Card Sorting for Information Architecture: Usage Areas, Methods and Samples IATagung Frankfurt :: 28./29.05.2005 :: Steffen Schilb Card Sorting for Information.

Card Sorting for Information Architecture: Usage Areas, Methods and Samples

IATagung Frankfurt :: 28./29.05.2005 :: Steffen Schilb

Card Sorting for Information Architecture

Usage Areas, Methods and Samples

Steffen Schilb ([email protected])

Outline



1.Introduction2.Card Sorting: The Standard Method3.Cluster Analysis4.Computer-Based Card Sorting5.Card Sorting Variants6.Conclusion7.References8.Questions and Discussion

Introduction



1Introduction

Introduction: Why do People browse the Internet?



Introduction: Why do People browse the Internet?



Typical User Behaviour (Wodtke, 2003)

• Search for specific Information

• Complete a Task

• Browsing around

ProblemInformation cannot be found

Introduction:Why does this happen?



Hierarchy, Navigation Scheme

No intuitive Navigation Scheme, Hierarchy

People expect Content somewhere else

Introduction:Why does this happen?



Misunderstood Wording

Inconsistent Terms

English Vs. German

Ambiguous Terms

Introduction



How can this be improved?

Introduction: How can this be improved?



With Card Sorting

• Users group the Contents and develop a Hierarchy themselves

• Helps to understand how Users group Information

• Can provide insight into mental Model

• Serves as helpful Input to specify IA

Introduction



Benfits of Card Sorting

• Simple, Cheap, Quick

• Established

• Involves Users

• Flexible

• Provides good Results

Introduction



Usage Areas

• Designing a new Site

• Designing a new Area of a Site

• Redesigning a Site

• Early Stages of Prototyping

• Large Websites

Card Sorting: The Standard Method



2Card Sorting:The Standard Method




Preparation




Preparation

• Write down the Topics

• Write each Content on a Card

• Size of Cards should be manageable

• Number of Cards should be manageable (30-100)

• Label is extremely important

Card Sorting: Preparation



Same Level of Detail Politics

Album Charts




Cover one distinguished Content

Tennis

Icehockey




Describe the Content in a unambiguous Way

Inspiration

Opening Hours




Before the Exercise starts...

• Define Test Conditions (Single, Group,...)

• Select Participants

• Invite Participants

Card Sorting: Conducting the Exercise



Conducting the Exercise




Procedure

• Welcome Participants

• Introduce Card Sorting Method

• Give Instructions• Sorting out Cards• Sorting into multiple Categories




Step 1: Sorting the Cards




Step 2: Finalizing the Sorting




Step 3: Labeling the Clusters

Card Sorting: Closed Card Sorting



Variant: Closed Card Sorting

• Categories are predefined

• Top-down Approach

• Redesign/Relaunch of Websites

Card Sorting: Analysis



(Manual) Analysis




Analysis Methods

• Documention

• „Data-Eyeballing“

• Spreadsheet Analysis

• (Clusteranalysis)




Data-Eyeballing

• Look for dominant Organization Schemes (Patterns)

• Adjust Scheme to make kinds of Categories consistent

• Set asside the odd Categories that don‘t match

Card Sorting: Data-Eyeballing



Result: Simple TaxonomySport

Fussball1. Bundesliga2. Bundesliga...

TennisWeltranglisteATP-Turniere...

BasketballNBA...

PolitikAktuelles

Aus aller WeltDeutschland...

InnenpolitikNews...

AußenpolitikEuropa...

WirtschaftDeutschland

News...

WeltweitNews...

BörseNewsDAXDow-Jones...

Card Sorting: Data-Eyeballing



Attributes of Data-Eyeballing

• Efficient

• Easy and fast

But:

• Highly subjective




Spreadsheet Analysis




Spreadsheet Analysis

• More information can be found atBoxes and Arrows: Analyzing Card Sort Results with a Spreadsheet Template

