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Research Methods – Measuring User Experience

Research Methods – Measuring User Experience. What might we measure in relation to user experience?. Measures of User Experience. Experience of a specific emotion Experience of a type of emotional response Experience of a type of pleasure Experience of “flow state”.

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Research Methods – Measuring User Experience

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  1. Research Methods – Measuring User Experience

  2. What might we measure in relation to user experience?

  3. Measures of User Experience • Experience of a specific emotion • Experience of a type of emotional response • Experience of a type of pleasure • Experience of “flow state”

  4. Lazzaro: Four Keys to More Emotion without Story • Hard Fun • Easy Fun • Serious Fun • People Fun • Emotions: fear, surprise, disgust, naches/kvell, fiero, schadenfreude, wonder

  5. Frome – Game Generated Emotion • Game Emotions • Emotions of competition • Narrative emotions • Emotions from engaging with artwork • Artefact emotions • Emotions of aesthetic evaluation • Ecological Emotions • Response to what the artwork represents

  6. Player Pleasures

  7. Csikszentmihalyi - Flow

  8. Neilsen – Usability Attributes • Learnability • Memorability • Efficiency • Errors and their severity • Subjective satisfaction

  9. Juul & Norton • Different from productivity-based software • User challenge /difficulty is expected (sought out) • Challenge can be in any aspect of the games, including the interface

  10. Mandryke

  11. Heuristic Evaluation • Traditionally – examining compliance with recognised usability principles

  12. Neilsen – Usability Heuristics • Visibility of system status • Match between system and real world • User control and freedom • Consistency & standards • Error prevention • Error diagnosis and recovery • Recognition rather than recall • Flexibility & efficiency of use • Aesthetic and minimalist design • Help and documentation

  13. Pinelle, Wong & Stach – Game Usability • Unpredictable / inconsistent response to user’s actions • Does not allow enough customization • Artificial intelligence problems • Mismatch between camera/view and action • Does not let user skip non-playable content • Clumsy input scheme • Difficult to control actions in the game • Does not provide enough information on game status • Does not provide adequate training and help • Command sequences are too complex • Visual representations are difficult to interpret • Response to user’s action not timely enough

  14. Desurvire, Caplan & Toth – Heuristic Evaluation for Playability (HEP) • Gameplay • Game story • Game mechanics • Game usability

  15. Physiological Data • Galvanic skin response (GSR) • Respiration • Blood volume pulse (BVP) • Heart rate variation (HRV) • Electromyography (EMG) • Pupil dilation (PD) • Arousal (GSR, Resp, BVP, HR) • Mental effort (HRV, PD, EMG) • Valance (EMG, HRV, PD)

  16. Electrodermal Activity • Galvanic skin response (GSR) • Measures variation in electrodermal activity between tonic baseline and phasic responses • Uses eccrine sweat glands – palms of hands and soles of feet

  17. Cardiovascular • Blood pressure – pressure needed to push blood through circulatory system • Blood Volume – how much blood is being pushed around • Heart rate – number of beats per minute • Heart rate variability – change in heart rate

  18. Muscles • Electromyography – measure of muscle activity • Brow • Jaw • Cheek

  19. Arousal • Increases in galvanic skin response • Increased respiration • Decreased blood volume pulse • Increased heart rate

  20. Mental Effort • Decreased heart rate variability • Greater pupil dilation • Increases in jaw clenching or brow-raising • Increased respiration rate • Decreased variability of respiration rate

  21. Positive vs. Negative Emotions • Valance of an emotion • Facial muscle analysis of brow and cheek • Heart rate, • Irregularity of respiration • Pupil diameter

  22. Physiological Data - Advantages • Continuously collected to evaluate process not just outcome • Doesn’t interfere with experience • High bandwidth – lots of data • Can be used to infer underlying emotions

  23. Physiological Data - Disadvantages • High variability between individuals • Sensor error, interference and noise is prevealent • Requires baseline and normalization techniques • Can be invasive and impact performance

  24. System Gathered Data • Time on task • Number/type of errors • Choices made • Number of times help system used • Number of time area/page visited • Any user input

  25. Research Case Study: Red-eye Removal • Eastman Kodak – Removal of red-eye defect from images in direct print kiosks

  26. Red-Eye: Pre-Artefact • Research, evaluation/review of existing systems • Scoping parameters for system design - range of size of pupils with red-eye defect • Negotiated system requirements and specifications • Touch screen • Screen resolution • Amount of zoom

  27. Red-Eye: Building Artefacts • System captured data • Time on task – how long to adjust each of three • How many something was undone and what was undone

  28. Red-Eye: User Testing • 24 participants – Kodak factory workers variety of ages and gender • Three versions of the system – all participants used all • Variation in order that the versions were tested • Used talk aloud – video recorded sessions • Post test questionnaire – subjective/qualitative

  29. Red-Eye: Data Analysis • Time on task analysis • Error rates/types • Speak aloud comment classification • Which did users say they preferred/found easiest • Correlation between: • Order used and user preference • Order used and time on task • Order used and speak aloud comment types

  30. Sources • http://www.nngroup.com/articles/ten-usability-heuristics/ • http://www.useit.com/papers/heuristic/heuristic_evaluation.html • http://userbehavioristics.com/downloads/usingheuristics.pdf • http://userbehavioristics.com/downloads/usingheuristics.pdf • http://mi-lab.org/wp-content/blogs.dir/1/files/publications/uxInGames_Koeffel_et_al.pdf

  31. Crawford (1982) “Why do people play games?” in The Art of Computer Game Design. [online] Available at: http://www.scribd.com/doc/140200/Chris-Crawford-The-Art-of-Computer-Game-Design (Last Accessed 31 January 2013) • Frome, J. (2007) "Eight Ways Videogames Generate Emotion" in Situated Play, Proceedings of DiGRA 2007 Conference. [Online] Available at http://www.digra.org/dl/db/07311.25139.pdf(Last Accessed 28/01/13) • Lazzaro, N. (2004) Why we play videogames: Four keys to more emotion without story. XEODesign. [Online] Available at: http://xeodesign.com/xeodesign_whyweplaygames.pdf  (Last Accessed 7 Feb 2013)

  32. Pinelle, D., Wong, N., Stach, T. (2008) “Heuristic Evaluation for Games: Usability Principles for Video Game Design” in Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI 2008), 1453-1462. (http://hci.usask.ca/publications/2008/p1453-pinelle.pdf) • Isbister, K. & Schaffer, N. eds. (2008) Game usability: advice from the experts for advancing the player experience. London: Morgan Kaufmann. • http://www.jesperjuul.net/text/easydifficult/ • http://armorgames.com/play/4309/this-is-the-only-level

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