Screen shot from Bentham City
In light of the recently released Ethics and Game Design: Teaching Values through Play (IGI Press), I thought I would write a brief entry about our game (Bentham City) and its current status. In our chapter in Ethics and Game Design (co-authored by myself and Steve Fiore from Philosophy and the Institute for Simulation and Training at UCF), we articulated a series of guidelines for game development targeted for ethical learning games. We suggested more obvious guidelines, such as defining learning objectives and playtesting and considering assessment mechanisms, but we also suggested crafting opportunities for players to take advantage of what James Paul Gee calls the “projective identity,” or the projection of one’s own beliefs and desires onto a player-avatar.
This is easier said than done, however. We’ve gone through a few variations of this game so far, struggling to find a balance between interesting game scenarios and useful opportunities for ethical decision making. We finally decided upon a mechanic in which both self-worth and reputation can be manipulated through actions which occur in the game. As we finish up the game, we’re going to make it so that one’s reputation may decline, but self-worth improves, leading to situations in which the player’s character is not highly regarded, but the player is still successful because of a high self-worth. The question we are struggling with now is this: reputation is easy to connect to the gameworld (we just animate the characters’ expressions differently to show annoyance or script different dialog feedback depending on the value of the player’s reputation). But, self-worth is more difficult. We are trying to figure out how to connect a self-worth value (primarily an internal mechanism) to the environment. Perhaps the answer is that it has no affect on the world, other than lowering or raising the player’s overall “score”.
For anyone interested, the game can be accessed from here: http://sulley.dm.ucf.edu/~ethicsgame/bentham/game.html. We welcome feedback as we are in the process of playtesting and debugging the game.