Difference between revisions of "Experimenting"
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[[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 [[Competition|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. | [[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 [[Competition|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 Gameplay]], 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]]). | + | Actions that are closely related to [[Constructive Gameplay]], 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]]). The possibility to have [[Save Files]] also encourages [[Experimenting]] since players can rely on being able to go back to previous game states before initiating potentially riskily gameplay actions. |
=== Interface Aspects === | === Interface Aspects === | ||
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[[Red Queen Dilemmas]], | [[Red Queen Dilemmas]], | ||
[[Safe Havens]], | [[Safe Havens]], | ||
+ | [[Save Files]], | ||
[[Stimulated Planning]], | [[Stimulated Planning]], | ||
[[Testing Achievements]] | [[Testing Achievements]] |
Revision as of 13:28, 10 November 2015
Exploratory actions done to learn the rules or state of a game, or to practice one's skills or strategies.
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, but in other cases they may be necessary to do in all game sessions. 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. 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. Puzzle-solving in Sokoban can take the form of Experimenting since failures only require players to replay levels.
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 to reach goal states by making the objects interact with each other in certain ways. 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.
Creating potions in The Elder Scrolls III: Morrowind can require Experimenting if players are not alchemist masters, as not all effects of ingredients are known until one reaches that skill level.
Using the pattern
Experimenting can rely on the presence of Gain Information or Gain Competence goals so that players try to reach these goals by performing different variations of actions in a game, but this is not always enough since harsh Penalties for failure may make players cautious. Complex Gameplay can either by itself or in combination with Gain Information or Gain Competence make players engage in Experimenting since a trial by error method may be the easiest (and possibly best) way of learning about how the game system works.
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, being able to do Stimulated Planning or combining Predictable Consequences with Limited Foresight is necessary for Experimenting to be worthwhile, while for the last case Experimenting can be supported by offering to possibility of gaining information about other players' Avatars, Units, Skills, Technology Trees, etc. Puzzle Solving is related to Gain Information in that the activity can be seen as wanting to find the right actions to perform. However, since testing this affects the game state games need to support Reversibility if the games overall should promote Experimenting. A specific type of Experimenting required in games with Enemies can be to figure out their Achilles' Heels or other types of Vulnerabilities. While the need for Predictable Consequences can make the presence of Randomness counterproductive for Experimenting, it can also make it required to experiment to figure out the nature of game environment (NetHack requires this to figure out the effects of scrolls, potions, and rings).
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 Gameplay, 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). The possibility to have Save Files also encourages Experimenting since players can rely on being able to go back to previous game states before initiating potentially riskily gameplay actions.
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, Tension
with Non-Renewable Resources
Can Modulate
Casual Gameplay, Challenging Gameplay, Strategic Knowledge
Can Be Instantiated By
Arithmetic Progression, Complex Gameplay, Gain Competence, Red Queen Dilemmas, Safe Havens, Save Files, 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
Puzzle Solving together with Reversibility
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
-
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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