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Target-Shooting Skills
Auto-competition can be a real challenge.
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Many investigative techniques are available, some better than others. But conducting studies on a digital computer seems to have an edge when dealing with severely non-linear problems, such as skill development. It becomes particularly promising if it is part of a game. This approach uses the computer to run science-grounded diagnostic tests of the skills, to help you understand and try to bring your actions closer to what is best for you, personally, without creating ineffective practices impossible to break. The Challenge part comes in to test what you have learned. You need to assess your own capabilities and potential. The method depends on simulation to conduct the studies and can be applied to all skills. It is this method that l deal with here. I illustrate it by looking specifically at the hitting skills of tennis and the trajectories generated in the hitting. The racket becomes the "gun'" if you will, and the target is any individual spot on the opponent's court. The setting (turf) for the simulation is of course the tennis court itself, which is to be understood as the diagnostic study context. It is within that context that you apply your tennis techniques. It is this learning option that we explore.
The basic idea for the game is simplicity itself. The tennis activity occurs at the tennis court, so we first lay out the physical court quantitatively, in simulation. The next step is then to embed the tennis student/player in that context, again in simulation. And of course the individual naturally brings an action potential. The court itself is to be presented in perspective, to reflect the player's perception. (This would be analogous to the real person setting up at the actual court to begin hitting the ball in a practice session.) Finally, test trajectories in simulation (first having been formulated and made available in the design) can now be launched, one at a time, to the simulated hitter to begin the games, just as a coach might hit them to a student. Each trajectory can be dealt with in a Practice mode or a Challenge mode, just as you might find at the court (or for that matter at any shooting range).
The trajectories in the simulation are formed using equations of motion that involve starting conditions and include a gravitational constant together with coefficients to deal with air resistance and the friction that occurs between the ball and the surface of the court. In games that I've written I selected (shaped, designed) subsets of the trajectories to be available to the student as practice vehicles. One at a time, then, the student selects a trajectory and responds to it in some way, as one step in an inductive learning process.
Similar systems can be devised for many other operational settings, such as a busy street, a hospital ward, a manufacturing workstation, a concert hall or schoolroom, a soccer field, the interior of an airplane, boat, or train, a crime scene, or outer space,...,wherever. You can first put together the objective structure of the context. This becomes the ground in which you embed the appropriate skilled agent (nurse, teacher, director, athlete, driver, detective, worker, astronaut, and so on). Then you can proceed with your studies using relevant transaction exchange materials for the context.
Naturally you want to improve the way you hit your shots; hitting, after all, is the crux of the game, the reason for being out on the court in the first place. To be competitive you need to understand how the ball is to be hit, for the striking action affects its path through the court. (Reading books like The Physics and Technology of Tennis can be helpful here.) But that's not enough. The need to grasp the underlying ideas applies not only to hitting but also to tracking and interception. You need to track the ball accurately and intercept it properly to make it possible to swing your racket freely and meet the ball correctly to make planned shots. Seeing, recognizing, and intercepting trajectories are a necessary part of the process -- it is the ongoing perception and action (read and react) procedure that predominates.
Even this isn't enough, however, for you still have to know precisely how to meet the ball with your racket before you can correct your strokes. And there is much to understand if you wish to play the game well. For any shot to be good, of course, the ball has to stay within the court boundaries, and you have to learn how to keep it there. But what is more important, you need to aim accurately to reach very specific (or pinpoint) targets. The ultimate purpose of the sgame would therefore be to sharpen your shots and let you access target areas that presently, at your current skill level, might not be reachable.
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No Shooting without a Target
As an example of skills learning in a man-machine relationship, consider the problem of landing an aircraft. Three ways to learn come to mind immediately:
Think of this as a target shooting exercise, the landing field being the target and the plane the bullet. In the first technique, you might learn a great deal about landing procedures, but wouldn't get practical experience -- you wouldn't do any landing. However, the instruction might involve step-by-step procedures in which you imagine being in an airplane and handling the controls. Under these conditions, you'd be applying a rudimentary form of simulation. But in this case, since your operations would only be imagined, there would be no way to test your knowledge, even if you have a vivid imagination. You wouldn't have an objective assessment of your actions.
The second technique is the real thing, assuming you can get off the ground to begin with. But here you encounter serious risk, for even if you've learned a lot about flying, chances are you'll still make mistakes, because you still won't have flown before. You'll know what to do, but won't have practiced. You may not even recover from the mistakes. Even if you do, there's no reason to think you'd know what mistakes you made or how to correct them. In this case, too, you wouldn't have an objective assessment.
The third technique, using simulation, combines aspects of the first two methods. You get to "fly" a vehicle with realistic controls and flight characteristics. To make the system work, though, both the structural and operational characteristics of the aircraft have to be like the real thing. That is, you must have a realistic model, a realistic flight simulator.
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A bonus from simulation is that it provides feedback on any actions you might take. With the return of information, what develops is the prospect of running new trials and learning to correct for errors, because the computer can record what happens during an exercise and play it back for you. It keeps tabs on the objective aspects of your "flight," and lets you know how you did. This significantly enhances your chances for learning to fly the plane. And significantly reduces the likelihood of getting hurt.
However, the simulation has to copy the aircraft controls and flight characteristics so well that there are no significant differences between flying the real and the make-believe system. The moves you learn to make in simulation can then be transferred to the real aircraft. The decisions you make in the simulator would correspond to real-world choices.
The model for any other simulation for learning -- for any other skill -- should meet the same criterion, if it's to be successful. In Simulations for Skills Training, I show how to understand models and how to develop and apply them to represent the situations.
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