dundee phd symposium 2013
TRANSCRIPT
Michael CrabbUniversity of Dundee, Scotland, UK.
Combining Cognitive Psychology and Web Usability to create better insights into User Experience
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Computer InteractionHUMAN
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ComputerM
ouse
tablet
smartphone
PC
MAC
Monitor
Printer
Calculator
Keyb
oard
Interaction
Type
Swipe
Browse
Adjust
Touch
Mov
e
wri
te
HUMAN
?
?
?
?
?
?
?
?
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Fluid Intelligence
Audi
tory
Abi
lity
Crystallised IntelligenceInternet Usage Internet Confidence
Short TermMemory
Long Term Memory
Processing Speed
Reading Ability
Writing Ability
Visu
al P
roce
ssin
g
Cognitive Psychology
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Fluid Intelligence
Internet Usage
Internet Confidence
Short Term Memory
Long Term Memory
Processing Speed
Amount of time spent using the internet for various activities.
Confidence in carrying out computer based tasks that are focused around internet activities.
Mental operations that are used when faced with a task that cannot be done automatically.
The ability to perform tasks quickly and accurately while under pressure.
Store information and recall it at a later time through association.
Ability to hold and use information within a few second of acquiring it.
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Fluid IntelligenceLetter Sets
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BCDE FGHI JKLM PRST VWXY
CERT KMTV FHXZ BODQ HJPR
KGDB DFIM KIFB HJMQ LHEC
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Ps
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IU
Glr
Gsm
ICPs
Gf
IU
Glr
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IC Ps
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User1
User2
User3
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Push OK to continue...
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How can we use a cognitive analysis of people to understand more about how
they use computers?
research question
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Study 2INFORMATION RETRIEVAL TASK. Participants answer questions to find info on individual sites. Metrics gathered related to ‘ease’ of use and feeing of ‘lostness’
Study 1BASIC SEARCH TASK. Participants asked to find information related to booking a holiday online. Metrics gathered related to speed of searching
Study 3USABILITY ANALYSIS. Participants visit website and perform usability analysis on sites themselves to discover problems that exist
Software DevelopmentWEBSITE DEVELOPMENT OF SITES TO TEST CREATED USABILITY GUIDELINE METRICS
USED TO IMPROVE
USED WITHIN
USED TO
TEST
Software DevelopmentCREATION OF SOFTWARE TO HOLD USABILITY METRICS AND ANALYSE INDIVIDUAL WEB PAGES TO GENERATE VALUES TO THESE METRICS
Studies
Research Software
Bi-productSoftware
PROBLEM SOLVEDSystem created and tested within second study
MAIN PROBLEMLarge amount of data, very time consuming to get into a format that is suitable for analysis
Software DevelopmentCREATION OF SOFTWARE TO STORE INDIVIDUAL STUDY DATA AND PRESENT IN A FORMAT SUITABLE FOR STATISTICAL ANALYSIS SOFTWARE
Software DevelopmentCREATION OF SOFTWARE TO ANALYSE AN INDIVIDUAL WEBPAGE AND GIVE USABILITY FEEDBACK BASED ON VARIOUS COGNITIVE FACTORS
DEVELOPED AS A RESULT OF
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Study 1Recap
TwelveParticipants
Find a Destination
Book Flights
Check Weather
Local Attractions
Buy a Camera
FiveTasks
•Very difficult to use pragmatic goals when comparing between younger and older adults.•Gathering information manually in an
experiment like this is time consuming
Results
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Study 2INFORMATION RETRIEVAL TASK. PARTICIPANTS ANSWER QUESTIONS TO FIND INFO ON INDIVIDUAL SITES. METRICS GATHERED RELATED TO ‘EASE’ OF USE AND FEEING OF ‘LOSTNESS’
Study 1BASIC SEARCH TASK. PARTICIPANTS ASKED TO FIND INFORMATION RELATED TO BOOKING A HOLIDAY ONLINE. METRICS GATHERED RELATED TO SPEED OF SEARCHING
Study 3USABILITY ANALYSIS. PARTICIPANTS VISIT WEBSITE AND PERFORM USABILITY ANALYSIS ON SITES THEMSELVES TO DISCOVER PROBLEMS THAT EXIST
