Theories of Games and Interaction for Design (7: On theories, design, objectivity, and murk)

Approximate Reading Time: 3 minutes

These are public postings of my writings for the first course of the Graduate Certificate Program in Serious Game Design and Research at Michigan State University.

Please note: these posts are not intended as any kind of commentary on or assessment of the course I’m taking, or its instructor, OR of Michigan State University or the College of Communication Arts and Sciences, or the Department of Telecommunication, Information Studies and Media. They are solely my thoughts and reactions that stem from the readings.

Feel free to comment, disagree, or what have you.

Week 7

These are the readings for the week (Topics: Theories of Behavior Part 2: Community Organization, Diffusion of innovation, Media Effects, Putting Theory into Practice Using Planning Models):

  • Peng, W. (2009). Design and evaluation of a computer game to promote a healthy diet for young adults. Health Communication, 24, 115-127.
  • NIH Theory at a glance (pg. 22-31, 35-46 – USE PAGE NUMBERS IN DOCUMENT, NOT THE ONES IN ACROBAT) National Institutes of Health (2005). Theory at a glance: A guide for health promotion practice. Retrieved August 15, 2010 from
  • Optional:  Daley, A. J. (2009). Can Exergaming Contribute to Improving Physical Activity Levels and Health Outcomes in Children? Pediatrics, 124, 763-771
  • Optional: Anderson-Hanley, C., Snyder, A., Nimon, J., Arciero, P. (2011). “Social facilitation in virtual reality-enhanced exercise: competitiveness moderates exercise effort of older adults,” Clinical Interventions Aging. 2011; 6: 275–280.

My head’s starting to swim from all the theories we’ve been talking about and I’m finding it harder and harder to hold a clear picture of the theories and their applications in my head.

I’m even still struggling with the word “theory” itself. I suspect that has to do with the fact that I’ve been a scientist for about 35 years. That is to say, I’ve been an actual scientist** doing natural and physical science stuff (as opposed to a political scientist, or any number of other social callings that feel the need to refer to themselves as scientists, presumably in the mistaken notion that using the word ‘science’ will somehow make what they do science). So, for my own clarity of mind, I will refer to all of the concepts we’ve been covering as “models”.

As I see it, there are two main ways we can approach theory driven design.

  1. Design a game around one or more theories.
  2. Settle on a main objective and then select one or more theories we believe will help us achieve that objective.

To me, the first one seems too much like an intellectual or academic exercise. If one is trying to test out or better understand a theory then this is a good way to go about it. However, in doing so, it seems to be you’re *still* choosing the objective first. In this case your objective just happens to be testing out a theory. It’s almost like a meta-objective.

When I am designing a serious game, the first thing I try and figure out is my primary goal, in other words, what is it players are supposed to be getting out of this experience? Until we have a reasonably good understanding of why we are creating this game we can’t really start to think about what theories might be useful in this context.

Many, if not most of the models we’ve been looking at are pretty subjective, both in terms of how one might measure whether or not the goals of the intervention are met, as well as whether or not the final design of our intervention is indeed an embodiment of the theory as described. That’s not to say that this approach isn’t worthwhile, I think it probably is, or at least, it can be. It does mean though, that there aren’t going to be any clear recipes for how to do this. In the end, the actual design and implementation of the application itself (in our case, a serious game) will probably proceed by following more familiar paths.

As a programmer and systems analyst, I tend to rely on my programming and software development experience when designing games, but that’s not enough. At the same time, I try to keep an eye on both sides of the machine, as it were:

  1. Inside the machine (i.e. at the code level), which where the programmers live.
  2. Outside the machine (i.e. the interface and behavior of the application), which is where the users live.

The models of behavior that we’ve been looking at have influence in the second perspective. We consider them when we do the designs, but not so much when we do the implementation. However, there are always changes that happen as the implementation is proceeding, and it is important to remain aware of whether or how implementation changes may affect the way a behavioral model is embodied.


Health Communication Unit, Ontario Public Health, A comparison of Workplace Health Planning Models

**For two notions on what is science, see:

A lecture by Richard Feynman, What is Science? Presented at the fifteenth annual meeting of the National Science Teachers Association, 1966 in New York City, and reprinted from The Physics Teacher Vol. 7, issue 6, 1969, pp. 313-320 by permission of the editor and the author.

A tirade by Neil deGrasse Tyson, recorded on youtube:

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