Perception and Attention

Information Processing Model

models human thought like its a computer

Sensory Register

Perception

Thought Decision Making

Response Selection

Response Execution

Attention Resources

Working Memory

Long Term

Memory

feedback

SensorsFeature Detectors, Pattern Recognition AI System

Output Routines

Output, Motor actions

Controller

RAM

Disk storage

feedback

Sensory Register

Perception

Thought Decision Making

Response Selection

Response Execution

Attention Resources

Working Memory

Long Term

Memory

feedback

Perception Processing Response

Perception

compares incoming sensory data to stored knowledge

reduces from many pieces of data to meaningful units

Three aspects, feature analysis (bottom up processing), unitization, and top down processing

Feature Analysis

Analysis of the raw features of an event Colour, size, shape, loudness

A A A A

Unitization

Matching sets of features with long term memory to create units E.g. reading words in a familiar language vs an

unfamiliar language

things are built up hierarchically feature-> letter -> word ->sentence

A A A A Appleunitisation: creating a unit out of features

Objects

Can also be broken down into features, and conversely unitized

Design Implications of Feature Analysis

Speed and accuracy greatest for most often seen fonts (use a common font)

For single words (labels) use all caps. STOP For sentences use upper and lower case,

NOT ALL CAPS ITS HARD TO READ Use print not script.

Design Implications of Feature Analysis

Minimize abbreviations and use complete words when possible (min abb.)

If you have to abb. trunc. don’t abvt. Leavespacesbetweenwords.

Top Down Processing

Uses the context of the situation to resolve the image

Occurs simultaneously with bottom up processing resolves ambiguous situations in the absence of

clear physical features your expectation of what you’ll see affects what

you’ll see

Exercise: Feature Analysis and Top Down Processing in

Conflict

GREEN

YELLOW

PURPLE

RED

BLACK

BLUE

RED

RED

GREEN

GREEN

GREENBLUE

BLUE

YELLOW

YELLOW

BLACK

BLACK

BLACK

PURPLE

PURPLE

GREEN

YELLOW PURPLE

RED

BLACK

BLUE

RED

RED

GREEN

GREEN

GREEN

BLUE BLUE

YELLOW

YELLOW

BLACK

BLACK

BLACK

PURPLE

PURPLE

X

XX

XXX

XXXX

XXXXX XXXXXX

X

XX

XXX

XXXX

XXXXX X

XX

XXX

XXXX

XXXXX

XXXXXX

XXXXXX

XXX

XXXX

1

22

333

4444

55555 666666

1

22

333

4444

55555 1

22

333

4444

55555

666666

666666

333

4444

2

11

555

1111

44444 222222

6

33

666

2222

33333 5

44

666

1111

66666

444444

555555

4443333

Attention

focuses resources like a spotlight filters out what you don’t need to know shifts:

multi-tasking when driving in a straightforward situation (drive, radio, friend)

focus when in heavy traffic, or accident seen

Two Kinds of Attention

Selective attention Focusing on the environment with the goal of

extracting certain information

Divided attention Processing two sources of information at once

Divided Attention: Resource Demands

Difficult tasks reduce ability to divide attention

“Resource theory” (Kahneman, 1974) Mental resources are shared by tasks Mental resources are finite Two tasks share resources

Divided Attention: Structural Similarity

People have multiple pools of resources Auditory vs. visual senses Spatial vs. verbal cognitive demands Stages of processing (memory vs. responding) Visual channel (focal vs. ambient)

Tasks share resources within a pool “Multiple resource theory”

Divided Attention: Task Confusion

More similar tasks will cause confusion Baseball scores and math Auditory background and words

How does this explanation fit with multiple resource theory?

Divided Attention: Task Management

Users choose a primary task vs. secondary task

Strategies Doing secondary tasks when primary task allows Success relies on switching appropriately

Automatic and Controlled Processing

when tasks are new they take alot of attention (e.g. learning to drive)

Controlled processing: Effortful cognitive processes that require attention to initiate and sustain them

With practice become automatic Automatic: can be run without cognitive demand on

attentional resources

How do things become automatic?

High degree of consistency Extremely strong mappings between world

and required action

STOP

World Action

Design Implications of Attention

use strong mappings to make things automatic

exploit visual and auditory information to share attention on different resource pools

make most critical things most salient (visible) to capture attention - attention is competitive!

SPOT exercise