(Science) Education and Simulations Matthew J. Koehler CEP 909, 11-21-02
School Science vs. Practiced Scienceaka…. 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.
CollectData
Make aTheory
EvaluateTheory
ReviseTheory
Use TheoryOr
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.
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
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)
Theory Building 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
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).
A model doesn’t have to be a simulation 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).