Cognitive models
• They model aspects of user:
chapter 12
–
–
–
–
cognitive models
understanding
knowledge
intentions
processing
• Common categorisation:
– Competence Models vs. Performance Models
– Competence: What users ideally should do
– Performance: What users actually do
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Cognitive models
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1
1 Goal and task hierarchies (GOMS, CCT)
2 Linguistic notations (BNF, TAG)
Goal and task hierarchies
• Granularity
– Where do we start?
– Where do we stop?
3 Physical and device models (KLM)
• Routine learned behaviour, not problem
solving
-> Architectural models, foundation for 1-3
• Conflict
(Display-based interaction, not modelled)
• Error
– The unit task
– More than one way to achieve a goal
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Techniques
1.1 GOMS
• Goals, Operators, Methods and
Selection (GOMS)
Goals
• Cognitive Complexity Theory (CCT)
• Hierarchical Task Analysis (HTA) Chapter 15
– what the user wants to achieve
Operators
– basic actions user performs
Methods
– decomposition of a goal into subgoals/operators
Selection
– means of choosing between competing methods
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1
GOMS example
1.2 Cognitive Complexity Theory
GOAL: CLOSE-WINDOW
.
[select GOAL: USE-MENU-METHOD
.
MOVE-MOUSE-TO-FILE-MENU
.
PULL-DOWN-FILE-MENU
.
CLICK-OVER-CLOSE-OPTION
GOAL: USE-CTRL-W-METHOD
.
PRESS-CONTROL-W-KEYS]
• Two parallel descriptions:
– User production rules
– Device generalised transition networks
• Production rules are of the form:
– if condition then action
For a particular user:
Rule 1: Select USE-MENU-METHOD unless another
rule applies
Rule 2: If the application is GAME,
select CTRL-W-METHOD
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Example: editing with vi
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Example: editing with vi
Why many users like the vi-Editor:
• Vi is available on many platforms; very important for system
adminstrators because they often work on different systems
• You don't need X or mouse for high efficiency
• Vi is compact, fully developed, and runs on *any* Unix-system
• Vi supports syntax highlighting
• Vi is very well configurable
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Example: editing with vi
Example: Petri-net based modelling
• Production rules are in long-term memory
• Model working memory as attribute-value
mapping:
An example from the lecturer’s research
is offered on slides 34-44. The title of
the subject is:
(GOAL perform unit task)
(TEXT task is insert space)
(TEXT task is at 5 23)
(CURSOR 8 7)
Petri-net based modelling
• Rules are pattern-matched to working
memory,
e.g., LOOK-TEXT task is at %LINE %COLUMN
is true, with LINE = 5 COLUMN = 23.
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2
Notes on Cognitive Complexity Theory
•
•
•
•
•
Parallel model
Proceduralisation of actions
Novice versus expert style rules
Error behaviour can be represented
Measures
– depth of goal structure
– number of rules
– comparison with device description
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2
Linguistic notations
• Understanding the user's behaviour and
cognitive difficulty based on analysis of
language between user and system.
• Similar in emphasis to dialogue models
• Backus–Naur Form (BNF)
• [ Task–Action Grammar (TAG) ]
Pro and cons of Cognitive
Complexity Theory
Advantage:
• Due to parallelism, the production rules allow for modeling of
complex procedures.
• Therefore, synchronous procedures can also be described; for
instance, drink tea AND edit a text.
• Through a comparison of user- and system-states, a degree of
dissonance can be discovered, allowing to optimize the user
interface.
Problems
• Even smaller parts of a user interface give very complex CCTModels.
• Alternative ways to model the same user—system lead to
different degrees of dissonance.
• Some elements of the CCT syntax have no cognitive analogue,
but are used due to the shortcomings of the annotation itself.
http://collide.informatik.uni-duisburg.de/Lehre/DidaktikSeminar/BuA/page04.php
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2.1 Backus-Naur Form (BNF)
• Very common notation from computer science
• A purely syntactic view of the dialogue
• Terminals
–
–
lowest level of user behaviour
e.g. CLICK-MOUSE, MOVE-MOUSE
• Nonterminals
–
–
–
ordering of terminals
higher level of abstraction
e.g. select-menu, position-mouse
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Backus-Naur Form (BNF), example
Backus-Naur Form (BNF), example
Consider this BNF for a US postal address
<postal-address>
::=
<name-part> <street-address> <zip-part>
<postal-address>
::=
<name-part> <street-address> <zip-part>
<personal-part>
::=
<name> | <initial> ".“
<name-part> ::=
<personal-part> <last-name> [<jr-part>] <EOL> |
<personal-part> <name-part>
<street-address>
::=
[<apt>] <house-num> <street-name> <EOL>
<zip-part>
::=
<town-name> "," <state-code> <ZIP-code> <EOL>
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<personal-part>
::=
<name> | <initial> ".“
<name-part> ::=
<personal-part> <last-name> [<jr-part>] <EOL> |
<personal-part> <name-part>
...
