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chapter 12

cognitive models
Cognitive models
• goal and task hierarchies
• linguistic
• physical and device
• architectural
Cognitive models
• They model aspects of user:
–
–
–
–

understanding
knowledge
intentions
processing

• Common categorisation:
– Competence vs. Performance
– Computational flavour
– No clear divide
Goal and task hierarchies
• Mental processing as divide-and-conquer
• Example: sales report
produce report
gather data
. find book names
. . do keywords search of names database
. . . … further sub-goals
. . sift through names and abstracts by hand
. . . … further sub-goals
. search sales database - further sub-goals
layout tables and histograms - further sub-goals
write description - further sub-goals
goals vs. tasks
• goals – intentions
what you would like to be true

• tasks – actions
how to achieve it

• GOMS

– goals are internal

• HTA

– actions external
– tasks are abstractions
Issues for goal hierarchies
• Granularity
– Where do we start?
– Where do we stop?

• Routine learned behaviour, not problem
solving
– The unit task

• Conflict
– More than one way to achieve a goal

• Error
Techniques
• Goals, Operators, Methods and
Selection (GOMS)
• Cognitive Complexity Theory (CCT)
• Hierarchical Task Analysis (HTA) Chapter 15
GOMS
Goals
– 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
GOMS example
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]
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
Cognitive Complexity Theory
• Two parallel descriptions:
– User production rules
– Device generalised transition networks

• Production rules are of the form:
– if condition then action

• Transition networks covered under
dialogue models
Example: editing with vi
• Production rules are in long-term memory
• Model working memory as attribute-value
mapping:
(GOAL perform unit task)
(TEXT task is insert space)
(TEXT task is at 5 23)
(CURSOR 8 7)

• Rules are pattern-matched to working
memory,
e.g., LOOK-TEXT task is at %LINE %COLUMN
is true, with LINE = 5 COLUMN = 23.
Four rules to model inserting
a space
Active rules:
SELECT-INSERT-SPACE
INSERT-SPACE-MOVE-FIRST
INSERT-SPACE-DOIT
INSERT-SPACE-DONE

New working memory
(GOAL insert space)
(NOTE executing insert space)
(LINE 5) (COLUMN 23)
SELECT-INSERT-SPACE
matches current working memory

(SELECT-INSERT-SPACE
IF (AND (TEST-GOAL perform unit task)
(TEST-TEXT task is insert space)
(NOT (TEST-GOAL insert space))
(NOT (TEST-NOTE executing insert space)))
THEN ( (ADD-GOAL insert space)
(ADD-NOTE executing insert space)
(LOOK-TEXT task is at %LINE %COLUMN)))
Notes on CCT
•
•
•
•
•

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
Problems with goal hierarchies
• a post hoc technique
• expert versus novice
• How cognitive are they?
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)
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
Example of BNF
• Basic syntax:
– nonterminal ::= expression

• An expression
– contains terminals and nonterminals
– combined in sequence (+) or as alternatives (|)
draw line
::= select line + choose points + last point
select line
::= pos mouse + CLICK MOUSE
choose points ::= choose one | choose one + choose points
choose one ::= pos mouse + CLICK MOUSE
last point
::= pos mouse + DBL CLICK MOUSE
pos mouse ::= NULL | MOVE MOUSE+ pos mouse
Measurements with BNF
• Number of rules (not so good)
• Number of + and | operators
• Complications
– same syntax for different semantics
– no reflection of user's perception
– minimal consistency checking
Task Action Grammar (TAG)
• Making consistency more explicit
• Encoding user's world knowledge
• Parameterised grammar rules
• Nonterminals are modified to include
additional semantic features
Consistency in TAG
• In BNF, three UNIX commands would be described as:
copy ::= cp + filename + filename | cp + filenames + directory
move ::= mv + filename + filename | mv + filenames + directory
link
::= ln + filename + filename | ln + filenames + directory

• No BNF measure could distinguish between this and a
less consistent grammar in which
link ::= ln + filename + filename | ln + directory + filenames
Consistency in TAG (cont'd)
• consistency of argument order made explicit
using a parameter, or semantic feature for file
operations
• Feature Possible values
Op = copy; move; link

• Rules
file-op[Op] ::=

command[Op] + filename + filename
| command[Op] + filenames + directory
command[Op = copy] ::= cp
command[Op = move] ::= mv
command[Op = link] ::= ln
Other uses of TAG
• User’s existing knowledge
• Congruence between features and
commands
• These are modelled as derived rules
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
Keystroke Level Model (KLM)
• lowest level of (original) GOMS
• six execution phase operators
– Physical motor:

K - keystroking
P - pointing
H - homing
D - drawing

– Mental

M - mental preparation

– System

R - response

• times are empirically determined.
Texecute = TK + TP + TH + TD + TM + TR
KLM example
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

B[LEFT up]

