Simulator Training Vs Traditional Training

Simulator Training Vs Traditional Training

Traditional training refers to the conventional method of introducing new concepts to learners in theory. The theory is then put into real-world application by applying machines, tools, and equipment to actual equipment. Technological advancements have facilitated the automation of some traditional practices to simplify the training process. Advanced domains use technology to simulate training when the concepts being taught are complex, or the equipment is expensive. For instance, the aviation industry relies on simulators to train pilots before they can be allowed to fly actual planes. Aviation engineering and mechanics are complex domains. They require simulators to teach concepts to help students understand concepts better via experience with the simulated reality.

Using simulators to train offers a superior experience. Students can understand the concepts as they are in reality instead of only using theory. Learning is a process that starts when a foreign concept, event, or object is introduced to one's environment. The first instance of exposure often acts as a reference point. Our minds are wired to retrieve the learned instance from the memory when the instance is experienced again. New information on a subject can then be updated at the reference point. This learning process means that a person can better understand a concept they can interact with. In the case of training, trainees must be introduced to concepts as they are in reality. This way, they get better references for when exposed to the experience again.

The learning process applied in simulator training is based on metacomprehension and metacognition. Simulator training is far superior to traditional training in many aspects but in cost. The importance of training and complexity are also crucial factors to consider. They impact the trainee and concept in many ways. Conservative training, in most cases, uses two-dimensional materials like books. They can be erroneous and flawed when a third dimension is introduced to the instance. Simulator training allows for many dimensions to be introduced to the instance, making it better for the student.

The added fidelity and complexity that can be achieved via simulators removes the element of surprise. Regardless of the complexity, a person will be more confident when they have the knowledge and have experienced the instance before. Using simulators does not remove the lack of confidence and surprise. However, it expedites both to ensure that they are exposed and resolved at the right time; when still in training. The confidence from using a simulator and transitioning to an actual instance is a perception. The mind has already recorded the instance. During application, there is more confidence because one already knows it. This has proven crucial in training surgeons (Bruppacher et al., 2010). They are comfortable operating tools and equipment because they are not entirely foreign as opposed to traditional training.

Using simulators in training helps students in many ways. A simulator reinforces an idea in the best possible way because it provides virtual reality. Documentation of training material in traditional training creates more confusion when one fails to execute their duties correctly. In the manuals and books used for traditional training, diagrams are close and ideal perspectives. It can easily confuse if one is not well oriented. In some cases, the reality would have changed even when the concept is still the same. The student's confusion when they fail can be eliminated by using simulator training for complex domains.

Simulator training relies on virtual reality and augmented reality to function. These two domains are critical as they impact the instance, learning experience, and outcome. The concept of metacomprehension is based on what someone knows and how many changes they can make based on their information. It is more complicated for one to predict how much is too much when handling complex error-sensitive domains. Only through interacting with reality, virtual reality, in this case, can one master skills at higher levels. Simulator training is used to protect institutions and trainees from damages that would happen in reality (Strayer & Drews, 2003). Simulation means that the damages can be experienced in an instance but with minimal effect in reality.

If cost were an issue, using a simulator for training would be preferable. In simulator training, concepts can be learned repeatedly at no extra cost other than initial acquisition cost and maintenance cost. It solves more issues that eventually justify the cost. The goal of training is to acquire and reinforce concepts to acquire knowledge. A learner uses this knowledge to solve issues once training is over. The complexity of complex domains can be in the possible scenarios rather than representation. Traditional training does not offer an avenue of training considering all possibilities. Select cases are used in training which limits a learner. Using a simulator allows trainees to visualize an instance and difference in scenarios accurately—better reinforcement is achieved from simulators in the virtual reality of complex and dynamic instances.

Research on how domain knowledge affects metacomprehension accuracy shows that knowledge improves comprehension (Griffin, Jee & Wiley, 2009). There are elements in any domain that require fine-tuning for one to understand them. Many are not entry-level and demand close attention. Knowledge is acquired in the intermediate level of understanding and applied in the expert stage. The concepts related to the elements require experience with a realistic model or equivalent for their comprehension. Griffin and his colleagues (2009) noted that people familiar with a subject "appear to make more effective use of domain familiarity in predicting absolute performance levels." They also add that the objectivity exhibited by experienced people is based on familiarity and logic.

References

Bruppacher, H. R., Alam, S. K., LeBlanc, V. R., Latter, D., Naik, V. N., Savoldelli, G. L., & Joo, H. S. (2010). Simulation-based training improves physicians' performance in patient care in high-stakes clinical setting of cardiac surgery. The Journal of the American Society of Anesthesiologists, 112(4), 985-992.

Griffin, T. D., Jee, B. D., & Wiley, J. (2009). The effects of domain knowledge on metacomprehension accuracy. Memory & Cognition, 37(7), 1001-1013.

Strayer, D. L., & Drews, F. A. (2003, July). Simulator training improves driver efficiency: Transfer from the simulator to the real world. In Proceedings of the second international driving symposium on human factors in driver assessment, training and vehicle design (pp. 21-24). Park City^ eUtahIowa Utah: University of Iowa.