Motivational Design

Lenses and Patterns for Motivational Game Design

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lenses:optimal_challenge

Optimal Challenge

Optimal Challenge refers to the concept of challenging the player at the level that creates the best balance for the player's experience. The two components of Optimal Challenge are difficulty and absorption potential. Difficulty is the simply the level of challenge that you present the player with, and ties into the expected player reaction to said challenge. Difficulty ranges from the extreme of frustration, to the opposite boredom, Absorption potential is the ability of the game to engross the player. Games require an active engrossment in contrast to other forms of media that are not inherently active, but generally passively engrossing. Providing optimal challenge will entice the player to maintain playing the game, but care must be taken to provide goals and obstacles that the player is capable of completing.

The diagram illustrates the various levels of difficulty the player can confront, leveled between the two extremes, frustration and boredom.

Focusing questions

  • What level of challenge do you want to present to the player?
    • Where in the balance between frustration and boredom do you want your game's challenge to be?
  • What interactions between the player, game mechanics and game environment are intended to challenge?
    • How do you prepare the player for the challenges you present?
    • Where/when during play do players experience spikes (large upward or downward shifts) in difficulty?
  • What abilities are afforded to the player?
    • How do those abilities interact with the game environment/enemies?
    • When do you provide time for the player to develop skills with these abilities?

Can be instantiated by

Lenses

Patterns

  • Afforded Abilities
  • Obstacles
  • Goals
  • Enemies

Examples

Mega Man 3

Optimal Challenge is a hard concept to visualize, as it is a very personal aspect of game experience. In Mega Man 3 the game provides ample challenge to the player, but designs all enemies and obstacles in a way that allows the given abilities to handle any situation. In the video above, we see both the state optimal challenge, and a situation that breaks that state. Overall, the video is an excellent example of Optimal Challenge, as his mastery over the controls of the game allows him to handle all enemies and game situations with ease. However, within the video the player encounters a platforming section in which his twitch movements cause him to fall off of the blocks. Player character bounding boxes are most certainly the reason, as he moves slightly too far, and the game considers him to be off of the platform. This disconnect slowly pulls him out of engrossment, as he has to repeatedly try to complete the simple puzzle. Designers must be aware that the decisions that they make, along with the programmer's decisions all have a direct impact on the lead up and development of the optimal challenge to players.

Super Smash Bros. Brawl

difficultyingames.jpg

Super Smash Bros. Brawl is the most recent iteration of the Super Smash Bros. Franchise. Since the earliest iterations, this fighting game had a campaign mode that allowed players to decide on what level of challenge they wanted to face. The designers realized that players would not all be able to face the same level of challenge when they began playing the game, and allowed for the players to improve by taking on harder challenges when they felt ready. The ability for the player to set the challenge heavily promotes Competence as the player will always be able to find a balance between their personal skill level and the challenge that they choose to set, maximizing the experience by removing designer error is setting hard difficulties pre-release.

Considerations

The Definition of Optimal

Optimal challenge is a tough problem to tackle. The true optimal challenge is subject to multiple factors including length of the game, how common or standard your mechanics are, the audience you are targeting and how the abilities you afford the player affect the state of the game. The length of the game is an important factor, as early and late game have very different optimal difficulties. The number of challenging elements and the amount of time the player has had to develop their skill is very important in establishing the optimum. Also to consider is how well known or widely used your mechanics are. If you are designing a first person shooter, you can generally ramp difficulty on a game faster than a game where the main mechanic is shifting gravity, as first person shooters are widely saturated. The audience you are designing for is also a great measuring tool, to design for children or college age students creates a need for very different levels of difficulty. The final aspect you should look to when deciding what is “optimal” is to take note of the mechanics of your game. Proper balancing will allow for proper optimums. Without properly balanced abilities or mechanics, the player can easily find exploits that radically alter the difficulty they encounter.

Establishing Engrossment

Engrossment is a very personal experience for each individual player. Design the game to allow for engrossment to be reached, but do not try to force a player into engrossment. Engrossment is ethereal and is not a pattern, it is a concept that is to be acknowledged and designed for, not implemented into the game itself. As a designer you must be prepared to playtest and iterate on the design of the game progression to maximize the player's experience of challenge and in turn, engrossment.

Player Choice

A common design decision for correctly leveling difficulty is to provide multiple levels of difficulty that the player can choose from. This design decision is widely used and very common, so if you are having trouble balancing the game correctly on a single difficulty, consider this method to create a better gradient of difficulty.

Tool

At the current time, there are no available tools

Metrics

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Validity

The lens is speculative.

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References

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lenses/optimal_challenge.txt · Last modified: 2014/05/14 22:08 by awilliams