An Introduction to ( Human Factors

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Presentations text content in An Introduction to ( Human Factors

Slide1

An Introduction to (Human Factors) Psychology

Dr. William Langston

Middle Tennessee State University

Slide2

Human FactorsDefinition:

The study of those variables that influence the efficiency with which the human performer can interact with the inanimate components of a system to accomplish the system goals

(Proctor & van Zandt, 1994, p.2)

Slide3

Slide4

http://www.silvermoorconsulting.co.uk

/human-

factors.html

Slide5

http://www.silvermoorconsulting.co.uk

/human-

factors.html

Slide6

http://www.silvermoorconsulting.co.uk

/human-

factors.html

Slide7

http://www.davidboettcher.uk

/

ergonomics.php

Slide8

Slide9

Human FactorsSystems approach:

Operator + machine/device + environment

Any failure = system failure. That

'

s to be avoided

There

'

s a lot more flexibility in manipulating the machine/device than in manipulating the operator

Slide10

Human FactorsPsychology is clearly relevant for predicting the behavior of the operator

Basic human capabilities:

Perception

Attention

Memory

Physical limitations

Slide11

AttentionSearch is a problem in a variety of contexts:

Baggage screeners

Van Wert, Horowitz, & Wolfe (2009, p. 543)

Slide12

AttentionWolfe, Horowitz, & Kenner (2005): Rare targets frequently missed in search tasks

Blue bars rare (1% 20/2000),

Yellow bars low (10%),

Red bars common (50%), x-axis = size of search set

Wolfe, Horowitz, & Kenner (2005, p. 439)

Slide13

AttentionWhy? A search task can be modeled as a signal detection task

You have background noise

A signal adds some information to this noise, shifting the distribution along the evidence dimension. The separation determines sensitivity

Slide14

Attention

Modified from

http://www.cns.nyu.edu/~david/handouts/sdt/sdt.html

(

Heeger

, 2007)

Noise

Signal + Noise

Slide15

AttentionUsers place a criterion along the evidence distribution to decide if a signal is present…

Slide16

Attention

Modified from

http://www.cns.nyu.edu/~david/handouts/sdt/sdt.html

(

Heeger

, 2007)

Noise

Signal + Noise

Criterion

Yes »

« No

Slide17

Attention

Modified from

http://www.cns.nyu.edu/~david/handouts/sdt/sdt.html

(

Heeger

, 2007)

Noise

Signal + Noise

Criterion

Yes »

« No

Hit

Slide18

Attention

Modified from

http://www.cns.nyu.edu/~david/handouts/sdt/sdt.html

(

Heeger

, 2007)

Noise

Signal + Noise

Criterion

Yes »

« No

False Alarm

Slide19

Attention

Modified from

http://www.cns.nyu.edu/~david/handouts/sdt/sdt.html

(

Heeger

, 2007)

Noise

Signal + Noise

Criterion

Yes »

« No

Miss

Slide20

Attention

Modified from

http://www.cns.nyu.edu/~david/handouts/sdt/sdt.html

(

Heeger

, 2007)

Noise

Signal + Noise

Criterion

Yes »

« No

Correct

Rejection

Slide21

AttentionThe problem is criterion shift:

When targets are rare, users become increasingly conservative, increasing the number of miss errors

Slide22

Attention

Modified from

http://www.cns.nyu.edu/~david/handouts/sdt/sdt.html

(

Heeger

, 2007)

Noise

Signal + Noise

Criterion

Hit

Miss

Slide23

AttentionSummation:

With current technology, understanding the human observer is the only way to improve system performance

That’s a psychology problem

Slide24

Human FactorsStep back:

Psychology is clearly relevant for predicting the behavior of the operator

But, let’s get a little farther back from specific examples

Are there general principles that can be used to predict human action?

Slide25

Human FactorsA bat and a ball cost $1.10 in total. The bat costs $1.00 more than the ball. How much does the ball cost?

Slide26

Human FactorsA bat and a ball cost $1.10 in total. The bat costs $1.00 more than the ball. How much does the ball cost?

10 cents?

Slide27

Human FactorsIf it takes 5 machines 5 minutes to make 5 widgets, how long would it take 100 machines to make 100 widgets?

Slide28

Human FactorsIf it takes 5 machines 5 minutes to make 5 widgets, how long would it take 100 machines to make 100 widgets?

100 minutes?

Slide29

Human FactorsIn a lake, there is a patch of lily pads. Every day, the patch doubles in size. If it takes 48 days for the patch to cover the entire lake, how long would it take for the patch to cover half of the lake?

