Gary Marsden Slide 1University of Cape Town

Case Study - Nokia 5110

We will try to put together what we have learnt to date by looking at a cell-phone, namely:

Nokia 5110

Gary Marsden Slide 2University of Cape Town

Brief description

Nokia 5110 is currently best selling GSM handset. Easy to use?

– “Use your phone as you want. Send short messages, save names and numbers, select a new ringing tone - all with the press of a single key, the Nokia Navi™ Key.”

Gary Marsden Slide 3University of Cape Town

Design criteria I

Affordance - not particularly relevantMapping - arrow keys for menuConstraints - SIM cardVisualising - one line menus, keypad lock, iconsMemory - one line menusKnowledge - no on line help, unlike banana phoneConceptual model - dial number and press “Call”Turing test - come back to thisRole Integrity - possible network / handset

conflict

Gary Marsden Slide 4University of Cape Town

Design Criteria II

Simplicity - Navi-key!Least astonishment - Ok so far.Modes - enter number in address book (not

banana)Equal opportunity - some, but not optimal

(ABC key, entry modes)Least effort - 6 key presses to change message

centre number, 11 to change ring volumeFeedback - Ok, generic messages problemCognitive dimensions - not applicable

Gary Marsden Slide 5University of Cape Town

Humans as 2nd class citizens

Thimbleby’s principle of equating humans to machines turns out to be very important

Is it possible to write an algorithm to interact with the 5110?

How efficient is the menu structure of the 5110?

Gary Marsden Slide 6University of Cape Town

Some definitions

We wish to find how efficient interface access is

Assume a perfect, naïve user (do not consider error recovery)

Interested in access to functions, not their activation

Count access in terms of key presses– 5110 only interacts via keys, therefore there is

a common ‘cost’ of interaction

Gary Marsden Slide 7University of Cape Town

Calculating cost

A simple measure of usability can be gained as follows

button presses

Number of functionsThe use of this type of simple model has

been shown (Card, Carroll, Moran, Newell)Increase usability by restructuring access to

functions, not increasing number of functions

Gary Marsden Slide 8University of Cape Town

5110 in-depth

5110 has 74 functions of interest to usArranged in a menu structure (see handout)

– Average time: 8.2 presses– Max search: 110 presses– Max time: 14 presses

Key presses

0

2

4

6

8

10

12

14

1 3 5 7 9 11 13 15

Key presses

Gary Marsden Slide 9University of Cape Town

5110 data structure

Is it sensible to structure the interface around an arbitrary menu?

As computer scientists, we know about data structures so can re-design to use a more efficient structure

Gary Marsden Slide 10University of Cape Town

Binary trees

This time, we have 74 functions in binary tree

Use left, right and select buttons– Average time: 5.4 presses– Max search: 152 presses– Max time: 7 presses

• Alphabetic– no worse than existing– functional clusters

• e.g. DIVERT

key presses

0

5

10

15

20

25

30

35

1 2 3 4 5 6 7

key presses

Gary Marsden Slide 11University of Cape Town

Who wants trees

The previous two solutions assume a tree structure, but is this a good idea?

Christopher Alexander’s classic paper - The City is not a Tree- argues against strict classification– e.g. Should volume be in “Tones” or “Phone

Settings”

Try some more data structures...

Gary Marsden Slide 12University of Cape Town

Linear lists

Using a list, we remove navigation cognitive load - checking existence is easy

Using alphabetic ordering– Average time: 37 presses– Max search: 74 presses– Max time: 74 presses

Improvements through– Software: frequency ordering– Hardware: jog wheel

Gary Marsden Slide 13University of Cape Town

Hashing

Using a technique known as hashing, we can exploit the letters on each key

7

PrincePrueQueen

77

PrincePrue

778

PrueAhmedAlbertAlfonce

Nothing in buffer User presses 7 User presses 7 User presses 8 and correct name selected

Figure 27 PQR 7 PQR 8 STU

Gary Marsden Slide 14University of Cape Town

Benefits

The average number of key presses required to access an individual item was reduced from 8.2 using menus to 3.1 using the mapping algorithms.

Commands could be added dynamically (by the user or service provider) without the need to restructure menus.

The user was freed from modes – e.g. if they had started to enter a function name in the address book, the contents of the buffer could be remapped to the correct domain with one key press.

The solution promoted awareness of functions, as they could be seen scrolling down the screen.

It is possible to improve user recall of command names by providing a “thesaurus” of alternatives for each function name.

The system has a more manageable search space, permitting the user to back track and easily correct keying mistakes.

Gary Marsden Slide 15University of Cape Town

Limitations of the approach

• Assumes error free– longer the sequences, more likely the errors

• No assumptions about cultural factors• No consideration of physical interaction

form• Time ignored

– Time out etc. only compound problem

• Trivial?– Yes, but why is it not being done!

Gary Marsden Slide 16University of Cape Town

Conclusions

Is any analysis done?Where / how does usability influence design?Do users care?

Computing Science has a role to play– Many more algorithms available