1990 Philip Duchastel

THEORETICAL LEARNING TECHNOLOGY

Adventures in an emerging learning landscape

1. Introduction ********************************************

A characterization of learning technology, not an exposition

The field of learning technology

A personal view, traveling through various perspectives

Overview

Disarray in learning theory leads to a highly personal view

Today's technology limited, so I look beyond it

An adventurous theoretical approach

A speculative approach, where progress is mostly made

A theory provides structure for thinking and acting

Theoretical, but not tight

Relations left to the reader to make, thus open-ended

Style loose, even tangled because of unsettled field

A perspective on the field

Views may seem radical at times

Dealing with a new technology, even if old learning

The issues laid out: info, intelligence, design, & learning

Their interrelationship leads to the crucial issue:

How will environment affect learning?

The field in perspective

Adventures because 1. often critical and 2. explores new territory

Aim achieved if it leads to new thinking by reader

Fascinating field for 3 reasons

2. Learning in the Information Technology Age ***********

The age of information access

Access to information in compelling forms

Lots of access + easy access

Gutenberg's revolution

Which led to new forms of learning

We are now on the verge of another increase

Even if exciting information is not always used

The effin factor

Appeal vs investment

Epistemic curiosity

Builds on natural curiosity

Delay in obtaining the required information increases mental effort

The more the effort needed, the more the topic must be interesting

Educational context of the future

List of 21st century educational context elements

Today's education like that 30 years ago

Although more resources

A schooling scenario

School is short

For sharing of resources + as a social experience

Most learning through computer interaction

Learning will be self-directed and fun

Teachers as mentors

Most learning to take place out of school

In home + SIGs + Centers

Applies to 6- and 20-years old as well

In sum, tool-based rather than teacher-based

Learner initiative

Can children manage their own learning?

Not today, for schools do not provide ideal conditions

But with unlimited resources + access, learning will be fun

I can drop a topic of study and take it up later without penalty

Whim learning and leisure learning

The learning needs paradox

More learning occurring but a lesser need for it

Specialized skills will be learned on the job

More problem-solving performed by KB systems

It will differ from today's curricula

Sequence: dip in and out of topics

Disciplinary fields not studied systematically

Materials will compete for learner interest

Disciplines will compete in a learning market

What about the surgeon or the pilot?

Issue of certification, not of learning

Schools now do both

Certification could be separate

Economics of information access

Basic problem of education is an economic one

All based on the availability of resources

There are good materials but they are not distributed

Thus education is a matter of investment

Experiential learning through simulation

Simulation is important in high-skills learning

Basis in the 'what if?'

Nature of simulation and artificial reality

Costly but will be future cornerstone of learning

Learning about China instead of learning of China

Sensual/analogue/symbolic forms of representation

The more experiential, the better

The more abstract, the more difficult

Except where constraints play, as with time and danger

Abstraction enables imagination

We participate as observers, as in a novel

Simulation will bring about artificial realities

Great scope for learning

Re-inventing guardian angels

A comeback is in the making

A KB-agent as an interface to K

A mentor, filter, friend, advisor

Its scope limited to learning and K

Matching interests to resources

Tutors are K-specific and people adaptable

Angels are person-specific and not topic cognizant

3. Intelligent Technology Structures for Learning ********

Currently emerging systems

5 of them, each with its own flavor

All are intelligent

Intelligence in a program

What is the characteristic

ITSs difficult to evaluate

List of features often associated with ITSs

Some are unimportant, some concern capabilities made possible

Some are primary constituents

Core element of AI is K as opposed to information

K processing skills for responding autonomously

Encapsulated K

What is the status of K in computer systems

K is structured info, irrespective of representation form

SCHOLAR's Buenos Aires ISA city

KB has a set of structural constraints

Some logical, some semantic

Information stored in a certain way, like in a DB

DB is syntactically structured, KB semantically

No spatial constraints, as in a DB

DB and KB are interchangeable forms

An issue of mere appropriateness

Now for K processing

The 'Is Buenos Aires in South America?' process

Collection of procedures constitute a system's intelligence

Just imported procedures, no deep meaning

Nothing mystical about intelligence; just symbol manipulation

Their power lies in mimicking us

And thus performing intelligent actions

Enables flexibility and autonomy

Somewhat unpredictable, like people

Sign of intelligence: responding appropriately to unforeseens

But all is relative: more or less intelligence

A prototypical intelligent tutoring system (ITS)

