CMSC434 Week 07 | Lecture 19 | Nov 4, 2014 Human ... · Card, Moran, and Newell, The Psychology of...

Human Computer Interaction Laboratory

@jonfroehlich Assistant Professor Computer Science

CMSC434 Introduction to Human-Computer Interaction

Week 07 | Lecture 19 | Nov 4, 2014

Human Information Processing

TODAY

1. Wrapping up Fitts’ Law

2. Improving Pointing

3. Human-Information Processing

4. GOMS Model

5. TA06 Check-In

wrapping up fitts’ law

FITTS’ LAW

A

(amplitude)

W

MT

(width)

There are different formulations in HCI

Different

formulati

ons for

fitt’s law;

this one

popular

movement time

Which will be faster on average?

pie menu (bigger targets & less distance)

[adapted from Hartmann, Landay]

FITTS’ LAW IN PRACTICE

PIE MENU VS. LINEAR MENU

USING A PIE MENU IN PRACTICE

Source: http://youtu.be/gzAN0E-xOyA

The Sims

Rainbow 6

Maya

[adapted from Landay]

Why aren’t Pie Menus more widely adopted?

OTHER PIE MENU EXAMPLES

MARKING MENUS

Source: http://youtu.be/8c58bN6ajJ4

improving pointing

TARGET ACQUISITION

[adapted from Findlater]

SUB-MOVEMENT ANALYSIS

[adapted from Findlater]

SUB-MOVEMENT ANALYSIS

[adapted from Findlater]

Bubble Cursor Grossman & Balakrishnan, CHI’05

leah findlater

alex jansen

kristen shinohara

morgan dixon

peter kamb

joshua rakita

jacob o. wobbrock

enhanced area cursors reducing fine pointing demands for

people with motor impairments

21

ENHANCED AREA CURSORS

[adapted from Findlater]

[adapted from Findlater]

ENHANCED AREA CURSORS: FOUR TYPES

[adapted from Findlater]

[adapted from Findlater]

[adapted from Findlater]

[adapted from Findlater]

[adapted from Findlater]

evaluation

lessen effects of small target size?

reduce need for corrective-phase pointing?

reduce need for accurate, steady clicking?

do the new cursors…

[adapted from Findlater]

task

36

12 participants

parkinson’s disease

multiple sclerosis

cerebral palsy

de quervain’s stenosynovitis

spinal cord injury

friedreich’s ataxia

tetraplegia

muscular dystrophy

[adapted from Findlater]

3 target sizes

12 participants

4px

8 px

16 px

[adapted from Findlater]

3 target sizes

3 target spacings

12 participants none

half-target

width

full-target

width [adapted from Findlater]

3 target sizes

3 target spacings

2 levels of clutter

12 participants

[adapted from Findlater]

3 target sizes

3 target spacings

2 levels of clutter

6 cursors

12 participants click-and-cross

point

cross-and-cross

motor-magnifier

visual-motor-

magnifier

bubble

[adapted from Findlater]

lessen effects of small target size?

do the new cursors…

[adapted from Findlater]

speed

point bubble motor-

magnifier

visual-

motor-

magnifier

click-

and-

cross

cross-

and-

cross

mean t

rial tim

e (

seco

nd

s)

error bars:

standard error

0

2

4

6

8

4 pixels 8 pixels 16 pixels

[adapted from Findlater]

0

2

4

6

8

speed

point bubble motor-

magnifier

visual-

motor-

magnifier

click-

and-

cross

cross-

and-

cross

mean t

rial tim

e (

seco

nd

s)

4 pixels 8 pixels 16 pixels

fastest for

smaller sizes

s

s s error bars:

standard error

[adapted from Findlater]

0

2

4

6

8

speed

point bubble motor-

magnifier

visual-

motor-

magnifier

click-

and-

cross

cross-

and-

cross

mean t

rial tim

e (

seco

nd

s)

reduced effect of

small target size

s

s s error bars:

standard error

4 pixels 8 pixels 16 pixels

[adapted from Findlater]

0

2

4

6

8

speed

point bubble motor-

magnifier

visual-

motor-

magnifier

click-

and-

cross

cross-

and-

cross

mean t

rial tim

e (

seco

nd

s)

s

s s error bars:

standard error

4 pixels 8 pixels 16 pixels

[adapted from Findlater]

0

0.1

0.2

0.3

0.4

0.5

mean e

rro

r ra

te

errors

point bubble motor-

magnifier

visual-

motor-

magnifier

click-

and-

cross

cross-

and-

cross

s

s s error bars:

standard error

4 pixels 8 pixels 16 pixels

[adapted from Findlater]

