Most trainers easily understand and accept the concept of a simulation. However, shallow understanding and mindless acceptance of this technique frequently results in its abuse. To prevent such abuse, I would like to explore four common misconceptions about simulations.
Bases of Simulations
Misconception: Simulations reflect reality.
Reality: Simulations reflect someone's model of reality. There is an important difference between reality and a model of reality. This difference has critical implications for the design and use of training simulations.
Let's assume that you want to simulate the quality-improvement process in a service organization. Exactly what features and processes you select for the simulation will depend on your professional discipline and personal preferences. For example, if you are a behaviorist, you may interpret the process in terms of stimuli from customers, responses from employees, and reinforcers from managers. If you are a humanist, you may look at the customer-service process in terms of customer expectation, employee empowerment, and manager motivation. If you are a sociologist, you may focus on organizational norms and individual roles. If you are a lawyer, you may emphasize contractual obligations, legal violations, and policy issues. If you are an accountant, you may compare the costs of providing different levels of service with the short- and long-term payoffs of satisfying a customer.
In addition to these professional filters, your model of reality depends on your personal preferences and personality characteristics. If you are an optimist, you may directly correlate better services with profitable bottom lines. If you are a pessimist, you may introduce such random variables as policy changes, governmental regulations, customer vacillations, and environmentalist agitations.
These concepts of multiple realities and of selective emphasis have important implications in the design of a simulation. You have to explicitly document what variables and relationships are included in your model and why you choose to include them (and to exclude others).
Varieties of Simulations
Misconception: All simulations are basically the same. If you have seen one, you have seen them all.
Reality: Simulations come in different shapes and sizes. While it is true that most simulations compress space and time, they may do so at a variety of levels using a variety of technologies and symbol systems.
Here are some simulations at a mega level: Scientists create computer models to explore the impact of the greenhouse effect on the planet Earth. Business people experiment with what-if scenarios of the global marketplace during the next century. Political scientists study the next world war in a simulated setting.
Here are some simulations at a macro level: Benefit specialists collect feedback about a new incentive system by piloting it in a branch office. Trainers present the new corporate sexual harassment policy by discussing simulated case studies. Recruiters assess potential executives by administering in-basket exercises.
Here are some simulations at the micro simulations: Forensic scientist study the impact of a bullet on a Kevlar vest. Marketers examine the behavior of people in a waiting line in the bank. Human factors people create models of the left thumb to explore repetitive stress injuries.
We can categorize simulations into computer and manual simulations. In a sample computer simulation, players read information displayed on the screen, make decisions, and enter them through a keyboard. Based on their decision, they receive a score and move to the next decision point. In the sample manual version of a similar simulation, players read a chapter of a novel, analyze the decision requirement at the end of the chapter, and choose among several alternatives. Based on their choice, they are directed to a different page of the book for the next installment of the scenario.
Here are some other types of simulations:
- Based on the system delivering the simulation, we can have mathematical simulations (such as a formula), graphical simulations (such as a flow diagram), or physical simulations (such as a working model of an automobile engine).
- Based on whether we emphasize the stimuli or the responses and whether we provide limited response choices or wide open ones, we can classify an activity into a roleplay or a simulation. For example, if we tell a doctor to talk to another doctor, imagining her to be a patient, we have a roleplay. If we provide a doctor with a computer simulation of a CAT scan and ask her to make a diagnosis, it is primarily a simulation.
- Based on how users interact with the simulation, we can have a static or a dynamic simulation. A globe is a static simulation of the Earth. A circular rug on which we attempt to stand increasing numbers of people provides a dynamic simulation of the overcrowding of earth.
- Based on the time span, we can have a historical simulation (such as the exploration of the New World), a current simulation (such as the construction of the space station), or a futuristic simulation (such as the terraforming of the Martian landscape).
Uses of Simulations
Misconception: Simulations are used for technical training.
Reality; Simulations can be used in a variety of ways to improve human performance. Here are some examples.
Training. Corporate trainers use simulations for helping the participants master principles and processes in business, management, and sales. Technical trainers use simulators to provide hands-on experience with equipment and machinery. As a training tool, simulations can help the participants to master complex concepts (for example, how production cost, customer demand, delivery channel, promotion strategy, and market position interact with each other and determine the appropriate price of a product). By forcing trainees to cope with several factors at the same time, simulations do a much better job of equipping them to handle complex interactions than other instructional methods that require a linear, one-variable-at-a-time presentation.
Performance assessment. Valid performance tests usually involve some form of simulation. Computerized management simulations assess the ability of an applicant to effectively manage limited resources. High-fidelity cases measure manager's decision-making skills. Appropriate roleplays, involving professional actors to provide standardized triggering behaviors, evaluate different interpersonal skills. In-basket exercises test a candidate's ability to organize and to prioritize.