Slide30

Human FactorsIn a lake, there is a patch of lily pads. Every day, the patch doubles in size. If it takes 48 days for the patch to cover the entire lake, how long would it take for the patch to cover half of the lake?

24 days?

Slide31

Human FactorsThese questions are from the Cognitive Reflection Test (CRT; Frederick, 2005)

The test evaluates thinking style:

Intuitionist: Compute the obvious (but incorrect answer) and stop

Reflectionist

: Reflect on your response, engage in analytic thinking, re-evaluate the problem (this requires ability as well) (Pennycook,

Fugelsang

, & Koehler, 2015)

Slide32

Human FactorsThere are clear implications of these types of thinking throughout psychology:

Moral reasoning

Prosocial behavior

Human factors

Belief

Slide33

Slide34

Human FactorsIntuitionist: Type 1 processes; fast, automatic, parallel, high capacity

Reflectionist

: Type 2 processes; slower, effortful (require resources), serial, limited (Pennycook et al., 2015)

Slide35

Human FactorsTo what extent do people engage in these types of processing?

Humans are “miserly cognitive processors and, as a consequence, irrational decision makers”

“when people do engage in effortful reasoning, it often comes in the form of justifying or rationalizing prior beliefs, intuitions, or actions”

“there are many cases in which heuristics (i.e., mental shortcuts) produce better and far more efficient outcomes than analytic thinking” (Pennycook et al., 2015, p. 425)

The utility of this approach for the user is complicated

Operating on a generally intuitionist basis is usually successful and is the result of an evolutionary adaptation to maximize outcomes

But, operating on intuition can cause problems

Slide36

Human FactorsPeople

can

engage in rational thought, and sometimes they do

This is driven by internal factors and by the situation

Slide37

Human FactorsIntuitionist mechanism? Probabilistic prediction

Lupyan

& Clark (2015, p. 280)

Slide38

Human FactorsYou only become consciously aware of the predictions when they are violated. For example, if you pour a glass of orange juice and discover upon tasting it that it is actually milk, you will then become aware of the expectation of orange juice (

Lupyan

& Clark, 2015)

Slide39

Human FactorsHuman factors example:

Slide40

Human FactorsViolated expectations…

“…Employee #1 was operating a lawn mower…when he thought that the grass was being mowed too low.

With the lawn mower running, Employee #1 attempted to adjust the blade

so that the grass would not be cut as low. As Employee #1 was going to adjust the lawn mower,

he attempted to pick up the lawn mower and when he did, his left hand came into contact with the blade

. Employee #1's left middle finger was partially amputated…” (https://

www.osha.gov

/

pls

/

imis

/

accidentsearch.accident_detail?id

=202715694)

Slide41

Human FactorsViolated expectations…

On November 7, 2012, Employee #1, a 30-year-old male with

Ronnys

Inc.,

reached under a Honda lawn mower and lacerated his index and middle fingers of his right hand

(

https://

www.osha.gov

/

pls

/

imis

/

accidentsearch.accident_detail?id

=202523171)

Slide42

Human FactorsTo be of use in a human factors context, awareness has to happen before a non-recoverable option has been selected

Two approaches:

Conform to intuitionist expectations

Trigger

reflectionist

thinking

The easier option is to conform to intuitionist expectations

Slide43

Human Factors ExamplesIdentifying expectations and conforming to them is non-trivial

Let’s consider

controls

From the designer

'

s point of view, the decision as to what direction of motion of a control shall produce a given movement of the controlled element is often a matter of indifference,

but, for the operator,

the directional relationship may be a variable which has a considerable influence

(Loveless, 1962, p.357)

Slide44

A Story of the RangeConsider the range:

Arguably the most dangerous piece of equipment in the home…

Slide45

A Story of the Range“In 2005, an estimated 146,400 U.S. home

structure fires involving cooking equipment

resulted in

480 civilian deaths

, 4,690 civilian injuries, and $876 million in direct property damage”

Ranges

, with or without ovens,

account for two-thirds (67%) of total reported…fires

involving cooking equipment and

even larger shares of associated civilian deaths (85%)

and civilian injuries (82%)” (National Fire Protection Association, 2008, NFPA No. USS11, abstract)

Slide46

Ahrens (2013, p. xiii)

Slide47

Ahrens (2013, p. xiii)

Slide48

A Story of the RangeWhat is the best layout to map burners to controls on a range?

A

B

D

C

A

B

C

D

Slide49

A Story of the RangeThere are a lot of possible mappings:

ABCD

ABDC

BACD

BADC

ADBC

DCBA…

A

B

D

C

Slide50

A Story of the RangeWhich arrangement is best?