0

0.1

0.2

0.3

0.4

0.5

mean e

rro

r ra

te

reduced errors

compared to point

errors

point bubble motor-

magnifier

visual-

motor-

magnifier

click-

and-

cross

cross-

and-

cross

s

s s e e e error bars:

standard error

4 pixels 8 pixels 16 pixels

[adapted from Findlater]

lessen effects of small target size?

reduce need for corrective-phase pointing?

do the new cursors…

[adapted from Findlater]

0

10

20

30

40

50

submovement analysis m

ean n

um

ber

of

sub

mo

vem

ents

point bubble motor-

magnifier

visual-

motor-

magnifier

click-

and-

cross

cross-

and-

cross

s

s s e e e error bars:

standard error

4 pixels 8 pixels 16 pixels

[adapted from Findlater]

0

10

20

30

40

50

submovement analysis m

ean n

um

ber

of

sub

mo

vem

ents

point bubble motor-

magnifier

visual-

motor-

magnifier

click-

and-

cross

cross-

and-

cross

reduced submovements

compared to point

s

s s e e e m m

m

error bars:

standard error

4 pixels 8 pixels 16 pixels

[adapted from Findlater]

submovement analysis m

ean n

um

ber

of

sub

mo

vem

ents

point bubble motor-

magnifier

visual-

motor-

magnifier

click-

and-

cross

cross-

and-

cross

s

s s e e e m m

m

error bars:

standard error

0

10

20

30

40

50

4 pixels 8 pixels 16 pixels

extra movement

for activation

[adapted from Findlater]

submovement analysis m

ean n

um

ber

of

sub

mo

vem

ents

point bubble motor-

magnifier

visual-

motor-

magnifier

click-

and-

cross

cross-

and-

cross

s

s s e e e m m

m

error bars:

standard error

0

10

20

30

40

50

4 pixels 8 pixels 16 pixels

[adapted from Findlater]

lessen effects of small target size?

reduce need for corrective-phase pointing?

reduce need for accurate, steady clicking?

do the new cursors…

[adapted from Findlater]

visual-motor-magnifier

cross-and-cross

click-and-cross

bubble

most preferred

number of

participants

slowest, but

still preferred

55

7

3

2

0

human-information processing

Cognitive psychology is the study of higher

mental processes such as attention, language

use, memory, perception, problem solving, and

thinking.

American Psychological Association http://www.apa.org/research/action/glossary.aspx#c

Stuart K. Card Thomas P. Moran Allen Newell

Stuart K. Card Thomas P. Moran Allen Newell

PhD in psychology from CMU

Early HCI Pioneer at PARC

Distinguished Engineer at IBM

PhD in from CMU w/Herb Simon

Early HCI Pioneer at RAND/CMU

The domain of concern to us, and the subject

of this book, is how humans interact with

computers. A scientific psychology should

help us in arranging this interface so it is

easy, efficient, error-free—even enjoyable.

Card, Moran, and Newell Early pioneers of the field of HCI

Quote from: The Psychology of Human-Computer Interaction, 1983, p. vii

Card, Moran, and Newell, The Psychology of Human-Computer Interaction, p. 26

Model Human Processor The Model Human Processor

offers a simplified view of the

human processing involved

in interacting with computing

systems.

Comprises three subsystems:

1. Perceptual system

2. Motor system

3. Cognitive systems

Model Human Processor

1. The perceptual system handles sensory stimuli from the outside world 3. The motor system

controls physical actions

2. The cognitive system provides the processing needed to connect the two

Model Human Processor

1. The perceptual system handles sensory stimuli from the outside world 3. The motor system

controls physical actions

2. The cognitive system provides the processing needed to connect the two

Each subsystem has its own processor and memory

Card, Moran, and Newell, The Psychology of Human-Computer Interaction, p. 26

The Model Human Processor

P0. Recognize-act cycle of cognitive processor P1. Variable perceptual processor rate principle P2. Encoding specificity principle P3. Discrimination principle P4. Variable cognitive processor rate principle P5. Fitts’ Law P6. Power law of practice P7. Uncertainty principle P8. Rationality principle P9. Problem space principle

The Principles of Operation

Card, Moran, and Newell, The Psychology of Human-Computer Interaction, p. 26

The Model Human Processor

P0. Recognize-act cycle of cognitive processor P1. Variable perceptual processor rate principle P2. Encoding specificity principle P3. Discrimination principle P4. Variable cognitive processor rate principle P5. Fitts’ Law P6. Power law of practice P7. Uncertainty principle P8. Rationality principle P9. Problem space principle