0.1

Total

3.75 s

assume hand starts on mouse
Total

2.03 s

1.1
Architectural models
• 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
• ACT
Display-based interaction
• Most cognitive models do not deal with
user observation and perception
• Some techniques have been extended
to handle system output
(e.g., BNF with sensing terminals, Display-TAG)

but problems persist

• Exploratory interaction versus planning

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E3 chap-12

  • 2. Cognitive models • goal and task hierarchies • linguistic • physical and device • architectural
  • 3. Cognitive models • They model aspects of user: – – – – understanding knowledge intentions processing • Common categorisation: – Competence vs. Performance – Computational flavour – No clear divide
  • 4. Goal and task hierarchies • Mental processing as divide-and-conquer • Example: sales report produce report gather data . find book names . . do keywords search of names database . . . … further sub-goals . . sift through names and abstracts by hand . . . … further sub-goals . search sales database - further sub-goals layout tables and histograms - further sub-goals write description - further sub-goals
  • 5. goals vs. tasks • goals – intentions what you would like to be true • tasks – actions how to achieve it • GOMS – goals are internal • HTA – actions external – tasks are abstractions
  • 6. Issues for goal hierarchies • Granularity – Where do we start? – Where do we stop? • Routine learned behaviour, not problem solving – The unit task • Conflict – More than one way to achieve a goal • Error
  • 7. Techniques • Goals, Operators, Methods and Selection (GOMS) • Cognitive Complexity Theory (CCT) • Hierarchical Task Analysis (HTA) Chapter 15
  • 8. GOMS Goals – 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
  • 9. GOMS example 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] 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
  • 10. Cognitive Complexity Theory • Two parallel descriptions: – User production rules – Device generalised transition networks • Production rules are of the form: – if condition then action • Transition networks covered under dialogue models
  • 11. Example: editing with vi • Production rules are in long-term memory • Model working memory as attribute-value mapping: (GOAL perform unit task) (TEXT task is insert space) (TEXT task is at 5 23) (CURSOR 8 7) • Rules are pattern-matched to working memory, e.g., LOOK-TEXT task is at %LINE %COLUMN is true, with LINE = 5 COLUMN = 23.
  • 12. Four rules to model inserting a space Active rules: SELECT-INSERT-SPACE INSERT-SPACE-MOVE-FIRST INSERT-SPACE-DOIT INSERT-SPACE-DONE New working memory (GOAL insert space) (NOTE executing insert space) (LINE 5) (COLUMN 23) SELECT-INSERT-SPACE matches current working memory (SELECT-INSERT-SPACE IF (AND (TEST-GOAL perform unit task) (TEST-TEXT task is insert space) (NOT (TEST-GOAL insert space)) (NOT (TEST-NOTE executing insert space))) THEN ( (ADD-GOAL insert space) (ADD-NOTE executing insert space) (LOOK-TEXT task is at %LINE %COLUMN)))
  • 13. Notes on CCT • • • • • 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
  • 14. Problems with goal hierarchies • a post hoc technique • expert versus novice • How cognitive are they?
  • 15. 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)
  • 16. 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
  • 17. Example of BNF • Basic syntax: – nonterminal ::= expression • An expression – contains terminals and nonterminals – combined in sequence (+) or as alternatives (|) draw line ::= select line + choose points + last point select line ::= pos mouse + CLICK MOUSE choose points ::= choose one | choose one + choose points choose one ::= pos mouse + CLICK MOUSE last point ::= pos mouse + DBL CLICK MOUSE pos mouse ::= NULL | MOVE MOUSE+ pos mouse
  • 18. Measurements with BNF • Number of rules (not so good) • Number of + and | operators • Complications – same syntax for different semantics – no reflection of user's perception – minimal consistency checking
  • 19. Task Action Grammar (TAG) • Making consistency more explicit • Encoding user's world knowledge • Parameterised grammar rules • Nonterminals are modified to include additional semantic features
  • 20. Consistency in TAG • In BNF, three UNIX commands would be described as: copy ::= cp + filename + filename | cp + filenames + directory move ::= mv + filename + filename | mv + filenames + directory link ::= ln + filename + filename | ln + filenames + directory • No BNF measure could distinguish between this and a less consistent grammar in which link ::= ln + filename + filename | ln + directory + filenames
  • 21. Consistency in TAG (cont'd) • consistency of argument order made explicit using a parameter, or semantic feature for file operations • Feature Possible values Op = copy; move; link • Rules file-op[Op] ::= command[Op] + filename + filename | command[Op] + filenames + directory command[Op = copy] ::= cp command[Op = move] ::= mv command[Op = link] ::= ln
  • 22. Other uses of TAG • User’s existing knowledge • Congruence between features and commands • These are modelled as derived rules
  • 23. 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
  • 24. Keystroke Level Model (KLM) • lowest level of (original) GOMS • six execution phase operators – Physical motor: K - keystroking P - pointing H - homing D - drawing – Mental M - mental preparation – System R - response • times are empirically determined. Texecute = TK + TP + TH + TD + TM + TR
  • 25. KLM example 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 B[LEFT up] 0.1 Total 3.75 s assume hand starts on mouse Total 2.03 s 1.1
  • 26. Architectural models • 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 • ACT
  • 27. Display-based interaction • Most cognitive models do not deal with user observation and perception • Some techniques have been extended to handle system output (e.g., BNF with sensing terminals, Display-TAG) but problems persist • Exploratory interaction versus planning