All systems of learning are reactive learning environments

I.e interactive

The student attempts some task and the computer reacts

Applies to CAI and ITS

Each program constitutes an informational environment

ITS characterized by greater sophistication in its reactions

The result is greater adaptability

Provided by their design based in AI methodology

Student pokes and it reacts

ITS contains a model of the environment (domain model)

You wander through an ITS

It is a symbolic simulation

It takes your input and tries to fit it or guides you towards a fit

This is the tutorial module

Directive vs open-ended: an issue of task-setting

More or less directive: different forms of pedagogy

The system's reaction should be adaptive

Example of Winnipeg in Manitoba instead of in Canada

Or provinces for the kids

Hinges on knowing who you are teaching (the student model)

The final element is the interface: the environment

2 interface levels

1: Communication channels: language, voice, direct manipulation

2: Interactive medium (metaphor): dialogue, game, simulation

Open to multimedia and multiple communication channels

Thus 4 modules; they can interrelate in numerous ways

Typical forms are emerging

Structures for intelligent tutoring

Articulate ESs ***

Not a teaching system, but a performance one instead

Domain experience is represented, so could be used (observing the expert)

Interface features for explanation-giving

Breakpoints possible for prediction/correction

But articulateness may be wanting

However, near-experts will profit

Also novices with simple ESs

Specific tutors ***

The core exemplar of an intelligent system for learning

Specificity lies in its goal-orientedness

Skills and K are broken into constituents, thus made articulate

All is subordinated to the structural features of the domain K

I will examine tutorial processes in later section

Coaches ***

Opportunistic intervention

Tutor grafted onto another system, often a game

There to play; learning is incidental

Tutorial task one of observing and commenting

Marriage of entertainment goals and instructional goals

Explicit consideration of motivational aspects

Advisor systems ***

A coach of sorts (opportunistic)

Host is a software product

Real-world practical information processing task

An active help system

Fine judgments regarding interventions

2 goals: immediate help + long-term learning

Possibly a delicate balance

Assimilatory tools ***

Interest-driven exploration

Contrast with the previous power tools

Characterized by ease of access

Learner-initiative central: no task-setting, no guidance

Appropriate for informal learning

Interaction led by curiosity, not by achievement needs

Not proactive, thus 'enabling access tools'

In sum ***

Each with an operational pedagogical context

Tutor interaction is for instruction

In other systems, interest is less didactic and may even conflict

Tutorial processes

The preceding diversity might seem overwhelming

So we focus on the essence of tutoring

Important for 2 reasons

1: Are there multiple types of learning, and hence tutoring?

2: Can we aspire to genericity (a practical issue)?

There are more differences than commonalities

Various objects of learning are considered

But there is often an attempt to build a unified cognitive science

Hope that general principles of design will emerge

But not at the expense of expressiveness or sophistication

So what's involved in tutoring?

List of some tutorial actions

Distinction to be made between the how and the what

We often confound them, as in 'presenting an overview"

We can converge on eg. information communication

Always 2 core decisions

1: Focus selection: what to teach

2: Cognitive tasking: how to teach it

Focus is decided irrespective of how

Occurs at various levels of detail

Will depend on the scope of the domain representation

Cognitive tasking: the extent of communicating vs discovery

The question is to tell or to guide (how socratic to be?)

Why 'cogn. tasking'? the tutor sets up the task for cognitive processing by the learner

Integrating information is different than problem-solving

There are varying degrees of telling vs guiding

Eg. a strong hint is nearly telling

Also, tutoring may often shift up and down along this dimension

Cogn. tasking can be constrained by K selection

Eg. Lima cannot be discovered as the capital of Peru

K communication is nevertheless a form of reactive learning environment

In fact, 2 systems (the tutor and the learner) poking each other

Cognitive tasking also occurs at various levels of detail

Doing a summary is very different than doing an exercise

In sum, the 2 core processes offer a perspective on instructional strategy & poise us for the genericity issue

We have not fully fleshed out the processes

But will get more involved in the next chapter

4. Learning Environment Design *********************************

Technology as a design process (the 'how to')

Contrastive approach in relation to ISD

May seem particularly provocative to ISD designers

ISD and LED

ISD is a goal-oriented process for learning effectiveness

LED loosely geared to objs but oriented to learner involvement

To engage epistemic curiosity

JSBrown's to pull, not push

ISD leads to a structured sequence for optimal learning

ISD is largely organizing learning events in a meaningful order

Very much a prescriptive process

Instruction of any kind is prescriptive

LED not characterized by structure but by engagement value

Sequence matters little

Fosters learning rather than prescribes learning activities

Learning occurs but its degree is difficult to ascertain

Are the 2 processes really different?

