I did that! Measuring Users’ Experience of Agency in their ...€¦ · I did that! Measuring...
Transcript of I did that! Measuring Users’ Experience of Agency in their ...€¦ · I did that! Measuring...
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I did that! Measuring Users’ Experience of Agency in their own ActionsAUTHORS: DAVID COYLE, JAMES MOORE, PER OLA KRISTENSSON, PAUL C. FLETCHER, AND ALAN F. BLACKWELL
PRESENTER: MARY YOUNG
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Agenda
Relevance in HCI
Background
Experimental Design
Conclusion
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Relevance in HCI
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“Users strongly desire the sense that they are in charge of the system and that the system responds to their actions.”
- Designing the User Interface: Strategies for Effective Human-Computer Interaction
Shneiderman’s Seventh Golden Rule of Interface Design:
Support an internal locus of control
Agency in interface design
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Examples of Users’ Experience of Agency
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Views of Agency in HCI
Media Agency Intelligent Agent
Design Agency
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Background
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Definition of Agency“A person’s innate sense of being in control of their actionsand through this control of being responsible for, or having ownership of, the consequences of these actions.”
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A Little Bit of NeurologyTwo theoretical positions:•Agency is based on the sensory comparison of predicted versus
actual consequences
• Agency is a reconstructive inference based on the assumption that one’s intention has cased an external event
Humans do not always perceive agency correctly• Ouija boards
• Gambling
• Neurological disorders
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Measuring Agency
Voluntary actions cause changes in our perception of time
This is termed intentional binding
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Measuring AgencyHigher temporal binding indicates a greater sense of agency
Two methods:◦ Libet Clock
◦ Robust measurement
◦ However, user must look at a clock
◦ Interval Estimation◦ Less robust
◦ No clock
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Libet Clock
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Calculating AgencyAction measurements
Baseline error Report time when button was pressed; no beep
Active error Report time when button was pressed; beep
Outcome measurements
Baseline error Report time when beep occurred; no button pushed
Active error Report time when the beep occurred; button was pushed
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Calculating Agency
Error = actual time – perceived time
Action binding = action error[active] – action error[baseline]
Outcome binding = outcome error[baseline] – outcome error[active]
Total binding = action binding + outcome binding
Again: greater total binding values indicate greater sense of agency.
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Experiment
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Goals of Experiments•Develop methods to implicitly measure agency in an HCI context
•Determine how perception of agency is affected by different input modalities
•Determine how perception of agency is affect by varying degrees of computer assistance
•Target demographic: everyone
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What’s it like to be a button?
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Experiment 1: Changing Input Modalities•Independent variable: input modality• Skinput vs MAC keyboard
•Dependent variable: length of binding• Libet clock
•Design: Within-subjects
•Participants• 21 right-handed individuals ages 20-40
•Recruited via email to a University bulletin board
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Experiment 1: ProcedureTrials:
40 trials of:• Action baseline error• Action active error• Outcome baseline error• Outcome active errorPer input modality or 320 total per participant.
Randomization: modality alternated, random order of measurements, but measured in blocks
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Experiment 1: Results
Modality Actionbinding
Outcomebinding
Total binding
Button 6.81ms(45.6ms)
36.11ms(45.46ms)
42.92ms(67.43ms)
Skin-based 29.66ms(42.84ms)
79.82ms(91.23ms)
109.47ms(74.54ms)
Significance testing:• Bonferroni corrected paired sample t-test• H0: No difference in total binding for input modality• t(18)=4.05, p<0.01• Conclusion: Reject H0
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Experiment 1: Analysis and Discussion•No significant difference in baseline conditions
•Greater sense of agency for skin-based input than keyboard
•Furthermore: input modality matters in a quantifiable way•Possible applications: stylus vs touch
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Experiment 2: Computer Assistance•Independent variable: level of computer assistance•No, mild, medium, and high assistance
•Dependent variable: difference in interval estimation
•Design: Within-subjects
•Training: 12 practice trials
•Participants•27 right-handed individuals ages 20-40•Recruited via email to a University bulletin board
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Experiment 2: ProcedureTrials:
12 trials of:• None (α = 0)• Mild (α = 3)• Medium (α = 6)• High (α = 9)
Per time interval (150ms, 400ms, 700ms) or 144 trials per participant
Randomization: assistance levels blocked, interval was random
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Experiment 2: Results
NoAssistance
MildAssistance
MediumAssistance
HighAssistance
-16.78ms(70.70ms)
-16.32ms(82.03ms)
9.93ms(85.92ms)
4.53ms(79.54ms)
• Bonferroni corrected paired sample t-tests• H0: No difference in estimation errors• No significant difference between no and mild
assistance, p=0.97• No significant difference between medium and
high assistance, p=0.679• Significant difference between mild and medium
assistance level, p < .01
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Experiment 2: Analysis and Discussion•Participants were aware of all four assistance levels
•Threshold for computer assistance, before which assistance doesn’t hinder experience
•Mapping of assistance variable to agency
•Future applications:•More complex systems such as machine learning or AI
• Level of agency when a computer hinders rather than helps
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Final Discussion and Conclusion• Paper provides two empirical methods for measuring agency
• Future interfaces can be evaluated based on user’s perception of agency
• Other factors to be researched:•Quality of feedback•Uncertainty•Differences between demographics
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ReferencesShneiderman, B., & Plaisant, C. (2004). Designing the user interface: Strategies for effective
human-computer interaction. (4 ed.). Pearson.
Harrison, C., Tan, D., & Morris, D. (2010, April). Skinput: Approximating the body as an input surface. 28th Annual SIGCHI conference on human factors in computing systems , New York, NY.
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Image creditsSlide 4:
Auto correct: http://www.freemake.com/blog/12-funny-autocorrect-mistakes/Auto complete: http://www.esarcasm.com/13557/google-autocomplete/Vim: http://www.celsius1414.com/tag/vim/Photoshop: http://pe-images.s3.amazonaws.com/photo-effects/photo-in-photo/new/photoshop-colorize.jpg
Slide 5:Auto correct: http://www.freemake.com/blog/12-funny-autocorrect-mistakes/Auto complete: http://www.esarcasm.com/13557/google-autocomplete/Vim: http://www.celsius1414.com/tag/vim/Photoshop: http://pe-images.s3.amazonaws.com/photo-effects/photo-in-photo/new/photoshop-colorize.jpg
Slide 10: Libet clock: http://www.informationphilosopher.com/solutions/scientists/libet/Libet_Clock.gif