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The advantage of simulation (or virtual reality) is that it can provide the proper setting (the real-world space) for performing the required skills, while reducing the risk of personal injury. As in traditional training methods, you can combine training with study (the former using the information provided by the latter). With simulation, practice sessions can occur in much the same context in which the skills being trained are normally performed. I've done this with my tennis tutorials, for instance. What's more, the training method can provide direct, detailed, and immediate feedback, something the real world can't offer -- it doesn’t stop to let you look at what just happened.) You can also repeat scenes to try to understand what occurred and make necessary adjustments.

To be any good, a simulation has to reflect the true state of affairs of the skills context, which is seldom well understood. The simulation also has to provide the features of the real setting that influence the performance of the athlete’s skill, either positively or negatively. In other words it has to match the level of competence of the athlete and the degree of subtlety of the skill(s) in solving problems. This can be difficult.

However, since the simulation only has to match the competence level of the skill being studied or trained, the simulation for a lower competence level skill needn't be as complex and as detailed as one for a higher competence level of the skill. Lower level simulations could then be first-stage vehicles and forerunners of the higher-level systems. This would make it possible to distribute costs and technical expertise more economically, over a range of skill levels. The argument is based on the fact that the degree of skill subtlety varies with the level of competence, so more subtle simulation detail is necessary to satisfy the training needs of better players.

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It's common to use training facilities in the form of a simulator that envelops the trainee in the appropriate environment for both the perceptual and the motor skills. Such a technique is employed to train airline or military pilots, for instance. Simulators are also used to train operators of military vehicles like tanks and trucks, and they can be used to train operating personnel of cars, trains, ocean liners, farm equipment, production machinery, and so on. These systems make good applications for simulation, because the trainee (usually seated) is stationary during real operations and the tools of his trade are at hand and fixed in place under normal conditions (like in a computer game), even though the system itself is moving. The trainee thus gets to practice real skills realistically. The usual procedure is to build a special simulator for each significantly different system, such as different types of aircraft, for instance.

So, if we furnish the trainee not only a simulation, but also the tools or instruments that are normally applied, and the trainee can use them realistically, we would have the training simulator. A flight trainer, for instance, houses a replica of a real airplane cabin, with appropriate displays, windows, and flight controls.

In the simulator, the pilot/trainee actually performs real-world perceptual-motor piloting skills, and you can measure the read/react responses directly. Typical training includes practice with operations like landing the aircraft, dealing with heavy turbulence, flying around or through a storm, or having to contend with a stall or with a bad engine. Visual displays at the windows depict the world "outside the moving aircraft" and real flight controls enable the trainee to "fly" the aircraft under a variety of flight conditions. The aircraft itself is "inside" the computer.

Unfortunately, though, we haven't reached that stage for sports, and certainly not for everyday skills; nor is it likely to happen any time soon. To provide an adequate format we would have to duplicate the arenas where games are played and the normal activities occur. For tennis training, specifically, we would need a chamber that was the same size as the court, or at least the trainee’s half of the court. (The player doesn’t perform his duties sitting on a chair, so the enclosure has to be large enough to accommodate the movement.) The simulator would then be equal in size to the real setting. But the playing arena (the court), like the aircraft in the flight simulator, would be in the computer.

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Simulation (without the superstructures of simulators) is ideally suited to explore your skills space. The ideal is to exactly copy the relevant aspects of the objective setting in which the skills occur. But the selection of characteristics of the setting to be represented depends on the level of skill being learned, much as the content in traditional teaching varies with the grade level of the students. For example, you wouldn't give the intricacies of Einstein's relativity theory in a basic physics class. You would rather leave those details to a more advanced class. The same is true in simulation -- the more advanced the student, the subtler the skills and the more intricately the space has to be spelled out in order for the simulation to be useful. And that's where the real challenge is, or where the main problems lie: providing increasingly accurate or realistic simulation.

For the study of tennis skills, in particular, you need a simulation that accurately reflects what is occurring at the tennis court. This can be difficult enough, but at least you don’t need to get involved with the complexities of a training simulator for the game. You don’t need an enclosure for the training or objects like flight control sticks or headphones or gauges or the like. In order to conduct a study of tennis tactics, say, you only need an accurate representation of the game. This would also be suitable for optimization work In my Select ', Shoot games I present the full court but use only the trajectory of the ball as my simulated entity, since my concern is with racket mechanics and trajectory dynamics.

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