Human Factors

1
Human Factors Problem Solving

• Cognitive Psychology
• 4
• Computer Scientists
• interactive seminar
• Lenko Grigorov
• School of Computing, Queen's University

2
Outline

• Meaning of truth
• Human factors
• Perception
• Memory
• Attention
• Problem solving
• States, operations, searching
• Intuition
• Conclusions

3
Meaning of truth

• WARNING
• Natural sciences are different from Math
• Theory ? Predictions ? Validation
• One can only disprove a theorem
• Scientists must live with uncertainty
• Mathematics is based on axioms
• Is it valid?

4
Human Factors

• Products of research are going to be used by real
  people.
• Articles can they be understood?
• Software is it functional and usable?
• HCI science about the interactions between
  software systems and people
• Information Visualization science about
  representing information in a useful form
• Cognitive Psychology science about human thinking

5
Why study thinking?

• Why is it important to understand human thinking?
• Artificial Intelligence
• Know what people expect
• Computer aid
• Most of software falls in this category
• Human and computer co-operate on task
• Know where human needs assistance
• Rule of thumb
• Where people excel, computers have trouble
• ...and vice versa (Dr. Brian Butler, PSYC, QU)

6
Shortest path?
7
Shortest path.

• Algorithmic solution 14! 87 178 291 200
  options
• Human solution 2 sec.

8
Human Cognitive Machine
Attention
Perception
9
Perception

• Humans acquire information from computers mostly
  through the visual channel
• Visual perception is a very complex process
• Involves not only physical sensations
• Brain processes sensations
• Many possible points of failure
• Individuals with impaired perceptual processes

10
Physical acuity

• One cannot expect acute perception of everything
  on the screen
• However, good sensitivity to change in the
  peripheral vision
• Attention is attracted

11
Perceptual assembly

• What where pathways
• Feature extraction and integration (Treisman)

shape
color
school bus
attention
location
12
Subitizing
13
Subitizing
14
Subitizing
15
Subitizing

• Immediate perception (knowing the exact count) of
  up to 4 5 items
• Linear increase in the time for perception of
  more items
• Need to employ counting

16
Pop-out

• Immediate perception of irregularities
• Doesn't work when irregularities involve more
  than one feature!

17
Gestalt dog

• The whole is more than the sum of its parts.

18
Gestalt principles
Proximity
Continuity
Similarity
19
Ideas
?

• How does all this apply to your work?

20
Memory

• Working memory
• Perceptual modalities
• Auditory, visual...
• Control unit
• Management
• Long-term memory
• Declarative
• Definitions, instructions...
• Procedural
• How to do things
• Can't explain, just perform

21
Working vs. Long-term memory

• Working memory
• Very fast
• Limited
• 4-5 items
• Items can be chunked and/or encoded
• 613 is one item local area code

• Long-term memory
• Slow
• Both to encode and retrieve information
• Unlimited (in practice)
• Can't be used directly

22
Expert memory

• How do people cope with a complex world with so
  little memory?
• Experts have long-term working memory...
• Fast and unlimited
• Information arranged in associative structures
  which improve access and storage
• Needs a lot of practice
• An average student became expert on remembering
  digit sequences
• After 1 year of regular training could remember
  over 80 digits after hearing them once

23
Ideas
?

• How does all this apply to your work?

24
Design for experts, but beware of the learning
curve!
Expertise
Time of experience
25
Integration of memory stores?

• How do working memory and long-term memory work
  together?
• Learning (WM?LTM)
• See that the Turn off computer option is in the
  Start menu ?
• Always click on the Start menu to turn off your
  computer
• Retrieval (LTM?WM)
• Notice that the terminal window appears frozen no
  matter what you press on the keyboard ?
• Remember to try Ctrl-Q before rebooting

26
Emergence of cognition?

• How do perception and memories work together?
• Bottom-up processing
• Crossing the street, see a car coming, run!
• Top-down processing
• About to cross the street, watch for oncoming
  cars!
• ...These processes must be integrated

27
Attention

• Theories
• Attention is necessary to glue sensations into a
  coherent perception
• There is a single memory store (aka long-term
  memory) and working memory is the section of that
  store to which we pay attention
• Attention is the arbitrator between competing
  responses
• Human capacity for attention is limited
• ? Attention is a cognitive bottle-neck

28
Attention as selector (1)

• Say the colors in which these words are written,
  fast

GREEN YELLOW BLUE
29
Attention as selector (2)

• Say the colors in which these words are written,
  fast

GREEN YELLOW BLUE
30
Ideas
?

