SIMS 213: User Interface Design & Development

SIMS 213: User Interface Design & Development

Marti HearstThurs, March 3, 2005

Today

Content Layout Technique: WireframingContent Expression Normalization: Card Sorting

Wireframing

What is the main idea?– Separate content from layout and display– Graphic Design:

• Use the page layout to signal the flow of interaction• Group conceptually related items together

– Nielsen: • What does the layout communicate?• Test if a page of content becomes more usable because of the layout• A template (for a home page) should contain what items?

How WireFraming Fits In

Kelly Goto & Eric Ott of Macromedia

http://www.gotomedia.com/macromedia/monterey/architecture/

From http://www.gotomedia.com/macromedia/monterey/architecture/

From http://www.gotomedia.com/macromedia/monterey/architecture/

How to Test A Layout

Study conducted by Thomas S. Tullis from Fidelity Investments in 1998Assessed the usability of five alternative template designs for their intranets. Method:– Show templates with “greeked” text– Draw labeled boxes around each page corresponding

to 9 elements– No overlapping allowed– Indicate if something appears not to be there

The Elements

1. Main content selections for this page 2. Page title 3. Person responsible for this page 4. Intranet-wide navigation (e.g., intranet home, search) 5. Last updated date 6. Intranet identifier/logo 7. Site navigation (e.g, major sections of this section of the

intranet) 8. Confidentiality/security (e.g, Public, Confidential, etc.) 9. Site news items

From http://www.useit.com/alertbox/980517.html




Nielsen Wireframing Example

Different parts of the designs scored betterBest parts were taken from each design and combinedResulted in an overall better score

Results of Study

CorrectPage

Elements

Subjective Appeal

(-3 to +3)

Template 1 52% +1.3

Template 3 67% +0.9

Final Design 72% +2.1

The Vocabulary Problem

If you ask a set of people to describe a set of things there is little overlap in the results.Some nice studies have been done on this:– Furnas, Landauer, Gomez, Dumais: The Vocabulary

Problem in Human-System Communication. Commun. ACM 30(11): 964-971 (1987)


Idea: see how often people agree on word choiceData sets examined (# of participants):– Main verbs used by typists to describe edit types (48)– Commands for a hypothetical “message decoder” computer

program (100)– First word used to describe 50 common objects (337)– Categories for 64 classified ads (30)– First keywords for a each of a set of recipes (24)

Furnas, Landauer, Gomez, Dumais: The Vocabulary Problem in Human-System Communication. Commun. ACM 30(11): 964-971 (1987)


We get really bad results– If one person assigns the name, the probability of it

NOT matching with another person’s is about 80%



What if we pick the most commonly chosen words as the standard? Still not good:


The Solution? Card Sorting

Content-focusedTwo main purposes– Determine how to organize a set of information

• Determine a collective mental model of the collection’s contents– Determine good labels for the items in that organization

How is it done?– User-centered

• Write topics on cards• Ask different participants to organize them for a given task

– Need strategies for “difficult” cards• Consolidate the results

– Do another round for labels

Slide adapted from Rashmi Sinha's, www.rashmisinha.com

Consolidating Card Sorting Results

At root of all categorization techniques is question: “How far is A from B?”Proximity / similarity matrix can organize the results– Each cell shows how often 2 items were in the same category

Cheese Burger

Chicken McNuggets

Fish sandwich

French Fries

Shake

Cheese Burger 7 6 2 4 5

Chicken McNuggets 6 7 4 3 2

Fish sandwich 2 4 7 3 1

French Fries 4 3 3 7 4

Shake 5 2 1 4 7

Self correlation


Analyzing Results viaHierarchical Clustering

ContinentalBuick

CadillacMercedesCorvette

JaguarFirebirdCamaro

Monte CarloCapri

ChevyVegaDart

Volkswagen

Cluster Analysis for dataset about carsAdvantages– Suggests a structural solution

Disadvantages– Prescriptive– Averages over different

dimensions


Analyzing Results via Multidimensional Scaling (MDS)


Advantages of Multidimensional Scaling (MDS)

Hints at possible solutions rather than prescribes. Tells you the possibilities, leaves specifics of solution to you.Dimensions (axes) can suggest facets.Similarity maps are easy to understandHelps identify which dimensions are important– Do cluster analysis using the axes identified by MDS– Cluster Analysis and MDS are complementary

How Many Participants forCard Sorting?

How many participants?– Tullis and Wood ’04, discussed by Nielsen:

• http://home.comcast.net/%7Etomtullis/publications/UPA2004CardSorting.pdf• http://www.useit.com/alertbox/20040719.html

– Study included 168 participants, 46 cards– Nielson concludes:

• 5 for usability studies – Evaluating and reacting to an existing design– Fewer potential responses

• 15 participants for card sorting – (to get 90% agreement)– Generating something, so more diversity in responses– (Numbers based on only one site!)

• (Interface design should interweave generating and testing)

Let’s Do Some Sorting!

There are many tools out thereLet’s try WebSort – http://websort.net

Documents

SIMS 213: User Interface Design & Development