Although the technological advances of the last 20 years have revolutionised the development of games and simulations, Gredler’s book is still worth a look. The dazzling possibilities offered by technology can sometimes distract from fundamental design issues but Gredler, writing at a time when the Apple II was cutting edge, keeps her focus on learning objectives rather than the enabling technologies.
Gredler begins as she intends to go on, asserting a clear distinction between games and simulations and then proceeds to sub-divide simulations into 2 major types, and then 6 sub-types as she doggedly follows her categorising agenda. A comprehensive listing of the resulting hierarchy would be exhausting, so here‘s the short version:
Games and Simulations
Game: a world unto itself, determined by rules that are not replications of real life; involves winning by taking any course of action allowed by the rules; consequences experienced as a player do not extend to real life (so any skills developed would help only in playing the game better)
Simulation: based on real life; problem-based unit of learning; problems without easily determined solutions; participants carry out functions associated with their defined roles and circumstances; participants experience “reality of function” (given bona fide roles, address problems seriously and conscientiously); outcomes primarily determined by actions of participants – not by chance or luck.
Types of Simulation
Tactical-Decision Simulation: The primary interactions are with a complex problem in which participants, in executing their roles, use their skills in interpreting data, organising findings and managing a solution strategy to the problem. There are 3 sub-types – diagnostic (define nature of a complex problem and implement strategies), crisis management (allocate resources to avert or minimise an impending threat) and data management (manage a set of data to fulfil defined goals).
Social-Process Simulation: The primary interactions are among participants as they try to achieve a social or political goal. Again there are 3 sub-types – social system (participants engage in the social or political processes that form the fabric of organised social groups), language skills/communication (participants placed in a challenging situation requires participants to stretch their communication skills) and empathy/insight (participants undergo a frustrating or traumatic event and struggle to function in this changed environment).
I think Gredler’s definition of a simulation is more successful than her take on games (why can’t the rules of a game be replications of real life?) and maybe simply “not a simulation” would have been a better definition. I think the participants intent or attitude is also a factor worth mentioning here. And although she accepts that a simulation may have elements of more than one type, I suspect that in practice some simulations may sit uneasily between categories. Gredler goes on to devote chapters to academic games and then to each major simulation type and subtype.
Green Revolution seems to fit best in the ‘Data Management simulation' (DMS) sub-type of Gredler’s taxonomy, though with elements of the ‘empathy/insight’ sub-type. In DMSs participants are required to allocate resources to achieve a particular goal and the main focus is on the interrelationships and trade-offs among variables.
Gredler offers some general guidelines in designing simulations of this type:
- problem and variables must be meaningful to the participants – otherwise it will be treated as a game (so don’t ask the average primary school kid to run the World Bank)
- participants in their roles must feel compelled to address the problem
- defined roles must allow maximum opportunity to engage with the problem (don’t create roles peripheral to the main task)
- participants are empowered to address the problem (they have the expertise and authority to act)
- participants decisions and actions (not random events) are the major determinants in the outcome (they feel some measure of control)
- underlying model should be logical and credible to participants (make sense and be consistent)
- variables must be quantifiable (as simulation based on a mathematical model that calculates the outcomes) - but avoid trying to quantify the unquantifiable
Gredler suggests that a sufficiently comprehensive array of variables and a wide range of decision options be made available to the participants to make the simulation realistic and engaging. She also suggests thinking through a range of action/decision scenarios and about the information the participants need be given (what and when).
Gredler has clear views on to evaluating performance. She believes that judging participants as winners or losers is counterproductive for several reasons:
- it can encourage unhelpful behaviours e.g. desperation plays (huge gambles) and end of activity plays (focusing on very short-term goals)
- it can encourage excessive competitiveness which may lead some participants to treat the simulation as a simply a game where the only object is to ‘beat everyone else’.
- some participants may simply disengage physically or mentally if the focus is simply on winning.
- in the post-simulation discussion, winners tend not to question their own decisions or acknowledge the help they received from others.
This all seems well and good but raises questions regarding simulations of real-world situations in which there are winners and losers and where life is anything but equitable. (Gredler, perhaps failing to recognise the empathy/insight aspect of the simulation, takes a swipe at the original Green Revolution Game because the social inequalities modelled in the game led some participants feeling humiliated when they had to ask wealthier players for a loan). There’s clearly a balance to be struck when designing a simulation which gives the participants a positive learning experience but doesn’t shy away from reflecting real-life inequalities.
To be effective the simulation should lead to reflection on the experience and to new patterns of thinking and so Gredler devotes a chapter to post-simulation activities, which she sees as a crucial to the learning process. She suggests that the post-simulation discussion should be given as much time as the simulation itself, but notes (in the chapter on empathy/insight simulations) it may take several weeks for participants to fully process the impact of the simulation. Therefore several activities should be planned to give them opportunities to explore their experience. She applies both Lewin’s and Piaget’s models of experiential learning in her discussions. Here’s one possible composite scheme pulled from her various notes:
- immediately after the simulation give participants a short informal break (without co-ordinators) to give them space to release any pent up feelings
- participants then complete a questionnaire that focuses on their memories of the experience.
- co-ordinator then invites participants to make any immediate comments.
- discussion proceeds to more orderly discussion of the simulation:
+ determine what actually took place
+ identify participants thoughts and feelings about the events and the perceptions that led to decisions
+ explore possible alternative actions
+ develop generalisations
- discussion broadens to include wider implications of experience
- a second meeting should be scheduled for 1 or 2 weeks later to revisit the experience.
In all this she emphasises that the co-ordinator's role is that of facilitator, not “expert”.
In summary - the book does feel a bit dated and Gredler's relentlessly systematic and prescriptive approach to her subject can be irritating. However she has produced a well-structured book that succeeds in it's stated aim of addressing the core issues involved in the design of games and simulations.