The Principles of Operation

The time Tn to perform a task on the n th trial follows a power law: Tn = T1n -α

Card, Moran, and Newell, The Psychology of Human-Computer Interaction, p. 26

The Model Human Processor

P0. Recognize-act cycle of cognitive processor P1. Variable perceptual processor rate principle P2. Encoding specificity principle P3. Discrimination principle P4. Variable cognitive processor rate principle P5. Fitts’ Law P6. Power law of practice P7. Uncertainty principle P8. Rationality principle P9. Problem space principle

The Principles of Operation

The time Tn to perform a task on the n th trial follows a power law: Tn = T1n –α

where α = .4 [0.2 – 0.6]

POWER-LAW OF PRACTICE

The power law of practice states that the logarithm of the completion time for a particular task decreases linearly with the logarithm of the number of practice trials taken

Source: Newell & Rosenbloom, Mechanisms of skills acquisition and the law of practice, 1980

Trail Making Test Match-to-Sample Task

http://en.wikipedia.org/wiki/Match-to-sample_task

http://en.wikipedia.org/wiki/Trail_Making_Test

POWER-LAW OF PRACTICE: EXAMPLE TASKS

Card, Moran, and Newell, The Psychology of Human-Computer Interaction, p. 26

The Model Human Processor

P0. Recognize-act cycle of cognitive processor P1. Variable perceptual processor rate principle P2. Encoding specificity principle P3. Discrimination principle P4. Variable cognitive processor rate principle P5. Fitts’ Law P6. Power law of practice P7. Uncertainty principle P8. Rationality principle P9. Problem space principle

The Principles of Operation

The time Tpos to move the hand to a target of size S which lies a distance D away: Tpos = IM log2 (D/S + 0.5)

Card, Moran, and Newell, The Psychology of Human-Computer Interaction, p. 26

The Model Human Processor

P0. Recognize-act cycle of cognitive processor P1. Variable perceptual processor rate principle P2. Encoding specificity principle P3. Discrimination principle P4. Variable cognitive processor rate principle P5. Fitts’ Law P6. Power law of practice P7. Uncertainty principle P8. Rationality principle P9. Problem space principle

The Principles of Operation

A person acts so as to attain his goals through rational action, given the structure of the task and his inputs of information and bounded limitations on his knowledge and processing ability: Goals + Task + Operators + Inputs + Knowledge + Process-limits -> Behavior

GOMS Model

A GOMS model, as proposed by Card, Moran, and

Newell (1983), is a description of the knowledge that a

user must have in order to carry out tasks on a device

or system; it is a representation of the "how to do it"

knowledge that is required by a system in order to get

the intended tasks accomplished.

[Kieras, A Guide to GOMS Analysis, 1994; Card et al., The Psychology of Human-Computer Interaction, 1983]

GOMS Model

[Rogers et al., Interaction Design, Chapter 15, 2011; Card et al., The Psychology of HCI, 1986]

An attempt to model the

knowledge and cognitive

processes involved when a

user interacts with a system

1

2

3

4

Goals refers to a particular state the

user wants to achieve

Operators refers to the cognitive

processes and physical actions that

need to be performed to achieve those

goals

Methods are learned procedures for

accomplishing the goals

Selection rules are used to determine

which method to select when there is

more than one available.

GOMS Model Example 1

2

Goal: find a website about GOMS

Operators: Decide to use search

engine, decide which search engine to

use,

GOMS Model Example 1

2

3

4

Goal: find a website about GOMS

Operators: Decide to use search

engine, decide which search engine to

use, think up and enter keywords.

Methods: I know I have to type in

search terms and then press the search

button.

Selection: Do I use the mouse button

or hit the enter key?

GOMS Model

The goal of this work [GOMS modeling] is to radically

reduce the time and cost of designing usable systems

through developing analytic engineering models for

usability based on validated computational models of

human cognition and performance.

[Kieras, GOMS Models: An Approach to Rapid Usability Evaluation, http://web.eecs.umich.edu/~kieras/goms.html]

DavidKieras Professor in EECS and Psychology at the University of Michigan

GOMS Advocate

GOMS Model

GOMS is such a formalized representation that it can be

used to predict task performance well enough

that a GOMS model can be used as a substitute for

much (but not all) of the empirical user testing needed

to arrive at a system design that is both functional and

usable.

[Kieras, GOMS Models: An Approach to Rapid Usability Evaluation, http://web.eecs.umich.edu/~kieras/goms.html]

DavidKieras Professor in EECS and Psychology at the University of Michigan

GOMS Advocate

TA06 Mid-Fi Prototypes Check-In Remember: In-Class Design Critiques This Thursday!

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