Cognitive modelling, Users models and Mental models

1
Cognitive modelling, Users models and Mental
models

• Whats cognitive modelling ?
• The human information processing approach
• Cognitive Models of Users in HCI
• Knowledge, representations and Mental Models
• Conceptual models

2
Whats cognitive modelling ?

• Cognitive modelling is a discipline based on
• Experimental cognitive psychology and
• Artificial intelligence and linguistics methods
• In HCI the main objective has been to understand
  and represent how humans interact with computers
• Knowledge about this processes depend strongly on
  the particular model of cognition chosen
• 56 Information processing system
• 90Distributed Cognition (Hutchins, E.)
• 90 Situated action (Suchman, L.)
• 90Activity theory (Kaptelinin, V. Engeström, Y.
  )

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Information processing approach

• During 1960 and 1970 the main paradigm in
  cognitive psychology was to characterise humans
  as information processors
• Information enters and exists the human mind
  through a series of ordered processing stages
• Information is unidirectional and sequential and
  each stage takes a certain amount of time
• Information processing model has been highly
  influencial in shaping the development of
  cognitive models of the user in HCI

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Information Processing Psychology ingredients

• Model from the computer
• In contrast to previous cognitive models that
  were often statistical
• A modelling language - production rules
• In contrast to verbal descriptions
• A qualitative method to derive information
  processes
• In contrast to quantitative methods

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Model from the computer

• But people are not computers, we have to use
  reverse engineering to understand the mechanisms
  by which they proceed
• Define problem
• Identify process
• Derive specific strategy from process
• Derive general cognitive architecture from
  several studies

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Modelling language

• If-then rules. The current state is matchted
  towards the system of rules. The first rule that
  matches the current state is fired
• Then a new state results, that is matched
• What does this remind us of?

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A qualitative method to derive information
processes

• The think-aloud protocol was used to elicit data
  on sequential problem solving
• Hypotheses people expressed (parts of) that what
  existed in their working memory
• i.e. part of the current knowledge state

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Defining problem and problem space

• A problem exists when you have a goal and an
  initial state. The initial state does not
  correspond to the goal and you do not know how to
  get from the initial state to the goal
• A problem space consists of the hypothetical
  states that a problem solver goes through in its
  processing/transformation of the initial state to
  the goal state.
• Ex. Problem space intitial state operations
  required to reach goal state

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Example of problem- Tower of Hanoi
You have three disks on a peg (A) as in the
figure. These should be moved to the right peg
(C). You are only allowed to move one disk at a
time. You can only place a smaller disk on top of
a bigger one.
A B C
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Think aloud protocol example Tower of Hanoi
First I put the smallest one here (on C) Then I
put the next smallest here (on B) Then I take the
biggest one - O no, that is not allowed, OK I
move the smallest back to A And the next smallest
to C Then I take the smallest to B And the next
smallest to - where should it go...
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Production rules that produce the think aloud
protocol
IF goal achieved THEN end If disc1 free THEN
move disc1 If move disc1 THEN check if C is
possible IF C possible THEN move disc1 to C IF C
is not possible THEN move disc1 to A If disc2
free THEN move disc2 If move disc2 THEN check if
B is possible If B empty, THEN move disc2 to
B IF disc3 free THEN move disc3 IF move disc 3
THEN check if C is possible
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But rules are not sufficient

• We need a system to interpret the rules!
• What can the system perceive?
• How should the objects be represented?
• In what order are the productions tested?
• How will the actions performed be remembered?

