Simulations present or model the essential elements of real or imaginary situations. This is shown in Figure \(\PageIndex{3}\). Computer-based simulations (e.g., flight simulators) allow students to learn by manipulating the model in similar ways to real world situations. Simulations can immediately respond with consequences to learner decisions. However, some consequences may not initially be apparent, depending on when the effect is normally seen (e.g., the effects of changes in interest rates may be seen years later). Students can learn by observing results and relationships (this can be through a discovery-learning strategy) or receiving specific diagnostic feedback, especially when detailed feedback is provided for both right and wrong answers.
Ideally, simulations should approximate real systems as closely as possible. This helps facilitate transferring the knowledge learned to the real world and can make the simulation particularly meaningful to the learners. How closely a simulation must approach reality depends on the complexity of the real situation, how well the skills learned will transfer to the real situation, and the benefits and costs of making the simulation more realistic. Conduct a detailed analysis to determine all of the relevant skills needed and their importance.
Simulations can be used for teaching many skills including:
Properties of physical objects such as a comet in its orbit
Rules and strategies such as in war games, making predictions about forest fire behaviour or avalanche potential, or building a city
Processes such as laws of supply and demand
Procedures such as diagnosing illnesses
Situations such as teaching instructors how to deal with student behaviour and attitudes
Simulations are often used when real situation training is:
Dangerous (e.g., nuclear power plant procedures and police maneuvers)
Expensive (e.g., landing a space shuttle)
Unethical (e.g., when it is not appropriate to use humans)
Not easily repeatable (e.g., avoiding a run on a bank)
Unavailable (e.g., historical events such as the economics of the Great Depression, how to respond in a robbery, or operating a business)
Not conducive to learning (e.g., when learning is difficult because the learner must consider too many stimuli at once, such as in the cockpit of a modern airplane)
Affected by reality such as time (e.g., simulations can provide genetic data about successive generations immediately, where reality could take months or years)
Inconvenient (e.g., experiencing Arctic survival, undersea, and outer space conditions).
Figure \(\PageIndex{1}\): Drill and practice sampleFigure \(\PageIndex{2}\): Tutorial sampleFigure \(\PageIndex{3}\): Simulation sampleFigure \(\PageIndex{4}\): Educational game sample
Simulations can be very effective.
The knowledge gained tends to transfer well to real situations if students can apply their existing knowledge and experience. Active student participation is critical.
Effectiveness increases if the simulation is logical or comparable to real situations.
Effectiveness is enhanced if students are aware of the learning outcomes.
Effectiveness increases if students can gradually build their skills. For example, when first learning how to operate a nuclear power plant, the student should first learn each system independently, then combinations of dependent systems, and then the entire system.
Effectiveness can stem from students being very motivated to learn. Imagine your motivation if you are involved in a life and death situation, or investing your life savings.
Attaining excellent results requires more explanations of the goals, learning outcomes, and directions than tutorials or drill and practice methods. Some learners, such as young or immature students, will have trouble explaining what has happened in a simulation, or transferring the knowledge to real situations.
Note
Students may not necessarily believe the results of a simulation. As an example, in a simulation, students may end up in a car accident if they chose to drink and drive. However, there is no guarantee that students believe that could happen to them in real life.
Simulations can be very efficient for relatively quick learning. The efficiency increases if:
the model or simulation closely represents reality.
learners receive useful feedback with respect to the learner outcomes.
the model or simulation is aimed at the appropriate learning level.
Novices may learn best when only some of the variables can be manipulated, and experts when presented with the entire model.
the level of detail is appropriate.
If too much detail or too many parts of the system are shown, learning may be hindered since the learner may not be able to mentally process all of the information.
supplementary material is provided.
Text summaries and checklists can be very beneficial.
Effective, efficient simulations are usually expensive and time-consuming to create. Cost-justification is particularly important before creating a simulation.
