COGNITIVE FRAMEWORKS: MODES OF COGNITION, HUMAN PROCESSOR MODEL, GOMS

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Human Computer Interaction (CS408)

Lecture

Lecture 6. Cognitive Frameworks

Learning Goals

As the aim of this lecture is to introduce you the study of Human Computer

Interaction, so that after studying this you will be able to:

Understand the importance of Cognition

Understand different cognitive frameworks in HCI

6.1 Introduction

Imagine trying to drive a car by using just a computer keyboard. The four arrow keys

are used for steering, the space bar for braking, and the return key for accelerating. To

indicate left you need to press the F1 key and to indicate right the F2 key. To sound

your horn you need to press the F3 key. To switch the headlights on you need to use

the F4 key and, to switch the windscreen wipers on, the F5 key. Now imagine as you

are driving along a road a ball is suddenly kicked in front of you. What would you do?

Bash the arrow keys and the space bar madly while pressing the F4 key? How would

rate your chance of missing the ball?

Most of us would bald at the very idea of driving a car this way. Many early video

games, however, were designed along these lines: the user had to press an arbitrary

combination of function keys to drive or navigate through the game. More recently,

computer consoles have been designed with the user's capabilities and demands of the

activity in ming. Much better way of controlling and interacting, such as through

using joysticks and steering wheels, are provided that map much better onto the

physical and cognitive aspects of driving and navigating.

We have to understand the limitations of the people to ease them. Let us see what is

cognitive psychology and how it helps us.

Cognitive Psychology

Psychology is concerned primarily with understanding human behavior and the

mental processes that underlie it. To account for human behavior, cognitive

psychology has adopted the notion of information processing. Everything we see, feel,

touch, taste, smell and do is couched in terms of information processing. The

objective cognitive psychology has been to characterize these processes in terms of

their capabilities and limitations. For example, one of the major preoccupations of

cognitive psychologists in the 1960s and 1970s was identifying the amount o f

information that could be processed and remembered at any one time. Recently,

alternative psychological frameworks have been sought which more adequately

characterize the way people work with each other and with the various artifacts,

including computers, that they have use. Cognitive psychology have attempted to

apply relevant psychological principles to HCI by using a variety of methods,

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including development of guidelines, the use of models to predict human performance

and the use of empirical methods for testing computer systems.

Cognition

The dominant framework that has characterized HCI has been cognitive. Let us define

cognition first:

Cognition is what goes on in out heads when we carry out our everyday activities.

In general, cognition refers to the processes by which we become acquainted with

things or, in other words, how we gain knowledge. These include understanding,

remembering, reasoning, attending, being aware, acquiring skills and creating new

ideas.

As figure indicates there are different kinds of cognition.

What goes on in the mind?

perceiving..

thinking..

understanding others

remembering..

talking with others

learning..

manipulating others

planning a meal

making decisions

imagining a trip

solving problems

painting

daydreaming...

writing

composing

The main objective in HCI has been to understand and represent how human interact

with computers in term of how knowledge is transmitted between the two. The

theoretical grounding for this approach stems from cognitive psychology: it is to

explain how human beings achieve the goals they set.

Cognition has also been described in terms of specific kinds of processes. These

include:

· Attention

· Perception and recognition

· Memory

· Learning

· Reading, speaking, and listening

· Problem solving, planning, reasoning, decision-making.

Human Computer Interaction (CS408)

It is important to note that many of these cognitive processes are interdependent:

several may be involved for a given activity. For example, when you try to learn

material for an exam, you need to attend the material, perceive, and recognize it, read

it, think about it, and try to remember it. Thus cognition typically involves a range of

processes. It is rare for one to occur in isolation.

6.2 Modes of Cognition

Norman (1993) distinguishes between two general modes:

1. Experiential cognition

2. Reflective cognition

Experiential cognition

It is the state of mind in which we perceive, act, and react to events around us

effectively and effortlessly. It requires reaching a certain level of expertise and

engagement. Examples include driving a car, reading a book, having a conversation,

and playing a video game.

Reflective cognition

Reflective cognition involves thinking, comparing, and decision-making. This kind of

cognition is what leads to new ideas and creativity. Examples include designing,

learning, and writing a book.

Norman points out that both modes are essential for everyday life but that each

requires different kinds of technological support.

Information processing

One of the many other approaches to conceptualizing how the mind works, has been

to use metaphors and analogies. A number of comparisons have been made, including

conceptualizing the mind as a reservoir, a telephone network, and a digital computer.

One prevalent metaphor from cognitive psychology is the idea that the mind is an

information processor.

During the 1960s and 1970s the main paradigm in cognitive psychology was to

characterize humans as information processors; everything that is sensed (sight,

hearing, touch, smell, and taste) was considered to be information, which the mind

processes. Information is thought to enter and exit the mind through a series of

ordered processing stages. As shown in figure, within these stages, various processes

are assumed to act upon mental representations. Processes include comparing and

matching. Mental representations are assumed to comprise images, mental models,

rules, and other forms of knowledge.