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A cognitive architecture

• Defines how rules are interpreted
• In what order they are taken
• What conditions prevail for how the rules may be
  written. For instance how many conditions and
  actions are possible for one rule
• How the results of actions are stored

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A cognitive architecture for Human Information
Processing

• Must comply with knowledge about human beings
• Knowledge from various sources
• Senso-motoric
• Attention
• Perception
• Memory
• Metacognition

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Information processing applied to HCI

• Quasi-empirical approach
• GOMS
• Analyses a task from an experts actions
• Goals, Operations, Methods and Selection rules
• Further applications of GOMS
• Cognitive walkthrough - what will a user find
  difficult in the system?
• Goals, operations, methods analysed with respect
  to the designers knowledge about the user

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Further applications of GOMS

• Keystroke level calculations How long will it
  take to perform a task with the system?
• Has been used to compare different system
  solutions, for instance for telephone operators
  asking callers questions
• A small change in the time taken may mean much
  when many small tasks are performed by many
  persons

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Key-stroke level of GOMS

• Task Copy a word and position it at some place
  at the text
• Method Get the operations from the menu
• 1. Time to identify the word
• 2. Time to mark the word
• 3. Time to move to the menu and find the word
  copy
• 4. Time to click on copy
• 5. Time to go to the position in the text were
  the word should be placed
• 6. Time to click in order to move the cursor to
  this place
• 7. Time to move to the menu and get the command
  paste.
• 8. Time to click for placing the word.
• 9. Time for checking that the result is OK
• The time for the hand movements is calculated
  according to Fitts law

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Cognitive Models of users in HCI

• Focus on the interface and interest in
  measurements (errors, time) predictions of user
  performance, how easy an interface will be to
  learn, without instruction, or without manual.
• Usability is a measure of the ease of use once
  learning is in some sense complete
• Tasks
• Slips or accidental mistakes
• Hierarchical representation of the users task
  and goal structure
• GOMS Goals, operations, methods and selection
  rules (Card, Moran and Newell, 1983)
• Linguistic and grammatical models
• Physical and device-level models

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Knowledge

• How is knowledge organised in the users mind?
• How is knowledge represented in memory ?
• Analogical representations images
• Schema and scripts
• Propositional representations language
• Mental models
• Distributed representations nodes and links-
• Semantic networks

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Representations

• The ability to represent perceptions,
  experiences in some medium other than that in
  which they have occurred
• People construct representations that facilitate
  their interaction with events and absent in
  space and time
• Representations
• Capture the important, critical features of the
  represented world while ignoring the irrelevant,
• Are appropriate for the person,
• Are appropriated for the task, enhancing the
  ability to discover relevant regularities and
  structures.

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Mental Models (MM)

• The model people have of themselves, others, the
  environment, and the things which they interact.
  People form mental models through experience,
  training and instruction (Norman, 1988 p.17).
• MM are either analogical representations or a
  combination of analogical and propositional
  representations. They are distinct but related to
  images (Johnson-Laird, 1983,1988).
• MM are used to make inferences or a prediction
• Images are one-off representation

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Mental Models (cont)

• Two main types of MM identified when interacting
  with computers
• Structural how does it works ?
• components and parts of a device
• Context-free
• Functional or task-action mapping model how
  to use it ?
• connections between tasks and actions
• context dependent
• Utility of MM in HCI
• People do use MM but they often are incomplete,
  unstable, vague

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Key points

• There are three types of mental representations
• Analogical, propositional and distributed
• General knowledge is stored as schemata, which
  when activated, can be used to construct mental
  models
• Mental models enable people to generate
  descriptions and explanations about systems and
  to make predictions about future events
• Structural models describe how devices work
• Functional models describe how to use a system
• Most peoples understanding of devices or systems
  is functional
• Conceptualizing users knowledge in terms of
  mental models can help deigners to develop
  appropriate interfaces

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Conceptual Modelsor modeling a Mental model

• A generic term that describes the various way in
  which computer systems are understood by
  different people
• The way users conceptualize and understand the
  system
• The way designers conceptualize and view the
  system
• The problem is to design the system so that
• It follows a consistent coherent
  conceptualisation a design model- and,
• the user can develop a mental model of that
  system a user model- consistent with the design
  model (cf. Norman, 1986 p.46)

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Conceptual Models (cont)

• Ideally, the user model should completely map
  onto the design model (system image)
• Learnability
• Functionality
• Usability
• But
• Users develop a partial mental model of the
  design model
• Their understanding and ability to use the system
  is limited
• Design model could be inappropiated for what the
  user wants to achieve