I am experimenting with finding a way to trace behaviors back to design features for a game and I figured affordances may be the way to go. The goal is through participant observation and interviews to tie behaviors back to affordances that are aimed back at artifacts. Here is what I have in mind with an example.
Say I want to study players playing FIFA online.
Stage 1: Play the game and attempt to identify artifacts and affordances. Artifacts do not have to just be part of UI but they can also non-visual (e.g., algorithms and other pieces of code). The view that I would build is still one of perceptual affordances but probably closer to a designers model rather than a user's model. That's okay. Also, I am expecting that of the affordances I discover not all users will perceive the same affordances or utilize all features in a game. In fact, some artifacts that lead to affordances may be a mystery to some players.
Example:
=Artifact= =Affordances=
Team Score indicator tracking game progress
predicting game outcome*
Player rank tracking players skill in the world
* An artifact can have more than one affordance. Some are implicit while others explicit. Not all affordances have to be confirmed at this stage either. This is so that I will have something to work with.
** I also may or may not categorize affordances at this point.
Stage 2: Play the game but this time attempt to actively talk to people as well as have interviews. The goal is to verify as many of the affordances identified as I can and even link them to the artifacts. At this stage, I also aim to expand affordances to further behaviors.
Example:
=Artifact= =Affordances= =Behavioral outcomes/effects=
Team Score indicator tracking game progress feeling pressured
predicting game outcome becoming more aggressive near the end of the game
Player rank tracking players skill in the world feeling exposed
* At this point some of affordances will be dropped if not verified. Others may be added. Behavioral are linked to affordances all the way to artifacts.
Grouping of artifacts and affordances under themes will be done at this point.
Stage 3: Ask actors more direct questions that aim to provide a more definitive picture of the links identified.
I omitted a lot of the process but kept the gist.
Thank you both for your feedback! This is most useful! I am hoping that as I will start researching the game more, I will understand more in-depth behavioral patterns that may emerge and other aspects. The idea on telemetry data may be possible too. The only issue is that the problem may not so easily solvable using quantitative data due to the complexity of interactions. However, quantitative data may help provide support for qualitative or theoretical arguments. In many ways, I am going without firm hypotheses and just build a theory and explore topics as they emerge. Far from what I've done in the past but figured it doesn't hurt to try an alternative approach.
Incorporating feedback is definitely the way to go.Some sort of feedback mechanism in real-time (e.g. an unravelling/evolving map of location vis-a-vis others), tends to enhance the interpretation of affordances. Or may serve as affordances all on their own. Cues to opportunistic possibilities in a strategic setting. In contrast to this, the classics such as pacman, which presents all the information on-screen during the game play (except for the edge of the maze), is a more faithful interpretation of affordances - ala J.J.Gibson, on line of sight. Frameworks that may be more amendable for this kind of experiments can be adapted from environmental psychology.The environment being a hybrid between the virtual and the real, as the gamer envisions him/herself in such a context.
Some Implications:
Michael,
You don't describe how you assess outcomes/efforts in stage 2 such as "feeling pressured", "becoming more aggressive near the end of the game". I am working on HCI using the humanities -- maybe you can apply my ideas in your research.
You could measure behavior using means of the humanities defined in my research as modeling dimensions. For example, dimension 'space' measuring physical proximity between persons could influence behavioral aspects in games and be implemented using infrastructure of RoboCup (Simulation League). See section 3.5 "Summary of significant modeling dimensions", section 6.4 "Implementations of agent-specific modeling dimensions", section 6.5 "Implementations of simulation-wide modeling dimensions" for detailed information (see below).
Chapter Scenarios of Social Interaction
Chapter Prototypes of Social Simulation
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