Content

1. CAI: What and Why?

2. How can they be developed?

3. What are the essential elements in a CAI system?

4. What makes a good CAI system?

5. What makes a good user interface?

6. How CAI can be used effectively? CAI and Instructional Model.

7. Can CAI replace teachers?

Developing of CAI

During the mid-60’s, 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 appropri

ate to the student’s overall performance.

What is CAI

• Using computers to facilitate instruction (CAI)

• Using computers to facilitate learning (CAL)

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

Evolution of CAI1927 1949 1952 1958 1964 1968 1972 1976 1980 1984 1990 1992

Teaching Machine (Pressey)

Programmed Instruction (Skinner)

Discovery Learning (Brunner)

Cognitive Psychology (Piaget)

Information Processing Theory (Card et al.)

2nd generation computer

3 rd generation computer

4 th generation computer

5 th generation computer

FORTRAN BASICPILOT

LogoLISPPROLOG

Test generation & Scoring

Tutorial CAI

Microworlds ICAI

Computer-Assisted Learning

• Theoretical Background– individualization,

– behavioral objectives-- (Baker, 1978)

• Characteristics– a sequenced series of e

xperiences --alternate paths

– independent pacing -- controlled, contingent reinforcement given

– evaluate performance quickly and accurately.

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

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.

CAI

Multimedia

WWW

Computer-based Learning Environment

Computer-based Learning Environment

Objectives

• Understand the framework for characterizing computer-based learning environments

• Understand the framework with respect to the cognitive, pedagogical and interactive featuresWhat 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

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

The Components of View

• view space

• command space

view

Viewspace

Commandspace

Information is display

Interactions are elicited

The Contents of View Space

• types of knowledge– The representation of knowledge

• pedagogical strategies– The communication of knowledge

• multimedia pieces

Types of Knowledge

• Domain knowledge– Declarative knowledge, procedural knowledge,

strategic knowledge

• Operating knowledge

• Affective content

• Knowledge for implementation

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

Advanced pedagogical methods

• modeling

• coaching

• reflecting

• articulating

• scaffolding and fading

• exploration

Multimedia pieces

• media pieces– Words, pictures, animations and movies in

digitized forms

• interface pieces– Button, hot spot, hot object, menu, hypermedia

Command Space

• Forms of interaction

• Functions of interaction

• Directionality of operating

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

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

The Theoretical background of the framework

• Behaviorism: Classical Conditioning and Instrumental Conditioning

• Cognitive development view of learners and learning– Piagetian cognitive development theory, Vygotskian soc

io-historical perspective of knowledge

• Instructional perspective on optimal conditions of learning– Gagne’s conditions of learning

• Cognitive theories relevant to learning and instruction– Information processing model

Advantages of CAI

• Interactivity

• Individualized instruction – self-paced– difficulty-adjusted– personalized

• Motivation

• Immediate Response

• Learner-control

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

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.

Types of CAI

• Drill and Practice 例 :, Electronic Homework, Vocab Builder

• Tutorials 例 : 波浪理論 , 資訊科技大賽 99

• Microworlds: 例 Logo

• Simulations 例 : momentum, 資訊科技大賽 99, Bunsen Burner, 資訊科技大賽 99

• Instructional games 小動物與我 , 繽紛都市

CAI?

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

Tutorials 個別輔導呈現事實與規則 ,

例子以及問題

學生應答

計算機評判

預備的補救

診斷性提問

補救

反饋

補救充

份

不正確

補救不充份

預備的材料可望奏效

補救不充份

正確應答

確定原因

錄自劉儒德 , 教學軟件的選用與評價

Types of Tutorials

• Linear: identical learning path

• Branching: different learning paths according to student’s responses

Advantages of Tutorial Software

• Interactive

• Individualize

• Efficiently replace teacher when not available

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)

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

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.

