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Games User Research & User Testing 101


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Games User Research & User Testing 101 - talk on games and user research at IGCMG in 2015

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Games User Research & User Testing 101

  1. 1. A D VA N C I N G G A M E D E S I G N W I T H E Y E - T R A C K I N G A N D T H I N K - A L O U D S T U D I E S J O H A N N A P I R K E R J P I R K E R @ M I T. E D U G R A Z U N I V E R S I T Y O F T E C H N O L O G Y C H I P L AY - G U R T O O L S
  2. 2. • GUR is not QA and not Marketing! -> UX • Methods sometimes similar • E.g. Playtesting
  3. 3. G A M E S A R E M A D E F O R T H E P L AY E R S
  4. 4. • Understanding player behaviour • Determine issues and difficulties • Object awareness and usability insights • Does the user understand how to play the game? • Does the user understand how to interact with the game objects and the environment? • Is the user interface easy to learn? • Does the user enjoy the experience?
  5. 5. M E T H O D S • Think Aloud Protocol (TA) • Retrospective Testing • Heuristic Evaluation (HE) • Playtesting • Game Analytics • Physiology-based Playtesting / Biometrics
  6. 6. M E T H O D S + D ATA • Think Aloud Protocol (TA) • Notes, Audio, Video, .. • Retrospective Testing • Annotations in video, notes, audio,.. • Heuristic Evaluation (HE) • Notes • Playtesting • Surveys, Interviews, Game Logs • Game Analytics • Quantitative data <3 e.g. engagement • Physiology-based Playtesting / Biometrics • Biodata, “feelings”, phyiscal states, emotions,
  7. 7. Christian Rohrer -
  8. 8. T H E G A M E I S T E S T E D 
 N O T T H E U S E R
  9. 9. T H I N K - A L O U D ( TA ) P R O T O C O L S • Users share thoughts and feelings loudly while performing specific tasks • Data is collected by noting or recording what users say while testing • Data = explanations & reasoning
  10. 10. E Y E - T R A C K I N G • User’s gaze while playing the game is recorded • What does the user see? • What does he miss?
  11. 11. E Y E - T R A C K I N G • Live Eye Gaze (real-time) • Analyze users intention and their behaviour in areas where users would expect specific interactions • Quantitative data (Fixation counts, revisits, ..) • Visualisations (heat map) • Illustrate areas of interest • Analyze more complex data (find unnoticed areas, needlessly complex interactions)
  12. 12. C O M B I N I N G E T A N D TA •Qualitative TA-Data (User speaks out loud) • Analysis of verbal in-play probes (+/-)* • Analysis in-play responses (Bored, Frustrated, Lost, Annoyed, Puzzled,...)* •ET- Data (User’s gaze) • Analysis of eye movement data • Quantitative Analysis of eye movement data: Fixations, Variation of mean fixations*
  13. 13. Jeanne H. Brockmyer, Christine M. Fox, Kathleen A. Curtiss, Evan McBroom, Kimberly M. Burkhart, Jacquelyn N. Pidruzny. (2009). The development of the Game Engagement Questionaire: A measure of engagement in video game playing. Journal of Experimental Social Psychology. Vol. 45, pp. 624-634.
  14. 14. Usability / Learning Experience and Motivation Testing • U S A B I L I T Y, M O T I VAT I O N , L E A R N I N G P R O G R E S S • C O M PA R E D I F F E R E N T M E T H O D S • T H I N K I N G A L O U D T E S T • E Y E T R A C K I N G
  15. 15. I T E R AT I V E G A M E D E V E L O P M E N T
  16. 16. B I G D ATA ! ! !
  17. 17. C H I P L AY • What Drives People: Creating Engagement Profiles of Players from Game Log Data • 120 mio race entries from 1.2 mil players = 9812ced8096f35d127f3a
  18. 18. J O B S ? • UX/Usability: • Psychology / Design / Computer Science • Data Analyst / Engineer • Math, Statistics, CS (Machine Learning) • research-jobs/
  19. 19. T H A N K Y O U F O R Y O U R AT T E N T I O N . J O H A N N A P I R K E R , J P I R K E R @ M I T. E D U , W W W. J P I R K E R . C O M , @ J O E Y P R I N K