3. Formal models for design: details of conceptual modeling

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3. Formal models for design details of
conceptual modeling

• The modeling zoo of HCI (Streitz)
• Competence models
• Process models
• Dialogue models

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The modeling zoo of HCI (Streitz)

• In HCI there are many different approaches,
  depending on the goals of modeling, the use of
  the models, and the topic to be modeled.
• Why formal conceptual models?
• Conceptual models are for design decisions (team
  work)
• Conceptual models are for implementation
  (engineers)
• Evaluation models are for evaluation - answering
  design questions (design experts, client of
  design, and users)
• Formal models enable documentation
• This is valid for all models discussed here The
  design view (Moran)

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Competence models

• The Psychological view
• Models to understand the users view of the
  interaction. Used to analyze and specify
  knowledge the user needs in order to apply the
  system.
• Helps assessing the usability of the system
• GOMS
• CCT
• Action Language

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GOMS

• Card, Moran, Newell
• simulation of interaction
• simplification of cognitive processes
• prototype user
• goals
• operators
• methods
• selection rules

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GOMS, example

• Goals
• GOAL INVITE-KEYNOTE-SPEAKER
• GOAL IDENTIFY-RELEVANT-EXPERTS
• GOAL FIND-COORDINATES(expertname)
• GOAL COLLECT-INFO-SOURCES
• GOAL VERIFY-ADDRESS
• Operators
• GET-FROM-REFERENCE-LIST(expertname,
  list-of-keywords)
• WEBSEARCH(expertname, coordinates)
• GET-FROM-SOURCE-INFO(documentdate)
• Methods
• ONE-AT-THE-TIME-METHOD
• REDUCE-SOURCELIST
• CHECK-SOURCE-DATE
• Selection Rules
• LONG-LIST-REDUCTION
• UNFAMILIAR-INSTITUTE-VERIFICATION
• CONTINGENCY-CHOICE

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GOMS, example

• GOAL FIND-COORDINATES(expertname)
• METHOD
• ONE-AT-THE-TIME-METHOD
• GOAL COLLECT-INFO-SOURCES
• SELECTION-RULES
• LONG-LIST-REDUCTION
• if sourcelist length gt5 REDUCE-SOURCELIST
• UNFAMILIAR-INSTITUTE-VERIFICATION
• if institute unfamiliar add goal
  VERIFY-ADDRESS
• CONTINGENCY-CHOICE
• if number of experts found lt3 add goal
  FIND-COORDINATES(expertname)
• GOAL VERIFY-ADDRESS
• METHOD
• GET-FROM-SOURCE-INFO(documentdate)

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Cognitive complexity theory (CCT)

• Kieras Polson (based on GOMS)
• based on human information processing model
• production rules
• to be learned and stored in long term memory
  (LTM)
• to be used during interaction with the machine,
  through processes in working memory (WM)

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CCT

• Production rules in working memory
• if (condition) then (action)
• condition test input against content of WM
• action output content of WM to activity
• if more than one rule applies priority rule
  (e.g. highest one applies)
• complexity
• number of production rules in LTM index for
  learnability
• number of cycles in WM index for ease of use
• number of shared productions for 2 systems index
  of transfer

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CCTExample

• Check source info
• user wants to validate address info
• no telephone available, or address at other
  continent
• CCT model for novice in web use, and for expert

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CCT example novice user

• novice
• 1. if (and (goal validate source info)
• 2. (e-mail adress is on current web page))
• 3. then (and (add goal wait 3 days for email
  answer
• resume search if failure)
• 4. (send email for verification))

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CCT example expert user

• expert
• 1. if (and (goal validate source info)
• 2. (e-mail adress is on current web
  page))
• 3. then (if document date available in source
  info
• 4. (reject if date before 1-1-2002))
• 5. else (and (add goal wait 3 days for email
  answer
• 6. resume search if failure)
• 7. (send email for
  verification))

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Action Language

• Reisner Psychological BNF
• analysis focuses on user behavior and
  communication
• attention on human knowledge and knowledge sources

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Action Language, example

• Get web document date USE MUSCLE MEMORY
  
  (ltretrieve syntax infogt ltinspect dategt)
• ltretrieve syntax infogt ltretrieve from human
  memorygt ltretrieve
  from external sourcegt
• ltretrieve from human memorygt RETRIEVE FROM
  LTM
• RETRIEVE FROM WM
• ltretrieve from external sourcegt RETRIEVE FROM
  BOOK
• ASK SOMEONE EXPERIMENT
• USE ON-LINE HELP
• ltinspect dategt ltopen document source
  windowgt
• SCAN WINDOW FOR DATE
• ltdelete windowgt
• ltopen document source windowgt PRESS RIGHT
  MOUSE BUTTON
• POINTER TO DOCUMENT INFO
• RELEASE MOUSE BUTTON
• ltdelete windowgt ..

