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My colleague Steve Fairclough recently posted an article on PhysiologicalComputing.net in which he discusses the potential pitfalls of biometric research and how it is currently being sold to the game industry. I will present some of his ideas here.
Steve outlines that "psychophysiological methods are combined with computer games in two types of context: applied psychology research and game evaluation in a commercial context. With respect to the former, a researcher may use a computer game as a platform to study a psychological concept, such as effects of game play on aggression or how playing against a friend or a stranger influences the experience of the player."
Similar to Mike Ambinder's presentation of user research and game design at Valve (PDF), he makes the point that games in this context are analysed using principles of experimental psychology.
They are used as tasks or virtual worlds within which a research can study the behavior of players (you might recall John Hopson's Gamasutra article on behavioral game design).
He characterises the experimental psychology approach by 4 features:
- Comparing controlled conditions
- Importance of statistical power (large N)
- Controlled participant sample
- Counterbalanced design (removing order effects)
He makes a point about the sensitivity of physiological data as being volatile, variable and difficult to interpret without a high level of experimental control. He warns that the use of think aloud protocol might influence the physiological data being recorded because it influences heart rate and respiration considerably.
He also warns about the oversimplification regarding the interpretation of physiological data (something I have seen way too often), regarding its one-to-many relationship to psychological impact.
For example, galvanic skin response is used too often to infer emotional qualities although it is a highly ambiguous measure regarding emotional labels.
Steve closes with a discussion of the question of how to make physiological data and experimentation valuable to the game industry. Meaning, what questions can we answer with this type of data that the game industry does not already know?
(Please read Steve's original post here, too)
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