Experimenting
Exploratory actions to learn how the rules of cause and effect work in a game.
This pattern is a still a stub.
In all but the most simple of games, the complete consequences from actions performed are difficult to understand, but Experimenting can aid in understanding them. Actions may be tested for this reason simply because they have not been tested before if a player is willing to see a game session primarily as a learning period. Some games explicitly build experimenting into gameplay as puzzles. In these cases, the actions used to test possible solutions are usually reversible.
Linderoth[1] points out that actions in games are either exploratory or performatory, where the former can be seen as a form of Experimenting.
Contents
Examples
Gameplay in Mastermind consists of one player guessing the correct combination of colored pegs. As the chance for guessing correctly based only on luck is very small, successful gameplay requires that the player combines the results from different guesses to draw conclusions and uses the guesses as experiments.
In Pontifex, players' goals are to build bridges and to learn how the physics model works. The players' have to experiment with how cable, joints, and metal beams interact.
The Incredible Machine game series lets players use a limit set of objects such as pipes, bowling balls, cats, candles, ropes, and balloons to try and reach goal states by making the objects interact with each other in certain ways.
The abstract game Zendo require players to set up arrangements of different colored pyramids to extrapolate the correct arrangement rules that a game master has decided to use for that particular game instance.
Creating potions in The Elder Scrolls III: Morrowind can be an experiment if the player is not an alchemist master, as not all effects of ingredients are known until one reaches that level.
Using the pattern
Experimenting relies on the presence of Gain Information or Gain Competence goals that players can try to complete by performing different variations of actions in a game, but this is not enough since harsh Penalties for failure may make players cautious.
When Gain Information goals lie behind the need for Experimenting, it also implies a presence of Imperfect Information. The Imperfect Information can be about the fundamental rules of cause and effect in computer games, about the long-term consequences of actions, or about the game state. For the first two cases, Predictable Consequences need to be combined with Limited Foresight for the Experimenting to be worthwhile while for the last case Experimenting can provide information about other players' Avatars, Units, Skills, Technology Trees, etc. A specific type of Experimenting required in games with Enemies can be to figure out their Achilles' Heels or other types of Vulnerabilities.
Gain Competence goals that are to support Experimenting have similar requirements as those for Gain Information goals but here it may also be that players need to experiment as part of learning their skills. However, the need for Experimenting can be mechanically encouraged by Combos - either because they are part of Hidden Rules (something sometimes done in Fighting Games) or to identify emergent effects of Construction.
Competition puts players in situations where the effect of every action can have the potential of affecting the overall outcome, and this may work against players willingness to experiment. This can be compensated by making the Competitions contain Red Queen Dilemmas. Severe consequences of Experimenting may not be a problem in Quick Games as long as they have no Extra-Game Consequences, as a new game session can be started again. In Single-Player Games, problematic consequences can be avoided by having Reversibility or supporting Save-Load Cycles. Time Limits can work against players considering alternatives, but can also force players to try something simple because they are running out of time.
Actions that are closely related to Constructive Play, for example Construction, are often better suited to support Experimenting than other actions because they are less likely to result in Competition. Specific design solutions to encourage Experimenting in a more general fashion include Safe Havens (players can experiment without feeling threatened), Arithmetic Progression (erroneous efforts have limited consequences), and Testing Achievements (players are given these Extra-Game Consequences as rewards for simply Experimenting).
Can Instantiate
Potentially Conflicting With
Can Be Instantiated By
Interface Aspects
While the exploratory actions in games described by Linderoth[1] can be seen as Experimenting, some patterns can work against this since they remove the need for players to do these actions. Examples of this include Point of Interest Indications, Vision Modes, or Geospatial Game Widgets used for highlighting game objects or otherwise pointing out important game entities for players.
Consequences
The act of planning and Experimenting promotes Cognitive Engrossment in games, and both Casual and Challenging Gameplay can be modulated by how costly it is to do Experimenting. When Experimenting can have severe or costly consequences, they create Tension and can require Leaps of Faith but also encourage Stimulated Planning, especially if Non-Renewable Resources need to be used for the Experimenting. As the actions performed when Experimenting do not usually fulfill a goal in the game, the activity gives Illusionary Rewards, but these can be valuable for gameplay since they may let players discover the Strategic Knowledge which is possible to acquire.
The possibility of testing various ways of performing actions and trying to reach goals in games makes Experimenting support Smooth Learning Curves. Related to this, Experimenting in a game can aid in avoiding Analysis Paralysis, as players can try the effects and consequences of their ideas and plans rather than try to deduce the effects and consequences.
Rather obviously, Irreversible Events work against making players engage in Experimenting.
Relations
Can Instantiate
Illusionary Rewards, Leaps of Faith, Randomness, Smooth Learning Curves, Stimulated Planning, Tension
Can Modulate
Casual Gameplay, Challenging Gameplay, Strategic Knowledge
Can Be Instantiated By
Arithmetic Progression, Gain Competence, Red Queen Dilemmas, Safe Havens, Stimulated Planning, Testing Achievements
Combos together with Construction or Hidden Rules
Enemies together with Achilles' Heels or Vulnerabilities
Gain Information together with Imperfect Information
Predictable Consequences together with Limited Foresight
Single-Player Games together with Reversibility or Save-Load Cycles
Quick Games when no Extra-Game Consequences exist
Can Be Modulated By
Possible Closure Effects
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Potentially Conflicting With
Analysis Paralysis, Competition, Geospatial Game Widgets, Irreversible Events, Point of Interest Indications, Randomness, Vision Modes
History
An updated version of the pattern Experimenting that was part of the original collection in the book Patterns in Game Design[2].
References
- ↑ 1.0 1.1 Linderoth, J. (2010). Why gamers donʼt learn more - An ecological approach to games as learning environments. In proceedings of Nordic DiGRA 2010.
- ↑ Björk, S. & Holopainen, J. (2004) Patterns in Game Design. Charles River Media. ISBN1-58450-354-8.
Acknowledgements
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