Bartle's Types

I used Bartle's 4 types as a starting ground to brainstorm possible underlying motivations. Bartle elaborates on these 4 types in his paper - Hearts, Clubs, Diamonds, Spades: Players Who Suit Muds. Here is a brief summary of Bartle's 4 Types:

- Achievers are driven by in-game goals, usually some form of points gathering - whether experience points, levels, or money.

- Explorers are driven to find out as much as they can about the virtual construct - including mapping its geography and understanding the game mechanics.

- Socializers use the virtual construct to converse and role-play with their fellow gamers.

- Killers use the virtual construct to cause distress on other players, and gain satisfaction from inflicting anxiety and pain on others.

Bartle weaves a fairly elaborate model on how these different types interact with other, as well as how the balance of these different types will cause drifts to occur in the player base. While elegant and cleverly modeled, Bartle's types were not constructed from empirical data, but rather, from a long discussion among MUD wizards.

One problem with such a just-so model is that the 4 types may overlap. For example, it may be the case that most Achievers are Explorers, because to advance in levels quickly, one has to know about the game mechanics. Another problem is that the types may not be well-constructed, and may include unnecessary traits and exclude important traits. For example, perhaps the Achiever scale should be based upon a desire for power rather than points accumulation. Or perhaps, mapping geography is not that important to most Explorers who are actually much more interested in the game mechanics.

The problem of employing a just-so model is that it becomes self-fulfilling. If a questionnaire is constructed such that a respondent has to choose between being an Achiever or an Explorer, then the end result will be a dichotomy where none may exist to begin with. It would be like asking - Do you prefer pizza or ice-cream?

Nevertheless, Bartle's preliminary model serves as a good starting point, and gives us a foundation on which to understand underlying motivations, as well as a model to test against empirical data.

Copyright, March 2002, by Nicholas Yee.

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