Revision Same as Building and Evaluation above Teaching Theories Making tradition teaching of theories come alive, by linking phenomena to the the theoretical explanations and representations. (e.g. DiSessa’s Physics World, Snir’s density world, etc.) Pro and Cons of Simulation #1 PRO: Simulations afford the opportunity to do the otherwise impossible, difficult, or impractical (e.g., launch a rocket, Dissect a Dodo bird) CON: Impossible: May distort reality for students (e.g. shooting people in video games is rewarded) Difficult: May also distort reality when difficult things are commonplace. Impractical?: Virtual pendulum, why not a real pendulum Pro and Cons of Simulation #2 PRO: Simulations can focus on the relevant, and ignore the irrelevant (i.e. they can make the “phenomena” more ideal) Physics - Movement of objects without friction Biology - Distinctive body parts that are easier to identify CON: Who gets to decide what’s “relevant”? What if the “irrelevant” is relevant? Danger of oversimplifying Confusing the theory with reality (Reality is more complex) Hiding the process of construction underlying theories and models Pro and Cons of Simulation #3 PRO: Simulations can allow students to make manipulations and see their effects Opens up the process of theory (model) building and evaluation Invites students to see causation between the mechanisms in the model and the effects on the phenomena CON: Misrepresenting Reality: Manipulations might not be possible in the real world (You can’t change the mouth on an existing fish like you can in the virtual aquarium) Cognitive overload: requires reasoning about multiple causations, which may overload students’ cognitive capacities. Pro and Cons of Simulation #4 PRO: Simulations can make stuff that is hidden in the real world visible in the simulation (e.g. vectors of momentum, a trail of movement, color to represent temperature, etc). Theories become visible Connections between the accepted notations and the phenomena being modeled. CON: Correspondence: Lack of correspondence between reality and the simulation (far too many to mention). Obscures the process of deciding what to make visible, and what representations are profitable for that phenomena (dependent on the developer of the system). Pro and Cons of Simulation #5 PRO: Allows theory building and modeling to be more visible accessible, assessable, and sharable to all. Connections between the “sterile theory” and the rich phenomena becomes more accessible (e.g., Newtonian billiard ball simulations). Requires theories to be fully specified. In some cases, the simulations become so accessible, that children can make them (e.g. StarLogo). CON: Immersive: The simulation can be so compelling, students can forget to ask important questions like: Who’s doing the theory building and modeling? Why should I believe them? Does Simulation = Theory ? It can be Most scientific simulations explicitly or implicitly embed a theory (Newtonian physics, water cycle, movement of the solar system, etc.) But not necessarily Example: Cow-eye dissection. There isn’t a theory (in the explanatory sense) embedded in the the simulation. It’s more of a virtual training guide to a scientific procedure to be performed. Does Simulation = Model ? I think a simulation is a model A model doesn’t have to be a simulation Every simulation has a simplified world, a model of some more complex system. This includes the cow-eye dissection (the model eye is less “messy” than a real one). For example, a model airplane (to scale) doesn’t simulate anything about a real plane (other than the relative proportions and positions of real plane features). It doesn’t virtually fly, predict when it would stall out, it’s terminal velocity, nor its’ stability. A theory might be the same as a conceptual model Does Theory = Model ? It often does Most theories have models that instantiate them (Newtonian physics has plenty of models that behave accordingly - for example DiSessa’s moving ball model, Evolutionary theories have many associated models - we saw some in StarLogo). Doesn’t have to be Model w/o a theory - Example: model airplane (to scale). Theory without a model - Constructivism as an educational theory (Although one might argue that the development of the theory is not far along enough to warrant the creation of a model yet). The End … ? Questions, comments, criticisms, critical acclaim, … ?