First consider terminology, then design activities

ID focuses on the instructional side; the instructor is in charge

LED focuses on the learning side; the learner decides

ID effective in only 2 ways

1. making materials attractive and effective through structure

2. simply concentrate on structure and rely on context for motivation of the learner

The second approach is all too prevalent

Instructional design activities

Systematic process for the preparation of plans and materials

2 principle sets of activities:

1. defining and structuring the content

2. defining and structuring the delivery and interactions

In tutoring: focus selection and cognitive tasking

Content activities include task analysis and content analysis

Task analysis the more prominent because many skills to be learned

Content analysis for the non-task-oriented domains

Analyses define the content and the sequence

Result in the learning objectives for a system

For the delivery, define the medium and the interaction specifics

Global and specific decisions respectively

Both types are constrained by content decisions and the content itself

LED on the other hand is not content-centered

Learning environment design

Aim to provoke curiosity

Session to evolve in response to learner's needs and interests

The goals are not pre-established, but evolve with the context

LED treats content in a very different way

It emphasizes interaction

It involves content analysis and interest analysis (motivational potential)

Content analysis similar to ID but not exclusive in scope and no sequencing

Content decisions are broad ones, no selection for presentation

Content selection affected by interestingness

A relative matter, but take advantage of intuition in this matter

Now for interactions

Because learning is voluntary, it must be made attractive

Apart from content, the process must be made attractive

Largely unexplored area of design

A number of means, eg. iconics, enactiveness, interactiveness, two-way communication, gaming, and surely others

In sum, breath of coverage and interest, both in content and interaction

One approach is to consider the cognitive processes

Learning strategies center on exploration and consolidation

Exploration: browsing and searching

Consolidation: integration and different perspectives, which is curiosity-inducing

Thus, curiosity provocation then fulfillment

Information must be extensive and interesting

Some means (external) mentioned above

More internal ones are surprise & variability

Eg incongruity and uncertainty, especially perspective contrast

Ex. of the American revolution, and physics

A subtle art, tricky for user appeal

LED relies on topic, learning, and interest analyses

The context for design

I identified 2 design processes for learning materials development

Now how applicable is each?

Is one superior or are they alternates?

Could they not be combined?

The context of learning needs examining

Not uncommon to distinguish education and training

Learning objectives are at the heart of the matter

eg. in the behavioral objectives debate of the '60s

We need to tune the terminology

'Informal learning' instead of education

ISD and LED are tuned to achieving their own goals: effectiveness & interest

Their goals achieved at the expense of the other's

Each thus appropriate in its own realm

An interplay might well emerge

ISDers paying more attention to interest factors

And forms of instruction changing to games, simulation...

Also LEDers including specific objectives within the knowledge base

ISD attuned to the training side of the continuum & LED to the other

But LED will gradually take over in importance

The role of curiosity

As humans, we are learning animals

Learning is rooted in survival and one's prospering

Examples given

We are also curious

For no identifiable reward except excitement

Examples given

Required learning is often dull

Curiosity-based learning is always liked because it is interesting

Otherwise we would not engage

Our design task is to bring that about

Distinction between studying and learning

Examples given

Learning is cognitive processing

Studying is a set of activities

Instruction is organizing a person's studying

Required learning is involved here

But what to call studying for curiosity-based learning?

Not 'self-study' nor 'self-initiated learning'

We need a term for instructionless studying

Not 'learning'; let's call it 'curiosing'

ISD/required learning/training vs LED/curiosing

Now and later

The training/curiosing contrast involves timing

Training and education involve learning now for use later

Eg. pilots, etc.

Likewise in school, the multiplication table

Learning is artificially removed from usage

Which can create motivational problems

There is good reason for this, eg. our pilot on my plane

But there remains the time chasm

This is where LED will have its opportunity

Anything that unifies learning with usage helps learning

Hence the value of simulation

5. Learning Processes ****************************************

Previous chapters have dealt with learning indirectly

Now explicitly

The need for an analytical view

Inadequacy of our vocabulary

Learning is too broad, eg learning to ski & learning trigonometry

Likewise the products of learning: K or skills

And there are the broad theoretical approaches

Different forms of learning or core processes?

