cognitive modelling, users models and mental models what’s cognitive modelling ? the human...
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Cognitive modelling, Users models and
Mental models
What’s cognitive modelling ?
The human information processing approach
Cognitive Models of Users in HCI
Knowledge, representations and Mental Models
Conceptual models
What’s 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 90´Distributed Cognition (Hutchins, E.) 90’ Situated action (Suchman, L.) 90´Activity theory (Kaptelinin, V. Engeström, Y. )
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
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
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
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?
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”
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
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
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...
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
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?
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
A cognitive architecture for Human Information Processing
Must comply with knowledge about human beings
Knowledge from various sources :
Senso-motoric Attention Perception Memory Metacognition
Information processing applied to HCI
Quasi-empirical approach GOMS
Analyses a task from an expert’s 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 designer’s knowledge about the user
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 caller’s questions
A small change in the time taken may mean much when many small tasks are performed by many persons
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 ”Fitt’s law”
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 user’s 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
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
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.
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
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
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 people’s understanding of devices or systems is functional
Conceptualizing users’ knowledge in terms of mental models can help deigners to develop appropriate interfaces
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)
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