Cluster Analysis



3Cluster Analysis

Cluster Analysis



Cluster Analysis

• Statistical Analysis Method for identifying Groups

• Most common Analysis Method

• Mostly done with Computer

• Procedure:• Step 1: Distance Matrix• Step 2: Tree Diagram

Cluster Analysis



Distance Matrix

Cluster Analysis: Distance Matrix



ExampleParticipant 1

ProjekteAG‘sAktuelle Projekte

StudentischesFachbereicheInsitute

CampusLageplanAnreise

Participant 2Aktivitäten

AG‘sAktuelle Projekte

StudiumFachbereicheInstitute

Allgemeine InfosLageplanAnreise


AG‘s

StudiumFachbereicheAktuelle ProjekteInstitute

InformationenLageplanAnreise




Distance Matrix P1AG‘s

Aktuelle Projekte

Fach-bereiche

Institute Lageplan Anreise

AG‘s 1.00 0.00 1.00 1.00 1.00 1.00

Aktuelle Projekte 0.00 1.00 1.00 1.00 1.00 1.00

Fach-bereiche 1.00 1.00 1.00 0.00 1.00 1.00

Insitute 1.00 1.00 0.00 1.00 1.00 1.00

Lageplan 1.00 1.00 1.00 1.00 1.00 0.00

Anreise 1.00 1.00 1.00 1.00 0.00 1.00




Distance Matrix P1AG‘s

Aktuelle Projekte

Fach-bereiche


AG‘s 1.00 0.00 1.00 1.00 1.00 1.00


Fach-bereiche 1.00 1.00 1.00 0.00 1.00 1.00

Insitute 1.00 1.00 0.00 1.00 1.00 1.00

Lageplan 1.00 1.00 1.00 1.00 1.00 0.00

Anreise 1.00 1.00 1.00 1.00 0.00 1.00




Distance Matrix P1 + P2AG‘s

Aktuelle Projekte

Fach-bereiche


AG‘s 1.00 0.00 1.00 1.00 1.00 1.00


Fach-bereiche 1.00 1.00 1.00 0.00 1.00 1.00

Insitute 1.00 1.00 0.00 1.00 1.00 1.00

Lageplan 1.00 1.00 1.00 1.00 1.00 0.00

Anreise 1.00 1.00 1.00 1.00 0.00 1.00




ExampleParticipant 1

ProjekteAG‘sAktuelle Projekte

StudentischesFachbereicheInsitute

CampusLageplanAnreise


AG‘sAktuelle Projekte

StudiumFachbereicheInstitute

Allgemeine InfosLageplanAnreise


AG‘s

StudiumFachbereicheAktuelle ProjekteInstitute

InformationenLageplanAnreise




Distance Matrix (P1+P2)+P3AG‘s

Aktuelle Projekte

Fach-bereiche


AG‘s 1.00 0.33 1.00 1.00 1.00 1.00


Fach-bereiche 1.00 0.67 1.00 0.00 1.00 1.00

Insitute 1.00 0.67 0.00 1.00 1.00 1.00

Lageplan 1.00 1.00 1.00 1.00 1.00 0.00

Anreise 1.00 1.00 1.00 1.00 0.00 1.00




How to calculate

∑KF(AF/BF) =

Kt(At/Bt)

Tt=1

T

K: Relative CoordinateA: Relative X-CoordinateB: Relative Y-CoordinateF: Final MatrixT: Number of Participants

t: Participant




From Distance Matrix to Tree Diagrams

• Single Linkage Algorithm

• Complete Linkage Algorithm

• Average Linkage Algorithm

Cluster Analysis: Single Linkage Algorithm



Distance Matrix

AG‘s ASTAAktuelle Projekte

Alumni

AG‘s 1.00 0.69 0.42 0.83

ASTA 0.69 1.00 0.92 0.81

Aktuelle Projekte 0.42 0.92 1.00 0.86

Alumni 0.83 0.81 0.86 1.00




How it works

• Pair (Aktuelle Projekte/AG‘s) is most frequently grouped together (58%)

• Combine Pair to one Cluster and calculate new Distances

• d(E; CE1 + CE2) = min{d(E;CE1), d(E;CE2)}

• d(ASTA; AG‘s + Aktuelle Projekte) = min{d(ASTA;AG‘s), d(ASTA; Aktuelle Projekte)} = min{0.69, 0.92}= 0.69




New Distance MatrixAG‘s+

Aktuelle Projekte

ASTA Alumni

AG‘s+Aktuelle Projekte

1.00 0.69 0.83

ASTA 0.69 1.00 0.81

Aktuelle Projekte 0.83 0.81 1.00




Steps

1. AG‘s+Aktuelle Projekte 0.42

2. (AG‘s+Aktuelle Projekte)+ASTA 0.69

3. ((AG‘s+Aktuelle Projekte)+ASTA)+Alumni 0.81




Final DendogramAG‘s

AktuelleProjekte

ASTA

Alumni

0.00 0.50 1.00

0.42 0.69 0.81




Attributes

• min{0.69;0.92}=0.69

• Nearest-Neighboor-Method

• Minimum-Distance Rule

• Chaining Phenomenon

• Isolates Outliners (Most important Attribute)