All somewhat relative: we can emphasize differences or similarities

Greatest problem is 'learning' used to talk about both internal & external manifestations

It refers to change itself (internal)

And also to the process that brings about the change eg. rehearsal, imagery (external activities)

Even overlaps with studying ('learning chemistry')

There are thus confusions and we need a theoretical account

I present a 'levels' theory of learning

No attempt to ground it empirically, just fit ideas together

Levels of functioning

Earlier dimension from sensual to abstract

Behaviorist and cognitive approaches map onto it

Beh: sensual/enactive Cogn: iconic/symbolic

Also: motor & affective are sensual; conceptual is symbolic

Functioning involves operating directly or abstractly

Hard sensation/behavior or internal representation first in analogue, then in symbolic terms

Thought can then combine and elaborate

This progression is evolutionary and developmental

Also present in everyday dealings

We interact at different levels with the world

What cuts across those levels, if anything?

Association and structure

Both together are the cornerstones of learning

Behaviorism builds on associationism

And cognitivism on structure

Philosophically going back to empiricist/rationalist dispute

They relate to one another through the dimension of coherence

Nutshell description: we first attempt comprehension, then fall back on rehearsal

Comprehension and rehearsal are the 2 processes through which we learn

Which occurs is function of situational coherence

Now to elaborate, we invoke memory and thought

Learning results in memory changes

Occurs all the time + forgetting

Not just school subjects / party invitation example

Learning is a recording of experiences, with no value judgements

Memory essentially an associative affair

Strengthened connections, strength depending on circumstances

Memory as a jumble of associations - tons of them

Physics example and physics-death

Varied connections - examples

K elements are relative in scope and perspective

Scope: particular or general / herbs

Perspective: eg. name, image...

Actually different associations, since they can exist without the other

Relativity of K is interesting but not central

Central: basic constituents of memory are associative

Enter thought: the process of modeling reality

Evident in protocols

Process of building a structural representation of objects, processes and procedures

Modeling mediated through iconic, physical means, but most often just symbolic ones

All terms (schemata...) basically symbolic models

We build them during learning and use them thereafter

But memory is still associative

Not an internal structure to inspect and manipulate

Our usage of the term is merely a manner of speech

Mental structures do not exist as such

I have talked about the result of learning, not the process

It is in the process that structure is important

Learning

Earlier described learning in an external perspective: combination of comprehension and rehearsal

Internal manifestation: recording of regularities and irregularities of experience

Learning: the consignment of these to memory

Event recurrence is noticed and encoded

Regularity as one aspect of coherence (the sun rising ex.)

It cuts across abstraction: conditioning + abstract mental structs

Associative processes are built upon regularity

Learning is activated by regularity in context

It 'gets' encoded

Another form: self-initiated rehearsal (eg citta)

Abstraction is composing concepts (labels embodying regularity)

But rare; usually start from label (dog) or juggle features to derive new concept (wolf)

In sum, regularity is the sum of learning

Rather simple elements or abstractions

Coherence

Now for coherence: the logical way things fit together

Ex: Kiev is the capital, so there is no other

The logical implications constrain thought, thus making it possible

Without the constraint, cognition would be impossibly difficult

Learning is a constant search for coherence

Understanding is the grasping of this coherence

Applies to learning in 2 ways

1: internal consistent; ex. of 3 parts to brain in textbook

2: fit with the current cognitive structure

Why cognitive structure is an important factor in ed psych

Focuses attention on ensuring a potential match in instruction

It also embodies the structural aspects of mental models

But we are concerned with process, not conditions of learning

If the search for coherence fails, then we go for rote learning

Interesting relationship here

If understanding is difficult, it will be well remembered & vice versa

EG. the discovery approach to learning

Based on the coherence principle; difficulty leads to exploration

Effort after meaning not the crucial element, but the achieved coherence

But why should learning suffer from ease of understanding?

Because of degree of coherence achieved, and in non-coherent information present

The required cognitive structure already well established

What is learned is more factual than structural

Ex of general biology where coherence requirements are limited

In sum, coherence is central

If coherence is lacking then one must rely on replicability

Much of our world is arbitrary, ex. John, not Paul

Or marsupials, dogs...

Although some terms are derived from others, eg. microscope

Many non-language elements are also arbitrary, eg Jupiter's 16 moons

Constraining makes certain elements non-arbitrary

If my telephone is gray, then not yellow etc.