Teambuilding. Simulations, especially of the non-computerized kind, are used for eliciting, maintaining, and improving the performance of teams. Any simulated project (such as crossing a mine field, surviving a plane crash in a desert, or finding a mythical treasure) that requires a team to plan and implement a strategy produces powerful insights. During and after the simulated activity, team members improve their performance in such interpersonal areas as giving feedback, setting goals, making decisions, solving problems, resolving conflicts, managing diversity, negotiating roles, and persuading others.
Research. Simulations provide useful research data at a fraction of the usual cost. Sophisticated computer simulations are replacing animal testing of cosmetics and pharmaceuticals. Crash dummies provide data useful for saving real dummies who forget to fasten their seat belts. Playing the Prisoner’s Dilemma identifies basic factors that induce cooperative and competitive behaviors. A focus group’s behavior predicts reactions of the customer group.
Therapy. Simulations provide metaphors for different behaviors and their consequences. Participation in simulated activities provides powerful insights. For example, a solitaire game may reflect the consequences of taking inappropriate risks. After playing the game, we can encourage the player to draw analogies between what happened in the game and what happens in real life. The participant can figure out appropriate changes in the game strategy to increase the final score. From there, he or she can transfer the insights to real-life situations to reduce self-defeating behaviors.
Fidelity of Simulations
Misconception: High fidelity simulations are more effective than low fidelity simulation.
Reality: Either type of simulation can be equally effective in different contexts.
High fidelity simulations incorporate a large number of elements and attempt to capture every interaction. The physical artifacts used in these simulations are the same as their real-world counterparts; if not, they are created with a high degree of verisimilitude. A complex model involving huge amounts of quantitative data and thousands of rapid calculations drives the simulation. For example, a virtual reality flight trainer uses the actual cockpit from a fighter plan, complete with all the instruments and controls. A computer-driven rear-screen projector shows an authentic view out of the pilot's window. The computer program responds to the pilot-trainee's every move and dynamically alters the outside view and the inside readings on different indicators. The program produces alternative terrain and weather conditions at the request of the instructor.
Low-fidelity simulations, in contrast, focus on only a few critical elements and use a simplified model of the interactions among them. The physical artifacts and the environment do not correspond to what is being simulated in any detail. For example, a facilitator may say, “Imagine you and the other five people at your table are in a leaky lifeboat in a shark-infested ocean. Your lifeboat can only handle four people…” Participants, left to their own devices, attempt to persuade the others to volunteer to jump in the ocean. Nothing physically changes in the situation, except in the imagination of the players.
You need sophisticated technology and proven principles from hard sciences to design and use high-fidelity simulations. Engineers have appropriate formulas to simulate the landing of a missile, after a flight of hundreds of miles, correct to a nearest meter. You can use these high-fidelity simulations to make accurate predictions. Training devices that employ such simulations result in very reliable transfer and application of skills. A high-fidelity dress rehearsal of a fully-equipped ethnic restaurant with invited guests helps us identify and fix last-minute glitches before opening for business with the general public.
This effectiveness of high-fidelity simulations is obtained at a high cost or at a potentially high risk. In matters of life and death, such costs are more than justified. In other situations, cost-effectiveness considerations may suggest a reduced level of fidelity.
Low-fidelity simulations have a few advantages. Let's consider a simulation game, Barnga, used for increasing participants' awareness factors in cross-cultural communication. In this simulation, groups of participants, seated at different tables, learn to play a simple card game. Unknown to the players, the rules at each table differ slightly from those in the other tables. As a result, an amazing amount of confusion and frustration results when winners from each table are promoted to the next table to play a tournament round,. Depending on the personality and perceptions of the participants at each table, they may or may not be able to reconcile their differences and continue playing.
Early rounds of Barnga simulate the enculturation process, the tournament reflects cross-cultural interactions, and the gag order represents language and communication problems. Admittedly, the correspondence between the simulation and a typical cross-cultural interaction is very low. However, participants invariably report powerful insights from the play of the game. For example, participants claim that they have learned to appreciate the importance of checking their assumptions in any novel situation. Follow-up studies suggest that participants' workplace behaviors include increased number of requests for clarifying assumptions. Branga becomes a metaphor to remind people to say, “Let's check what rules we are playing by.”
In general, high-fidelity simulations are more suited for teaching procedures while low-fidelity simulations are suited for teaching principles. Both types of simulations have critical roles to play in different situations. The question is not which type of simulation is more effective, but rather which type of simulation is more suited for achieving our objective within our cost constraints.