Difference between revisions of "Experimenting"

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[[Category:Staffan's current workpage]]
 
 
[[Category:Patterns]]
 
[[Category:Patterns]]
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[[Category:Action Patterns]]
 
[[Category:Needs revision]]
 
[[Category:Needs revision]]
[[Category:Needs examples]]
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''Exploratory actions done to learn the rules or state of a game, or to practice one's skills or strategies.''
[[Category:Needs references]]
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[[Category:Stub]]
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''Exploratory actions to learn how the rules of cause and effect work in a game.''
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This pattern is a still a stub.
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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.
  
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.
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Linderoth<ref name="Linderoth"/> points out that actions in games are either ''exploratory'' or ''performatory'', where the former can be seen as a form of [[Experimenting]].
  
 
=== Examples ===
 
=== Examples ===
Example: 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.
+
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.
  
Example: 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 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.
  
Example: The computer game The Incredible Machine 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.
+
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.
 
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Example: 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.
+
 
+
Example: Creating potions in 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 ==
 
== Using the pattern ==
ref to Gees learning principle and Linderoth's paper
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[[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.
  
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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).
  
Experimenting is a form of Gain Information goal and as such requires 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. In the first two cases, gaining the Imperfect Information gives Strategic Knowledge about the Predictable Consequences in the game, while the last case can provide information about other players' game elements and tactics. The actual actions used in the Experimenting can be any; with Experimenting, players learnabout the actions by performing them. However, it is especially common with Experimenting when doing Puzzle Solving , finding possible Combos, or trying to find Achilles' Heels of Enemies.
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[[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 [[:Category:Fighting Games|Fighting Games]]) or to identify emergent effects of [[Construction]].
  
In order to encourage Experimenting, the actions should not have severe consequences. In Quick Games, this may not be a problem if the outcome of the game has no Extra-Game Consequences, as a new game session can be started again. In other forms of games, Experimenting is encouraged by having Reversability of actions, either by allowing Save-Load Cycles or avoiding Irreversible Actions. This is typically easier to do in games with Dedicated Game Facilitators, as they can easily restore game states and not require players to do so. Actions that are closely related to Constructive Play, for example Construction, are better suited for Experimenting, because these actions are less likely to result in Competition. Providing Reversability in certain locations, which can be seen as a form of Safe Havens, allows for Smooth Learning Curves, as players can train and gain a certain level of Game Mastery before having to risk failure.
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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.
  
When Experimenting can have severe consequences, they create Tension and can require Leaps of Faith but also encourage Stimulated Planning. Competition puts players in situations where the effect of every action can have the potential of affecting the overall outcome of the Competition, and due to this act of Experimenting, these situations force players to make Risk/Reward choices between the potential benefits of the experiment against the possible loss of not performing the most optimal action.
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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.  
 
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=== Diegetic Aspects ===
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=== Interface Aspects ===
 
=== Interface Aspects ===
 
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While the ''exploratory'' actions in games described by Linderoth<ref name="Linderoth"/> 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 Indicators]], [[Vision Modes]], or [[Geospatial Game Widgets]] used for ''highlighting'' game objects or otherwise pointing out important game entities for players.
=== Narrative Aspects ===
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== Consequences ==
 
== Consequences ==
Experimenting relies on the presence of a Gain Information goal, which players try to complete by performing different variations of actions in a game. The act of planning and Experimenting promotes Cognitive Immersion and can modulate the Right Level of Difficulty of a game. 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 provide Strategic Knowledge.
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The act of planning and [[Experimenting]] promotes [[Cognitive Engrossment]] in games, and both [[Casual Gameplay|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 and can thereby let players acquire [[Gameplay Mastery]] over time.  
  
The possibility of Experimenting in a game can aid in avoiding the emergence of Analysis Paralysis, as players can try the effects and consequences of their ideas and plans rather than try to deduce the effects and consequences. This can provide Smooth Learning Curves.
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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.  
  
