Dynamic Training Trumps Linear Training



Does simulation increase a trainee’s desire to master a topic rather than simply achieve a good grade? You can answer this question by assessing if the trainee exhibits increased curiosity, looks for challenges, and strives to gain new knowledge within the simulation. When a student owns the desire to learn, we have tapped into their intrinsic motivation. Intrinsic motivation is powerful. When a student is intrinsically motivated, learning is easier and longer lasting. However, fostering intrinsic motivation isn’t easy.


Gaming and simulation shows evidence of increasing intrinsic motivation. Mihaly Csikszentmihalyi has studied how when engaged in entertainment and fascinating activity, we enter a state of “flow”. Achieving flow includes “challenge-skill balance, merging of action and awareness, clarity of goals, immediate and unambiguous feedback, concentration on the task at hand, paradox of control, transformation of time, loss of self-consciousness, and autotelic experience.” Building a simulation that achieves flow is not easy. I would like to suggest that a dynamic, non-linear simulation has a higher likelihood of enabling trainees to experience flow than a linear simulation. A dynamic simulation offers the trainee an environment where he or she can make many choices, each of which impact the environment in in a variety of ways. A dynamic simulation will represent each avatar, object, and device as its own independent entity with sensors, goals, functions, behaviors, and reactions. A linear simulation is scripted with structured choices and predictable impacts to the environment. The environment of a linear simulation serves the structured paths rather than creating a realistic scene to interact with and experience. Let’s look at each aspect of flow and consider how to achieve it.

Challenge-skill balance: As students gain skill, creating a virtual simulation that provides adequate challenge requires more realism. The best way to represent realism i