Output

Input

Response

Encoding

Comparison

execution

Selection

response

stimuli

Stage 1

Stage 2

Stage 3

Stage 4

Stage1 encodes information from the environment into some form of internal

representation. In stage 2, the internal representation of the stimulus is compared with

memorized representations that are stored in the brain. Stage 3 is concerned with

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deciding on a response to the encoded stimulus. When an appropriate match is made

the process passes on to stage 4, which deals with the organization of the response and

the necessary action. The model assumes that information is unidirectional and

sequential and that each of the stages takes a certain amount of time, generally

thought to depend on the complexity of the operation performed.

To illustrate the relationship between the different stages of information processing,

consider the sequence involved in sending mail. First, letters are posted in a mailbox.

Next, a postman empties the letters from the mailbox and takes them to central sorting

office. Letters are then sorted according to area and sent via rail, road, air or ship to

their destination. On reaching their destination, the letters are further forted into

particular areas and then into street locations and so on. A major aspect of an

information processing analysis, likewise, is tracing the mental operations and their

outcomes for a particular cognitive task. For example, let us carry out an information

processing analysis for the cognitive task of determining the phone number of a

friend.

Firstly, you must identify the words used in the exercise. Then you must retrieve their

meaning. Next you must understand the meaning of the set of words given in the

exercise. The next stage involves searching your memory for the solution to the

problem. When you have retrieved the number in memory, you need to generate a

plan and formulate the answer into a representation that can be translated into a verbal

form. Then you would need to recite the digits or write them down.

Extending the human information processing model

Two main extensions of the basic information-processing model are the inclusion of

the processes of attention and memory. Figure shows the relationship between the

different processes. [3]

Attention

Encoding

Comparison

Response

Selection

Execution

Memory

In the extended model, cognition is viewed in terms of:

1. how information is perceptual processors

2. how that information is attended to, and

3. how that information is processed and stored in memory.

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6.3 Human processor model

The information-processing model provides a basis from which to make predictions

about human performance. Hypotheses can be made about how long someone will

take to perceive and responds to a stimulus (also known as reaction time) and what

bottlenecks occur if a person is overloaded with too much information. The best-

known approach is

the human processor model, which models the cognitive processes of a user

interacting with a computer. Based on the information-processing model, cognition is

conceptualized as a series of processing stages where perceptual, cognitive, motor

processors are organized in relation to one another. The model predicts which

cognitive processes are involved when a user interacts with a computer, enabling

calculations to be made how long a user will take to carry out various tasks. This can

be very useful when comparing different interfaces. For example, it has been used to

compare how well different word processors support a range of editing tasks.

The information processing approach is based on modeling mental activities that

happen exclusively inside the head. However, most cognitive activities involve people

interacting with external kinds of representations, like books, documents, and

computers--not to mentions one another. For example, when we go home from

wherever we have been we do not need to remember the details of the route because

we rely on cues in the environment (e.g., we know to turn left at the red house, right

when the road comes to a T-junction, and so on.). Similarly, when we are at home we

do not have to remember where everything is because information is "out there." We

decide what to eat and drink by scanning he items in the fridge, find out whether any

messages have been left by glancing at the answering machine to see if there is a

flashing light, and so on. [2]

6.4 GOMS

Card et al. have abstracted a further family of models, known as GOMS (goals,

operations, methods and selection rules) that translate the qualitative descriptions into

quantitative measures. The reason for developing a family of models is that it enables

various qualitative and quantitative predictions to be made about user performance.

Goals

These are the user's goals, describing what the user wants to achieve. Further, in

GOMS the goals are taken to represent a `memory point' for the user, from which he

can evaluate what should be done and to which he may return should any errors occur.

[1]

Operators

These are the lowest level of analysis. They are the basic actions that the user must

perform in order to use the system. They may affect the system (e.g., press the `X'

key) or only the user's mental state (e.g., read the dialogue box). There is still a

degree of flexibility about the granularity of operators; we may take the command

level "issue the select command" or be more primitive; "move mouse to menu bar,

press center mouse button...." [1]

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Methods

As we have already noted, there are typically several ways in which a goal can be

split into sub goals. [1]

Selection

Selection means of choosing between competing methods [1]

One of the problems of abstracting a quantitative model from a qualitative description

of user performance is ensuring that two are connected. In particular, it a has been

noted that the form and contents of GOMS family of models are relatively unrelated

to the form and content of the model human processor and it also oversimplified

human behavior. More recently, attention has focused on explaining:

Knowledge Representation Models

How knowledge is represented

Mental Models

How mental models (these refer to representation people construct in their

mind of themselves, others, objects and the environment to help them know

what to do in current and future situations) develop and are used in HCI

User Interaction Learning Models

How user learn to interact and become experienced in using computer system.

