Computerassisted Instruction CAICAL

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Computer-assisted Instruction (CAI/CAL)
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Content

• CAI What and Why?
• How can they be developed?
• What are the essential elements in a CAI system?
• What makes a good CAI system?
• What makes a good user interface?
• How CAI can be used effectively? CAI and
  Instructional Model.
• Can CAI replace teachers?

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Developing of CAI

• During the mid-60s, Uhr and his collaborators
  implemented a series of systems which generated
  problems in arithmetic and in vocabulary recall
  (Uhr, 1969). Subsequently, a number of systems
  were devised
• To provide drill and practice in arithmetic
• To select problems at a level of difficulty
  appropriate to the students overall performance.

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What is CAI

• Using computers to facilitate instruction (CAI)
• Using computers to facilitate learning (CAL)

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• Tutorials come with computer programs
• CAI Computer Assisted Instruction
• ICAI Intelligent Computer Assisted Instruction
• ITS Intelligent Tutoring System

• Computer Assisted Instruction (CAI) also called
• CBE Computer-based education
• CAL Computer-assisted learning
• IAC Instructional application of computers
• CBI Computer-based instruction

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Computer-Assisted Learning

• Theoretical Background
• individualization,
• behavioral objectives-- (Baker, 1978)

• Characteristics
• a sequenced series of experiences --alternate
  paths
• independent pacing -- controlled, contingent
  reinforcement given
• evaluate performance quickly and accurately.

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What else can be achieved with CAI besides
technology?

• Simulation provide experiences in
  virtual-reality.
• Drill and practice useful in rote-learning
• Free exploration within system chances for
  elaboration

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Factors contribute to the success of CAL

• relevance to learning objectives compatible with
  syllabus, seen as relevant by student.
• teacher's philosophy of teaching and learning.
• hardware and software considerations.

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CAI
Computer-based Learning Environment
Multimedia
WWW
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Computer-based Learning Environment
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Objectives

• Understand the framework for characterizing
  computer-based learning environments
• Understand the framework with respect to the
  cognitive, pedagogical and interactive features

What is the problem? Education software might
function well, employ efficient algorithm, use
sophisticated multimedia technology, but just
does not deliver what students need, nor promotes
learning
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Computer-based Learning Environment

• A number of episode
• Each episode is composed of a sequence of views
• Each episode refers to a lesson or a set of
  exercises on a specific topic
• A view refers to a screen display and
  user-computer interactions associated with this
  particular screen display
• A view is changed when there is a significant
  shift of configurations of objects on the screen
• A view is a storyboard in the design process

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The Components of View

• view space
• command space

view
Information is display
Interactions are elicited
View space
Command space
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The Contents of View Space

• types of knowledge
• The representation of knowledge
• pedagogical strategies
• The communication of knowledge
• multimedia pieces

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Types of Knowledge

• Domain knowledge
• Declarative knowledge, procedural knowledge,
  strategic knowledge
• Operating knowledge
• Affective content
• Knowledge for implementation

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Basic pedagogical methods

• Setting goals
• Instructions
• Demonstrations
• Explanations
• Illustrations
• Asking questions
• Presenting tasks

• Providing working spaces)
• Providing examples
• Providing reminders
• Providing hints
• Providing references
• Evaluation
• Feedback

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Advanced pedagogical methods

• modeling
• coaching
• reflecting
• articulating
• scaffolding and fading
• exploration

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Multimedia pieces

• media pieces
• Words, pictures, animations and movies in
  digitized forms
• interface pieces
• Button, hot spot, hot object, menu, hypermedia

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Command Space

• Forms of interaction
• Functions of interaction
• Directionality of operating

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Forms of Interactions

• Clicking a button or pressing a key
• Selecting an item
• Typing a command
• Typing a word
• Typing a numerical string
• Typing sentences
• Manipulating the objects
• Manipulating instrumental devices, e.g. hand
  writing pad
• Using a software, e.g. word processing
• Programming

