Behaviours and Belief systems in User-Centred Game Design

Alessandro Canossa

“A game's value proposition is how it makes its players think and feel. Players don’t buy games, they buy experiences” Nicole Lazzaro

EXPERIENCE (Kant - Walter Benjamin)

• Erlebnis-Perception: “mentally unprocessed, immediately-perceived event”a one-off encounter, a particular sensation that does not build towards a greater whole; it is isolated, categorical, without cognition, “lived-through” aesthetic/ecstatic perception. It is immediate, pre-reflective and personal.

• Erfahrung-Reflection: “wisdom gained in subsequent reflection on events or interpretation of them” It is understanding of life and the world we live in; it is experience as an ongoing, cumulative and critical-cognitive process; “journeyed-through” knowledge, mature reflection on events.

GAME EXPERIENCE

• 1. The player controls the avatar. 2. The avatar interacts with the gameworld and its underlying mechanics. • 3. The avatar receives feedback from the gameworld (instigating stimulus). • 4. The player receives feedback both from the avatar and the gameworld; she is aroused by it (physiological

correlates).• 5. This arousal, together with personality traits, is interpreted as an emotion (cognitive appraisal).• 6. The player constructs knowledge (reflective experience) with that emotion embedded, it will be

remembered and used in the future to plan actions (motivational properties) at the same time emotional categories are redefined (reinforced or negated).

DESIGNING for EXPERIENCE

• Perception: hard approach, quantitative, game metrics, etc. (what, where, when)

• Reflection: soft approach, qualitative, surveys, etc. (why, who, how)

Play-personas: Tools used to design and evaluate a game while accounting for both sides of experience.

Play-personas are ways of modeling player behavior and understanding players’ relationship to the ludic and aesthetic affordances of specific computer games.

Play personas are defined as clusters of preferential interaction and navigation.

Traditional persona design in games is not new

Example:

Far Cry 2 designing game space for cover areas

- Rambo: partial to close combat, always in the same area of the hostiles, independently if it is densely covered or not.

- Sun Tzu: prefers strategic approach, favors being in areas with plenty of cover while the enemies are in open areas.

- Fugitive: needs freedom of movement while enemies are encumbered navigating a cluttered space

Position of enemies LOW cover HIGH cover

LOW cover RAMBO I FUGITIVE

HIGH cover SUN TZU RAMBO II

Position of players

The traditional persona is still a designer-centric tool, it allows consistent, focused design around hypothetical goals.

What is missing is ”to close the circle”: trying to unfold the play experience from the point of view of players and verifying the hypothetical goals

HYPOTHESIS ANALYSIS

• a-posteriori lens (analyses): data-driven representations of actual players’ behaviors

aggregate descriptions of player behaviour:

• a-priori metaphor (hypotheses): theoretical models of ideal users, expectations of the designer

Play-persona framework• Play-persona metaphor

- narrative description - unfolding navigation and interaction possibility fields - hypothesis on use of game mechanics and spaces

• Play-persona lens- data driven verification- tools: SPSS & ARCGIS- ethnographic and anthropologic methods- rebuilding experiences

Case study: Tomb Raider Underworld

Case study: Tomb Raider Underworld

From core game mechanics to ”axes” of the possibility space

• Shooting: Indicated by high or low number of deaths inflicted to enemies & animals (interaction with NPC)

• Jumping: Indicated by high or low number of deaths caused by environment: falling, drowning, etc. (navigation)

• Puzzle solving: Indicated by high or low requests for help to solve puzzles (interaction with the world)

The metrics tracking the main game mechanics individuate three axes of the possibility space

Case study: Tomb Raider Underworld

Grunt persona • Excels at shooting, enjoy fights and are quite good at them, interested in twitch stimulation, taking

pride on physical domination. Not so precise with movements, hence the risk of failing at jumps. Slightly annoyed by tight jumping puzzles. Not interested in figuring out solutions to puzzles, prone to bypass cerebral strain if possible.

Athlete persona: • Enjoy exploration of the environment and avoid fights if possible. Considering the amount of skill

involved in performing precise jumps we can assume that they are players with experience and are comfortable with navigation controls. Will rarely loose direction and display relatively fast completion times, this also reflects on relatively few requests for help for spatial puzzles

Chess-player persona: • Problem solving skills, will log no requests for help, few deaths caused by mistakes in solving puzzles,

they possesses a good sense of direction, few deaths caused by the environment. Not necessarily be good at precise jumps: could die several times by falling. Not particular skills with a gun. Could ask for hints but never for answers.

Mapping the possibility space with play-personas

Persona-as-metaphor and design:

Persona hypotheses emerge as relations between parameters that have been derived from core gameplay mechanics, this informs the level design

Statistical distribution of the player population according to hypothetical play-persona profiles

Play-persona as lens: bottom up

Six of all tracked features are used:– 1) Total number of deaths– 2) Completion time– 3) Death by Falling– 4) Death by Enemy– 5) Death by Environment– 6) Help On Demand

Emergent Self Organising Maps are used to look for clusters of players with similar patterns of behaviour

Veterans Solvers Pacifists Runners

Death count low average n/a average/low

Completion time low average/high average/low low

Death by falling low high average/high average/low

Death by enemy low average/low high high

Death by environment high low low High

Help on demand average/low low low high / low

Play-personas as metaphorsVs

Play-personas as lenses

Athletes = RunnersGrunts = Veterans

Chess-players = Solvers? = Pacifists

ConclusionsA game-system that is aware of what

persona is playing can radically improve play experience

Obvious advantages for phenomenological (experiential) debugging

Players empowered by better means for self- expression

Future work– cross cultural differences of patterns of behavior

(similarity in play patterns for players from same background, status, language, region);

– relation between persona and personality (Big 5 and personas: similarly scoring individuals in Big 5 present same persona profile in a given game?);

– portability of persona across different games (same user, different games: similar behaviour?)

– consistency of persona in time (same user, same game, different times: same behaviour?)

– application of same methods to non-game products (with google analytics)

Questions?

aca@dkds.dk // alessandroc@ioi.dk