Understanding and modeling human capabilities

1
Understanding and modeling human capabilities
2
Agenda

• Questions
• Overview of Modeling
• Humans as information processors
• DFAB sensory discussion
• CMN perceptual / motor / cognitive
• Fitts Law for modeling movement

3
Basic human capabilities

• Humans evolve much more slowly than technology
• There are limits to human capabilities

4
What is a model?

• Abstracted
• Often simplified
• Representation of real world concept (eg. People,
  objects, processes)
• Idea If we can build a model of how a user
  works, then we can predict how s/he will interact
  with the interface
• Predictive model ? predictive evaluation

5
Overview of Modeling

• What are the questions
• How to gather information
• How to model that information

6
What can we model

• Sensory / Motor processes
• Cognitive processes
• Tasks
• Contexts

7
Two types of user modeling

• Stimulus-Response
• Hicks law
• Fitts law
• Cognitive human as interperter/predictor
  based on Model Human Processor (MHP)
• Key-stroke Level Model
• Low-level, simple
• GOMS (and similar) Models
• Higher-level (Goals, Operations, Methods,
  Selections

8
Humans as I/O machines

• Senses
• vision
• hearing
• touch
• smell/taste
• Feed sensory memory, then processing
• What are the design implications?

9
Design implications

• Vision
• e.g., acuity and color, optical illusions
• Hearing
• e.g., frequency response, filtering
• Touch/motor movement
• e.g. tactile sensitivity, movement time

10
Memory

• 3 kinds
• distinguished by
• main code type
• storage capacity
• decay time of an item

11
Sensory/Perceptual memory an experiment
12
Sensory / Perceptual Memory

• physically encoded
• impacted by physical characteristics of signal
• low capacity
• rapid decay (msec)

13
Working/Short-term memory an experiment

• C R T I B M C B S N H L

14
Was was that?
15
Working/Short-term memory

• How about now?
• CRT IBM CBS NHL

16
Short-Term or Working Memory

• symbolic, nonphysical acoustic or visual coding
• 7 plus/minus 2 chunks
• decay 5-226 sec

17
What is a chunk

• a meaningful grouping of information
• 4 7 9 3 6 1 9 0 4 9
• vs
• 404 894 7243
• User and task dependent

18
Another experiment in working memory

• Two volunteers

19
9 words that begin with d

• Doughnut
• Deer
• Dog
• Dagger
• Door
• Dart
• Dress
• Dancing
• Duck

20
9 words that begin with f
21
Long term memory

• semantic information
• episodic information
• capacity (limitless?)
• no decay?
• Catch Retrieval depends on associations

22
Principles for retrieval

• How information is perceived, understood and
  encoded determines likelihood of retrieval

23
Variation in humans

• Human capabilities and limitations can be
  generalized only to an extent
• Variation between people (eg. age, gender,
  intelligence, physical capability)
• Variation within people (stress, fatigue)

24
Hicks Law

• Decision time to choose among n equally likely
  alternatives
• T Ic log2(n1)
• Ic 150 msec
• What might this be good for?

25
One possible use

• Menu selection
• Which will be faster as way to choose from 64
  choices? Go figure
• Single menu of 64 items
• Two-level menu of 8 choices at each level
• Two-level menu of 4 and then 16 choices
• Two-level menu of 16 and then 4 choices
• Three-level menu of 4 choices at each level
• Binary menu with 6 levels

26
Fitts Law

• Models movement times for selection (reaching)
  tasks in one dimension
• Basic idea Movement time (MT) is proportional to
  Index of difficulty (ID) of a selection task
• MT Increases as distance to target increases
• MT Decreases as size of target increases

27
Original Experiment
d
w

• 1-D

28
Index of difficulty (ID)

• Measure difficulty of selection task
• ID log2(2d/w)
• bits
• d distance between targets
• w target width

29
Movement time (MT)
MT

• MT a b ID

Difficulty
30
How MT is determined

• Empirical measurement establishes constants a and
  b
• Different for different devices and different
  ways the same device is used.

31
Applications

• When does it apply? When does it not?
• How used in interface design?

32
Extending to 2D

• What is w?

33
Possible ws for 2D

• smaller-of
• W (width of target along the approach vector)

34
Project time?
35
Upcoming

• Cognitive models
• CMN chapter (online), DFAB 12.2, 12.5 (skip 12.3,
  12.4)
• Part 1 due 6/02