Advantages of Simulation Software

• Much less-expensive compared with real situation

• motivational

• safe

• near-real; authentic experiences

• lower anxiety of failure

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

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 paradigm’s 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

Related Learning Theories

• Behaviorism– classical conditioning– instrumental conditioning– behavior modification; shaping

• Information Processing

行為主義學派

古典制約Classical Conditioning

操作 ( 工具 ) 制約Operant (Instrumental) Conditioning

行為主義Behaviorism

古典制約Classical Conditioning

Unconditioned Stimulus -- Food

Unconditioned Response -- Saliva

Before Training:

After Training:

Conditioned Stimulus -- Bell

Conditioned Response -- Saliva

Training: A bell is rang when the food is given to the dog

操作制約Operant Conditioning

Trial & Error

Reinforced 強化A

E

B

C

D

Behavior C has more chance to be repeated

對教育的影響• 注重學習中的遊戲成份• 注重獎勵 , 競爭

社會學習學說Social Learning Theory

學習不一定由於個人行為受到強化

而是由於觀察到他人的行為受到強化或懲罰 , 因而模仿這人的行為 , 學習因而產生

學習是由於模仿他人而產生

對教育的影響• 注重群體合作• 塑造模範學生 , 以作為其他學生的模仿

對象

認知理論 ( 一 ) Cognitive Theories

Information Processing Model

描 述 物 件 的 屬 性

Declarative K nowledge陳 述 性 知 識

如 何 進 行 一 件 動 作

Procdrucal K nowledge程 序 性 知 識

K nowledge知 識

Knowledge Compilation

Receptors Working Memory Long-term Memory Effectors

7+- 2 units

• 陳述性知識以組織方式貯藏於長期記憶中

• 陳述性知識以兩種方式貯藏 : 語意 (Semantic) 及影像 (Image), 因此促使學者形成心像 (Mental Image) 可協助記憶

認知理論 ( 二 ) Cognitive Theories

Flow of Information in a computer

ROMCPU

RAM

DISK

Information Processing Model

Sensory

Register

Effector

Receptor

Short T

erm M

emory

Long T

erm M

emory

Control

Sensory Register

Receptor Memory

Information

leaves in 1 to 3 seconds

perceived (organized) informationgoes to working memory

Attention

Short-term Memory

Working Memory

Elaborative Rehearsal

Knowledge from long-term memory

Long-term Memory

Decay (forgetting)

Interference (forgetting)

Maintenance rehearsal

Characteristics of Components of Cognitive Storage Systems

Storage Structur

eCode Capacity

Duration

RetrievalCauses of failure to

recall

Sensory "store"

Sensory: features

12-20 items to

huge

250 msec. - 4

sec.Complete

Masking or decay

Short-term

memory

Acoustic, visual,

semantic, sensory features

identified and named

7 +- 2 items

About 12 sec.;

longer with

rehearsal

Complete: with each item being retrieved every 35

msec.

Displacement,

interference; decay

Long-term

memory

semantic, visual know., abstractions,

meaning, images

Enormous, virtually unlimited

Indefinite

Specific and general

information available

given proper cueing

Interference, organic

dysfunctioning,

inappropriate cues

Recall as a function of recall interval where rehearsal was prevented

3 6 9 12 15 180

20

40

60

80

100

Recall interval (sec.)

To Memorize

To Store into the Long Term Memory

Environment

Sensory Register

Short Term Memory

Long Term Memory

all

attention

Elaboration or rehearsal

Thinking – Processing Information

Limited by the capacity of the Working Memory (7±2)Limited by the capacity of the Working Memory (7±2)

Elaboration – linking information in the Working Memory with those in the LTM

Elaboration – linking information in the Working Memory with those in the LTM

How the WM handles complicated information – Chunking

How the WM handles complicated information – Chunking

Chunking

FB IPH DTW AIB M

FBI PHD TWA IBM

Chunking enables STM to handle a large amount of information

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?

Pieces arranged in the form of a game in progress

Experts have better memory powers?

Pieces placed randomly on the board

Which screen do you find most readable and learnable?