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Functions of interaction

• flexibility
• Selecting tasks or activities
• Selecting task complexity
• Controlling the pace
• Controlling the sequences
• assistance
• Asking for information
• Selecting pedagogical strategies
• Selecting physical attributes of information

• learning activities
• Memorizing information
• Promoting understanding
• Applying procedures
• Transferring cognitive skills
• Constructing products
• Operating system is user friendly

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The Theoretical background of the framework

• Behaviorism Classical Conditioning and
  Instrumental Conditioning
• Cognitive development view of learners and
  learning
• Piagetian cognitive development theory,
  Vygotskian socio-historical perspective of
  knowledge
• Instructional perspective on optimal conditions
  of learning
• Gagnes conditions of learning
• Cognitive theories relevant to learning and
  instruction
• Information processing model

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Advantages of CAI

• Interactivity
• Individualized instruction
• self-paced
• difficulty-adjusted
• personalized
• Motivation
• Immediate Response
• Learner-control

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Characteristics

• Sophistication of the systems lay in the
  task-selection algorithms
• Models of the student were based more on
  parametric summaries of behavior than explicit
  representations of his knowledge
• Almost always based on inflexible presentations
  of didactic materials

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Drawbacks (compared with human tutor)

• Inability to conduct dialogues with the student
  in natural language
• Inability to understand the subject being taught
• The program cannot accept unanticipated
  responses
• Inability to understand the nature of the
  students mistakes or misconceptions
• Inability to profit from experience with students
  or to experiment with the teaching strategy.

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Types of CAI

• Drill and Practice?, Electronic Homework, Vocab
  Builder
• Tutorials ? ????, ??????99
• Microworlds? Logo
• Simulations? momentum, ??????99, Bunsen Burner,
  ??????99
• Instructional games ?????, ????

CAI?
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Drill Practice Software

• Training on specific skills
• immediate feedback
• can provide suitable quantity of quality training
• can provide individualized feedback
• motivate students with competition and multimedia
• too much emphasis on drill practice will
  sacrifice the development of problem solving
  abilities

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Tutorials ????
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Types of Tutorials

• Linear identical learning path
• Branching different learning paths according to
  students responses

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Advantages of Tutorial Software

• Interactive
• Individualize
• Efficiently replace teacher when not available

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Good tutorial software

• With Objectives
• with evaluation
• tutoring process, e.g., gain attention and
  motivation show objectives background
  knowledge display related information examples
  exercises feedback evaluation help transfer to
  other situations (applications)

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Microworld

• A software with which children play and discover
  concepts and cause-effect relationships through
  exploration and experimentation (Papert, 1993)
• A complete small version of some domain that is
  found in the world (Rieber, 1996)
• Examples a zoo, Simcity, LOGO

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Simulations

• Physical simulations simulations of physical
  phenomena
• procedure simulations by controlling simulated
  devices, students learn the controlling
  procedure.
• situational simulations role-playing in a
  situation, learn through experience
  decision-making.
• process simulations by changing some settings,
  results of the process will be generated.

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Advantages of Simulation Software

• Much less-expensive compared with real situation
• motivational
• safe
• near-real authentic experiences
• lower anxiety of failure

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Instructional Games

• Game as a factor to motivate students to learn
• mostly a competition game, the objective is earn
  the highest score
• good instructional game should be
• challenging
• arouse curiosity
• with imagination

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Conclusion

• From instructional systems to simulations
• From text to multimedia
• Traditional CAI
• statically orgainzed receptacles structured to
  embody both the domain and pedagogical knowledge
• strength resides in the paradigms ability to
  take direct advantage of the pedagogical
  experience and to reflect it in the behavior of
  programs
• Multimedia situated learning
• ITS guided by intelligent tutor

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Related Learning Theories

• Behaviorism
• classical conditioning
• instrumental conditioning
• behavior modification shaping
• Information Processing

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??????
????
Behaviorism
????
?? (??)??
Classical Conditioning
Operant (Instrumental) Conditioning
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????Classical Conditioning
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????Operant Conditioning
E
D
Trial Error
Reinforced ??
A
C
Behavior C has more chance to be repeated
B
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??????