With respect to applying this knowledge to HCI design, there has been considerable

research in developing:

Conceptual Models

Conceptual models are (these are the various ways in which systems are understood

by different people) to help designers develop appropriate interfaces.

Interface Metaphor

Interface metaphors are (these are GUIs that consists of electronic counterparts to

physical objects in the real world) to match the knowledge requirements of users.

6.5 Recent development in cognitive psychology

With the development of computing, the activity of brain has been characterized as a

series of programmed steps using the computer as a metaphor. Concept such as

buffers, memory stores and storage systems, together with the type of process that act

upon them (such as parallel verses serial, top-down verses down-up) provided

psychologist with a mean of developing more advanced models of information

processing, which was appealing because such models could be tested. However,

since the 1980s there has been a more away from the information-processing

framework with in cognitive psychology. This has occurred in parallel with the

reduced importance of the model human processor with in HCI and the development

other theoretical approaches. Primarily, these are the computational and the

connectionist approaches. More recently other alternative approaches have been

developed that has situated cognitive activity in the context in which they occur. [3]

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Computational Approaches

Computational approaches continue to adopt the computer metaphor as a theoretical

framework, but they no longer adhere to the information-processing framework.

Instead, the emphasis is on modeling human performance in terms of what is involved

when information is processed rather than when and how much. Primarily,

computational models conceptualize the cognitive system in terms of the goals,

planning and action that are involved in task performance. These aspects include

modeling: how information is organized and classified, how relevant stored

information is retrieved, what decisions are made and how this information is

reassemble. Thus tasks are analyzed not in terms of the amount of information

processed per se in the various stages but in terms of how the system deals with new

information. [3]

Connectionist Approaches

Connectionist approaches, otherwise known as neural networks or parallel distributed

processing, simulate behavior through using programming models. However, they

differ from conceptual approaches in that they reject the computer metaphor as a

theoretical framework. Instead, they adopt the brain metaphor, in which cognition is

represented at the level of neural networks consisting of interconnected nodes. Hence

all cognitive processes are viewed as activations of the nodes in the network and the

connections between them rather than the processing and manipulation of

information. [3]

6.6 External Cognition

External cognition is concerned with explaining the cognitive processes involved

when we interact with different external representations. A main goal is to explicate

the cognitive benefits of using different representations for different cognitive

activities and the processes involved. The main one include:

1. externalizing to reduce memory load

2. computational offloading

3. annotating and cognitive tracing.

Externalizing to reduce memory load

A number of strategies have been developed for transforming knowledge into external

representations to reduce memory load. One such strategy is externalizing things we

find difficult to remember, such as birthdays, appointments and addresses.

Externalizing, therefore, can help reduce people's memory burden by:

· reminding them to do something (e.g., to get something for their mother's

birthday)

· reminding them of what to do (e.g., to buy a card)

· reminding them of when to do something (send it by a certain date)

Computational offloading

Computational offloading occurs when we use a tool or device in conjunction with an

external representation to help us carry out a computation. An example is using pen or

paper to solve a math problem.[2]

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Annotating and cognitive tracing

Another way in which we externalize our cognitions is by modifying representations

to reflect changes that are taking place that we wish to mark. For example, people

oftern cross thinks off in to-do list to show that they have been completed. They may

also reorder objects in the environment, say by creating different piles as the nature of

the work to be done changes. These two kinds of modification are called annotating

and cognitive tracing:

· Annotating involves modifying external representations, such as crossing off

underlining items.

· Cognitive tracing involves externally manipulating items different orders or

structures.

Information Visualization

A general cognitive principle for interaction design based on the external cognition

approach is to provide external representations at the interface that reduce memory

load and facilities computational offloading. Different kinds of information

visualizations can be developed that reduce the amount of effort required to make

inferences about a given topic (e.g., financial forecasting, identifying programming

bugs). In so doing, they can extend or amplify cognition, allowing people to perceive

and do activities tat they couldn't do otherwise. [2]

6.7 Distributed cognition

Distributed cognition is an emerging theoretical framework whose goal is to provide

an explanation that goes beyond the individual, to conceptualizing cognitive activities

as embodied and situated within the work context in which they occur. Primarily, this

involves describing cognition as it is distributed across individuals and the setting in

which it takes place. The collection of actors (more generally referred to just as

`people' in other parts of the text), computer systems and other technology and their

relations to each other in environmental setting in which they are situated are referred

to as functional systems. The functional systems that have been studied include ship

navigation, air traffic control, computer programmer teams and civil engineering

practices.

A main goal of the distributed cognition approach is to analyze how the different

components of the functional system are coordinated. This involves analyzing how

information is propagated through the functional system in terms of technological

cognitive, social and organizational aspects. To achieve this, the analysis focuses on

the way information moves and transforms between different representational states

of the objects in the functional system and the consequences of these for subsequent

actions.[3]

References:

[1] Human Computer Interaction by Alan Dix

[2] Interaction Design by Jenny Preece

[3] Human Computer Interaction by Jenny Preece

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