Using Non-Renewable Resources when Experimenting can be costly but encourage Stimulated Planning, unless the game allows players to use Save-Load Cycles.
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Rather obviously, [[Irreversible Events]] work against making players engage in [[Experimenting]].
  
 
== Relations ==
 
== Relations ==
[[Irreversible Events]]
 
[[Time Limits]]
 
[[Achievements]]
 
[[Randomness]]
 
[[Challenging Gameplay]]
 
[[Combos]]
 
[[Characters]]
 
[[Stimulated Planning]]
 
[[Single-Player Games]]
 
[[Testing Achievements]]
 
[[Arithmetic Progression]]
 
[[Construction]]
 
[[Safe Havens]]
 
[[Strategic Knowledge]]
 
[[Predictable Consequences]]
 
 
 
=== Can Instantiate ===
 
=== Can Instantiate ===
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[[Illusionary Rewards]],
 +
[[Gameplay Mastery]],
 +
[[Leaps of Faith]],
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[[Randomness]],
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[[Smooth Learning Curves]],
 +
[[Tension]]
  
==== with ... ====
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==== with [[Non-Renewable Resources]] ====
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[[Stimulated Planning]]
  
 
=== Can Modulate ===
 
=== Can Modulate ===
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[[Casual Gameplay]],
 +
[[Challenging Gameplay]],
 +
[[Strategic Knowledge]]
  
 
=== Can Be Instantiated By ===
 
=== Can Be Instantiated By ===
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[[Arithmetic Progression]],
 +
[[Complex Gameplay]],
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[[Gain Competence]],
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[[Red Queen Dilemmas]],
 +
[[Safe Havens]],
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[[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]]
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 +
[[Puzzle Solving]] together with [[Reversibility]]
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 +
[[Single-Player Games]] together with [[Reversibility]] or [[Save-Load Cycles]]
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 +
[[Quick Games]] when no [[Extra-Game Consequences]] exist
  
 
=== Can Be Modulated By ===
 
=== Can Be Modulated By ===
 +
[[Time Limits]]
  
 
=== Possible Closure Effects ===
 
=== Possible Closure Effects ===
 +
-
  
 
=== Potentially Conflicting With ===
 
=== Potentially Conflicting With ===
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[[Analysis Paralysis]],
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[[Competition]],
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[[Geospatial Game Widgets]],
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[[Irreversible Events]],
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[[Point of Interest Indicators]],
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[[Randomness]],
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[[Vision Modes]]
  
 
== History ==
 
== History ==
Line 83: Line 98:
 
<references>
 
<references>
 
<ref name="Bjork & Holopainen 2004">Björk, S. & Holopainen, J. (2004) ''Patterns in Game Design''. Charles River Media. ISBN1-58450-354-8.</ref>
 
<ref name="Bjork & Holopainen 2004">Björk, S. & Holopainen, J. (2004) ''Patterns in Game Design''. Charles River Media. ISBN1-58450-354-8.</ref>
 +
<ref name="Linderoth">Linderoth, J. (2010). Why gamers donʼt learn more - An ecological approach to games as learning environments. In proceedings of Nordic DiGRA 2010.</ref>
 
</references>
 
</references>
  
 
== Acknowledgements ==
 
== Acknowledgements ==
 
-
 
-

Latest revision as of 07:57, 11 August 2016

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.

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 Indicators, 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 and can thereby let players acquire Gameplay Mastery over time.

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, Gameplay Mastery, Leaps of Faith, Randomness, Smooth Learning Curves, Tension

with Non-Renewable Resources

Stimulated Planning

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

Time Limits

Possible Closure Effects

-

Potentially Conflicting With

Analysis Paralysis, Competition, Geospatial Game Widgets, Irreversible Events, Point of Interest Indicators, 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. 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.
  2. Björk, S. & Holopainen, J. (2004) Patterns in Game Design. Charles River Media. ISBN1-58450-354-8.

Acknowledgements

-