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Yvonne Wærn Tema Kommunikation Information Processing - In humans and machines April 24, 2001

Yvonne Wærn Tema Kommunikation

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Yvonne Wærn Tema Kommunikation. Information Processing - In humans and machines April 24, 2001. Information Processing Psychology - IPP. Revolution and opposition against behaviorism Behaviorism characterised psychology in general from about 1900 to about 1970. What was behaviorism?. - PowerPoint PPT Presentation

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Page 1: Yvonne Wærn Tema Kommunikation

Yvonne WærnTema Kommunikation

Information Processing -In humans and machinesApril 24, 2001

Page 2: Yvonne Wærn Tema Kommunikation

Information Processing Psychology - IPP

Revolution and opposition against behaviorism

Behaviorism characterised psychology in general from about 1900 to about 1970.

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What was behaviorism?

Theory to describe (explain and predict) behaviour in observable terms only: Stimulus - Response

Pavlov: conditioned reflex (dogs salivating)Skinner: instrumental conditioning (pigeons playing

table-tennis)Watson: conditioned behaviour (Child afraid of

rabbits) Nowadays: Behavioural therapy (diverse phobias)Some computer supported learning

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Information Processing Psychology -

One of several approaches to model cognitive and mental processes - in opposition to behaviorism

(but still some behavioristic traits) Other approaches with similar aim: Gestalt Psychology, (contemporary with beh.) Piaget (contemporary with behaviorism) Bruner (inspired by Piaget)

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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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IP- model from the computer (skipping psychology)

Model from the computer - (1956!) Information processing: Transformation of ”knowledge states” from

start to goal: operations on symbols

Success: AI in form of ”The Logical Theorist” derived all theorems (and some more) in Russel & Whitehead’s volume on ”Logics”.

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IP- model from the computer

Was this human information processing?

No: people have ”bounded rationality”

Use heuristicsUse ”smart” ways of representing problemsAre restricted by their information processing

apparatus

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IP- modelling language

A modelling language - production rules In contrast to verbal descriptions

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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Information Processing : methods

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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IPP - prerequisites-psychology reintroduced

Since 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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Define problem

A problem exists when you have a goal and an initial state that does not correspond to the goal and you do not know how to get from the initial state to the goal

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Define problem space

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 nextsmallest 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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A think-aloud protocol can be regarded as ”the top of the iceberg”

• Toppen av isberget bild• Toppen av isberget bild

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Some production rules that may 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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What production rules may produce the shortest path?

Can production rules only solve this problem?

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No: 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 interpretedIn what order they are takenWhat 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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From IP to HIP (Psychology has been changed to human)

Human beings differ from computers in several ways.

Therefore, we have to define a ”mechanism” that processes information in a similar way as a human being, a HIP:

Human Information Processor

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A cognitive architecture for Human Information Processing (HIP)

Must comply with knowledge about human beings.

Knowledge from various sources: Senso-motoric Attention Perception Memory Metacognition

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Visual rendering of a Human Cognitive architecture (EPICS) (CHI 2001, p 130)

Task

Environ

ment

Auditory

input

Visual

input

Cognitive processor

Production rule

interpreter

Working

memory

Long-term memory

Productions

Auditory proc.

Visual proc.

Vocal motor

Manual motor

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Important HIP characteristics to be considered

Perceptual capacities (time for writing, time for retrieving)

Motor capacities Eye and hand movements, time

Long-term memory (productions) Time for writing, time for retrieving, type of productions

Working memory (restricts amount of material on which productions may

work)

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Important HIP characteristics to be considered

Working memory (restricts amount of material on which productions may

work)

5+/- 2 ”chunks” What is a chunk?

A meaningful unitWhat is that? Chunk på

Zoo

Chunk på Zoo

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Important HIP characteristics to be considered

Long-term memory (productions) Time for writing, time for retrieving, type of

productions

Long-term memory (declarative) Semantic networds Schemata Som

Choklad-pudding

Som

Choklad-pudding

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Characteristics of ingredients in the human information processor

From Newell & Simon, 1972

rendered by Card, Moran & Newell, 1983

Bild from C,M&N

Bild from C,M&N

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Applications of IP and HIP ideas

Rule-based systems: Knowledge base systems Intelligent tutoring User modelling

HCI Analytic models Simulation models Quasi-empirical approaches

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HIP applied to HCI

Analytic model: TAG: Task Action Grammar

Takes related tasks in a system, derives how many rules that have to be used to perform these tasks. The less rules, the easier to learn.

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HIP applied to HCI

Simulation models Different cognitive architectures:

ACT*SOAR

Input data are processed through simulated user model

Results: reaction times

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HIP 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)

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HIP applied to HCI

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.

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Key-stroke level av 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 handmovements is calculated according to ”Fitt’s law”

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HIP applied to HCI

Learning - The effect of prior knowledge

Positive (can use old rules):• Cognitive Complexity Theory (CCT)

Negative (interference with old rules)

Learning by doingA problem solving approach is possible

En tjusig morgon på kontoret

En tjusig morgon på kontoret

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Mismatching models

Conceptual models versus device models versus the user’s model of the system Designers have one particular (conceptual)

model in their mind about how a system should work

The system is implemented to show a model (device model) that may not be the same.

When users work with the system they may construct yet another model of the system

”Search!””Search!”

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Summary: There is a gulf between perception and execution. We may calculate the effects.

Goals

Intentions

Execution

Evaluation

Perception

System (Norman, 1986)

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Recent uses of IPP-models(from CHI 2001)

Out of 69 papers, eight use some kind of theory.

HIP theory is used in all eight cases.

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Recent uses of HIP-models(Examples from CHI 2001)

Ignoring Perfect Knowledge-in-the-world for Imperfect Knowledge-in-the head: Implications of rational analysis for Interface Design

Predicting the Effects of In-Car Interfaces on Driver Behavior Using a Cognitive Architecture

Towards Demystification of Direct Manipulation: Cognitive Modeling Charts the Gulf of Execution

Beyond Command Knowledge: Identifying and Teaching Strategic Knowledge for Using Complex Computer Applications

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Conclusions

HIP-models have a narrow range of application

Within this range, they are surprisingly successful

More so than any other models or theories within HCI.

How is success defined?

How is success defined?

How do we know which applications?

How do we know which applications?