Evaluating Game Heuristics
For Measuring Player
Experience
Björn Strååt
Magnus Johansson (magnus@dsv.su.se)
Henrik Warpefe...
Outline
•  Gameworld interaction (Gi) and Support interaction (Si)
•  Challenges, immersion and flow
•  Why work with heur...
Game interaction
Game world

Support

What the developer intended for you to do
12112013

Magnus Johansson, magnus@dsv.su....
Game world:
Challenges
Perform the task!
Explore the options…

Chess pieces… Duh!
06112013

Magnus Johansson, magnus@dsv.s...
Game world:
Flow and immersion

Flow model based on concept by Mihaly Csikszentmihalyi
06112013

Magnus Johansson, magnus@...
the game world experience

06112013

Magnus Johansson, magnus@dsv.su.se
Heuristic Evaluations of Game world
experience
Jakob Nielsen –
heuristic evaluations of interaction

Not suitable for games!
06112013

Magnus Johansson, magnus@dsv.su.se
Game heuristics
Federoff
Desurvire et al.
Desurvire &Wiberg

Pinelle et al

06112013

Magnus Johansson, magnus@dsv.su.se

...
Game heuristics
experience
Federoff
Desurvire et al.
Desurvire &Wiberg
Pinelle et al
• 
• 
• 
• 
06112013

New list with h...
The Net Heuristics list
Heuristic from Pinelle et al

1.  Provide visual representations that are easy to interpret and
that minimize the need for...
Heuristics from the HEP list
1.  Make effects of the Artificial Intelligence (AI) clearly
visible to the player by ensurin...
Heuristics from the PLAY list
1.  The game is paced to apply pressure without frustrating the
players. The difficulty leve...
Heuristics from the PLAY list
5.  Status score Indicators are seamless, obvious, available and
do not interfere with game ...
Relation between GI criteria and Net
heuristics

06112013

Magnus Johansson, magnus@dsv.su.se
Results from the game evaluation test
•  A total of 12 issues could be found using the Net list
•  10 resulting from desig...
Analysis and Discussion
•  The Net list, a tool for easy evaluations
•  The results from the game evaluation indicated tha...
Analysis and Discussion
•  Existing heuristics useful but can be refined
•  Combination of heuristic useful for pin-pointi...
Future work
•  No alternative heuristics
•  Cooperation with the gaming industry to examine the concept
of Gameworld inter...
Thank You for listening!
Questions?

06112013

Magnus Johansson, magnus@dsv.su.se
Upcoming SlideShare
Loading in …5
×

Evaluation of heuristics for designing believability in games gameon2013

464 views
325 views

Published on

Presentation held at the GameOn 2013 conference in Brussels.
We introduce a specific focus for heuristic evaluations of games, where the interface can be excluded and the gameplay isolated.
The heuristics used in this article are based on heuristics sited as the most used heuristics of the game industry

0 Comments
2 Likes
Statistics
Notes
  • Be the first to comment

No Downloads
Views
Total views
464
On SlideShare
0
From Embeds
0
Number of Embeds
5
Actions
Shares
0
Downloads
4
Comments
0
Likes
2
Embeds 0
No embeds