Chapanis

and

Lindenbaum

(1959):

Range I (in a bit…)

II: ABCD

III: ABDC

IV: BACD

A

B

D

C

A

B

C

D

A

B

D

C

A

B

C

D

A

B

D

C

A

B

C

D

Range II

Range III

Range IV

Slide51

A Story of the RangeWhich arrangement is best?

Chapanis

and

Lindenbaum

(1959):

Range

Errors (1200 trials)

I

0 (0%)

II

76 (6.3%)

III

116 (9.7%)

IV

129 (10.8%)

Slide52

A Story of the RangeWhat about Range 1?

ABDC

A

B

D

C

Slide53

A Story of the RangeIdentifying expectations and conforming to them is non-trivial

There is a lot of variation in the expected outcome from turning a particular knob, but that can be overcome with design

Create an intuitionist expectation that aligns with the desired outcome

Slide54

Human Factors ExamplesTelling people to

be careful

or

try harder

is not a solution. Neither is relying on a label.

More examples…

Slide55

http://

www.baddesigns.com

/3doors.html

Slide56

Slide57

Slide58

It appears to be telling you how to put in your credit card…

Slide59

But that can’t be it…

Slide60

Some More Psychology--DesignersFundamental attribution error: We tend to discount the situation (environment) when trying to understand people

'

s behavior (Jones & Harris, 1967)

The effect is usually associated with people doing something

bad

Violating a norm

Making a mistake

(Letting a weapon on a plane)

Slide61

Some More Psychology--DesignersHuman factors implication:

When people make a mistake using a device, we tend to make an internal attribution

Ignoring the device, the task, or the environment and how those interact with the user will get us no closer to understanding the nature of the mistake.

If you create an error-likely situation, fix it, don

'

t blame the victim.

Slide62

Some More Psychology--UsersUnrealistic optimism:

People have a tendency to rate their personal risk as lower than that of the average person (Dunning, Heath, &

Suls

, 2004). Knowing the actual risks does not seem to inform people

'

s predictions for themselves

Can account for a number of things people do that override impediments to human factors errors or that contribute to these errors

Slide63

Some More Psychology--UsersKeeping this spinning:

Slide64

Some More Psychology--UsersUnrealistic optimism:

For example, talking on a cell phone while driving is a bad idea (hands free or not). T

alking and driving has similar performance effects as drinking and driving

Slide65

Some More Psychology--Users

Kunar

, Carter, Cohen, & Horowitz (2008, p. 1137)

Slide66

Some More Psychology--UsersUnrealistic optimism:

Why do people do it? They know it's dangerous for the average person, but they don't estimate their own risk accurately

Slide67

Some More Psychology--UsersDunning-Kruger effect (Kruger & Dunning, 1999):

…the skills necessary to recognize competence are extremely close if not identical to those needed to produce competent responses

“…recognizing whether an argument is logically sound requires a firm grasp of the rules of logic. If people do not understand the rules of logic, not only will they make logical errors, but they will also not recognize that their arguments are logically defective…” (Dunning et al., 2004, p. 73)

Slide68

Some More Psychology--UsersDunning-Kruger effect (Kruger & Dunning, 1999):

In other words,

not having competence makes you unable to learn from or predict mistakes

Maybe talking and driving is caused by this. Talking degrades your driving skills

and

the ability to detect that your skills are degraded

Slide69

Some More Psychology--UsersDunning-Kruger effect (Kruger & Dunning, 1999):

Sanbonmatsu

,

Strayer

,

Biondi

,

Behrends

, & Moore (2015)

Control drivers: Correlation between serious driving errors and rated driving performance r(49) =

-.37

(

more errors, lower ratings

)

Cell phone drivers: r(49) =

.25

(

more errors, higher ratings!

)

Slide70

Some More Psychology--UsersDunning-Kruger effect (Kruger & Dunning, 1999):

Human factors implication: As hard as it is, don't let people make mistakes (e.g., my car will not show a DVD on the center console screen while driving)

Slide71

Human Factors Interim Wrap-upThere is a vast literature from experimental psychology that could be used to predict how an operator will interact with a device

Collecting the data to fill in gaps is a necessary step

Slide72

Human Factors Interim Wrap-upThe system is: Operator + machine/device + environment

The operator is relatively resistant to change. But, we can use data to understand what the operator will do

The machine/device and environment are under our control and should be designed with the operator in mind

The goal is to prevent system failure by taking the human operator into account

Slide73

Human Factors Psychology:Implications

Aside on Groups

Slide74

GroupsForming an effective group: Maximize collective intelligence

Slide75

GroupsCollective intelligence is an emergent property that is not predicted by the intelligence of group members

