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Human Computer Interaction

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Human Computer Interaction (CS408)
VU
Lecture
6
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.
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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
Response
Encoding
Comparison
or
or
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
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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Table of Contents:
  1. RIDDLES FOR THE INFORMATION AGE, ROLE OF HCI
  2. DEFINITION OF HCI, REASONS OF NON-BRIGHT ASPECTS, SOFTWARE APARTHEID
  3. AN INDUSTRY IN DENIAL, SUCCESS CRITERIA IN THE NEW ECONOMY
  4. GOALS & EVOLUTION OF HUMAN COMPUTER INTERACTION
  5. DISCIPLINE OF HUMAN COMPUTER INTERACTION
  6. COGNITIVE FRAMEWORKS: MODES OF COGNITION, HUMAN PROCESSOR MODEL, GOMS
  7. HUMAN INPUT-OUTPUT CHANNELS, VISUAL PERCEPTION
  8. COLOR THEORY, STEREOPSIS, READING, HEARING, TOUCH, MOVEMENT
  9. COGNITIVE PROCESS: ATTENTION, MEMORY, REVISED MEMORY MODEL
  10. COGNITIVE PROCESSES: LEARNING, READING, SPEAKING, LISTENING, PROBLEM SOLVING, PLANNING, REASONING, DECISION-MAKING
  11. THE PSYCHOLOGY OF ACTIONS: MENTAL MODEL, ERRORS
  12. DESIGN PRINCIPLES:
  13. THE COMPUTER: INPUT DEVICES, TEXT ENTRY DEVICES, POSITIONING, POINTING AND DRAWING
  14. INTERACTION: THE TERMS OF INTERACTION, DONALD NORMAN’S MODEL
  15. INTERACTION PARADIGMS: THE WIMP INTERFACES, INTERACTION PARADIGMS
  16. HCI PROCESS AND MODELS
  17. HCI PROCESS AND METHODOLOGIES: LIFECYCLE MODELS IN HCI
  18. GOAL-DIRECTED DESIGN METHODOLOGIES: A PROCESS OVERVIEW, TYPES OF USERS
  19. USER RESEARCH: TYPES OF QUALITATIVE RESEARCH, ETHNOGRAPHIC INTERVIEWS
  20. USER-CENTERED APPROACH, ETHNOGRAPHY FRAMEWORK
  21. USER RESEARCH IN DEPTH
  22. USER MODELING: PERSONAS, GOALS, CONSTRUCTING PERSONAS
  23. REQUIREMENTS: NARRATIVE AS A DESIGN TOOL, ENVISIONING SOLUTIONS WITH PERSONA-BASED DESIGN
  24. FRAMEWORK AND REFINEMENTS: DEFINING THE INTERACTION FRAMEWORK, PROTOTYPING
  25. DESIGN SYNTHESIS: INTERACTION DESIGN PRINCIPLES, PATTERNS, IMPERATIVES
  26. BEHAVIOR & FORM: SOFTWARE POSTURE, POSTURES FOR THE DESKTOP
  27. POSTURES FOR THE WEB, WEB PORTALS, POSTURES FOR OTHER PLATFORMS, FLOW AND TRANSPARENCY, ORCHESTRATION
  28. BEHAVIOR & FORM: ELIMINATING EXCISE, NAVIGATION AND INFLECTION
  29. EVALUATION PARADIGMS AND TECHNIQUES
  30. DECIDE: A FRAMEWORK TO GUIDE EVALUATION
  31. EVALUATION
  32. EVALUATION: SCENE FROM A MALL, WEB NAVIGATION
  33. EVALUATION: TRY THE TRUNK TEST
  34. EVALUATION – PART VI
  35. THE RELATIONSHIP BETWEEN EVALUATION AND USABILITY
  36. BEHAVIOR & FORM: UNDERSTANDING UNDO, TYPES AND VARIANTS, INCREMENTAL AND PROCEDURAL ACTIONS
  37. UNIFIED DOCUMENT MANAGEMENT, CREATING A MILESTONE COPY OF THE DOCUMENT
  38. DESIGNING LOOK AND FEEL, PRINCIPLES OF VISUAL INTERFACE DESIGN
  39. PRINCIPLES OF VISUAL INFORMATION DESIGN, USE OF TEXT AND COLOR IN VISUAL INTERFACES
  40. OBSERVING USER: WHAT AND WHEN HOW TO OBSERVE, DATA COLLECTION
  41. ASKING USERS: INTERVIEWS, QUESTIONNAIRES, WALKTHROUGHS
  42. COMMUNICATING USERS: ELIMINATING ERRORS, POSITIVE FEEDBACK, NOTIFYING AND CONFIRMING
  43. INFORMATION RETRIEVAL: AUDIBLE FEEDBACK, OTHER COMMUNICATION WITH USERS, IMPROVING DATA RETRIEVAL
  44. EMERGING PARADIGMS, ACCESSIBILITY
  45. WEARABLE COMPUTING, TANGIBLE BITS, ATTENTIVE ENVIRONMENTS