Software DevelopmentWEBSITE DEVELOPMENT OF SITES TO TEST CREATED USABILITY GUIDELINE METRICS
USED TO IMPROVE
USED WITHIN
USED TO
TEST
Software DevelopmentCREATION OF SOFTWARE TO HOLD USABILITY METRICS AND ANALYSE INDIVIDUAL WEB PAGES TO GENERATE VALUES TO THESE METRICS
Studies
Research Software
Bi-productSoftware
PROBLEM SOLVEDSystem created and tested within second study
MAIN PROBLEMLarge amount of data, very time consuming to get into a format that is suitable for analysis
Software DevelopmentCREATION OF SOFTWARE TO STORE INDIVIDUAL STUDY DATA AND PRESENT IN A FORMAT SUITABLE FOR STATISTICAL ANALYSIS SOFTWARE
Software DevelopmentCREATION OF SOFTWARE TO ANALYSE AN INDIVIDUAL WEBPAGE AND GIVE USABILITY FEEDBACK BASED ON VARIOUS COGNITIVE FACTORS
DEVELOPED AS A RESULT OF
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7 questions
Computing Comfort
15 Questions
Computer Usage
31 Questions
Internet Comfort
16 Questions
Internet Usage19 Questions
Fluid Intelligence
Processing Speed
Short Term Memory
Long Term Memory
Human Metrics
Technology Usage Cognitive Factors Demographics
Web
site
Met
rics
Page Layout
Navigation
Text Appearance
Headings
Scrolling and Paging
Images
Links
Writing Content
Forms
Searching
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Human Metrics
Technology Usage Cognitive Factors
Web
site
Met
rics
Page Layout
Navigation
Text Appearance
Headings
Scrolling and Paging
Images
Links
Writing Content
Forms
Searching
23 Guidelines
7 Guidelines
5 Guidelines
10 Guidelines
44 Guidelines
15 Guidelines
17 Guidelines
10 Guidelines
39 Guidelines
7 Guidelines
Demographics
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model of an individuals
cognitive abilities
model of webpage usability
measure the interactions
(hedonic goals)
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AgeInternet Usage
Internet ExperienceFluid IntelligenceProcessing Speed
Short Term MemoryLong Term Memory
independ
ent varia
bles
participants recruited.
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IR Task
Visit Website
Answer Questionnaire
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visited
337websites
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visited
337websites
DisorientationInformation
Usability GuidelineInformation
(1595 web pages)
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Younger Adults
Older Adults
Independent Sampled t-test
Kurtosis Testing
Multiple Regression
s 1 s2 s 3
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Total Disorientation
Age
InternetExperience
CognitiveFactors
r2 = x1
r2 = x2
r2 = x3
x3 -x2 = Unique Cognitive Variance24
Age
Tech Usage
Cognitive Factors
Age
Tech Usage
Cognitive Factors
Older Adults Younger Adults
R = .0152
R = .0982
R = .2462
R = .0172
R = .2722
R = .4272
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Age
Internet Confidence*
Long-Term Memory*
Processing Speed*
Fluid Intelligence
Short-Term Memory
Internet Usage
Age
Internet Confidence*
Long-Term Memory
Processing Speed
Fluid Intelligence*
Short-Term Memory*
Internet Usage
Older Adults
Younger Adults
disorientation level
disorientation level
* p < .001
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Metric1
Metric2
Metric3
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Guideline α
Guideline β
Guideline γ
Guideline δ
Older Adults
Guideline α
Guideline β
Guideline γ
Guideline δ
Younger Adults
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Guideline α
Guideline β
Guideline γ
Guideline δ
Older Adults
Guideline α
Guideline β
Guideline γ
Guideline δ
Younger Adults
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Low Fluid Intelligence
Guideline α
Guideline β
Guideline γ
Guideline δ
High Processing Speed
Guideline α
Guideline β
Guideline γ
Guideline δ30
Site Design A Site Design B
High Processing Guidelines
Low Fluid Guidelines
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Ps
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How can we use a cognitive analysis of people to understand more about how
they use computers?
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Michael CrabbUniversity of Dundee, Scotland, UK.
Thank You
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