Simulation and Training
Simulation is effective because it enables trial and error learning.
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The classroom is a form of simulated environment -- a place to learn ordinary skills without the risks of ordinary decision-making. The representation isn't literal, of course. It doesn't contain houses, streets, cars, etc. When a problem is posed, it is expressed mostly in words and you are expected to imagine the conditions of the problem and work out an answer. The same can be said for computer-based simulations, like the representation of "a tennis ball moving through the space of a tennis court and being hit by a tennis racket," as in my tennis programs. Or the depictions of a golf shot. Or the landing strip as seen from the cockpit of an airliner. In either of these instances there is presumed to be learning about one thing or another. But there is no training -- unless you can actually practice to perform skills as you might perform them in the real setting of the skills, as in a flight trauner.
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Computer-based simulation offers an advantage over ordinary training is that you can show precise quantitative conditions for any given skills context. Using the game of tennis as an example of a context, with the simulation you can display quantitatively precise ball trajectories and easily re-set game conditions for the displays in order to observe different properties. For the hitting phase, numerical assignments make it possible for you to be much more precise with your racket settings. Though you don't use numerical methods at the tennis court, the quantitative precision furnishes the explicit directions you need in order to refine your qualitative distinctions, thus letting you get closer to "the truth" of the ball/racket dynamics. The sharper settings invite you to learn more subtle techniques, which are so essential to expert play. You need the increased subtlety both in your visual discrimination and in your production of trajectories. Feedback at the court is meant to sharpen your insight.
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When training skills, the first thing you need is someone who knows what skills are to be performed, and you also need the skills environment to perform the skills. In a simulation, this means you have a simulator, like in a flight simulator. This is the skills context.
Training in the skills context means you need to know what job has to be performed or how to do it, and this isn't obvious or automatic. You have to study these skills to see what needs doing. The study provides best results and thus serves as a guide. Then you need to put the guide or guidance together with actual performance in the context and get feedback to calibrate the guidance and adjust the performance. It's a two-way street. You need a guide and you need knowledge of results. I refer to this training approach as computer-assisted, group-based training. The computer lets you do the studies, and feedback from the performance leads to performance adjustments and guidance correction. In other words you need a model of what is to be done and you need feedback to let you know how it was actually done. One is conceptual and the other is empirical. One is quantitative and the other is qualitative. The combination of computer and feedback mechanisms results in more effective training. Like in flight trainers, you practice according to guidelines and get feedback on tasks that you would perform in the ordinary environment of the tasks (like flying an airplane).
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