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Process models

• The linguistic view
• Process models aim at understanding the
  interactive process between human and machine,
  over time. These models focus explicitly /
  additionally / on the dialogue.
• Models may provide estimate of interaction time,
  and estimate of complexity of user behavior in
  interaction with the interface
• TAG
• Key-stroke model

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Task Action Grammar (TAG)

• Payne and Green
• focus on learnability and ease of use
• complexity (number of feature instances to be
  learned) learnability
• consistency (of rules to be applied) task effort
  / ease of use
• TAG is a feature grammar
• TAG does not consider the screen,
  nor the meaning of the
  features

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Task Action Grammar, example

• List of commands
• move cursor one character forward ctrl-C
• move cursor one character backward meta-C
• move cursor one word forward ctrl-W
• move cursor one word backward meta-W
• List of features possible values
• direction forward, backward
• unit character, word
• dictionary of simple tasks
• move cursor one character forward directionforw
  ard, unitchar
• move cursor one character backward directionbac
  kward, unitchar
• move cursor one word forward directionforward,
  unitword
• move cursor word backward directionbackward,
  unitword
• rule schemas
• task direction, unit ? symbol direction
  letter unit
• symbol direction forward ? ctrl
• symbol direction backward ? meta
• letter unit word ? W
• letter unit character ? C

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Key-stroke model

• Card, Moran, Newell
• model of sequential user actions and system
  actions
• estimates of times of actions based on empirical
  measurements
• estimate of mental actions are very global and
  fixed
• system reaction times are parameter of model
• predictions are accurate for errorless behavior,
  at low level of interaction only

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Key-stroke level model

• Operator description time (sec)
• K press key or button (shift or control key
  count separately)
• best typist (135 wpm) .08
• good typist (90 wpm) .12
• average non-secretary typist (40 wpm) .28
• typing complex codes .75
• P point with mouse to target on display (Fittss
  Law) 1.10
• H home hand on keyboard or device .40
• D(n,l) draw n straight-line segments of total
  length l cm
• (calculated for a square .56 cm grid) .9n
  .16l
• M mentally prepare 1.35
• R(t) system response t

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Key-stroke level model, example

• Line editor Poet
• go to next line MKLINEFEED
• type substitute command MKS
• type new word 5Kword
• end new word MKRETURN
• type word to be replaced 5Kword
• end word to be replaced MKRETURN
• end command KRETURN
• t(execute) 4 t(M) 15 t(K) 8.4 sec

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Key-stroke level model, example

• Direct manipulation editor Bravo
• take mouse Hmouse
• point word to be replaced Pword
• select word Kyellow
• hand to keyboard Hkeyboard
• type replace command MKR
• type new word 5Kword
• end new word MKESC
• t(execute) 2 t(M) 8 t(K) 2 t(H) t(P)
  6.2 sec

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Dialogue models

• Goal is to provide implementers with a complete
  specification of all that is relevant from the
  users point of view.
• Model the dialogue between human user and
  machine
• competence (what should the user know)
• process (what is the dynamic structure of the
  dialogue)
• Enables analysis of usability, learnability, and
  completeness of the detail specifications.

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New User Action Notation (NUAN)

• Based on Hix Hartson (1993) UAN
• all overt user actions
• interface feedback
• interface state info
• connection to computation
• Extended based on needs for specification in
  design practice

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NUAN considers mental actions

• RECALL (x from y)
• RETAIN (x in y)
• FORGET (x)
• FIND (x in y)
• CHOOSE (x from y)
• etc,
• where
• y can be different parts of human memory, or
  located outside the users mind

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NUAN is a feature grammar

• POINTERTO(ltanybuttongt) MOVEPOINTER(ltanybuttongt
  
• where ltanybuttongt ltyesbuttongtltnobuttongtlt..

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NUAN

• has a slot for prior states conditions
• replaces interface feedback by interface actions
• is clear on user understood simultaneous vs
  consecutive events
• allows audio-visual representation of user
  actions, interface actions and interface state

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Interaction New Email Interaction New Email Interaction New Email Interaction New Email
About About Interface Pre-state Interface Pre-state
This interaction describes the arrival of a new email, in case all previous mails have been read. If another message arrives during this dialogue, the dialogue would re-start immediately after the current one is finished. This interaction describes the arrival of a new email, in case all previous mails have been read. If another message arrives during this dialogue, the dialogue would re-start immediately after the current one is finished. 1. Email running as a background process though not represented at the interface. 2. All previous emails have been read (unread_mail false until the new arrival). 1. Email running as a background process though not represented at the interface. 2. All previous emails have been read (unread_mail false until the new arrival).
User Actions Interface Actions Interface State Connection to Computation
! MESSAGE("New email has arrived") unread_mail gt true
! ASK("Read now",Yes,No) Previous dialogue postponed, not aborted
CHOOSE(task to continue, from the set of previous tasks plus new_email task)
POINTERTO(ltyesbuttongt) CLICK(ltyesbuttongt) -gt InteractionRead Email POINTERTO(ltnobuttongt CLICK(ltnobuttongt) MOVEPOINTER(ltyesbuttongt)SHOW_EMAIL(latest) MOVEPOINTER(ltnobuttongt) unread_mail gt false unread_mail gt true
HIDE_MESSAGE() Previous dialogue enabled to continue