The Usability Perception Scale (UPscale): A Measure for Evaluating Feedback Displays
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Transcript of The Usability Perception Scale (UPscale): A Measure for Evaluating Feedback Displays
The Usability Perception Scale (UPscale): A Measure for Evaluating Feedback Displays
Beth Karlin Transformational Media Lab
Rebecca Ford Center for Sustainability
Underlying Assumptions 1. Technology and new media are changing how people
interact with our natural, built, and social worlds.
B. Karlin
Underlying Assumptions 1. Technology and new media are changing how people
interact with our natural, built, and social worlds. 2. There are potential opportunities to leverage these
changes for pro-social / pro-environmental benefit.
B. Karlin
Underlying Assumptions 1. Technology and new media are changing how people
interact with our natural, built, and social worlds. 2. There are potential opportunities to leverage these
changes for pro-social / pro-environmental benefit 3. A psychological approach provides a theoretical base
and empirical methodology to study this potential.
B. Karlin
Transformational Media Lab Mission:
Our lab studies how technology and new media are (and can be) used to transform individuals, communities, and systems.
Documentary Film
Campaigns
Home Energy Management
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Energy Feedback “Information about the result of a process or action that can be used in modification or control of a process or system”
Oxford English Dictionary
B. Karlin
Energy Feedback
1888
� Average frequency: monthly (approx. 12 data points/year)
� Average frequency: hourly (approx 8,760 data points/year)
Energy Feedback
B. Karlin
Energy usage tells its own story...
Powe
r Con
sum
ptio
n (W
atts)
Small changes, big impacts
$9.24 $5.28 Savings: $3.96 43%
B. Karlin
And the computer is still plugged in…
(uci@home project)
blu-ray netflix streaming
Appliance Disaggregation (up to 6.3 trillion data points/year)
200 microsecond sampling
B. Karlin (uci@home project)
Savings Add Up
“…without waiting for new technologies or regulations or changing household lifestyle.”
Dietz, Gardner, Gilligan, Stern, & Vandenbergh (2009)
“Household actions can provide a behavioral wedge to rapidly reduce carbon emissions …”
• 5-12% reduction in 5 years • 9-22% reduction in 10 years
B. Karlin
Over 200 devices on the market
(Karlin, Ford, & Squiers, in press) B. Karlin
What are we missing?
Public and Private Interest
Feedback is effective… � 100+ studies conducted since 1976 � Reviews found average 10% savings
� Mean r-effect size = .1174 (p < .001)
• Significant variability in effects (from negative effects to over 20% savings)
Darby, 2006; Ehrhardt-Martinez et al., 2010; Fischer, 2008; Karlin & Zinger, under review B. Karlin
Feedback is ✗ can be effective… � 100+ studies conducted since 1976 � Reviews found average 10% savings
� Mean r-effect size = .1174 (p < .001)
Darby, 2006; Ehrhardt-Martinez et al., 2010; Fischer, 2008; Karlin & Zinger, in preparation
• Significant variability in effects (from negative effects to over 20% savings)
B. Karlin
Feedback is ✗ can be effective…
Ehrhardt-‐Martinez, Laitner, & Donnely., 2010
It depends. . .
10% 15% 5%
2% 20% average savings
Feedback is It depends…
✗ can be effective…
Moderators identified in meta-analysis
• Study population (WHO?)
• Study duration (HOW LONG?)
• Frequency of feedback (HOW OFTEN?)
• Feedback medium (WHAT TYPE?)
• Disaggregation (WHAT LEVEL?)
• Comparison (WHAT MESSAGE?)
Karlin & Zinger, in preparation B. Karlin
Methodological Limitations 1. Not naturalistic
� Participants generally recruited to participate
� May be different from “active adopters”
2. Not comparative � Most studies tests one type of feedback (vs. control)
� Very few studies isolating or combining variables
3. Not testing mediation � DV is energy use, but studies rarely test possible
mediators to explain effectiveness
B. Karlin, 2013
Methodological Limitations � Not naturalistic
� Participants generally recruited to participate
� May be different from “active adopters”
� Not comparative � Most studies tests one type of feedback (vs. control)
� Very few studies isolating or combining variables
� Not testing mediation � DV is energy use, but studies rarely test possible
mediators to explain effectiveness
B. Karlin, 2013
Does program x lead to outcome y?
Program x Outcome y
Simple causal model
B. Karlin
What is the program?
What is going on here?
How do we measure outcomes?
How and for whom does program x lead to outcome y?
How and For Whom?
B. Karlin
Beyond kWh Model
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Experience
Usability
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Psychometrics
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• Theory and technique of measurement: knowledge, abilities, attitudes, traits
• Construction and validation of instruments: questionnaires, tests, assessments.
Psychometrics
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Psychometric Properties
1. Factor Structure
2. Reliability
3. Criterion Validity
4. Sensitivity
System Usability Scale
B. Karlin (Brooke, 1986)
Identified Factors: 1. System usability 2. Learnability
Other scales
ASQ 1. User satisfaction
SUMI 1. Affect 2. Efficiency 3. Learnability 4. Helpfulness 5. Control
PSSUQ 1. System usefulness 2. Information quality 3. Interface quality QUIS
1. Overall reaction 2. Learning 3. Terminology 4. Information flow 5. System output 6. System characteristics UMUX
1. Efficiency 2. Effectiveness 3. Satisfaction
Identified Limitations
B. Karlin
1. Designed primarily to evaluate products or systems rather than info-visualizations
2. Assessed with metrics primarily associated w/ease of use (e.g., learnability) & efficiency. Less focus on continued engagement.
Identified Needs
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1. Address the unique needs of eco-feedback displays (as opposed to systems or products)
2. Incorporate validated sub-scales for ease of use and engagement
UPscale (Usability Perception)
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Testing UPscale
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• Online survey (Mechanical Turk)
• 1103 people
• Part of larger study, testing framing messages and info-visualization
Results
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1. Factor Structure
2. Reliability
3. Criterion Validity
4. Sensitivity
Results
B. Karlin
1. Factor Structure
2. Reliability
3. Criterion Validity
4. Sensitivity
Results
B. Karlin
1. Factor Structure
2. Reliability
3. Criterion Validity
4. Sensitivity Overall scale (α=.85) Ease of use (α=.84) Engagement (α=.83)
Results
B. Karlin
1. Factor Structure
2. Reliability
3. Criterion Validity
4. Sensitivity Behavioral intention (p<.001) • overall scale (r=.536) • ease of use (r=.213) • engagement (r=.685)
Results
B. Karlin
1. Factor Structure
2. Reliability
3. Criterion Validity
4. Sensitivity Image Type. • Full scale (F=3.616, p=.001) • Ease of use subscale (F=6.411, p<.001) • Engagement subscale (F=1.744, p=.095). Demographic Variables. • Full Scale: Age, Environmentalism • Engagement: Gender, age, environmentalism, income • Ease of Use: None
UPscale (Usability Perception)
B. Karlin
Closing Thoughts “If you do not know how to ask the right question, you know nothing.”
– Edward Deming
Beth Karlin Transformational Media Lab
Rebecca Ford Center for Sustainability
Thank You!
Program x Outcome y
A theoretical approach
Hypothesis / Theory
Clearly defined and operationalized
Metrics tested for reliability & validity
B. Karlin, 2013
How and for whom does program x lead to outcome y?