Cognitive Overload

Long Term Memory

• Where the information is permanently stored

• Forgetting due to interference

• Dual encoding

• Retrieving depends on cues – links between concepts

Adjusted mean retention scores3.

3 m

o

9.3

mo

1 yr

. 11

mo.

3 yr

. 10

mo.

7 yr

. 5 m

o.

14 y

r. 6

mo.

25 y

r. 10

mo

34 y

r. 1

mo.

47 y

r. 7

mo.

Time after initial experience

0

20

40

60

80

100

Cor

rect

(%)

Name recognition Picture recognition Name matching

Picture matching Picture cueing Free recall

Information is permanently stored

情境認知Situated Learning

• 知識與情境不可分割 , 因此學習不可脫離情境

• 學習者是完整的個體 , 其主動探索可自我管理的能力 , 是學習成效的重要關鍵

Skill Acquisition 技能習得

文字描述 動作

按指示進行 自動化

操練

對教育的影響• 導引注意力於重點處• 促進自動化• 組織教材 , 協助學生記憶• 利用心像 (Mental Image) 以協助學生記

憶• 不同知識採用不同之教學方式

CAI & Learning Theories

Class Conditioning

Operant Conditioning

Social Learning Theories

Cognitive Theories

Drill and Practice

Tutorials

Microworlds:

Simulations

Instructional games

CAI and Teaching Models

An Example of using CAI in the classroom:

Prism & Cone

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

Inductive Teaching

Three Teaching Strategies

• Concept Formation

• Interpretation of Data

• Application of Principles

Concept FormationConcept Formation

Overt ActivityCovert Mental

OperationsEliciting

Questions

Enumeration, listingDifferentiation (identifying separate items)

What did you see? hear? note?

Grouping

Identifying common properties, abstracting

What belongs together? On what criterion?

Labeling, categorizing

Determining the hierarchical order of items super- and subordination.

How would you call these groups? What belongs to what?

Interpretation of DataInterpretation of Data

Overt ActivityCovert Mental

OperationsEliciting Questions

Identifying critical relationships

DifferentiatingWhat did you notice? see? find?

Exploring relationships

Relating categories to each other. Determining cause-and-effect relationships

Why did this happen?

Making inferences

Going beyond what is given. Finding implications, extrapolating.

What does this mean? What picture does it create in you mind? What would you conclude?

Application of principlesApplication of principlesOvert Activity

Covert Mental Operations

Eliciting Questions

Predicting consequences,

explaining unfamiliar

phenomena, hypothesizing

Analyzing the nature of the problem or

situation, retrieving relevant knowledge

What would happen if ...?

Explaining and/or supporting the predictions and

hypotheses

Determining the causal links leading to

prediction or hypothesis

Why do you think this would happen?

Verifying the prediction

Using logical principles of factual knowledge to determine necessary

and sufficient conditions.

What would it take for this to be generally true or probably true?

Deductive Inductivesuperior performance when one single rule; limited no. of problems

useful when the goal is the ability to learn how to form rules; how to transfer

most effective when the goal of instruction is limited to: similar or identical to those being taught

problem-solving strategies developed

Application of Deductive and Inductive Methods

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.

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.

References• Chan, M. (1995). A methodology for characterizing computer-based learnin

g environments. Instructional Science, 23, 183-220.• Centre for Computing and Information Systems R.I.D.E. : Theory and Pract

ice http://ccism.pc.athabascau.ca/html/ccism/deresrce/ride/Theory.xml • Ryder, M. Constructivism

http://carbon.cudenver.edu/~mryder/itc/constructivism.html• Papert, S. (1993). The Children’s Machine: Rethinking school in the age of

the computer, Basic Books, New York.• Rieber, L. Seriously considering play: Designing interactive learning enviro

nments based on the blending of microworlds, simulations, and games, Educational technology research & development, 44:2. Pp. 43-58.

• Joyce, B., Weil, M, & Showeres, B. (1992). Models of teaching. Allyn & Bacon. Chapter 6.