• ??????????
• ????, ??

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??????Social Learning Theory
???????????????
???????????????????,?????????, ??????
????????????
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??????

• ??????
• ??????, ????????????

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????(?) Cognitive Theories
7- 2 units
Information Processing Model
Receptors Working Memory Long-term
Memory Effectors
Knowledge Compilation
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????(?) Cognitive Theories

• ??????????????????
• ???????????? ??(Semantic) ??? (Image),
  ?????????? (Mental Image) ?????

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Flow of Information in a computer
RAM
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Information Processing Model
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Sensory Register
Attention
Information
perceived (organized) information goes to working
memory
Receptor
Memory
leaves in 1 to 3 seconds
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Maintenance rehearsal
Short-term Memory
Elaborative Rehearsal
Long-term Memory
Working Memory
Knowledge from long-term memory
Decay (forgetting)
Interference (forgetting)
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To Memorize
To Store into the Long Term Memory
Environment
all
Sensory Register
attention
Short Term Memory
Elaboration or rehearsal
Long Term Memory
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Thinking Processing Information
Elaboration linking information in the Working
Memory with those in the LTM
Limited by the capacity of the Working Memory
(72)
How the WM handles complicated information
Chunking
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FBI PHD TWA IBM
Chunking enables STM to handle a large
amount of information
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Cognitive Load How chunking helps memorizing

• chessboard where 24 pieces are arranged in a game
  in progress. Could you replicate the arrangement
  of the pieces after looking at the board for 10
  seconds?

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Pieces arranged in the form of a game in progress
Experts have better memory powers?
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Pieces placed randomly on the board
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Which screen do you find most readable and
learnable?
Cognitive Overload
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Long Term Memory

• Where the information is permanently stored
• Forgetting due to interference
• Dual encoding
• Retrieving depends on cues links between
  concepts

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Information is permanently stored
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????Situated Learning

• ?????????,??????????
• ?????????, ?????????????, ??????????

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Skill Acquisition ????
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??????

• ?????????
• ?????
• ????, ??????
• ???? (Mental Image) ???????
• ?????????????

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CAI Learning Theories
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CAI and Teaching Models
An Example of using CAI in the classroom
Prism Cone
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Questions

• What were the learning objectives?
• Was this really an inductive process?
• What the students were supposed to learn if they
  following an inductive Process?
• What did the students learn?
• Was the software used properly? In what ways?
• It is now the time to work on Activity A

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Inductive Teaching
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Three Teaching Strategies

• Concept Formation
• Interpretation of Data
• Application of Principles

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Application of Deductive and Inductive Methods
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Assumptions underlying Inductive Approach

• Thinking can be taught.
• Thinking is an active transaction between the
  individual and data. Mental operations cannot be
  taught directly. The process of internalization
  and conceptualization can be done by stimulating
  students to perform complex mental processes with
  progressively less direct support.
• Processes of thought evolve by a sequence that is
  "lawful". Strategies that observe these sequences
  have to be taught.

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Conclusion

• Teachers should be aware of the learning
  objectives of a piece of software and teach
  accordingly
• Be carefully to differentiate between what
  students know and what students have learned.

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References

• Chan, M. (1995). A methodology for characterizing
  computer-based learning environments.
  Instructional Science, 23, 183-220.
• Centre for Computing and Information Systems
  R.I.D.E. Theory and Practice http//ccism.pc.ath
  abascau.ca/html/ccism/deresrce/ride/Theory.xml
• Ryder, M. Constructivism http//carbon.cudenver.e
  du/mryder/itc/constructivism.html
• Papert, S. (1993). The Childrens Machine
  Rethinking school in the age of the computer,
  Basic Books, New York.
• Rieber, L. Seriously considering play Designing
  interactive learning environments based on the
  blending of microworlds, simulations, and games,
  Educational technology research development,
  442. Pp. 43-58.
• Joyce, B., Weil, M, Showeres, B. (1992). Models
  of teaching. Allyn Bacon. Chapter 6.