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 is by replicating the dynamic nature of situations.  A linear event may be the right challenge-skill balance for a novice, but as the student gains skill, it is more difficult to present a challenge in a linear simulation.

Merging of action and awareness, paradox of control, and concentration on the task at hand:  A dynamic environment includes events and effects from actions that cause the simulation environment to change.  In order to succeed in the simulation, the student must be aware of the context and understand that actions have impact.  In addition, the student must remain vigilant to detect what in the environment will be important for critical decision making.  If actions don’t require the development of situation awareness, then the student will take action without taking the time to observe.  The requirement for developing situation awareness and looking for new events and effects creates the sense of uncertainty in the outcome.  The student is forced to understand how things really work – not just the rules.  Therefore, the students must concentrate.

Immediate and unambiguous feedback & clarity of goals:  The more detailed the feedback, the less ambiguous it will be. A dynamic environment can provide a situation rich in detail, providing the information for reflection on good actions and/or undesirable actions.  The amount of data that can be used in feedback makes it more specific to the skills being developed in the student.  For the same reason, more specific goals can be stated.
Transformation of time, loss of self-consciousness, and autotelic experience: The last three aspects of flow are more personal and come from within the student.  There are personality traits, recent life experiences, and physical characteristics that come into play.

By creating immersive training simulations which are dynamic in nature, students are able to suspend their disbelief and engage in the experience.  By creating simulations that dynamically adapt based on a trainee’s choices, flow can be created much more easily than a linear alternative.


Thanks for reading. Please share with colleagues who might find value. This post was authored by Discovery Machine, creators of The RESITE Suite. RESITE enables instructors to capture their expertise to create their own realistic training scenarios. RESITE places trainees into an immersive 3D environment that helps them learn faster and see the cause/effect relationship of their decisions and hands-on interaction in real time. With over 16 years in the industry Discovery Machine delivers powerful, proven technology with a friendly, accessible front-end that translates to successful training programs empowered with intelligent interaction. For more information about The RESITE Suite, please visit Discovery Machine online or call 570-601-3226.



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Csikszentmihalyi, M. (1990). Flow: The Psychology of Optimal Experience. New York: Harper and Row. ISBN 0-06-092043-2

Geirland, John (1996). “Go With The Flow”. Wired magazine, September, Issue 4.09.

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