Dealing here with a practical logic, not formal logic

Ex of phone broken remaining so until fixed

Reduction in arbitrariness enables thinking

And reduces the need for arbitrary associations, and thus the load on learning

The reason: we also use logic in recalling info

Of no help in recalling arbitrary associations

It can regenerate information from bits & pieces

Ex. of symptom-fault relation in electronics

K builds on K

Declarative and procedural knowledge

K o what is & of how to

Little practical value for learning,even if useful in AI

Nothing special about proc. K in terms of L.

It does differ in being concerned with personal actions, ie skills

Learning about me in the world, about affecting the world

Thus, object of L is different, but process?

Skill can involve motor actions, but no fundamental difference

Still dealing with associative and structural processes

Condition-action relations are establishes and sequences

The subject to repetitive encounters and can use structural processing too

Ex of driving a car

Two concerns crop up

1: getting it right: first getting it wrong and gradually shaping the behavior

But no different than committing a poem to memory

Feedback shows the errors, then practice can proceed

Ex. of learning capitals & how to tie a bow tie

2: getting it quick: automaticity

So automatic that we lose insight into skills

Such robust associations, becomes unitized

Akin to conceptual abstraction: individual elements unitize into concepts

Super-practice makes skills quick and efficient because of need

We rarely need declarative K so quick, so we don't practice it

But we could, eg. in addition skills

Some of these examples strange because seem procedural

Not so much personal as facts about the world

But all involves performing, thus doing something

Just as procedural can be seen declaratively,so too can declarative be seen procedurally, even if just recalling something

No K is impersonal, so cannot be poured into the mind as with computers

Handling information

Cognitive processes are tuned to handling lots of info of all kinds

We seek regularities that can be predictive & seek to infer other consequences

As in perception, we seek cognitive closure that makes a tidy world

Attention is drawn to irregularities & illogical info

The odd element out will be remembered

This forms the basis for curiosity

Regularities form the basis for all L either naturally or artificially through practice

Also the activity cycle: exploration & consolidation

Driven by curiosity, but up against the wall of non-comprehension

Ever in an effort after meaning

6. Prospects ****************************************************

We will be looking at issues

Some of them provocative, to see how they fit

And we will seek to merge them into a synthesis

Time to assess the whole

Concerned in the book with four issues

Two about the future: context and intelligence

Two perennial ones: learning and its fostering

The future of learning

Difficult to predict, eg. personal computer

So what next? We will see

In meantime, we extrapolate to intense electronic flow

Thesis that more availability leads to more learning

Explained through effin factor

Why sensical ?

Because much of learning rests on propensity for curiosity

Eliminating the barriers through learning technology

Barriers: unavailability, schooling curricula

Magic of LT: ease of access due to electronic medium

Interest oftentimes fickle, wandering focus

LT makes pertinent information part of the picture

Gives it a chance to exert its own attraction

Learning not the only thing in life

But learning then has a chance to compete

Lack-luster climate of schooling is 2nd barrier

Basically because of the organizational features, eg bell

Progressive education, followed by situated learning, unable to establish itself

Situated L centers on usefulness, hence meaningfulness

L Technology centers on interesting-ness, not usefulness, even if both can work together

Just how pure is knowledge for its own sake?

It's because of our fickleness, our need for closure

In a general sense, I know knowledge is useful

What is not situated is current schooling

Situated L seeks to reform current schooling, but not LT

LT is not a teacher-based approach, but a tool-based one

Learning will be transformed, and take place in front of a tool

The economic factor will play a part: you get what you put in

So why should our children be oriented to learning?

Society will not change; some parents will push, others not

But children will get bored and curiosity will win out

The less interesting things will be learned surreptitiously through games

Secondary motivation shunned only when used for interesting stuff

The purpose of LED is to do away with non-intrinsic motivation

Further provocative ideas: learning and certification, diminishing learning needs, and competing disciplines

All build on L leaving school and becoming life-long

How quickly depends on the technology driving these changes

LT a panacea? Yes, but not for current schooling

It will happen in its own time

Intelligences around us

Electronics provide 2 capabilities: reproducibility and intelligence

Reproducibility establishes realistic environments to avoid over-abstraction

But intelligence will enable taking on an active role

Teachers are limited and costly, but intelligent systems will help

Over optimistic? Only if we insist on AI replicating human complexity

But we are merely building intellectual tools

Analogy to the initial rejection of evolution theory

Intelligence as the application of K

And K as encapsulated information in semantic constraints

Even in artifacts; ex of metal pot

Both inner world and built environment built on these constraints

We have gobs of information and computers have less, that's all

No qualitative difference

Intelligent assistance for learning

Learning as an individual activity

Teaching merely assists learning

Ex of parent filling child's room with books

Basis of L is interaction with information in environment

But it has to fit

Teaching is deciding the learner's needs and ensuring they are met with the proper information