No notes for slide

Evaluation of heuristics for designing believability in games gameon2013

  1. 1. Evaluating Game Heuristics For Measuring Player Experience Björn Strååt Magnus Johansson (magnus@dsv.su.se) Henrik Warpefelt Department of Computer and Systems Sciences/ Stockholm University 11/25/13
  2. 2. Outline •  Gameworld interaction (Gi) and Support interaction (Si) •  Challenges, immersion and flow •  Why work with heuristics? •  The Net heuristics list •  Results from pilot test •  Analysis and discussion •  Future work 06112013 Magnus Johansson, magnus@dsv.su.se
  3. 3. Game interaction Game world Support What the developer intended for you to do 12112013 Magnus Johansson, magnus@dsv.su.se FarCry, Crytek Studios, published by Ubisoft,2004
  4. 4. Game world: Challenges Perform the task! Explore the options… Chess pieces… Duh! 06112013 Magnus Johansson, magnus@dsv.su.se Mario Tennis Open, Nintendo, 2012
  5. 5. Game world: Flow and immersion Flow model based on concept by Mihaly Csikszentmihalyi 06112013 Magnus Johansson, magnus@dsv.su.se
  6. 6. the game world experience 06112013 Magnus Johansson, magnus@dsv.su.se
  7. 7. Heuristic Evaluations of Game world experience
  8. 8. Jakob Nielsen – heuristic evaluations of interaction Not suitable for games! 06112013 Magnus Johansson, magnus@dsv.su.se
  9. 9. Game heuristics Federoff Desurvire et al. Desurvire &Wiberg Pinelle et al 06112013 Magnus Johansson, magnus@dsv.su.se Well researched Used by the industry Based on Nielsen Based on best practice Used as design guidelines
  10. 10. Game heuristics experience Federoff Desurvire et al. Desurvire &Wiberg Pinelle et al •  •  •  •  06112013 New list with heuristics Focus Game world experience Adhere to the gameplay or game world Adhere to in-game challenges Not allow for immersion break Not allow for break of flow Magnus Johansson, magnus@dsv.su.se
  11. 11. The Net Heuristics list
  12. 12. Heuristic from Pinelle et al 1.  Provide visual representations that are easy to interpret and that minimize the need for micromanagement. Visual representations, such as radar views, maps, icons, and avatars, are frequently used to convey information about the current status of the game. Visual representations should be designed so that they are easy to interpret, so that they minimize clutter and occlusion, and so that users can differentiate important elements from irrelevant elements. Further, representations should be designed to minimize the need for micromanagement, where users are forced to interactively search through the representation to find needed elements. 06112013 Magnus Johansson, magnus@dsv.su.se
  13. 13. Heuristics from the HEP list 1.  Make effects of the Artificial Intelligence (AI) clearly visible to the player by ensuring they are consistent with the player’s reasonable expectations of the AI actor. 2.  The Player has a sense of control over their character and is able to use tactics and strategies. 3.  Provide consistency between the game elements and the overarching setting and story to suspend disbelief. 4.  The game transports the player into a level of personal involvement emotionally (e.g., scare, threat, thrill, reward, punishment) and viscerally (e.g., sounds of environment). 06112013 Magnus Johansson, magnus@dsv.su.se
  14. 14. Heuristics from the PLAY list 1.  The game is paced to apply pressure without frustrating the players. The difficulty level varies so the players experience greater challenges as they develop mastery 2.  Changes the player make in the game world are persistent and noticeable if they back-track to where they have been before 3.  There is an emotional connection between the player and the game world as well as with their “avatar.” 4.  The game utilizes visceral, audio and visual content to further the players’ immersion in the game 06112013 Magnus Johansson, magnus@dsv.su.se
  15. 15. Heuristics from the PLAY list 5.  Status score Indicators are seamless, obvious, available and do not interfere with game play 6.  Game provides feedback and reacts in a consistent, immediate, challenging and exciting way to the players’ actions. 7.  The game gives rewards that immerse the player more deeply in the game by increasing their capabilities, capacity or, for example, expanding their ability to customize. 8.  Players should be given context sensitive help while playing so that they are not stuck and need to rely on a manual for help 9.  Game story encourages immersion (If game has story component). 06112013 Magnus Johansson, magnus@dsv.su.se
  16. 16. Relation between GI criteria and Net heuristics 06112013 Magnus Johansson, magnus@dsv.su.se
  17. 17. Results from the game evaluation test •  A total of 12 issues could be found using the Net list •  10 resulting from designers not adhering to the heuristics •  One issue followed the heuristics but still had a negative effect on the immersion •  The last issue not part of any heuristic, negative effect on immersion 06112013 Magnus Johansson, magnus@dsv.su.se
  18. 18. Analysis and Discussion •  The Net list, a tool for easy evaluations •  The results from the game evaluation indicated that the Net list can be refined further. •  The strongest contribution is the definition of ”Gameworld interaction” 06112013 Magnus Johansson, magnus@dsv.su.se
  19. 19. Analysis and Discussion •  Existing heuristics useful but can be refined •  Combination of heuristic useful for pin-pointing softer values of game experience •  Most heuristics written on a high level of abstraction 06112013 Magnus Johansson, magnus@dsv.su.se
  20. 20. Future work •  No alternative heuristics •  Cooperation with the gaming industry to examine the concept of Gameworld interaction further •  Further evaluation of heuristic principles 06112013 Magnus Johansson, magnus@dsv.su.se
  21. 21. Thank You for listening! Questions? 06112013 Magnus Johansson, magnus@dsv.su.se

×