Cluster Analysis: Complete Linkage Algorithm



Attributes

• max{0.69;0.92}=0.92

• Furthest-Neighboor-Method

• A lot of small Groups are formed

• Large groups are mostly formed at the End

• Does not identify Outliners well

Cluster Analysis: Average Linkage Algorithm



Attributes

• 0,5x(0.69) + 0,5x(0.92) = 0.80

• Takes mean Distance

• No Chaining Phenonemon

Computer-Based Card Sorting



4Computer-BasedCard Sorting




Some Tools

• EZSort

• CardSort

Computer-Based Card Sorting: EZSort



EZSort

Computer-Based Card Sorting: EZSort



Features

• Most common Card Sorting Tool

• Developed by IBM in 1998

• USort for Sorting the Cards (Open Card Sort)

• EZCalc for Clusteranalysis

• Windows-only

Computer-Based Card Sorting: CardSort



CardSort

Computer-Based Card Sorting: CardSort



Features

• Developed in 2003

• www.cardsort.net

• Allows only Card Sorting (open and closed)

• Analysis with EZCalc

• Cross-plattform

http://www.cardsort.net/

http://www.cardsort.net/




Other Tools

• CardZorthttp://condor.depaul.edu/~jtoro/cardzort/

• CardSwordhttp://cardsword.sourceforge.net/

• WebSorthttp://www.websort.net/

http://condor.depaul.edu/~jtoro/cardzort/





http://cardsword.sourceforge.net/



Card Sorting Variants



5Card SortingVariants





• Card Sorting with Subgroups

• Labeling the Contents

• Rating the Contents

Card Sorting Variants: Card Sorting with Subgroups



Card Sorting with Subgroups

Card Sorting Variants: Card Sorting with Subgroups



Attributes

• Adding an additional Sorting Step

• First: Forming Clusters (Subgroups)

• Second: Forming Major Clusters

• Third: Labeling the (Major) Clusters

Card Sorting Variants: Labeling the Contents



Labeling the Contents

Card Sorting Variants: Labeling the Contents



Labeling the Contents

• Cards represent Content Descriptions

• Users label the Contents

On this page, students register online for their courses.

Card Sorting Variants: Rating the Contents



Rating the ContentsGerry McGovern (2002)

Card Sorting Variants: Rating the Contents



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Step 1

Step 2

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Begriff 24

Begriff 16

Begriff 1

Begriff 2

Begriff 1Begriff 3

Begriff 5

Begriff 8

Begriff 9

Begriff 10

Begriff 11

Begriff 13

Begriff 15

Begriff 17

Begriff 1Begriff 18

Begriff 21

Begriff 22

Begriff 25

Begriff 26

Begriff 4

Begriff 6

Begriff 7

Begriff 14

Begriff 16

Begriff 19

Begriff 20

Begriff 23

Begriff 24

Conclusion



6Conclusion

Conclusion



Summary

• Card Sorting is an easy and cheap Method to get an Insight into the users‘ mental Model

• Many different Variants

• Not a silver Bullet

• Generates Suggestions for Navigation, Hierarchy, Wording

Conclusion



Summary

• Can be done paper-based or computer-based

• Computer-based Method is better for Analysis-> Clusteranalysis

• Manual Method is easier for Users to handle

Conclusion



Keep in Mind

• Only for large Websites

• Users‘ Tasks are not integrated

• May capture “Surface” Characteristics only

References



7References

References



Links, Books, Articles

• IAWiki Card Sortinghttp://www.iawiki.net/CardSorting

• Boxes and Arrowshttp://www.boxesandarrows.com

• James Robertsonhttp://www.steptwo.au

• Donna Maurerhttp://www.maadmob.net/donna/

http://www.iawiki.net/CardSorting

http://www.iawiki.net/CardSorting

http://www.boxesandarrows.com/

http://www.boxesandarrows.com/

http://www.steptwo.au/

http://www.maadmob.net/donna/

http://www.maadmob.net/donna/

Card Sorting Variants: Card-Based Classification Evaluation



Thank you!




8Questions and Discussion

Card Sorting Variants: Card-Based Classification Evaluation



Further Questions?Contact me!

[email protected]

Card Sorting for Information Architecture: Usage Areas, Methods and Samples IATagung Frankfurt :: 28./29.05.2005 :: Steffen Schilb Card Sorting for Information.

Documents

introduction card sorting

steffen schilb card

card sorting method

preparation card sorting

exercise card sorting

card sorting users

outline card sorting

card sorting variants