Two core decisions: what to provide and how to provide

The issue of control is a political one

But L is not wanton exploration of information

Goal guidance provides the cognitive tasking of teaching

Thus teaching is always a question of what information to provide, either task info, feedback, or detailed info

Control is an issue of 2 active systems poking each other

Control is central, though, to forms of intelligent structures

Emerging forms

Learning is the goal-directed interaction between learner and information, the latter provided by learning technologies

The learner can be more or less goal-directed

and the technologies can be more or less broad in cognitive tasking

All systems involve cognitive tasking

Hypermedia is very broad: to explore, even an intelligent one

Tutors' cognitive tasking is much more focused

They put the learner in situation and lead his train of thought

They provide the goal-orientation, despite the appearance of learner control

Control to the learner for information, but to system for skills

Information is structured and meaningful and the student the best judge of understanding

Skill less meaningful and requires practice, so the learner more willing to hand over control

The context establishes role of systems

If task is inherently less interesting, then gaming is appropriate

Guardian angels are a special case, not a learning technology

The forms described here must be seen in current context

Other forms will surely come about as well

Designing learning technologies

LED was proposed to replace ISD

At the expense of interest, even if success is there for the good learners

Crucial difference lies in goal-orientation

ISD:knowledge communication, LED: knowledge exploration, even though there is a general intent to influence

The handing over of control to the teacher

The teacher only has a vague idea of interests, though

And will often be off the mark, hence the need for external motivation

The point of LED is to make materials attractive

They have to be given the competition

Provocation of curiosity is the challenge, and variability, incongruity, etc. the way to do it

Can it be done? Or is it the holy grail of teaching?

It will happen, and does not even need political will

How? Through the emerging technologies

Simulation as the core; it structures information and provides the reactivity and interactivity for learning

Two issues: abstraction and need context

1. Abstraction is an important sector, most important

What is needed is constant travel between abstraction and the sensuous experience

The current tragedy is that the sensuous is often lacking

2. Remote needs vs immediacy of learning need

The future to the rescue

Easier to get information when needed

Remote needs can be made immediate through simulation

Ex. of liver removal, or trigonometry for amphitheater design

The remaining remote needs will be fewer and tackled through games

Before leaving, statement that interaction will increase between learners, not decrease

Dyads and groups around one computer

Pinpointing learning

All learning requires is the right information at the right time

Accessibility also engages the effin factor for perseverance

How simple is learning? The recording of regularities, including those we force through rehearsal

That is the associative basis of learning

Thought puts coherence to work: logical implications reduce arbitrariness of a situation

The inferential approach simplifies learning

Striving for meaning also occurs during recall, thereby diminishing the need for repetition, actually diminishing learning

Thought frames our interaction with the world and only when the information is arbitrary do we resort to rehearsal

Also when the proper information is not available and we artificially rehearse what should be meaningful

It all derives from our natural curiosity: the need for closure and predictive regularity, out of evolution

Philosophers made much of it, and Piaget in particular in equilibration from assimilation and accommodation

I prefer viewing it as an information transaction

The learner reaches out and what is found stimulates consolidation

Thus a constant interplay between curiosing and consolidating

These are the core processes

It all boils down to the right information

A theory for learning technology

2 underlying theories: coherence theory of learning and LED

At the core, interaction between learner and information leads to a transaction theory of learning technology

Deal with the near future, not the present

Transformations in how & what we learn, plus interaction with technology and learning institutions

LED accents interest and wants to do away with non-intrinsic motivation, thus taking advantage of human curiosity

How we process information may change

Not psychological processes, but understanding made easier, which removes some reliance on rehearsal

Without eliminating it , since we are also phenomenological

Learning as a single phenomenon, modulated by degree of coherence

Transactional view brings out right information at right time in a process of curiosity fulfillment that is consolidation

Learning prospects are tremendous

The views seem plausible and coherent, but who am I to say?

General level of discussion, open to other formulations

Grounding shunned so that ideas rest on their own merits

Ideas may lack precision, as a result of adventurous theorizing

Many issues thus remain open

This will hopefully lead to learning technology taking off as a field of study