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Research Methods – Measuring User Experience. What might we measure in relation to user experience?

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Presentation on theme: "Research Methods – Measuring User Experience. What might we measure in relation to user experience?"— Presentation transcript:

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 LeBlancCrawford SensationFantasy/Exploration FantasyFantasy/Exp Nose Thumbing NarrativeFantasy/Exp ChallengeProving Oneself Exercise FellowshipSocial Lubrication DiscoveryFantasy/Exp ExpressionNeed for Ack. SubmissionExercise Player Pleasures

7 Csikszentmihalyi - Flow 08:40

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 1.Unpredictable / inconsistent response to user’s actions 2.Does not allow enough customization 3.Artificial intelligence problems 4.Mismatch between camera/view and action 5.Does not let user skip non-playable content 6.Clumsy input scheme 7.Difficult to control actions in the game 8.Does not provide enough information on game status 9.Does not provide adequate training and help 10.Command sequences are too complex 11.Visual representations are difficult to interpret 12.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 heuristics/ aluation.html aluation.html stics.pdf stics.pdf stics.pdf stics.pdf content/blogs.dir/1/files/publications/uxInGames_K oeffel_et_al.pdf content/blogs.dir/1/files/publications/uxInGames_K oeffel_et_al.pdf

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

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. ( pinelle.pdf) pinelle.pdf Isbister, K. & Schaffer, N. eds. (2008) Game usability: advice from the experts for advancing the player experience. London: Morgan Kaufmann. level

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