This translates into English as
"A postal-address consists of a name-part, followed by a street-address
part, followed by a zip-code part. A personal-part consists of either a
first name or an initial followed by a dot. A name-part consists of
either: a personal-part followed by a last name followed by an
optional "jr-part" (Jr., Sr., or dynastic number) and end-of-line, or a
personal part followed by a name part (recursion in BNFs, covering
the case of people who use multiple first and middle names and/or
initials).
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3
Backus-Naur Form (BNF), example
Apropos: Backus-Naur Form (BNF)
examples comes from Foldoc
... continued:
<street-address>
::=
[<apt>] <house-num> <street-name> <EOL>
<zip-part>
::=
<town-name> "," <state-code> <ZIP-code> <EOL>
This translates into English as (continued)
“… A street address consists of an optional apartment
specifier, followed by a street number, followed by a
street name. A zip-part consists of a town-name,
followed by a comma, followed by a state code, followed
by a ZIP-code followed by an end-of-line."
http://wombat.doc.ic.ac.uk/foldoc/
3
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Physical and device models
• The Keystroke Level Model (KLM)
• Buxton's 3-state model
• Based on empirical knowledge of
human motor system
• User's task: acquisition then execution.
– these only address execution
• Complementary with goal hierarchies
FOLDOC is a searchable dictionary of acronyms, jargon,
programming languages, tools, architecture, operating systems,
networking, theory, conventions, standards, mathematics, telecoms,
electronics, institutions, companies, projects, products, history, in fact
anything to do with computing.
http://wombat.doc.ic.ac.uk/foldoc/
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3.1 Keystroke Level Model (KLM)
• six execution phase operators
– Physical motor:
K - keystroking
P - pointing (use Fitt’s Law)
H - homing
D - drawing
– Mental
M - mental preparation
– System
R - response
• times are empirically determined.
Texecute = TK + TP + TH + TD + TM + TR
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Fitt’s Law for ann Estimation
of Pointing Time
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Fitt’s Law, example 1:
http://ei.cs.vt.edu/~cs5724/g1/tap.html
T = a + b log2(D/S + 1)
D:
S:
a, b:
Distance to target
Size of target
Empirically estimated constants
Original form of Fitt‘s Law, 1954, without a constant:
Width 40, Height 37
time = 0.0
T = log2(2A/W)
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Width 29, Height 22
time = ?
Width 63, Height 92
time = ?
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4
Fitt’s Law, example 2:
www.tele-actor.net/fitts/
Keystroke Level Model (KLM)
Demo application intro page
Demo application program
1. Move hand to mouse H[mouse]
2. Position mouse after bad character PB[LEFT]
3. Return to keyboard H[keyboard]
4. Delete character MK[DELETE]
5. Type correction K[char]
6. Reposition insertion point H[mouse]MPB[LEFT]
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KLM example
3.2 Buxton's 3-state model
GOAL: ICONISE-WINDOW
[select
GOAL: USE-CLOSE-METHOD
.
MOVE-MOUSE-TO- FILE-MENU
.
PULL-DOWN-FILE-MENU
.
CLICK-OVER-CLOSE-OPTION
GOAL: USE-CTRL-W-METHOD
PRESS-CONTROL-W-KEY]
•
•
compare alternatives:
• USE-CTRL-W-METHOD vs.
• USE-CLOSE-METHOD
USE-CTRL-W-METHOD
USE-CLOSE-METHOD
H[to kbd]
0.40
P[to menu]
M
1.35
B[LEFT down] 0.1
K[ctrlW key]
0.28
M
1.35
P[to option]
1.1
assume hand starts on mouse
Total
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Buxton's 3-state model
2.03 s
1.1
B[LEFT up]
0.1
Total
3.75 s
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Architectural models,
basis for all (1-3)
• All of these cognitive models make
assumptions about the architecture of
the human mind.
• Long-term/Short-term memory
• Problem spaces
• Interacting Cognitive Subsystems
• Connectionist
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5
Example: Automating Inspection Methods - Analysis Support—Web UIs
Lecture on Monday 28th February, 13-15:
Moved to: VASA A.
Reason: MTS-Dagar
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http://www.ipo.tue.nl/homepages/mrauterb/amme/ACMCSivory%5B2001%5D.pdf
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