• How does all this apply to your work?

31
Types of problems

• Insight problems
• How to operate a new coffee machine?
• How to solve a crossword puzzle?
• Problems with gradual advancement
• How to solve a quadratic equation?
• How to get from Napanee,ON to Honolulu,HI?
• can be viewed as a succession of small insights

32
Insight

• Steps
• Preparation
• Impasse
• Incubation
• Illumination
• Verification
• Do not shy away from using your intuition!
• Brainstorming is a very helpful tool.

33
Gradual advancement?

• How many of the problems you solve daily are of
  the sort
• y x2 3 x 15.6
• Do you know in advance what you want to get?
• Looking for a room to rent
• Cheap
• Clean
• Close to campus
• ...ended up in an expensive room at a rundown
  shack, but with awesome housemates?

34
Optimal solution?

• Einstellung mechanization of thought
• In order to call the elevator to go down from the
  6th floor, you press the down button even
  though the elevator will go to the 7th floor
  first
• If you press the up button, the elevator will
  stop on the 6th floor first and, once inside, you
  can tell it to go down
• Repeated use of a procedure leaves humans blind
  for better solutions

35
Logic?

• Each card has a letter on one side and a number
  on the other.
• Which cards have to be flipped to verify the
  rule
• If there is a vowel on one side, there is an even
  number on the other.
• 79 E or E,4... 4 E,7

E
K
7
4
36
Do you agree?

• Wars are prosperous.
• Prosperity is desirable.
• Thus, wars are desirable.
• All procrastinators do their work slowly.
• All graduate students do their work slowly.
• Thus, all graduate students are procrastinators.

37
Ideas
?

• How does all this apply to your work?

38
Effect of background knowledge

• What we know and what we expect greatly
  influences our problem-solving activity.
• Problem solving through analogy
• Models of interaction
• Priming
• Influence of conditions on memory
• Environments
• Bodily predispositions
• Subjectivity of cues
• Our won cues don't work for someone else

39
Is the human mind a computer?

• Simon and Newell
• Yes.
• Complexity of the system is just a reflection of
  its environment.
• Humans use simple rules
• Akl
• ...it's an online computer!
• The Turing Machine won't cut it

40
How do we solve problems?

• State space
• Each possible configuration of the variables in a
  problem defines a state. The space of all states
  may be enormous (or even infinite)
• Operations
• A transformations of the variables leading from
  one state to another
• Physical actions, induction steps, etc
• Tree exploration
• Initial state and goal state(s)
• Find a sequence of operations which will
  transform the initial state to one of the goals

41
Tree exploration (tic-tac-toe)
Initial state
...
...
...
Goal state
42
Heuristics

• Rules used to explore the tree.
• Brute-force
• Random
• Means-end analysis
• Must be able to evaluate the difference between
  any state and the goal
• At each step, choose the operation that reduces
  the difference most
• ...analogous to hill climbing, but back-tracking
  is applied when stuck
• If the person can recognize they are stuck!

43
Satisficing

• When does problem solving end?
• We find a solution. OR
• We cant find a solution within the portion of
  the state space we can explore.
• However
• Is the solution we find the real/most optimal
  solution? Are we able to recognize the solution?
• How do we cope with so much uncertainty?
• Use satisficing
• Proclaim a discovered solution is good enough
• Thats what we do every day with (almost) all
  problems

44
Does it matter what representation we use?

• Representation Data Operations
• Verbal 1D access, Image 2D access
• There is no good and bad representation
• There is suitable and unsuitable

45
Verification Bias

• How do we check for the validity of a solution?
• Given a hypothesis A ? B and having A
• Humans tend to generate examples of B and check
  if they are valid
• Little effort is put into generating examples of
  ?B and checking if they are valid
• Debugging GUIs
• Click on all menus as intended, no crash, ?!
• What about clicking on the menus in the wrong
  order?

46
Ideas
?

• How does all this apply to your work?

47
What about insight problems?

• Theories for why incubation helps
• Johnson-Laird selecting which constraints on the
  solution to remove
• Simon looking for the correct problem
  representation
• Others
• Alleviation of Einstellung
• Recovering from fatigue
• Gaining new experiences
• Unconscious work on the problem

48
Conclusions

• Remember
• The designer knows their product
• The user has no experience
• Human users
• Have a limited capacity for attention
• Take shortcuts whenever possible
• Make errors
• If an error is possible, someone will make it for
  sure!
• Most importantly Validate your design decisions
  by testing with real users!