“having a group of smart people is not enough, alone, to make a smart group” (Woolley, Aggarwal, & Malone, 2015, p. 421)

Bottom-up influences:

Slide76

GroupsSocial perceptiveness:

Reading the Mind in the Eyes Test

Ashamed Serious Alarmed Bewildered

Baron-Cohen, Wheelwright, Hill,

Raste

, & Plumb (2001, p. 242)

Slide77

GroupsSocial perceptiveness:

Reading the Mind in the Eyes Test

Ashamed

Serious

Alarmed Bewildered

Baron-Cohen, Wheelwright, Hill,

Raste

, & Plumb (2001, p. 242)

Slide78

GroupsSocial perceptiveness:

Reading the Mind in the Eyes Test

https://www.questionwritertracker.com/quiz/61/Z4MK3TKB.html

Slide79

GroupsCollective intelligence is an emergent property that is not predicted by the intelligence of group members

Group diversity in cognitive styles (e.g., context dependence/independence, rule-based/intuitive, internal/external;

Kozhevnikov

, Evans, &

Kosslyn

, 2014, p. 23) is also a predictor of collective intelligence (at moderate levels; Woolley et al., 2015)

Slide80

GroupsCollective intelligence is an emergent property that is not predicted by the intelligence of group members

Top-down influences (Woolley et al, 2015):

Have more communication

Divide participation across more group members

Slide81

GroupsHaving an effective group: Avoid social loafing

Slide82

GroupsSocial loafing occurs when group members do less than their individual level of performance

would predict (1 + 1 + 1 = 2)

How to improve (van Dick,

Tissington

, &

Hertel

, 2009)

Select group members to maximize group loyalty; artificially created groups don’t do well

Development matters “setting their own objectives, reaching consensus, regular well run focused meetings, benchmarking to other teams, etc.” (p. 241)

Slide83

GroupsHow to improve (van Dick,

Tissington

, &

Hertel

, 2009)

Openly compare performance across teams

Peg outcomes to benchmarks and not a single winner

Make teams interdependent

E.g., design tasks to require coordination

Have team symbols that are meaningful to members

Slide84

Human Factors Psychology:Implications

Aside on Affordances

Slide85

Example 1

http://

sunburn.stanford.edu

/~nick/

compdocs

/, click on Practical HI

Examples.pdf

Slide86

Example 2

http://

www.baddesigns.com

/

mopsnk.html

Slide87

Come on…

Slide88

What it makes me think

Slide89

Etc.

Slide90

Happy to share…

X

Slide91

Hogging the whole table…

X

Slide92

Etc.

Slide93

Etc.

Slide94

More Examples

http://

www.baddesigns.com

/

file.html

http://

www.baddesigns.com

/

sidewalk.html

Slide95

AffordancesWhat do all of these have in common? They all afford an action that isn't intended

Gibson (e.g., 1950) proposed a theory of direct perception. A caricature:

Light is structured into an ambient optic array. Each point in this array carries potential information

This information takes the form of affordances if a particular organism happens to be there to pick it up

Information pick-up is direct

Slide96

AffordancesPerceiving affordances:

If I

'

m looking for a place to sit, sit-on-

ableness

will be perceived by me in objects that have that property. If I need something to throw, that will be afforded

It

'

s kind of like an automatic process in that there

isn

'

t conscious mediation. The affordance is just there

(Tie to intuitionist thinking)

Slide97

AffordancesEvidence:

Warren (1984) had people look at various configurations of stairs to rate

climbability

There

'

s an optimal configuration for minimum energy expenditure, people preferred stairs that fit this configuration

People could accurately perceive

climbability

(based on a biomechanical model) from looking at the stairs

Slide98

AffordancesThe implication:

When people are interacting with a machine/device, what it affords will have a big impact on what they do

Our examples:

A pull handle affords pulling, not pushing

A urinal shaped device affords pee-in-

ableness

(or hand washing, depending on the user

'

s goals)

A drawer handle affords pulling

A path affords walking (even if it

'

s not explicit)

Slide99

AffordancesSignificant human factors implication:

In the context of controls, I think there are important relations between design and affordances

Things you push should look like things to push, etc. (clock radio)

There could be a high level interaction. If my goal is to turn it down, a control that affords pull-down-

ableness

is more likely to hit me than an arbitrary control

Remember that affordances are a function of the user

'

s body. If something is supposed to afford a particular action, it needs to be designed for all possible users

Slide100

Human Factors Psychology:Is Now over…

Slide101


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