dundee phd symposium 2013

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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III

BCDE FGHI JKLM PRST VWXY

CERT KMTV FHXZ BODQ HJPR

KGDB DFIM KIFB HJMQ LHEC

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IU

Glr

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ICPs

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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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19

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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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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